Sparkify.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />

<title>Sparkify</title>

<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>


<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
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<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
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.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
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.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>
<style type="text/css">
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<h1 id="Sparkify-Project-Workspace">Sparkify Project Workspace<a class="anchor-link" href="#Sparkify-Project-Workspace">&#182;</a></h1><p>This workspace contains a tiny subset (128MB) of the full dataset available (12GB). Feel free to use this workspace to build your project, or to explore a smaller subset with Spark before deploying your cluster on the cloud. Instructions for setting up your Spark cluster is included in the last lesson of the Extracurricular Spark Course content.</p>
<p>You can follow the steps below to guide your data analysis and model building portion of this project.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># import libraries</span>
<span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="k">import</span> <span class="n">SparkSession</span>
<span class="kn">from</span> <span class="nn">pyspark.sql.functions</span> <span class="k">import</span> <span class="n">avg</span><span class="p">,</span> <span class="n">col</span><span class="p">,</span> <span class="n">concat</span><span class="p">,</span> <span class="n">desc</span><span class="p">,</span> <span class="n">explode</span><span class="p">,</span> <span class="n">lit</span><span class="p">,</span> <span class="nb">min</span><span class="p">,</span> <span class="nb">max</span><span class="p">,</span> <span class="n">split</span><span class="p">,</span> <span class="n">udf</span><span class="p">,</span> <span class="n">isnull</span>
<span class="kn">from</span> <span class="nn">pyspark.sql.types</span> <span class="k">import</span> <span class="n">IntegerType</span>
<span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="k">import</span> <span class="n">Window</span>

<span class="kn">from</span> <span class="nn">pyspark.ml</span> <span class="k">import</span> <span class="n">Pipeline</span>
<span class="kn">from</span> <span class="nn">pyspark.ml.classification</span> <span class="k">import</span> <span class="n">LogisticRegression</span><span class="p">,</span> <span class="n">RandomForestClassifier</span><span class="p">,</span><span class="n">LinearSVC</span><span class="p">,</span> <span class="n">GBTClassifier</span><span class="p">,</span> <span class="n">DecisionTreeClassifier</span><span class="p">,</span> <span class="n">NaiveBayes</span>
<span class="kn">from</span> <span class="nn">pyspark.ml.evaluation</span> <span class="k">import</span> <span class="n">MulticlassClassificationEvaluator</span>
<span class="kn">from</span> <span class="nn">pyspark.ml.feature</span> <span class="k">import</span> <span class="n">CountVectorizer</span><span class="p">,</span> <span class="n">IDF</span><span class="p">,</span> <span class="n">Normalizer</span><span class="p">,</span> <span class="n">PCA</span><span class="p">,</span> <span class="n">RegexTokenizer</span><span class="p">,</span> <span class="n">StandardScaler</span><span class="p">,</span> <span class="n">StopWordsRemover</span><span class="p">,</span> <span class="n">StringIndexer</span><span class="p">,</span> <span class="n">VectorAssembler</span>
<span class="kn">from</span> <span class="nn">pyspark.ml.regression</span> <span class="k">import</span> <span class="n">LinearRegression</span>
<span class="kn">from</span> <span class="nn">pyspark.ml.tuning</span> <span class="k">import</span> <span class="n">CrossValidator</span><span class="p">,</span> <span class="n">ParamGridBuilder</span>

<span class="kn">import</span> <span class="nn">re</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">import</span> <span class="nn">datetime</span>
<span class="kn">from</span> <span class="nn">time</span> <span class="k">import</span> <span class="n">time</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create a Spark session</span>
<span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span> \
    <span class="o">.</span><span class="n">builder</span> \
    <span class="o">.</span><span class="n">appName</span><span class="p">(</span><span class="s2">&quot;Sparkify&quot;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">getOrCreate</span><span class="p">()</span>
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<h1 id="Load-and-Clean-Dataset">Load and Clean Dataset<a class="anchor-link" href="#Load-and-Clean-Dataset">&#182;</a></h1><p>In this workspace, the mini-dataset file is <code>mini_sparkify_event_data.json</code>. Load and clean the dataset, checking for invalid or missing data - for example, records without userids or sessionids.</p>

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<h3 id="Preprocessing-Steps">Preprocessing Steps<a class="anchor-link" href="#Preprocessing-Steps">&#182;</a></h3><p>I will perform below steps in the preprocessing part to discover and analyze the dataset in a better way.</p>
<ol>
<li>Loading the data from json file and make transformation to pandas dataframe.</li>
<li>Dealing with missing variables.<ol>
<li>Analyzing the variables of columns and removing empty entries, '', in userID.   </li>
<li>Identifying the missing features and removing or replacing them.</li>
</ol>
</li>
<li>Converting the timestamp column in more readible way. </li>
<li>Converting gender information to binary variable from Female to Male. </li>
</ol>
<p>After performing these steps, <em>Churn</em> will be defined according to Cancellation Confirmation feature. In the Churn column, 1 will represent the user has churned and 0 otherwise.</p>

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<h4 id="Loading-The-Data">Loading The Data<a class="anchor-link" href="#Loading-The-Data">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_path</span> <span class="o">=</span> <span class="s1">&#39;mini_sparkify_event_data.json&#39;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">read</span><span class="o">.</span><span class="n">json</span><span class="p">(</span><span class="n">data_path</span><span class="p">)</span>
<span class="c1"># df.persist()</span>
<span class="c1"># See the frame schema</span>
<span class="n">df</span><span class="o">.</span><span class="n">printSchema</span><span class="p">()</span>
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<pre>root
 |-- artist: string (nullable = true)
 |-- auth: string (nullable = true)
 |-- firstName: string (nullable = true)
 |-- gender: string (nullable = true)
 |-- itemInSession: long (nullable = true)
 |-- lastName: string (nullable = true)
 |-- length: double (nullable = true)
 |-- level: string (nullable = true)
 |-- location: string (nullable = true)
 |-- method: string (nullable = true)
 |-- page: string (nullable = true)
 |-- registration: long (nullable = true)
 |-- sessionId: long (nullable = true)
 |-- song: string (nullable = true)
 |-- status: long (nullable = true)
 |-- ts: long (nullable = true)
 |-- userAgent: string (nullable = true)
 |-- userId: string (nullable = true)

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<p>Since I am more familiar with pandas dataframe, I will convert the spark object to pandas df.</p>
<p>[1] <a href="https://stackoverflow.com/questions/29226210/what-is-the-spark-dataframe-method-topandas-actually-doing">https://stackoverflow.com/questions/29226210/what-is-the-spark-dataframe-method-topandas-actually-doing</a></p>
<p>[2] <a href="https://www.oreilly.com/library/view/pyspark-cookbook/9781788835367/fe13b699-9b45-4295-a0cb-6375fa98a3e3.xhtml">https://www.oreilly.com/library/view/pyspark-cookbook/9781788835367/fe13b699-9b45-4295-a0cb-6375fa98a3e3.xhtml</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
<span class="n">df_pandas</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
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        vertical-align: middle;
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        vertical-align: top;
    }

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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>artist</th>
      <th>auth</th>
      <th>firstName</th>
      <th>gender</th>
      <th>itemInSession</th>
      <th>lastName</th>
      <th>length</th>
      <th>level</th>
      <th>location</th>
      <th>method</th>
      <th>page</th>
      <th>registration</th>
      <th>sessionId</th>
      <th>song</th>
      <th>status</th>
      <th>ts</th>
      <th>userAgent</th>
      <th>userId</th>
    </tr>
  </thead>
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    <tr>
      <th>0</th>
      <td>Martha Tilston</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>50</td>
      <td>Freeman</td>
      <td>277.89016</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1.538173e+12</td>
      <td>29</td>
      <td>Rockpools</td>
      <td>200</td>
      <td>1538352117000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Five Iron Frenzy</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>79</td>
      <td>Long</td>
      <td>236.09424</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1.538332e+12</td>
      <td>8</td>
      <td>Canada</td>
      <td>200</td>
      <td>1538352180000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Adam Lambert</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>51</td>
      <td>Freeman</td>
      <td>282.82730</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1.538173e+12</td>
      <td>29</td>
      <td>Time For Miracles</td>
      <td>200</td>
      <td>1538352394000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Enigma</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>80</td>
      <td>Long</td>
      <td>262.71302</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1.538332e+12</td>
      <td>8</td>
      <td>Knocking On Forbidden Doors</td>
      <td>200</td>
      <td>1538352416000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Daft Punk</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>52</td>
      <td>Freeman</td>
      <td>223.60771</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1.538173e+12</td>
      <td>29</td>
      <td>Harder Better Faster Stronger</td>
      <td>200</td>
      <td>1538352676000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
  </tbody>
</table>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># To know nulls</span>
<span class="n">df_pandas</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 286500 entries, 0 to 286499
Data columns (total 18 columns):
artist           228108 non-null object
auth             286500 non-null object
firstName        278154 non-null object
gender           278154 non-null object
itemInSession    286500 non-null int64
lastName         278154 non-null object
length           228108 non-null float64
level            286500 non-null object
location         278154 non-null object
method           286500 non-null object
page             286500 non-null object
registration     278154 non-null float64
sessionId        286500 non-null int64
song             228108 non-null object
status           286500 non-null int64
ts               286500 non-null int64
userAgent        278154 non-null object
userId           286500 non-null object
dtypes: float64(2), int64(4), object(12)
memory usage: 39.3+ MB
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<h4 id="Dealing-With-Missing-Values">Dealing With Missing Values<a class="anchor-link" href="#Dealing-With-Missing-Values">&#182;</a></h4>
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<p>Before proceeding the data cleaning, lets see the NaN values in the dataset columns..</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>artist           58392
auth                 0
firstName         8346
gender            8346
itemInSession        0
lastName          8346
length           58392
level                0
location          8346
method               0
page                 0
registration      8346
sessionId            0
song             58392
status               0
ts                   0
userAgent         8346
userId               0
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">dropna</span><span class="p">(</span><span class="n">how</span> <span class="o">=</span> <span class="s1">&#39;any&#39;</span><span class="p">,</span> <span class="n">subset</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;sessionId&#39;</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+
|userId|
+------+
|      |
|    10|
|   100|
|100001|
|100002|
+------+
only showing top 5 rows

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<pre>artist           58392
auth                 0
firstName         8346
gender            8346
itemInSession        0
lastName          8346
length           58392
level                0
location          8346
method               0
page                 0
registration      8346
sessionId            0
song             58392
status               0
ts                   0
userAgent         8346
userId               0
dtype: int64</pre>
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<p>It is seen that <em>FirstName, Gender, LastName, Location, Registration, and UserAgent</em> have the same number of missing values.</p>

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<pre>array([&#39;Logged In&#39;, &#39;Logged Out&#39;, &#39;Cancelled&#39;, &#39;Guest&#39;], dtype=object)</pre>
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<pre>array([&#39;M&#39;, &#39;F&#39;, None], dtype=object)</pre>
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<p>It is seen that we have None values in gender section.</p>

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<pre>array([&#39;paid&#39;, &#39;free&#39;], dtype=object)</pre>
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<pre>array([&#39;PUT&#39;, &#39;GET&#39;], dtype=object)</pre>
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<pre>array([&#39;NextSong&#39;, &#39;Add to Playlist&#39;, &#39;Roll Advert&#39;, &#39;Thumbs Up&#39;,
       &#39;Downgrade&#39;, &#39;Thumbs Down&#39;, &#39;Home&#39;, &#39;Logout&#39;, &#39;Help&#39;, &#39;Login&#39;,
       &#39;Upgrade&#39;, &#39;Add Friend&#39;, &#39;About&#39;, &#39;Settings&#39;, &#39;Submit Upgrade&#39;,
       &#39;Submit Downgrade&#39;, &#39;Error&#39;, &#39;Save Settings&#39;, &#39;Cancel&#39;,
       &#39;Cancellation Confirmation&#39;, &#39;Register&#39;, &#39;Submit Registration&#39;], dtype=object)</pre>
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<span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()</span>
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<pre>array([200, 307, 404])</pre>
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<pre>array([&#39;30&#39;, &#39;9&#39;, &#39;74&#39;, &#39;54&#39;, &#39;&#39;, &#39;4&#39;, &#39;101&#39;, &#39;78&#39;, &#39;88&#39;, &#39;95&#39;, &#39;25&#39;,
       &#39;142&#39;, &#39;13&#39;, &#39;45&#39;, &#39;39&#39;, &#39;87&#39;, &#39;28&#39;, &#39;131&#39;, &#39;126&#39;, &#39;146&#39;, &#39;59&#39;,
       &#39;15&#39;, &#39;36&#39;, &#39;120&#39;, &#39;92&#39;, &#39;33&#39;, &#39;51&#39;, &#39;27&#39;, &#39;143&#39;, &#39;140&#39;, &#39;6&#39;, &#39;124&#39;,
       &#39;141&#39;, &#39;93&#39;, &#39;81&#39;, &#39;40&#39;, &#39;94&#39;, &#39;113&#39;, &#39;98&#39;, &#39;137&#39;, &#39;65&#39;, &#39;53&#39;, &#39;42&#39;,
       &#39;115&#39;, &#39;38&#39;, &#39;58&#39;, &#39;77&#39;, &#39;52&#39;, &#39;29&#39;, &#39;70&#39;, &#39;61&#39;, &#39;46&#39;, &#39;35&#39;, &#39;132&#39;,
       &#39;127&#39;, &#39;136&#39;, &#39;80&#39;, &#39;110&#39;, &#39;129&#39;, &#39;121&#39;, &#39;82&#39;, &#39;100&#39;, &#39;117&#39;, &#39;18&#39;,
       &#39;85&#39;, &#39;118&#39;, &#39;105&#39;, &#39;96&#39;, &#39;20&#39;, &#39;55&#39;, &#39;3&#39;, &#39;12&#39;, &#39;41&#39;, &#39;73&#39;, &#39;17&#39;,
       &#39;86&#39;, &#39;7&#39;, &#39;67&#39;, &#39;32&#39;, &#39;5&#39;, &#39;106&#39;, &#39;114&#39;, &#39;69&#39;, &#39;99&#39;, &#39;16&#39;, &#39;49&#39;,
       &#39;50&#39;, &#39;24&#39;, &#39;103&#39;, &#39;102&#39;, &#39;122&#39;, &#39;75&#39;, &#39;135&#39;, &#39;128&#39;, &#39;111&#39;, &#39;112&#39;,
       &#39;145&#39;, &#39;66&#39;, &#39;83&#39;, &#39;44&#39;, &#39;11&#39;, &#39;91&#39;, &#39;37&#39;, &#39;90&#39;, &#39;104&#39;, &#39;138&#39;,
       &#39;148&#39;, &#39;107&#39;, &#39;97&#39;, &#39;109&#39;, &#39;134&#39;, &#39;10&#39;, &#39;2&#39;, &#39;144&#39;, &#39;76&#39;, &#39;119&#39;,
       &#39;89&#39;, &#39;14&#39;, &#39;62&#39;, &#39;19&#39;, &#39;150&#39;, &#39;68&#39;, &#39;147&#39;, &#39;8&#39;, &#39;56&#39;, &#39;34&#39;, &#39;60&#39;,
       &#39;125&#39;, &#39;47&#39;, &#39;133&#39;, &#39;26&#39;, &#39;43&#39;, &#39;57&#39;, &#39;149&#39;, &#39;64&#39;, &#39;21&#39;, &#39;71&#39;,
       &#39;108&#39;, &#39;79&#39;, &#39;123&#39;, &#39;116&#39;, &#39;152&#39;, &#39;63&#39;, &#39;139&#39;, &#39;23&#39;, &#39;154&#39;, &#39;155&#39;,
       &#39;72&#39;, &#39;151&#39;, &#39;153&#39;, &#39;22&#39;, &#39;84&#39;, &#39;156&#39;, &#39;100009&#39;, &#39;100022&#39;, &#39;100001&#39;,
       &#39;100025&#39;, &#39;100005&#39;, &#39;100016&#39;, &#39;100011&#39;, &#39;100015&#39;, &#39;100007&#39;,
       &#39;100013&#39;, &#39;100004&#39;, &#39;100012&#39;, &#39;100023&#39;, &#39;100024&#39;, &#39;100018&#39;,
       &#39;100006&#39;, &#39;100019&#39;, &#39;100010&#39;, &#39;100002&#39;, &#39;100003&#39;, &#39;100008&#39;,
       &#39;100014&#39;, &#39;100021&#39;, &#39;100017&#39;, &#39;200014&#39;, &#39;200019&#39;, &#39;200002&#39;,
       &#39;200023&#39;, &#39;200001&#39;, &#39;200020&#39;, &#39;200022&#39;, &#39;200006&#39;, &#39;200011&#39;,
       &#39;200010&#39;, &#39;200015&#39;, &#39;200004&#39;, &#39;200021&#39;, &#39;200017&#39;, &#39;200008&#39;,
       &#39;200024&#39;, &#39;200003&#39;, &#39;200018&#39;, &#39;200009&#39;, &#39;200025&#39;, &#39;200016&#39;,
       &#39;200007&#39;, &#39;200005&#39;, &#39;200012&#39;, &#39;300001&#39;, &#39;300017&#39;, &#39;300015&#39;,
       &#39;300011&#39;, &#39;300008&#39;, &#39;300023&#39;, &#39;300021&#39;, &#39;300009&#39;, &#39;300025&#39;,
       &#39;300002&#39;, &#39;300012&#39;, &#39;300007&#39;, &#39;300005&#39;, &#39;300010&#39;, &#39;300014&#39;,
       &#39;300016&#39;, &#39;300019&#39;, &#39;300020&#39;, &#39;300022&#39;, &#39;300013&#39;, &#39;300018&#39;,
       &#39;300006&#39;, &#39;300003&#39;, &#39;300004&#39;, &#39;300024&#39;], dtype=object)</pre>
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<p>It is seen that we have <strong>' '</strong> value as an entry in the dataset. So we can clear them first and then check the None values in the gender section.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span><span class="p">[</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;&#39;</span><span class="p">][</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
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<pre>8346</pre>
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<p>Lets check the count in the spark dataframe.</p>
<p>[1] <a href="https://docs.databricks.com/spark/latest/dataframes-datasets/introduction-to-dataframes-python.html">https://docs.databricks.com/spark/latest/dataframes-datasets/introduction-to-dataframes-python.html</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">filter</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">userId</span> <span class="o">==</span> <span class="s1">&#39;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
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<pre>8346</pre>
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<p>Next step will be removing the <strong>' '</strong> values in UserId.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">filter</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">userId</span> <span class="o">==</span> <span class="s1">&#39;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
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<pre>0</pre>
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<span class="n">df_pandas</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>artist           50046
auth                 0
firstName            0
gender               0
itemInSession        0
lastName             0
length           50046
level                0
location             0
method               0
page                 0
registration         0
sessionId            0
song             50046
status               0
ts                   0
userAgent            0
userId               0
dtype: int64</pre>
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<p>Let's observe the missing values after the conversion.</p>

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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>artist</th>
      <th>auth</th>
      <th>firstName</th>
      <th>gender</th>
      <th>itemInSession</th>
      <th>lastName</th>
      <th>length</th>
      <th>level</th>
      <th>location</th>
      <th>method</th>
      <th>page</th>
      <th>registration</th>
      <th>sessionId</th>
      <th>song</th>
      <th>status</th>
      <th>ts</th>
      <th>userAgent</th>
      <th>userId</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>8</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>54</td>
      <td>Freeman</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>Add to Playlist</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>None</td>
      <td>200</td>
      <td>1538352905000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>11</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>84</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Roll Advert</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538353150000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>14</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>86</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>307</td>
      <td>1538353376000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>35</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Alexi</td>
      <td>F</td>
      <td>4</td>
      <td>Warren</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Spokane-Spokane Valley, WA</td>
      <td>GET</td>
      <td>Downgrade</td>
      <td>1532482662000</td>
      <td>53</td>
      <td>None</td>
      <td>200</td>
      <td>1538354749000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:32.0) G...</td>
      <td>54</td>
    </tr>
    <tr>
      <th>44</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Alexi</td>
      <td>F</td>
      <td>7</td>
      <td>Warren</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Spokane-Spokane Valley, WA</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1532482662000</td>
      <td>53</td>
      <td>None</td>
      <td>307</td>
      <td>1538355255000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:32.0) G...</td>
      <td>54</td>
    </tr>
    <tr>
      <th>47</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>95</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>Thumbs Down</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>307</td>
      <td>1538355306000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>51</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>97</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538355504000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>53</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>99</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>Logout</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>307</td>
      <td>1538355687000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>56</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ashlynn</td>
      <td>F</td>
      <td>9</td>
      <td>Williams</td>
      <td>NaN</td>
      <td>free</td>
      <td>Tallahassee, FL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1537365219000</td>
      <td>217</td>
      <td>None</td>
      <td>307</td>
      <td>1538355711000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>74</td>
    </tr>
    <tr>
      <th>57</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>104</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538355855000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>67</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>71</td>
      <td>Freeman</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>Thumbs Down</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>None</td>
      <td>307</td>
      <td>1538356524000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>71</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Warren</td>
      <td>M</td>
      <td>1</td>
      <td>Miller</td>
      <td>NaN</td>
      <td>free</td>
      <td>Baltimore-Columbia-Towson, MD</td>
      <td>PUT</td>
      <td>Logout</td>
      <td>1538169823000</td>
      <td>240</td>
      <td>None</td>
      <td>307</td>
      <td>1538356651000</td>
      <td>Mozilla/5.0 (Windows NT 6.0; rv:31.0) Gecko/20...</td>
      <td>4</td>
    </tr>
    <tr>
      <th>72</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Warren</td>
      <td>M</td>
      <td>4</td>
      <td>Miller</td>
      <td>NaN</td>
      <td>free</td>
      <td>Baltimore-Columbia-Towson, MD</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538169823000</td>
      <td>240</td>
      <td>None</td>
      <td>200</td>
      <td>1538356686000</td>
      <td>Mozilla/5.0 (Windows NT 6.0; rv:31.0) Gecko/20...</td>
      <td>4</td>
    </tr>
    <tr>
      <th>75</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ashlynn</td>
      <td>F</td>
      <td>15</td>
      <td>Williams</td>
      <td>NaN</td>
      <td>free</td>
      <td>Tallahassee, FL</td>
      <td>PUT</td>
      <td>Add to Playlist</td>
      <td>1537365219000</td>
      <td>217</td>
      <td>None</td>
      <td>200</td>
      <td>1538356816000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>74</td>
    </tr>
    <tr>
      <th>80</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Warren</td>
      <td>M</td>
      <td>6</td>
      <td>Miller</td>
      <td>NaN</td>
      <td>free</td>
      <td>Baltimore-Columbia-Towson, MD</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538169823000</td>
      <td>240</td>
      <td>None</td>
      <td>200</td>
      <td>1538356954000</td>
      <td>Mozilla/5.0 (Windows NT 6.0; rv:31.0) Gecko/20...</td>
      <td>4</td>
    </tr>
    <tr>
      <th>82</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ashlynn</td>
      <td>F</td>
      <td>18</td>
      <td>Williams</td>
      <td>NaN</td>
      <td>free</td>
      <td>Tallahassee, FL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1537365219000</td>
      <td>217</td>
      <td>None</td>
      <td>307</td>
      <td>1538357104000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>74</td>
    </tr>
    <tr>
      <th>85</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>111</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>307</td>
      <td>1538357160000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>95</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>77</td>
      <td>Freeman</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>None</td>
      <td>307</td>
      <td>1538357649000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>99</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ashlynn</td>
      <td>F</td>
      <td>22</td>
      <td>Williams</td>
      <td>NaN</td>
      <td>free</td>
      <td>Tallahassee, FL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1537365219000</td>
      <td>217</td>
      <td>None</td>
      <td>307</td>
      <td>1538357916000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>74</td>
    </tr>
    <tr>
      <th>101</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>79</td>
      <td>Freeman</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>None</td>
      <td>307</td>
      <td>1538357991000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
    </tr>
    <tr>
      <th>105</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ashlynn</td>
      <td>F</td>
      <td>24</td>
      <td>Williams</td>
      <td>NaN</td>
      <td>free</td>
      <td>Tallahassee, FL</td>
      <td>PUT</td>
      <td>Thumbs Down</td>
      <td>1537365219000</td>
      <td>217</td>
      <td>None</td>
      <td>307</td>
      <td>1538358192000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>74</td>
    </tr>
    <tr>
      <th>111</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Alex</td>
      <td>M</td>
      <td>1</td>
      <td>Hogan</td>
      <td>NaN</td>
      <td>free</td>
      <td>Denver-Aurora-Lakewood, CO</td>
      <td>GET</td>
      <td>Home</td>
      <td>1535066380000</td>
      <td>100</td>
      <td>None</td>
      <td>200</td>
      <td>1538358605000</td>
      <td>Mozilla/5.0 (Windows NT 6.2; WOW64; rv:31.0) G...</td>
      <td>101</td>
    </tr>
    <tr>
      <th>115</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>119</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Roll Advert</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538358779000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>120</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Ainsley</td>
      <td>F</td>
      <td>0</td>
      <td>Farley</td>
      <td>NaN</td>
      <td>free</td>
      <td>McAllen-Edinburg-Mission, TX</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538304455000</td>
      <td>187</td>
      <td>None</td>
      <td>200</td>
      <td>1538359181000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>78</td>
    </tr>
    <tr>
      <th>123</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>122</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>Add to Playlist</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538359261000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>132</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Alex</td>
      <td>M</td>
      <td>7</td>
      <td>Hogan</td>
      <td>NaN</td>
      <td>free</td>
      <td>Denver-Aurora-Lakewood, CO</td>
      <td>GET</td>
      <td>Help</td>
      <td>1535066380000</td>
      <td>100</td>
      <td>None</td>
      <td>200</td>
      <td>1538359923000</td>
      <td>Mozilla/5.0 (Windows NT 6.2; WOW64; rv:31.0) G...</td>
      <td>101</td>
    </tr>
    <tr>
      <th>137</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>124</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Upgrade</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538360042000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>138</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>125</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Upgrade</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538360044000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>139</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Zyonna</td>
      <td>F</td>
      <td>1</td>
      <td>Bird</td>
      <td>NaN</td>
      <td>free</td>
      <td>Columbus, GA-AL</td>
      <td>GET</td>
      <td>Home</td>
      <td>1536663902000</td>
      <td>241</td>
      <td>None</td>
      <td>200</td>
      <td>1538360138000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>88</td>
    </tr>
    <tr>
      <th>144</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>127</td>
      <td>Long</td>
      <td>NaN</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>GET</td>
      <td>Roll Advert</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>None</td>
      <td>200</td>
      <td>1538360228000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
    </tr>
    <tr>
      <th>...</th>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
    </tr>
    <tr>
      <th>278013</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Joshua</td>
      <td>M</td>
      <td>375</td>
      <td>White</td>
      <td>NaN</td>
      <td>paid</td>
      <td>San Antonio-New Braunfels, TX</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1528780738000</td>
      <td>492</td>
      <td>None</td>
      <td>307</td>
      <td>1543593541000</td>
      <td>"Mozilla/5.0 (iPhone; CPU iPhone OS 7_1_2 like...</td>
      <td>300015</td>
    </tr>
    <tr>
      <th>278021</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>8</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>Settings</td>
      <td>1538336771000</td>
      <td>496</td>
      <td>None</td>
      <td>200</td>
      <td>1543594576000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278024</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Joshua</td>
      <td>M</td>
      <td>382</td>
      <td>White</td>
      <td>NaN</td>
      <td>paid</td>
      <td>San Antonio-New Braunfels, TX</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1528780738000</td>
      <td>492</td>
      <td>None</td>
      <td>307</td>
      <td>1543594794000</td>
      <td>"Mozilla/5.0 (iPhone; CPU iPhone OS 7_1_2 like...</td>
      <td>300015</td>
    </tr>
    <tr>
      <th>278040</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Joshua</td>
      <td>M</td>
      <td>389</td>
      <td>White</td>
      <td>NaN</td>
      <td>paid</td>
      <td>San Antonio-New Braunfels, TX</td>
      <td>PUT</td>
      <td>Add Friend</td>
      <td>1528780738000</td>
      <td>492</td>
      <td>None</td>
      <td>307</td>
      <td>1543596785000</td>
      <td>"Mozilla/5.0 (iPhone; CPU iPhone OS 7_1_2 like...</td>
      <td>300015</td>
    </tr>
    <tr>
      <th>278041</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Joshua</td>
      <td>M</td>
      <td>390</td>
      <td>White</td>
      <td>NaN</td>
      <td>paid</td>
      <td>San Antonio-New Braunfels, TX</td>
      <td>PUT</td>
      <td>Add Friend</td>
      <td>1528780738000</td>
      <td>492</td>
      <td>None</td>
      <td>307</td>
      <td>1543596786000</td>
      <td>"Mozilla/5.0 (iPhone; CPU iPhone OS 7_1_2 like...</td>
      <td>300015</td>
    </tr>
    <tr>
      <th>278054</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>12</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543600395000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278059</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>17</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543601677000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278060</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>18</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Add to Playlist</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>200</td>
      <td>1543601693000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278064</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>22</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543602458000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278068</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>26</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543603099000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278074</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>31</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Logout</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543604084000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278075</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>35</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>GET</td>
      <td>Home</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>200</td>
      <td>1543604239000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278076</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>36</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Add Friend</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543604240000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278080</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emma</td>
      <td>F</td>
      <td>3</td>
      <td>Allen</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Wilson, NC</td>
      <td>PUT</td>
      <td>Logout</td>
      <td>1537611935000</td>
      <td>498</td>
      <td>None</td>
      <td>307</td>
      <td>1543604493000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>300021</td>
    </tr>
    <tr>
      <th>278083</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emma</td>
      <td>F</td>
      <td>7</td>
      <td>Allen</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Wilson, NC</td>
      <td>GET</td>
      <td>Home</td>
      <td>1537611935000</td>
      <td>498</td>
      <td>None</td>
      <td>200</td>
      <td>1543604786000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>300021</td>
    </tr>
    <tr>
      <th>278085</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>41</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>307</td>
      <td>1543605019000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278089</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Lauren</td>
      <td>F</td>
      <td>43</td>
      <td>Boone</td>
      <td>NaN</td>
      <td>paid</td>
      <td>St. Louis, MO-IL</td>
      <td>GET</td>
      <td>Home</td>
      <td>1534859694000</td>
      <td>485</td>
      <td>None</td>
      <td>200</td>
      <td>1543605457000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>300009</td>
    </tr>
    <tr>
      <th>278103</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emma</td>
      <td>F</td>
      <td>23</td>
      <td>Allen</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Wilson, NC</td>
      <td>PUT</td>
      <td>Thumbs Down</td>
      <td>1537611935000</td>
      <td>498</td>
      <td>None</td>
      <td>307</td>
      <td>1543608481000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>300021</td>
    </tr>
    <tr>
      <th>278107</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emma</td>
      <td>F</td>
      <td>27</td>
      <td>Allen</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Wilson, NC</td>
      <td>GET</td>
      <td>Home</td>
      <td>1537611935000</td>
      <td>498</td>
      <td>None</td>
      <td>200</td>
      <td>1543609421000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>300021</td>
    </tr>
    <tr>
      <th>278109</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emma</td>
      <td>F</td>
      <td>29</td>
      <td>Allen</td>
      <td>NaN</td>
      <td>paid</td>
      <td>Wilson, NC</td>
      <td>GET</td>
      <td>Home</td>
      <td>1537611935000</td>
      <td>498</td>
      <td>None</td>
      <td>200</td>
      <td>1543609683000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>300021</td>
    </tr>
    <tr>
      <th>278113</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>2</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>307</td>
      <td>1543614016000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278116</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>5</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>PUT</td>
      <td>Thumbs Down</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>307</td>
      <td>1543614528000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278126</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>15</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>200</td>
      <td>1543617317000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278132</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>21</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>PUT</td>
      <td>Thumbs Up</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>307</td>
      <td>1543618270000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278136</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>25</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>PUT</td>
      <td>Add Friend</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>307</td>
      <td>1543618841000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278139</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>28</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>200</td>
      <td>1543619556000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278147</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>36</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>200</td>
      <td>1543621485000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278150</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>39</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>PUT</td>
      <td>Logout</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>307</td>
      <td>1543622122000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278151</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>43</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>Home</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>200</td>
      <td>1543622248000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
    <tr>
      <th>278152</th>
      <td>None</td>
      <td>Logged In</td>
      <td>Emilia</td>
      <td>F</td>
      <td>44</td>
      <td>House</td>
      <td>NaN</td>
      <td>paid</td>
      <td>New York-Newark-Jersey City, NY-NJ-PA</td>
      <td>GET</td>
      <td>About</td>
      <td>1538336771000</td>
      <td>500</td>
      <td>None</td>
      <td>200</td>
      <td>1543622398000</td>
      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>
      <td>300011</td>
    </tr>
  </tbody>
</table>
<p>50046 rows × 18 columns</p>
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<p>Since we will make analysis based on Chunk, it is not needed to drop the None values in artist, length, and song column. Because, they indicate that user is logged in but not listening any song yet therefore no length value.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in auth  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;auth&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in gender  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in level  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;level&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in method  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;method&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in page  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;page&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Unique values in status  column : </span><span class="se">\n</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span>
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<pre>Unique values in auth  column : 
[&#39;Logged In&#39; &#39;Cancelled&#39;]
Unique values in gender  column : 
[&#39;M&#39; &#39;F&#39;]
Unique values in level  column : 
[&#39;paid&#39; &#39;free&#39;]
Unique values in method  column : 
[&#39;PUT&#39; &#39;GET&#39;]
Unique values in page  column : 
[&#39;NextSong&#39; &#39;Add to Playlist&#39; &#39;Roll Advert&#39; &#39;Thumbs Up&#39; &#39;Downgrade&#39;
 &#39;Thumbs Down&#39; &#39;Home&#39; &#39;Logout&#39; &#39;Help&#39; &#39;Upgrade&#39; &#39;Add Friend&#39; &#39;Settings&#39;
 &#39;Submit Upgrade&#39; &#39;About&#39; &#39;Submit Downgrade&#39; &#39;Error&#39; &#39;Save Settings&#39;
 &#39;Cancel&#39; &#39;Cancellation Confirmation&#39;]
Unique values in status  column : 
[200 307 404]
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<p>It is seen that after dropping the ' ' values in UserId column, we also clean the FirstName, Gender, LastName, Location, Registration, and UserAgent columns which have the same missing number count as UserId ' ' count.</p>

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<p>When we compare the unique values in dataset before and after the cleaning of UserId column, it is seen that we have lost two information in the auth column, Logged out and Guest. Additionaly, in the page column, we do not have Login, Registration, and Submit Registration informations anymore.</p>
<p>Since we have dropped the <em>empty</em> user ıds, it might be logical in the sense of users without userid can be guests or logged out users. It make sense for page column also because the lost informations are related to guest users and logged out users.</p>
<p>It is also logical that we have lost None values in gender column, because guest users or logged out users do not have gender information.</p>

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<h4 id="Converting-The-Timestamp">Converting The Timestamp<a class="anchor-link" href="#Converting-The-Timestamp">&#182;</a></h4>
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<p>[1] <a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html">https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html</a></p>
<p>[2] <a href="https://stackoverflow.com/questions/13890935/does-pythons-time-time-return-the-local-or-utc-timestamp">https://stackoverflow.com/questions/13890935/does-pythons-time-time-return-the-local-or-utc-timestamp</a></p>
<p>[3] <a href="https://stackoverflow.com/questions/2265357/parse-date-string-and-change-format">https://stackoverflow.com/questions/2265357/parse-date-string-and-change-format</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span><span class="p">[</span><span class="s1">&#39;ts&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>0    1538352117000
1    1538352180000
2    1538352394000
3    1538352416000
4    1538352676000
Name: ts, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">get_time</span> <span class="o">=</span> <span class="n">udf</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">fromtimestamp</span><span class="p">(</span><span class="n">x</span> <span class="o">/</span> <span class="mf">1000.0</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S&quot;</span><span class="p">))</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s2">&quot;time&quot;</span><span class="p">,</span> <span class="n">get_time</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">ts</span><span class="p">))</span>
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<p>In order to use Python function in Spark, I have used udf.</p>
<p>[1] <a href="https://changhsinlee.com/pyspark-udf/">https://changhsinlee.com/pyspark-udf/</a></p>
<p>[2] <a href="https://docs.databricks.com/spark/latest/spark-sql/udf-python.html">https://docs.databricks.com/spark/latest/spark-sql/udf-python.html</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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      <th></th>
      <th>artist</th>
      <th>auth</th>
      <th>firstName</th>
      <th>gender</th>
      <th>itemInSession</th>
      <th>lastName</th>
      <th>length</th>
      <th>level</th>
      <th>location</th>
      <th>method</th>
      <th>page</th>
      <th>registration</th>
      <th>sessionId</th>
      <th>song</th>
      <th>status</th>
      <th>ts</th>
      <th>userAgent</th>
      <th>userId</th>
      <th>time</th>
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      <th>0</th>
      <td>Martha Tilston</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>50</td>
      <td>Freeman</td>
      <td>277.89016</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Rockpools</td>
      <td>200</td>
      <td>1538352117000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:01:57</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Five Iron Frenzy</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>79</td>
      <td>Long</td>
      <td>236.09424</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>Canada</td>
      <td>200</td>
      <td>1538352180000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
      <td>2018-10-01 00:03:00</td>
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    <tr>
      <th>2</th>
      <td>Adam Lambert</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>51</td>
      <td>Freeman</td>
      <td>282.82730</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Time For Miracles</td>
      <td>200</td>
      <td>1538352394000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:06:34</td>
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    <tr>
      <th>3</th>
      <td>Enigma</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>80</td>
      <td>Long</td>
      <td>262.71302</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>Knocking On Forbidden Doors</td>
      <td>200</td>
      <td>1538352416000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
      <td>2018-10-01 00:06:56</td>
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      <th>4</th>
      <td>Daft Punk</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>52</td>
      <td>Freeman</td>
      <td>223.60771</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Harder Better Faster Stronger</td>
      <td>200</td>
      <td>1538352676000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:11:16</td>
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<p>Since the registration column is also in timestamp format, I will perform the same conversion of ts column for registration column.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;registration_time&#39;</span><span class="p">,</span> <span class="n">get_time</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">registration</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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      <th>gender</th>
      <th>itemInSession</th>
      <th>lastName</th>
      <th>length</th>
      <th>level</th>
      <th>location</th>
      <th>method</th>
      <th>page</th>
      <th>registration</th>
      <th>sessionId</th>
      <th>song</th>
      <th>status</th>
      <th>ts</th>
      <th>userAgent</th>
      <th>userId</th>
      <th>time</th>
      <th>registration_time</th>
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      <th>0</th>
      <td>Martha Tilston</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>50</td>
      <td>Freeman</td>
      <td>277.89016</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Rockpools</td>
      <td>200</td>
      <td>1538352117000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:01:57</td>
      <td>2018-09-28 22:22:42</td>
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      <th>1</th>
      <td>Five Iron Frenzy</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>79</td>
      <td>Long</td>
      <td>236.09424</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>Canada</td>
      <td>200</td>
      <td>1538352180000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
      <td>2018-10-01 00:03:00</td>
      <td>2018-09-30 18:20:30</td>
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      <th>2</th>
      <td>Adam Lambert</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>51</td>
      <td>Freeman</td>
      <td>282.82730</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Time For Miracles</td>
      <td>200</td>
      <td>1538352394000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:06:34</td>
      <td>2018-09-28 22:22:42</td>
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    <tr>
      <th>3</th>
      <td>Enigma</td>
      <td>Logged In</td>
      <td>Micah</td>
      <td>M</td>
      <td>80</td>
      <td>Long</td>
      <td>262.71302</td>
      <td>free</td>
      <td>Boston-Cambridge-Newton, MA-NH</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538331630000</td>
      <td>8</td>
      <td>Knocking On Forbidden Doors</td>
      <td>200</td>
      <td>1538352416000</td>
      <td>"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebK...</td>
      <td>9</td>
      <td>2018-10-01 00:06:56</td>
      <td>2018-09-30 18:20:30</td>
    </tr>
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      <th>4</th>
      <td>Daft Punk</td>
      <td>Logged In</td>
      <td>Colin</td>
      <td>M</td>
      <td>52</td>
      <td>Freeman</td>
      <td>223.60771</td>
      <td>paid</td>
      <td>Bakersfield, CA</td>
      <td>PUT</td>
      <td>NextSong</td>
      <td>1538173362000</td>
      <td>29</td>
      <td>Harder Better Faster Stronger</td>
      <td>200</td>
      <td>1538352676000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:31.0) G...</td>
      <td>30</td>
      <td>2018-10-01 00:11:16</td>
      <td>2018-09-28 22:22:42</td>
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<h1 id="Exploratory-Data-Analysis">Exploratory Data Analysis<a class="anchor-link" href="#Exploratory-Data-Analysis">&#182;</a></h1><p>When you're working with the full dataset, perform EDA by loading a small subset of the data and doing basic manipulations within Spark. In this workspace, you are already provided a small subset of data you can explore.</p>
<h3 id="Define-Churn">Define Churn<a class="anchor-link" href="#Define-Churn">&#182;</a></h3><p>Once you've done some preliminary analysis, create a column <code>Churn</code> to use as the label for your model. I suggest using the <code>Cancellation Confirmation</code> events to define your churn, which happen for both paid and free users. As a bonus task, you can also look into the <code>Downgrade</code> events.</p>
<p>Customer churn occurs when customers/subscribers stop doing business with a company or service. We can define a user as churned if there is an Cancellation Confirmation event. And Churn is defined both free and paid users. In order to track the downgrade event of a paid user can also be sight about customer churn.</p>
<p>[1] <a href="https://blog.recurly.com/better-way-to-calculate-your-churn-rate">https://blog.recurly.com/better-way-to-calculate-your-churn-rate</a></p>

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<p>First look for cancellation confirmation events to define Churn.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create churn label</span>
<span class="n">flag_cancellation</span> <span class="o">=</span> <span class="n">udf</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">x</span> <span class="o">==</span> <span class="s1">&#39;Cancellation Confirmation&#39;</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span> <span class="n">IntegerType</span><span class="p">())</span>

<span class="c1"># Apply it to the dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">flag_cancellation</span><span class="p">(</span><span class="s1">&#39;page&#39;</span><span class="p">))</span>

<span class="c1"># label user who churned</span>
<span class="n">windowval</span> <span class="o">=</span> <span class="n">Window</span><span class="o">.</span><span class="n">partitionBy</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span>

<span class="c1"># Apply it to the dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">over</span><span class="p">(</span><span class="n">windowval</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<p>Now, look for downgrade events.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># create downgrade label</span>
<span class="n">flag_downgrade</span> <span class="o">=</span> <span class="n">udf</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">x</span> <span class="o">==</span> <span class="s2">&quot;Submit Downgrade&quot;</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span> <span class="n">IntegerType</span><span class="p">())</span>

<span class="c1"># Apply it to the dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s2">&quot;downgrade&quot;</span><span class="p">,</span> <span class="n">flag_downgrade</span><span class="p">(</span><span class="s2">&quot;page&quot;</span><span class="p">))</span>

<span class="c1"># label user who&#39;ve ever downgraded</span>
<span class="n">windowval</span> <span class="o">=</span> <span class="n">Window</span><span class="o">.</span><span class="n">partitionBy</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span>

<span class="c1"># Apply it to the dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;downgrade&#39;</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="s1">&#39;downgrade&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">over</span><span class="p">(</span><span class="n">windowval</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
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    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>artist</th>
      <th>auth</th>
      <th>firstName</th>
      <th>gender</th>
      <th>itemInSession</th>
      <th>lastName</th>
      <th>length</th>
      <th>level</th>
      <th>location</th>
      <th>method</th>
      <th>...</th>
      <th>sessionId</th>
      <th>song</th>
      <th>status</th>
      <th>ts</th>
      <th>userAgent</th>
      <th>userId</th>
      <th>time</th>
      <th>registration_time</th>
      <th>churn</th>
      <th>downgrade</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>185153</th>
      <td>Jamie T</td>
      <td>Logged In</td>
      <td>Daniel</td>
      <td>M</td>
      <td>161</td>
      <td>Marks</td>
      <td>259.65669</td>
      <td>paid</td>
      <td>Chicago-Naperville-Elgin, IL-IN-WI</td>
      <td>PUT</td>
      <td>...</td>
      <td>94</td>
      <td>Sheila (Explicit)</td>
      <td>200</td>
      <td>1539972314000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>
      <td>100012</td>
      <td>2018-10-19 18:05:14</td>
      <td>2018-09-19 18:19:14</td>
      <td>1</td>
      <td>1</td>
    </tr>
    <tr>
      <th>12368</th>
      <td>Energy 52</td>
      <td>Logged In</td>
      <td>Alexi</td>
      <td>F</td>
      <td>30</td>
      <td>Warren</td>
      <td>462.13179</td>
      <td>free</td>
      <td>Spokane-Spokane Valley, WA</td>
      <td>PUT</td>
      <td>...</td>
      <td>963</td>
      <td>CafÃÂ© Del Mar</td>
      <td>200</td>
      <td>1539789477000</td>
      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:32.0) G...</td>
      <td>54</td>
      <td>2018-10-17 15:17:57</td>
      <td>2018-07-25 01:37:42</td>
      <td>1</td>
      <td>1</td>
    </tr>
    <tr>
      <th>178657</th>
      <td>P.O.D.</td>
      <td>Logged In</td>
      <td>Erick</td>
      <td>M</td>
      <td>153</td>
      <td>Brooks</td>
      <td>258.16771</td>
      <td>paid</td>
      <td>Selma, AL</td>
      <td>PUT</td>
      <td>...</td>
      <td>1069</td>
      <td>Youth Of The Nation (2006 Remastered Album Ver...</td>
      <td>200</td>
      <td>1540023127000</td>
      <td>"Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebK...</td>
      <td>58</td>
      <td>2018-10-20 08:12:07</td>
      <td>2018-09-26 10:12:31</td>
      <td>1</td>
      <td>0</td>
    </tr>
    <tr>
      <th>190882</th>
      <td>DJ Khaled</td>
      <td>Logged In</td>
      <td>Kaylenn</td>
      <td>F</td>
      <td>82</td>
      <td>Jenkins</td>
      <td>227.08200</td>
      <td>paid</td>
      <td>Price, UT</td>
      <td>PUT</td>
      <td>...</td>
      <td>649</td>
      <td>All I Do Is Win (feat. T-Pain_ Ludacris_ Snoop...</td>
      <td>200</td>
      <td>1540054668000</td>
      <td>"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_2...</td>
      <td>141</td>
      <td>2018-10-20 16:57:48</td>
      <td>2018-09-02 15:57:58</td>
      <td>0</td>
      <td>1</td>
    </tr>
    <tr>
      <th>256047</th>
      <td>LMFAO</td>
      <td>Logged In</td>
      <td>Anika</td>
      <td>F</td>
      <td>10</td>
      <td>Osborne</td>
      <td>227.99628</td>
      <td>free</td>
      <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>
      <td>PUT</td>
      <td>...</td>
      <td>1262</td>
      <td>I'm In Miami Bitch</td>
      <td>200</td>
      <td>1540478927000</td>
      <td>"Mozilla/5.0 (iPhone; CPU iPhone OS 7_1_2 like...</td>
      <td>13</td>
      <td>2018-10-25 14:48:47</td>
      <td>2018-08-02 06:40:32</td>
      <td>0</td>
      <td>1</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 22 columns</p>
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<p>Let's observe the spark dataframe</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+
|userId|
+------+
|    10|
|   100|
|100001|
|100002|
|100003|
+------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">([</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="s1">&#39;downgrade&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
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<pre>+------+-----+---------+
|userId|churn|downgrade|
+------+-----+---------+
|100010|    0|        0|
|200002|    0|        0|
|   125|    1|        0|
|   124|    0|        0|
|    51|    1|        0|
|     7|    0|        0|
|    15|    0|        0|
|    54|    1|        1|
|   155|    0|        0|
|100014|    1|        0|
|   132|    0|        0|
|   154|    0|        0|
|   101|    1|        0|
|    11|    0|        1|
|   138|    0|        0|
|300017|    0|        0|
|100021|    1|        0|
|    29|    1|        0|
|    69|    0|        0|
|   112|    0|        0|
+------+-----+---------+
only showing top 20 rows

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<p>Now we have defined <strong>churn</strong> and <strong>downgrade</strong> events as seperate columns.</p>

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<h3 id="Explore-Data">Explore Data<a class="anchor-link" href="#Explore-Data">&#182;</a></h3><p>Once you've defined churn, perform some exploratory data analysis to observe the behavior for users who stayed vs users who churned. You can start by exploring aggregates on these two groups of users, observing how much of a specific action they experienced per a certain time unit or number of songs played.</p>

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<h5 id="Gender-distribution-on-churn-event">Gender distribution on churn event<a class="anchor-link" href="#Gender-distribution-on-churn-event">&#182;</a></h5><p>First, we can explore the gender distribution on churn event to understand gender has an effect or not.</p>
<p>[1] <a href="https://medium.com/@andykashyap/top-5-tricks-to-make-plots-look-better-9f6e687c1e08">https://medium.com/@andykashyap/top-5-tricks-to-make-plots-look-better-9f6e687c1e08</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">([</span><span class="s2">&quot;userId&quot;</span><span class="p">,</span> <span class="s2">&quot;gender&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;churn&quot;</span><span class="p">,</span> <span class="s2">&quot;gender&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="s2">&quot;churn&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<pre>+-----+------+-----+
|churn|gender|count|
+-----+------+-----+
|    0|     M|   89|
|    0|     F|   84|
|    1|     F|   20|
|    1|     M|   32|
+-----+------+-----+

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas_gender</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">([</span><span class="s2">&quot;userId&quot;</span><span class="p">,</span> <span class="s2">&quot;gender&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;churn&quot;</span><span class="p">,</span> <span class="s2">&quot;gender&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="s2">&quot;churn&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">barplot</span><span class="p">(</span><span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="n">hue</span> <span class="o">=</span> <span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_gender</span><span class="p">,</span>  <span class="n">palette</span> <span class="o">=</span> <span class="s2">&quot;Blues_d&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Churn&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">title</span> <span class="o">=</span> <span class="s1">&#39;Gender&#39;</span><span class="p">,</span> <span class="n">loc</span> <span class="o">=</span> <span class="s1">&#39;best&#39;</span><span class="p">,</span> <span class="n">ncol</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span>

<span class="n">plot</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Gender Distribution of Churn Event&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
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<p>It is seen that male customers are slightly like to be churn than the female users.</p>

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<h5 id="Number-of-played/listened-songs">Number of played/listened songs<a class="anchor-link" href="#Number-of-played/listened-songs">&#182;</a></h5><p>It might be a good indicator to understand the number of played songs in a session among the genders. Therefore, we may see the reason of male users have more likely to be churned.</p>
<p>[1] <a href="https://www.datacamp.com/community/blog/seaborn-cheat-sheet-python">https://www.datacamp.com/community/blog/seaborn-cheat-sheet-python</a></p>
<p>[2] <a href="https://seaborn.pydata.org/generated/seaborn.violinplot.html">https://seaborn.pydata.org/generated/seaborn.violinplot.html</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas_song</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="s1">&#39;page == &quot;NextSong&quot;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;sessionId&#39;</span><span class="p">,</span><span class="s1">&#39;gender&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>\
    <span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;gender&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">agg</span><span class="p">({</span><span class="s1">&#39;count&#39;</span><span class="p">:</span><span class="s1">&#39;avg&#39;</span><span class="p">})</span>\
    <span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;avg(count)&#39;</span><span class="p">,</span> <span class="s1">&#39;avg_songs_played&#39;</span><span class="p">)</span>\
    <span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;avg_songs_played&#39;</span><span class="p">,</span> <span class="n">hue</span> <span class="o">=</span> <span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_song</span><span class="p">,</span> <span class="n">palette</span><span class="o">=</span><span class="s2">&quot;Set2&quot;</span><span class="p">,</span> <span class="n">split</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">inner</span><span class="o">=</span><span class="s2">&quot;quartile&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Average count of listened songs per session&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">title</span> <span class="o">=</span> <span class="s1">&#39;Gender&#39;</span><span class="p">,</span> <span class="n">loc</span> <span class="o">=</span> <span class="s1">&#39;best&#39;</span><span class="p">,</span> <span class="n">ncol</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Listened music distribution among gender&#39;</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">despine</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">);</span>
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<p>It is seen that churned users had listened less music than the others. And also churned female users average listened songs are more than males.</p>

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<h6 id="Notes-on-Violin-Plot">Notes on Violin Plot<a class="anchor-link" href="#Notes-on-Violin-Plot">&#182;</a></h6><p>A violin plot plays a similar role as a box and whisker plot. It shows the distribution of quantitative data across several levels of one (or more) categorical variables such that those distributions can be compared. Unlike a box plot, in which all of the plot components correspond to actual datapoints, the violin plot features a kernel density estimation of the underlying distribution.</p>
<p>Violin plots have many of the same summary statistics as box plots:</p>
<ul>
<li>The white dot represents the median</li>
<li>The thick gray bar in the center represents the interquartile range</li>
<li>The thin gray line represents the rest of the distribution, except for points that are determined to be “outliers” using a method that is a function of the interquartile range.</li>
</ul>
<p>On each side of the gray line is a kernel density estimation to show the distribution shape of the data. Wider sections of the violin plot represent a higher probability that members of the population will take on the given value; the skinnier sections represent a lower probability.</p>
<p>[1] <a href="https://mode.com/blog/violin-plot-examples">https://mode.com/blog/violin-plot-examples</a></p>
<p>[2] <a href="https://blog.bioturing.com/2018/05/16/5-reasons-you-should-use-a-violin-graph/">https://blog.bioturing.com/2018/05/16/5-reasons-you-should-use-a-violin-graph/</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas_likes</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="s1">&#39;page == &quot;NextSong&quot; OR page == &quot;Thumbs Up&quot;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="s1">&#39;page&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
<span class="n">df_pandas_likes</span> <span class="o">=</span> <span class="n">df_pandas_likes</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span><span class="s1">&#39;churn&#39;</span><span class="p">,</span><span class="s1">&#39;gender&#39;</span><span class="p">],</span> <span class="n">values</span><span class="o">=</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;page&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_likes</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;NextSong&#39;</span><span class="p">,</span> <span class="n">hue</span> <span class="o">=</span> <span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="n">split</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>  <span class="n">inner</span> <span class="o">=</span> <span class="s2">&quot;quartile&quot;</span><span class="p">,</span> <span class="n">palette</span><span class="o">=</span><span class="s2">&quot;Set2&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Churn Event&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Played songs count according to NextSong Event&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">title</span> <span class="o">=</span> <span class="s1">&#39;Gender&#39;</span><span class="p">,</span> <span class="n">loc</span> <span class="o">=</span> <span class="s1">&#39;best&#39;</span><span class="p">)</span>
<span class="n">title</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Total listening song distribution effect on churn by gender&#39;</span><span class="p">)</span>
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<p>It seems that the mean of the total listened songs do not change that much among churned and unchurned users. However, we can say that female users have larger mean value and distribution than the male users.</p>

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<div class="prompt input_prompt">In&nbsp;[46]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_likes</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;Thumbs Up&#39;</span><span class="p">,</span> <span class="n">hue</span> <span class="o">=</span> <span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="n">split</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>  <span class="n">inner</span> <span class="o">=</span> <span class="s2">&quot;quartile&quot;</span><span class="p">,</span> <span class="n">palette</span><span class="o">=</span><span class="s2">&quot;Set3&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Churn event&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Liked song count according to ThumbsUp event&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="s1">&#39;Gender&#39;</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="s1">&#39;best&#39;</span><span class="p">)</span>
<span class="n">title</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Total liked song distribution effect on churn by gender&#39;</span><span class="p">)</span>
</pre></div>

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<p>Also for the liked song distribution, churned and normal users have similar characteristics.</p>

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<h6 id="Churned-user-status">Churned user status<a class="anchor-link" href="#Churned-user-status">&#182;</a></h6><p>It might me a good indicator to see which payment status of user had churned most.</p>

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<div class="prompt input_prompt">In&nbsp;[47]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas_level</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">filter</span><span class="p">(</span><span class="s1">&#39;page == &quot;Cancellation Confirmation&quot;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;level&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<div class="prompt input_prompt">In&nbsp;[48]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">barplot</span><span class="p">(</span><span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_level</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;level&#39;</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="n">palette</span><span class="o">=</span><span class="s2">&quot;Set1&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Payment level&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">12</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Churned user payment level distribution&#39;</span><span class="p">,</span> <span class="n">fontsize</span> <span class="o">=</span> <span class="mi">14</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">despine</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">);</span>
</pre></div>

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ABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA5zhqmqumNVnV1V66vqC1X17HH+0VX1jao6f3wcuPTlAgAsL6vm0eb6JM9trZ1XVb+Q5DNVdda47DWttVcuXXkAAMvbnGGqtXZZksvG51dX1fokt1/qwgAAVoLNGjNVVbsluXeST46znllVF1TVcVW14yLXBgCw7M07TFXVrZO8O8lzWmvfS/L6JHdNsibDmatXbWS9I6tqXVWt27BhwyKUDACwfMwrTFXVdhmC1EmttX9Oktba5a21H7fWfpLkTUn2mW3d1tqxrbW1rbW1q1evXqy6AQCWhfnczVdJ3pJkfWvt1RPzd51odkiSCxe/PACA5W0+d/M9IMnjk3y+qs4f570wyWFVtSZJS3JJkqOWpEIAgGVsPnfznZukZln0/sUvBwBgZfEN6AAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADqs2toFLKV1a/fZ2iXAzdLadZ/a2iUAbDHOTAEAdBCmAAA6CFMAAB2EKQCADsIUAEAHYQoAoIMwBQDQQZgCAOggTAEAdJgzTFXVHavq7KpaX1VfqKpnj/NvW1VnVdVF488dl75cAIDlZT5npq5P8tzW2p5J7pfkD6vqHklekOTDrbU9knx4nAYAuFmZM0y11i5rrZ03Pr86yfokt0/yyCQnjM1OSHLwUhUJALBcbdaYqaraLcm9k3wyyS6ttcuSIXAl2XmxiwMAWO7mHaaq6tZJ3p3kOa21723GekdW1bqqWrdhw4aF1AgAsGzNK0xV1XYZgtRJrbV/HmdfXlW7jst3TXLFbOu21o5tra1tra1dvXr1YtQMALBszOduvkryliTrW2uvnlh0epLDx+eHJzlt8csDAFjeVs2jzQOSPD7J56vq/HHeC5O8PMk7quqIJF9L8uilKREAYPmaM0y11s5NUhtZvO/ilgMAsLL4BnQAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAhznDVFUdV1VXVNWFE/OOrqpvVNX54+PApS0TAGB5ms+ZqeOTHDDL/Ne01taMj/cvblkAACvDnGGqtfaxJN/eArUAAKw4PWOmnllVF4yXAXfcWKOqOrKq1lXVug0bNnR0BwCw/Cw0TL0+yV2TrElyWZJXbaxha+3Y1tra1tra1atXL7A7AIDlaUFhqrV2eWvtx621nyR5U5J9FrcsAICVYUFhqqp2nZg8JMmFG2sLAHBTtmquBlV1SpIHJ9mpqi5N8udJHlxVa5K0JJckOWoJawQAWLbmDFOttcNmmf2WJagFAGDF8Q3oAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAdhCkAgA7CFABAB2EKAKCDMAUA0EGYAgDoIEwBAHQQpgAAOghTAAAd5gxTVXVcVV1RVRdOzLttVZ1VVReNP3dc2jIBAJan+ZyZOj7JAVPzXpDkw621PZJ8eJwGALjZmTNMtdY+luTbU7MfmeSE8fkJSQ5e5LoAAFaEhY6Z2qW1dlmSjD93XrySAABWjiUfgF5VR1bVuqpat2HDhqXuDgBgi1pomLq8qnZNkvHnFRtr2Fo7trW2trW2dvXq1QvsDgBgeVpomDo9yeHj88OTnLY45QAArCzz+WqEU5J8IsndqurSqjoiycuTPKyqLkrysHEaAOBmZ9VcDVprh21k0b6LXAsAwIrjG9ABADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHVb1rFxVlyS5OsmPk1zfWlu7GEUBAKwUXWFq9JDW2pWLsB0AgBXHZT4AgA69Yaol+VBVfaaqjlyMggAAVpLey3wPaK19s6p2TnJWVX2xtfaxyQZjyDoySe50pzt1dgcAsLx0nZlqrX1z/HlFkvck2WeWNse21ta21tauXr26pzsAgGVnwWGqqm5VVb8w8zzJfkkuXKzCAABWgp7LfLskeU9VzWzn5NbamYtSFQDACrHgMNVa+2qSey1iLQAAK46vRgAA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB0EKYAADoIUwAAHYQpAIAOwhQAQAdhCgCggzAFANBBmAIA6CBMAQB06ApTVXVAVX2pqr5cVS9YrKIAAFaKBYepqto2yT8keXiSeyQ5rKrusViFAQCsBD1npvZJ8uXW2ldba9cleVuSRy5OWQAAK0NPmLp9kq9PTF86zgMAuNlY1bFuzTKv3ahR1ZFJjhwnr6mqL3X0yc3HTkmu3NpFsEA129sDLAveW1aweuljtnSXZ7bWDpirUU+YujTJHSem75Dkm9ONWmvHJjm2ox9uhqpqXWtt7dauA7hp8d7CUui5zPfpJHtU1e5VtX2SxyQ5fXHKAgBYGRZ8Zqq1dn1VPTPJB5Nsm+S41toXFq0yAIAVoOcyX1pr70/y/kWqBSa5NAwsBe8tLLpq7UZjxgEAmCd/TgYAoIMwxVZRVc+qqvVVddLWrgW4eaqql1TVQ2eZ/+CqOmNr1MTK1DVmCjo8I8nDW2sXz8yoqlWtteu3Yk3AzUhr7cVbuwZuGpyZYourqjckuUuS06vqu1V1bFV9KMk/VtW2VfW3VfXpqrqgqo6aWO9/T8z/i622A8CyVFW7VdUXq+qE8X3iXVX181X14vG948Lx/abG9sdX1aHj8wPGdc9N8qituiOsOMIUW1xr7WkZvuD1IUlek+S+SR7ZWntskiOSfLe1tneSvZM8dfwus/2S7JHhb0KuSXLfqvrtrbIDwHJ2tyTHttZ+Pcn3MpwFP6a1tndr7Z5Jfi7JQZMrVNUtk7wpySOS/FaS223ZklnphCmWg9Nba9eOz/dL8oSqOj/JJ5P8UoYQtd/4+GyS85LcfZwPMOnrrbWPj89PTPLAJA+pqk9W1eeT/E6SvabWuXuSi1trF7XhFvcTt1y53BQYM8Vy8P2J55Xkj1prH5xsUFX7J3lZa+2NW7QyYKWZ/r6fluR1Sda21r5eVUcnueU81oN5c2aK5eaDSZ5eVdslSVX9alXdapz/5Kq69Tj/9lW181asE1ie7lRV9x+fH5bk3PH5leP7x6GzrPPFJLtX1V0n1oN5c2aK5ebNSXZLct44SHRDkoNbax+qqj2TfGIcO3pNkscluWJrFQosS+uTHF5Vb0xyUZLXJ9kxyeeTXJLh78reQGvth1V1ZJL3VdWVGQLYPbdYxax4vgEdgJuEqtotyRnjQHPYYlzmAwDo4MwUAEAHZ6YAADoIUwAAHYQpAIAOwhRws1ZV51TVU5a4j6Oryrdqw02UMAVsVFVdUlXXVtU1VXV5Vb115otTV4KqeuL4h2sBlowwBczlEa21Wye5T4Y/Pv2irVwPwLIiTAHz0lr7RpIPZPxm6Kp6UlWtr6qrq+qrVXXUTNuqurCqHjExvV1VXVlVa6pqt6pq4/pfr6rvVNXTqmrvqrqgqq6qqmMm+66qJ499faeqPlhVd55Y1sb1LxqX/0MN9kzyhiT3H8+sXTWf/dxYX1X1hqp65VTb06rqj8fnv1xV766qDVV1cVU9a3NfY2BlEqaAeamqOyY5MMlnx1lXJDkoyS8meVKS11TVfcZl/5jhz/3MODDJZa218yfm/UaSPZL8fpK/S/JnSR6aZK8kv1dVDxr7PTjJC5M8KsnqJP+S5JSp8g7KcNbsXkl+L8n+rbX1SZ6W5BOttVu31naYxz5uqq+Tk/z++GeOUlU7Jtkvyduqapsk703yuSS3T7JvkueMf6AbuIkTpoC5nDqe1Tk3yUeT/HWStNbe11r7Sht8NMmHkvzWuM6JSQ6sql8cpx+f5J+mtvuXrbUfttY+lOT7SU5prV0xngH7lyT3HtsdleRlrbX1rbXrx/7XTJ6dSvLy1tpVrbWvJTk7yZoF7uum+vqXJG1iHw/NENS+mSHIrW6tvaS1dl1r7atJ3pTkMQusA1hBhClgLge31nZord25tfaM1tq1SVJVD6+qf6uqb49h68AkOyXJGDA+nuR3q2qHJA9PctLUdi+feH7tLNMzA93vnOS14+W/q5J8O0llOAM041sTz38wse7m2mhfbfhzEW9LctjY9rET+3TnJL88s9647guT7LLAOoAVZNXWLgBYearqFkneneQJSU5rrf13VZ2aIXjMOCHJUzK8z3xiPOO0EF9P8lettekwNh+b+/ey5urrlCQfqqqXZ7hMecjEehe31vZYQI3ACufMFLAQ2ye5RZINSa6vqodnGD806dQMdwA+O8MYqoV6Q5I/raq9kqSqblNVj57nupcnuUNVbb8YfbXWPpthn9+c5IOttZlB7Z9K8r2qen5V/VxVbVtV96yqvefZL7CCCVPAZmutXZ3kWUnekeQ7GS55nT7V5toMZ692T/LPHX29J8krMgz0/l6SCzNcNpyPjyT5QpJvVdWVi9TXKRkGyp88sd6Pkzwiw1iti5NcmSFw3WaedQIrWA3DAAAWX1W9OMmvttYeN2djgBXKmClgSVTVbZMckeFOPoCbLJf5gEVXVU9imisVAAAAN0lEQVTNMCj7A621j23tegCWkst8AAAdnJkCAOggTAEAdBCmAAA6CFMAAB2EKQCADsIUAECH/w/fKkgsVVLIWwAAAABJRU5ErkJggg==
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<p>It is seen that paid users had churned more than free users.</p>

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<h6 id="Page-distribution">Page distribution<a class="anchor-link" href="#Page-distribution">&#182;</a></h6><p>Let see the page distribution of churned and current users to understand the differences between them.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">churned_user</span> <span class="o">=</span> <span class="n">df_pandas</span><span class="p">[</span><span class="n">df_pandas</span><span class="o">.</span><span class="n">churn</span> <span class="o">==</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;page&#39;</span><span class="p">])[</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
<span class="n">churned_user</span> <span class="o">=</span> <span class="n">churned_user</span> <span class="o">/</span><span class="n">churned_user</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

<span class="n">active_user</span> <span class="o">=</span> <span class="n">df_pandas</span><span class="p">[</span><span class="n">df_pandas</span><span class="o">.</span><span class="n">churn</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;page&#39;</span><span class="p">])[</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
<span class="n">active_user</span> <span class="o">=</span> <span class="n">active_user</span> <span class="o">/</span><span class="n">active_user</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

<span class="n">users_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">&#39;Cancelled&#39;</span><span class="p">:</span> <span class="n">churned_user</span><span class="p">,</span><span class="s1">&#39;Active users&#39;</span><span class="p">:</span><span class="n">active_user</span><span class="p">})</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ax</span> <span class="o">=</span> <span class="n">users_df</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">10</span><span class="p">),</span> <span class="n">cmap</span> <span class="o">=</span> <span class="s2">&quot;plasma&quot;</span><span class="p">);</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;Percent of envent occurence (%)&#39;</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Percent of envent occurence for active and cancelled users&#39;</span><span class="p">);</span>
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<p>Since Next Song creates a bias in the figure, I have decided to drop it.</p>

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<div class="prompt input_prompt">In&nbsp;[51]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">churned_user</span> <span class="o">=</span> <span class="n">df_pandas</span><span class="p">[</span><span class="n">df_pandas</span><span class="o">.</span><span class="n">churn</span> <span class="o">==</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;page&#39;</span><span class="p">])[</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;NextSong&#39;</span><span class="p">)</span>
<span class="c1"># Define percentage to visualize better</span>
<span class="n">churned_user</span> <span class="o">=</span> <span class="n">churned_user</span> <span class="o">/</span><span class="n">churned_user</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

<span class="n">active_user</span> <span class="o">=</span> <span class="n">df_pandas</span><span class="p">[</span><span class="n">df_pandas</span><span class="o">.</span><span class="n">churn</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;page&#39;</span><span class="p">])[</span><span class="s1">&#39;userId&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;NextSong&#39;</span><span class="p">)</span>
<span class="c1"># Define percentage to visualize better</span>
<span class="n">active_user</span> <span class="o">=</span> <span class="n">active_user</span> <span class="o">/</span><span class="n">active_user</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span>

<span class="n">users_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">&#39;Cancelled&#39;</span><span class="p">:</span> <span class="n">churned_user</span><span class="p">,</span><span class="s1">&#39;Active users&#39;</span><span class="p">:</span><span class="n">active_user</span><span class="p">})</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ax</span> <span class="o">=</span> <span class="n">users_df</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">10</span><span class="p">),</span> <span class="n">cmap</span> <span class="o">=</span> <span class="s2">&quot;plasma&quot;</span><span class="p">);</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;Percentage of envent occurence (%)&#39;</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Percentage distribution of page events among the active and cancelled users &#39;</span><span class="p">);</span>
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PG7VqGZT9Ldm3Ej3Q27I0/YW5/neaXXelWNJIU70D39bGT5Yrpfco9r9X5EN2Z/Qu14nwxc1c7TDnRDzq5IcgfwfuD5VfWbMaq/j26Y3k10x2UyvS3jxXEzXfL8Orpk8vXA06tqwmu1qq6gu/n6M3RfqG+neyjAneNU+Vdgj7a/X5hE+6tyfE+nOzc/oLtufsN9hxa9h+4L8xl0X3D/le4YwkpeLz0n0fUmnjRq+aq8Tx5J955yO90X+1V5+tZH6fbxUuBiugR/TL333IcDPwF+SpegQ5eE7kP3sICvrKydMdq9gO7BHe9t9c/m3t6/Vfq86HkD3Xk9P8ltwDdovYJV9TW6a/3MVubMCdp6E10P0y10+9k/V9u3mG6je3DC2XTD1FYn9v2A77TX6Zfo7j29ehL7qmksVavawyxJUyfJO4Htq+rPpzoW3VeSRXQ3AX9sLbTleZ5i6f6T4FuBR/iFT9JMYg+OpGkt3f9/slcbhrI/3fCt/5ionmYWz/P0kOQZbZjgHLrHRC+lu2dKkmYMHzIgabrbkm7ozw50w2X+CfjilEakdcHzPD08k26IYOjuWXt+OdRD0gzjEDVJkiRJg+EQNUmSJEmD4RA1rZFtt9225s2bN9VhSJIkaeAuuuiim6pqu4nKmeBojcybN4/FixdPdRiSJEkauCTXTqacQ9QkSZIkDYYJjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRHkiRJ0mCY4EiSJEkaDB8TrTWyopay7K5d1knbcze+ap20K0mSpOGyB0eSJEnSYJjgSJIkSRoMExxJkiRJg2GCM4WSzEty+ahlRyc5cj3GcFCS09bX9iRJkqR1yQRngNLx3EqSJGmD45fgaSrJoiTvS3JeksuT7N+Wb5fk60kuTvKRJNcm2bb1Bn03yQeBi4GdknwoyeIkVyQ5ptf2U5N8L8m5wLN7y+ckOSHJhUkuSfLM9b7jkiRJ0hrwMdHT25yq+v0kTwROAPYE3gKcWVXvSPJUYGGv/G7AS6vqrwCSvLGqfplkNvBfSfYCfgB8FPgD4EfAKb36b2xtvyzJVsAFSb5RVb/qB5Vk4ch2w1bsNLcfwtp07KRK3bb8qHW0fUmSJM009uBMrZpg+ckAVXUOcP+WdBwIfKYt/0/gll69a6vq/N7885JcDFwCPBrYA9gduLqqflhVBXyqV/4Q4KgkS4BFwKbAzr8TXNXxVbWgqhYkc1ZlfyVJkqR1yh6cqXUz8IBRy7YGrm7ToxOgArKS9n7b05LkYcCRwH5VdUuSE+kSlrHa/W014DlV9f2JQ5ckSZKmH3twplBV3QHckOTJAEm2Bp4KnNuKHNqWHwgsq6plbd3z2vJD+N0EacT96RKeZUkeBPxxW/494GFJdm3zh/XqnA68Kkla+3uv8U5KkiRJ65E9OFPvJcC/JPmnNn9MVf245Ri3JDmPLll52ch64OQkhwJnAzcAtwNb9ButqkuTXAJcAVwFfKst/027h+YrSW6iS5j2bNXeBrwPuKwlOdcAT1/7uyxJkiStG+luw9B0k2QRcGRVLR61fBNgRVXdneQA4ENVNX8qYgSYPWvHmrPJEVO1ecCHDEiSJG0IklxUVQsmKmcPzsyzM3Bq+39u7gJeMcXxSJIkSdOGCc40VVUHjbP8h4D3xkiSJEljMMHRGtl7n+1ZvNghYpIkSZoefIqaJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRHkiRJ0mCY4EiSJEkaDBMcSZIkSYOx0VQHoJltRS1l2V27THUYkiRJWsfmbnzVVIcwKfbgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHDWUJJtkixpfzcm+VmbvjXJletom4uSLFiNevOSXD5q2dFJjlx70UmSJElTxwRnDVXVzVU1v6rmAx8G3tum5wP3TG10kiRJ0obFBGfdmp3ko0muSHJGks3gvj0wSbZNck2bPjzJF5J8OcnVSY5I8jdJLklyfpKte22/KMl5SS5Psn+r/6Reb9IlSbZclWBbXO8b3a4kSZI0U5jgrFuPAP6lqh4N3Ao8ZxJ19gReAOwP/CPw66raG/g28JJeuTlV9fvAXwEntGVHAn/depCeACxfjZjHaleSJEmaEfx/cNatq6tqSZu+CJg3iTpnVdXtwO1JlgFfbsuXAnv1yp0MUFXnJLl/kq2AbwHvSfJp4PNV9dNRbdc42+wv/512q+rWfuEkC4GFAGErdpq7cBK7JUmStHbctvyoqQ5B05g9OOvWnb3pFdybUN7Nvcd+05XUuac3fw/3TUhHJytVVccCLwc2A85PsvuoMjcDDxi1bGvgppW1y+gFVcdX1YKqWpDMGb1akiRJmjImOFPjGmDfNv3c1WzjUIAkBwLLqmpZkl2ramlVvRNYDNwnwamqO4Abkjy51d0aeCpw7sraXc34JEmSpPXOIWpT493AqUleDJy5mm3ckuQ84P7Ay9qy1yY5mK636Erga2PUewnwL0n+qc0fU1U/nqBdSZIkaUZI1Xi3ZWhDk2QRcGRVLZ5sndmzdqw5mxyx7oKSJEkaxXtwNkxJLqqqCf8vSIeoSZIkSRoMh6jpt6rqoKmOQZIkSVoTJjhaI3vvsz2LF9tNLEmSpOnBIWqSJEmSBsMER5IkSdJgmOBIkiRJGgwTHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDcZGUx2AZrYVtZRld+0y1WFoHZu78VVTHYIkSdKk2IMjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4TZJtkixpfzcm+VmbvjXJletom4uSLFjNuitafFckuTTJ3yTxfEqSJGmD5lPUmqq6GZgPkORo4I6qeneSecBpUxfZuJZX1Ui8DwROAuYCb5nSqCRJkqQp5C/+kzM7yUdbb8kZSTaD+/bAJNk2yTVt+vAkX0jy5SRXJzmi9bBckuT8JFv32n5RkvOSXJ5k/1b/Sb3epEuSbLmy4Krqv4GFwBHpbJrk35IsbfUPbu1+NclebfqSJG9u029L8vIkB7V9+lyS7yX5dJKs3UMpSZIkrTv24EzOI4DDquoVSU4FngN8aoI6ewJ7A5sCPwLeUFV7J3kv8BLgfa3cnKr6/SRPBE5o9Y4E/rqqvpVkC+A3EwVYVVe1IWoPBF7Ulj0mye7AGUkeCZwDPKElYncDj2/VD2z78+AW86OB64FvtTLn9reVZCFdQkXYip3mLpwoPM14x66zlm9bftQ6a1uSJG147MGZnKurakmbvgiYN4k6Z1XV7VX1C2AZ8OW2fOmo+icDVNU5wP2TbEWXWLwnyauBrarq7knGOdLbciDwydbu94BrgUcC3wSe2NZ/BdgiyebAvKr6fqt7QVX9tKruAZaMta9VdXxVLaiqBcmcSYYmSZIkrXsmOJNzZ296Bff2fN3Nvcdw05XUuac3fw/37TmrUfWqqo4FXg5sBpzfemFWKskuLbb/5t5EZ7QLgQXAE+h6cy4BXkGXtI0Vd39fJUmSpGnPBGfNXAPs26afu5ptHAqQ5EBgWVUtS7JrVS2tqncCi4GVJjhJtgM+DBxXVUWXvLywrXsksDPw/aq6C7gOeB5wPl2PzpHtX0mSJGnG89f5NfNu4NQkLwbOXM02bklyHnB/4GVt2WvbgwFWAFcCXxuj3mZJlgD3o+tJ+iTwnrbug8CHkyxt6w6vqpGemW8CT66qXyf5JrAjJjiSJEkaiHQ/+EurZ/asHWvOJkdMdRiawXzIgCRJmowkF1XVhP+HpEPUJEmSJA2GQ9S0RvbeZ3sWL/YXeEmSJE0P9uBIkiRJGgwTHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgbTXUAmtlW1FKW3bXLuOvnbnzVeoxGkiRJGzp7cCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgZjg0hwkrwxyRVJLkuyJMnjJih/dJIj12B7r0zykjZ9eJIdxim3KMmC3vy8JJev7nZXV5Jrkmy7vrcrSZIkrW2Df4pakgOApwP7VNWd7Yv8xutym1X14d7s4cDlwPXrcpujJdmoqu5en9uUJEmSptqG0IPzYOCmqroToKpuqqrr4b49F0kWJFnUq/fYJGcm+WGSV7QyByU5O8mpSX6Q5NgkL0xyQZKlSXZt5Y5OcmSS5wILgE+3nqPNJht06/n5YpL/TPL9JG/prXtTku8l+XqSk0d6m1qP0P9NcjbwmiTPSPKdJJck+UaSB7Vy2yQ5oy3/CJBe2y9q+7MkyUeSzF6NYy5JkiRNicH34ABnAG9O8gPgG8ApVXX2JOrtBfweMAe4JMlX2vLHAo8CfglcBXysqvZP8hrgVcBrRxqoqs8lOQI4sqoWr0bs+wN7Ar8GLuzF8Bxgb7rzdzFwUa/OVlX1JIAkDwB+r6oqycuB1wOvA94CnFtVb03yNGBhK/8o4FDg8VX1P0k+CLwQ+EQ/qCQLf1uHrdhp7sKV7MKx3Lb8qNXYdUmSJGnVDT7Bqao7kuwLPAE4GDglyVFVdeIEVb9YVcuB5UnOoks2bgUurKobAJL8mC6BAlja2l+l8CZY9vWqurlt6/PAgaNiI8mXR9U/pTe9I93+PphuWN7VbfkTgWcDVNVXktzSlj8Z2JcumQLYDPjv3wmw6njgeIDZs3Ycax8kSZKkKTH4BAegqlYAi4BFSZYCfw6cCNzNvcP0Nh1dbZz5O3vL7unN38OqH8+bgQf05rcGbpoghomGFf6qN/3PwHuq6ktJDgKOXknb0A1V+3hV/d0E25AkSZKmpcHfg5NktySP6C2aD1zbpq+h67GAbthX3zOTbJpkG+Ag4MLVDOF2YMtx1i0CXpTWXUKXeJ3VW/+HSbZu9+48C/gWcC7wjBbbFsDTVrLtucDPem2POIdu6BlJ/ph7k6z/Ap6b5IFt3dZJHjrxLkqSJEnTw+ATHGAL4ONJrkxyGbAH9/ZkHAO8P8k3gRWj6l0AfAU4H3jbyIMJVsOJwIfHecjA8XQJ0KVJLm2xvru3/lzgk8AS4N+ranFVXQh8CbgU+DywGFg2zraPBj7b9q/fM3QM8MQkFwOHAD8BqKorgX8AzmjH6ut0D2mQJEmSZoRUeQvFdJTkcGBBVR0xxrot2r1Fm9P1xiysqovXd4zQ3YMzZ5PfCfE+fMiAJEmS1lSSi6pqwUTlNoh7cAbo+CR70N039PGpSm4kSZKk6cYeHK2RBQsW1OLFq/MEbEmSJGnyJtuDsyHcgyNJkiRpA2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRHkiRJ0mCY4EiSJEkaDBMcSZIkSYNhgiNJkiRpMExwJEmSJA2GCY4kSZKkwTDBkSRJkjQYJjiSJEmSBsMER5IkSdJgmOBojayopSy7axeW3bXLVIciSZIkmeBIkiRJGg4THEmSJEmDYYIjSZIkaTBmTIKT5I1JrkhyWZIlSR43Qfmjkxy5Btt7ZZKXtOnDk+wwTrkTk1yd5NIkP0jyiSQPWd3trm9JDkpy2lTHIUmSJK0NG011AJOR5ADg6cA+VXVnkm2BjdflNqvqw73Zw4HLgevHKf63VfW5JAFeC5yVZM+qumtdxjieFkeq6p6p2L4kSZI0VWZKD86DgZuq6k6Aqrqpqq4HSHJNS3hIsiDJol69xyY5M8kPk7yilTkoydlJTm09LscmeWGSC5IsTbJrK3d0kiOTPBdYAHy69RxtNl6Q1XkvcCPwx62dw1q7lyd5Z1v2vCTvadOvSXJVm941ybm9/TomycWt/u5t+XZJvt6WfyTJtUm2TTIvyXeTfBC4GNgpyYeSLG49X8eMxJnkqUm+17b17N7yOUlOSHJhkkuSPHN1T5gkSZI0FWZKgnMG3Rf2HyT5YJInTbLeXsDTgAOAN/eGmT0WeA3wGODFwCOran/gY8AQ/IxwAAAgAElEQVSr+g1U1eeAxcALq2p+VS2fxHYvBnZv23sn8AfAfGC/JM8CzgGe0Mo+Abi5DWs7EPhmr52bqmof4EPAyHC7twBntuX/AezcK78b8Imq2ruqrgXeWFUL2nF4UpK9kmwKfBR4Rtv29r36b2xt7wccDLwryZzRO5dkYUucFl968ebsNHchO81dOInDIkmSJK1bMyLBqao7gH2BhcAvgFOSHD6Jql+squVVdRNwFrB/W35hVd3QeoR+TJdAASwF5q2FkNP+3Q9YVFW/qKq7gU8DT6yqG4EtkmwJ7AScBDyRLuHoJzifb/9e1IvrQOAzAFX1n8AtvfLXVtX5vfnnJbkYuAR4NLAHsDtwdVX9sKoK+FSv/CHAUUmWAIuATblvAkXb7vFVtaCqFoyR/0iSJElTZkbcgwNQVSvovnQvSrIU+HPgROBu7k3UNh1dbZz5O3vL7unN38PaOSZ7A//FyhPIbwMvBb5Pl9S8jK6n6XW9MiNxrejFFcb3q5GJJA+j6/XZr6puSXIi9x6f0cflt9WA51TV91eyDUmSJGnamhE9OEl2S/KI3qL5wLVt+hq63h2A54yq+swkmybZBjgIuHA1Q7gd2HIScSbJq+nuGfpP4Dt0Q8O2TTIbOAw4uxU/hy4BOYeuh+Vg4M6qWjbBZs4Fnte2dwjwgHHK3Z8u4VmW5EG0e4KA7wEPG7nXqMU04nTgVe0hBSTZe6J9liRJkqaTGZHgAFsAH09yZZLL6IZaHd3WHQO8P8k36Xo6+i4AvgKcD7xt5MEEq+FE4MMrecjAu5JcCvyAbljawVV1V1XdAPwd3fC4S4GLq+qLrc436YanndN6p66jS14mcgxwSBt69sfADXQJ2H1U1aV0idMVwAnAt9ry39AN9ftKe8jAtb1qbwPuB1yW5PI2L0mSJM0Y6W7D0EyRZBNgRVXd3R6f/aGqmj9V8cyetWPN2eQIAG5bftRUhSFJkqSBS3JRe4DWSs2Ye3D0WzsDpyaZBdwFvGKK45EkSZKmDROcGaaqfkj3EANJkiRJo5jgaI3svc/2LF7s0DRJkiRNDzPlIQOSJEmSNCETHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgbTXUAmtlW1FKW3bXLVIcx7c3d+KqpDkGSJGmDYA+OJEmSpMEwwZEkSZI0GCY4kiRJkgbDBGeaSPLGJFckuSzJkiSPW0nZw5Ps0Jt/bZLNe/NfTbLVuo5ZkiRJmm5McKaBJAcATwf2qaq9gKcA162kyuHADr351wK/TXCq6k+q6tZ1EKokSZI0rZngTA8PBm6qqjsBquqmqro+yb5Jzk5yUZLTkzw4yXOBBcCnW0/Pa+iSnbOSnAWQ5Jok2yaZl+S7ST7aeofOSLJZK7Nf6y36dpJ3Jbm8LX90kgta25clecSUHBFJkiRpNaSqpjqGDV6SLYBz6XphvgGcApwHnA08s6p+keRQ4I+q6mVJFgFHVtXiVv8aYEFV3dSfB7YAftTWLUlyKvClqvpUS2gWVtV5SY4Fnl5Veyb5Z+D8qvp0ko2B2VW1fFS8C4GFAGGrfbfY9A3r8OgM123Lj5rqECRJkmaMJBdV1YKJyvn/4EwDVXVHkn2BJwAH0yU4bwf2BL6eBGA2cMNqNH91VS1p0xcB89r9OVtW1Xlt+Ul0Q+QAvg28McmOwOer6odjxHs8cDzA7Fk7miFLkiRp2jDBmSaqagWwCFiUZCnw18AVVXXAGjZ9Z296BbAZkJXEcVKS7wBPA05P8vKqOnMNY5AkSZLWC+/BmQaS7DbqXpf5wHeB7doDCEhyvySPbutvB7bslR89v1JVdQtwe5Lfa4ue34tlF+CqqvoA8CVgr1XdH0mSJGmqmOBMD1sAH09yZZLLgD2ANwPPBd6Z5FJgCfD7rfyJwIfbgwA2oxsu9rWRhwxM0l8Axyf5Nl2PzrK2/FDg8iRLgN2BT6zZrkmSJEnrjw8Z2EAl2aKq7mjTRwEPrqrXrGo7s2ftWHM2OWKtx7ch8CEDkiRJk+dDBjSRpyX5O7pr4Fq6/1tHkiRJmtFMcDZQVXUK3dPaJEmSpMEwwdEa2Xuf7Vm82KFWkiRJmh58yIAkSZKkwTDBkSRJkjQYJjiSJEmSBsMER5IkSdJgmOBIkiRJGgwTHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg7HRVAegmW1FLWXZXbusVt25G1+1lqORJEnShs4eHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgnOOJK8MckVSS5LsiTJ49bhtnZLsqht57tJjp+g/LwkL+jNz0/yJ735P01y1LqKV5IkSZqufMjAGJIcADwd2Keq7kyyLbDxOtzkB4D3VtUX2/YfM0H5ecALgJPa/HxgAfBVgKr6EvCldRKpJEmSNI3ZgzO2BwM3VdWdAFV1U1VdD5DkzUkuTHJ5kuPTeVSSC0Yqtx6Wy9r0vknOTnJRktOTPHic7f10ZKaqlra6s5O8q23vsiR/2YocCzyh9fi8AXgrcGibPzTJ4UmOa22cmOQDSc5LclWS57bls5J8sPVSnZbkq711xya5sm3z3Wv1yEqSJEnrkAnO2M4Adkryg5YEPKm37riq2q+q9gQ2A55eVd8FNk4y8rzkQ4FTk9wP+GfguVW1L3AC8I9jbO+9wJlJvpbk/yTZqi3/C2BZVe0H7Ae8IsnDgKOAb1bV/Kp6J/Bm4JQ2f8oY7T8YOJCuV+rYtuzZdD1BjwFeDhwAkGRr4H8Bj66qvYC3T/6wSZIkSVPLIWpjqKo7kuwLPAE4GDglyVFVdSJwcJLXA5sDWwNXAF8GTgWeR5dAHNr+dgP2BL6eBGA2cMMY2/u3JKcDTwWeCfxlkscChwB7jfSsAHOBRwB3reIufaGq7gGuTPKgtuxA4LNt+Y1JzmrLbwN+A3wsyVeA00Y3lmQhsBAgbMVOcxeuYjgjulzrtuXeLiRJkqS1wwRnHFW1AlgELEqyFPjzJJ8BPggsqKrrkhwNbNqqnAJ8Nsnnu+r1w3YvzRVVdcAktnc9XQ/PCUkup0uMAryqqk7vl01y0Cruzp396qP+HR3H3Un2B54MPB84AviDUWWOB44HmD1rx1rFWCRJkqR1xiFqY2hPNXtEb9F84FruTWZuSrIFMNKzQlX9GFgBvIku2QH4PrBde2gBSe6X5NFjbO+pbTgbSbYHtgF+BpwO/O/eukcmmQPcDmzZa2L0/GScCzyn3YvzIOCgto0tgLlV9VXgtW3fJUmSpBnBHpyxbQH8c7sX5m7gR8DCqro1yUeBpcA1wIWj6p0CvAt4GEBV3dWGl30gyVy64/0+umFtfYcA70/ymzb/t1V1Y5KP0d0nc3G6MW6/AJ4FXAbcneRS4ETg48BRSZYA75jkPv47XS/N5cAPgO8Ay+gSpS8m2ZSul+f/TLI9SZIkacqlyhFGG6okW7T7jbYBLgAeX1U3rkobs2ftWHM2OWKN4vAeHEmSJE0kyUVVtWCicvbgbNhOa71UGwNvW9XkRpIkSZpuTHA2YFV10FTHIEmSJK1NJjhaI3vvsz2LFzvETJIkSdODT1GTJEmSNBgmOJIkSZIGwwRHkiRJ0mCY4EiSJEkaDBMcSZIkSYNhgiNJkiRpMExwJEmSJA2GCY4kSZKkwTDBkSRJkjQYJjiSJEmSBsMER5IkSdJgmOBIkiRJGgwTHEmSJEmDYYIjSZIkaTA2muoANLOtqKUsu2uXqQ5DWm1zN75qqkOQJElrkT04kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCsxYlWZFkSZLLk3w5yVYTlJ+X5PI2fVCS01ZS9v1JfpZk3HOW5Jok267+Htynrb9fG+1IkiRJ65MJztq1vKrmV9WewC+Bv14bjbak5n8B1wFPXBttrmRbadszwZEkSdKMY4Kz7nwbeAj8Nml4V+vZWZrk0FVs62DgcuBDwGEjC5Nsk+SMJJck+QiQtvydSf6qV+7oJK9r03+b5MIklyU5pi2bl+S7ST4IXAz8K7BZ64369GofAUmSJGk98//BWQeSzAaeTJcoADwbmA88FtgWuDDJOavQ5GHAycAXgf+b5H5V9T/AW4Bzq+qtSZ4GLGzlPwO8D/hgm38e8NQkhwCPAPanS4a+lOSJwE+A3YCXVtVftX34s6qaP87+LRzZVtiKneYuHKuYNEMcO9UBaBJuW37UVIcgSZoh7MFZuzZLsgS4Gdga+HpbfiBwclWtqKqfA2cD+02mwSQbA38CfKGqbgO+AxzSVj8R+BRAVX0FuKVNXwI8MMkOSR4L3FJVP2n1DgEuoeup2Z0u4QG4tqrOn0xMVXV8VS2oqgXJnMlUkSRJktYLe3DWruVVNT/JXOA0untwPkAbOraangrMBZYmAdgc+DXwlba+xqn3OeC5wPZ0PTq0ON5RVR/pF0wyD/jVGsQoSZIkTQv24KwDVbUMeDVwZJL7AecAhyaZnWQ7up6XCybZ3GHAy6tqXlXNAx4GHJJk89buCwGS/DHwgF69zwDPp0tyPteWnQ68LMkWrc5DkjxwnO3+T4tdkiRJmjFMcNaRNkzsUrok4z+Ay9r8mcDrq+rGidpoScwfcW9vDVX1K+Bc4BnAMcATk1xMN/TsJ71yVwBbAj+rqhvasjOAk4BvJ1lKl/hsOc7mjwcu8yEDkiRJmklSNd4IJ2lis2ftWHM2OWKqw5A0cD5kQJKU5KKqWjBROXtwJEmSJA2GDxnQGtl7n+1ZvNhfViVJkjQ92IMjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRHkiRJ0mBsNNUBaGZbUUtZdtcuUx2GNlBzN75qqkOQJEnTjD04kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCM80luWOKtvvaJJtPxbYlSZKk1WWCo/G8FjDBkSRJ0oxigjMDJXlokv9Kcln7d+e2fNck5ye5MMlbR3p/0nlXksuTLE1yaFt+UJLTeu0el+TwJK8GdgDOSnLWVOyjJEmStDr8f3BmpuOAT1TVx5O8DPgA8Czg/cD7q+rkJK/slX82MB94LLAtcGGSc8ZrvKo+kORvgIOr6qbR65MsBBYChK3Yae7CtbVf0io6FoDblh81xXFIkqTpwh6cmekA4KQ2/UngwN7yz7bpk3rlDwROrqoVVfVz4Gxgv9XdeFUdX1ULqmpBMmd1m5EkSZLWOhOcYagJ1mec5Xdz32tg07UTjiRJkjQ1THBmpvOA57fpFwLntunzgee06ef3yp8DHJpkdpLtgCcCFwDXAnsk2STJXODJvTq3A1uuo/glSZKkdcJ7cKa/zZP8tDf/HuDVwAlJ/hb4BfDStu61wKeSvA74CrCsLf8PuuFrl9L19ry+qm4ESHIqcBnwQ+CS3naOB76W5IaqOnid7JkkSZK0lqVqotFNmina/1uzvKoqyfOBw6rqmetym7Nn7VhzNjliXW5CmpAPGZAkafiSXFRVCyYqZw/OsOwLHJckwK3Ay6Y4HkmSJGm9sgdHa2TBggW1ePHiqQ5DkiRJAzfZHhwfMiBJkiRpMExwJEmSJA2GCY4kSZKkwTDBkSRJkjQYJjiSJEmSBsMER5IkSdJgmOBIkiRJGgwTHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRqMjaY6AM1sK2opy+7aZarDkCRJa8Hcja+a6hCkNWYPjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRnBkpyx6j5w5McN1XxSJIkSdOFCY4kSZKkwTDBGZgkD03yX0kua//u3JafmORDSc5KclWSJyU5Icl3k5zYq39Ikm8nuTjJZ5NsMWU7I0mSJK0iHxM9M22WZElvfmvgS236OOATVfXxJC8DPgA8q617APAHwJ8CXwYeD7wcuDDJfOCnwD8AT6mqXyV5A/A3wFv7G0+yEFgIELZip7kL18EuSpKkNXXb8qOmOgRpvTPBmZmWV9X8kZkkhwML2uwBwLPb9CeB/9er9+WqqiRLgZ9X1dJW/wpgHrAjsAfwrSQAGwPfHr3xqjoeOB5g9qwda63tlSRJkrSGTHCGr5+A3Nn+vac3PTK/EbAC+HpVHbaeYpMkSZLWKu/BGZ7zgOe36RcC565C3fOBxyd5OECSzZM8ci3HJ0mSJK0zJjjD82rgpUkuA14MvGayFavqF8DhwMmt/vnA7usiSEmSJGldSJW3UGj1zZ61Y83Z5IipDkOSJI3BhwxoSJJcVFULJipnD44kSZKkwTDBkSRJkjQYPkVNa2TvfbZn8WK7vyVJkjQ92IMjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJjiRJkqTBMMGRJEmSNBgmOJIkSZIGwwRHkiRJ0mBsNNUBaGZbUUtZdtcuUx3GtDZ346umOgRJkqQNhj04kiRJkgbDBEeSJEnSYJjgSJIkSRoME5wBSXLHqPnDkxw3QZ0Jy0iSJEkzhQmOJEmSpMEwwdlAJNkuyb8nubD9PX6MMicm+XCSbyb5QZKnT0WskiRJ0uryMdHDslmSJb35rYEvten3A++tqnOT7AycDjxqjDbmAU8CdgXOSvLwqvpNv0CShcBCgLAVO81duHb3YgBuW37UVIcgSZK0QTLBGZblVTV/ZCbJ4cCCNvsUYI8kI6vvn2TLMdo4taruAX6Y5Cpgd6CfNFFVxwPHA8yetWOt1T2QJEmS1oAJzoZjFnBAVS3vL+wlPCNGJywmMJIkSZoxvAdnw3EGcMTITJL545T7sySzkuwK7AJ8f30EJ0mSJK0NJjgbjlcDC5JcluRK4JXjlPs+cDbwNeCVo++/kSRJkqazVDkCSZ0kJwKnVdXnJltn9qwda84mR0xccAPjQwYkSZLWriQXVdWCicrZgyNJkiRpMHzIgH6rqg6f6hgkSZKkNWGCozWy9z7bs3ixw7EkSZI0PThETZIkSdJgmOBIkiRJGgwTHEmSJEmDYYIjSZIkaTBMcCRJkiQNhgmOJEmSpMEwwZEkSZI0GCY4kiRJkgbDBEeSJEnSYJjgSJIkSRoMExxJkiRJg2GCI0mSJGkwTHAkSZIkDYYJzv9v797D7arqe/+/P4SQcA2CIGiQABW5m4SAIogRFaxSJUIFSkWwcqkipd6Keo7Q2iIH/FV/CCKgFBEMKDRIlWIqRMJFJRcCgSQYgXC4WK4ViIaL4Xv+WDNhsd03kp3sZOX9ep717DnHHGPM75wz68n6rjHmXJIkSZI6xtqDHYBWb4trNk89v+0rajNinXtXUDSSJEla0zmCI0mSJKljmOBIkiRJ6hgmOJIkSZI6hvfgdIAki4HZbUWXVdXpgxWPJEmSNFhMcDrDoqoa3VuFJEOqanHb+tpV9ce+Ou5vPUmSJGlVYILTwZIsAC4E9gfOTnI8cAuwN3B1kiua7ZsBjwFHV9X/TXIR8CQwBpgJfHrlRy9JkiS9ciY4nWHdJLPa1r9SVZc3y89W1T4ATYKzcVW9vVn/D+Diqvpuko8CZwEHNe22B97VPuojSZIkrepMcDpDb1PULu9lfS/gg83y94Az2rb9sKfkJsmxwLEAYWO2GnFsr8E9vejkXrdLkiRJA8WnqHW+3/ex3q76U6+qzq+qcVU1Lll/uYKTJEmSBpIJzprtFuCwZvkI4KZBjEWSJElabk5R6wxd78G5tqr6My/sRODCJJ+lecjAColOkiRJWklMcDpAVQ3poXxUl/XxXdYXAPt10+6oAQtOkiRJWomcoiZJkiSpY5jgSJIkSeoYTlHTchkzdgumT/cx0JIkSVo1OIIjSZIkqWOY4EiSJEnqGCY4kiRJkjqGCY4kSZKkjmGCI0mSJKljmOBIkiRJ6hgmOJIkSZI6hgmOJEmSpI5hgiNJkiSpY5jgSJIkSeoYJjiSJEmSOoYJjiRJkqSOYYIjSZIkqWOY4EiSJEnqGGsPdgBavS2u2Tz1/LaDHYa6MWKdewc7BEmSpJXOERxJkiRJHcMER5IkSVLHMMGRJEmS1DFMcCRJkiR1DBOcAZBkcZJZSe5KcnuSTyVZbc5tkouSHDLYcUiSJEnLy6eoDYxFVTUaIMnmwPeBEcApgxVQkrWr6o+DtX9JkiRpMKw2owyri6p6FDgWOCEtw5P8W5LZSW5L8g6AJNck2a1Zvi3Jl5rlLyf5WJLxSX6e5Iok85JcmiRNnfc2ZTclOSvJj5vyU5Ocn2QycHGSUUluTDKzeb21qZckZyeZk+QnwOZL4k+ye5IbksxI8tMkW67M8ydJkiQtD0dwVoCqureZorY58NdN2a5JdgAmJ9kemAq8LckC4I/A3k3zfYBLgC2BMcDOwMPAzcDeSaYD5wH7VtV9SSZ22f3uwD5VtSjJesC7q+rZJG8AJgLjgAnAG4FdgdcAc4ALkwwFvgF8oKoeS3Io8C/AR9t3kORYWkkcYWO2GnHs8p80LbenF5082CFIkiQNOhOcFSfN331oJQ1U1bwk9wPbAzcCJwL3AT8B3t0kJKOq6u5m5OTWqnoQIMksYBSwELi3qu5r+p9Ik2w0rq6qRc3yUODsJKOBxc1+AfYFJlbVYuDhJNc35W8EdgH+qxksGgL8tuuBVdX5wPkAQ9YaWctwbiRJkqQVwgRnBUiyLa2E4lFeSnS6mkZrNOVe4L+AVwPHADPa6jzXtryY1vXqqb8lft+2/PfAI8CbaE1HfLZtW3eJSYC7qmqvPvYhSZIkrZK8B2eAJdkM+BZwdlUVraloRzTbtgdeD9xdVc8DDwAfAn5Ja0TnM83f3swDtk0yqlk/tJe6I4DfVtWLwIdpjcjQxHRYkiHNSNE7mvK7gc2S7NXEOzTJzv05bkmSJGlV4AjOwFi3mUI2lNb9NN8D/rXZ9k3gW0lmN9uOqqolIzM3Au+sqj8kuREYSR8JTnNvzceBa5M8DtzaS/VvAlcm+UtgCi+N7kwC9gNmA78Gbmj6fr55XPRZSUbQ+vfxdeCufp4HSZIkaVClNcig1UmSDapqYfNUtXOA+VX1tcGIZchaI2v9YScMxq7VhQ8ZkCRJnSzJjKoa11c9p6itno5pRozuojUN7bxBjkeSJElaJTiCo+Uybty4mj59+mCHIUmSpA7nCI4kSZKkNY4JjiRJkqSOYYIjSZIkqWOY4EiSJEnqGCY4kiRJkjqGCY4kSZKkjmGCI0mSJKljmOBIkiRJ6hgmOJIkSZI6hgmOJEmSpI5hgiNJkiSpY5jgSJIkSeoYJjiSJEmSOoYJjiRJkqSOYYIjSZIkqWOY4EiSJEnqGCY4kiRJkjqGCY4kSZKkjmGCI0mSJKlj9JngJNkiyWVJ7kkyJ8k1SbZfGcElWdj8HZXkzj7qjkryV23r45KcNUBxbJDkvOYc3JVkapI3L2NfOySZleS2JNsluWUgYuxmP6OTvLdt/f1JTl4R+5IkSZJWFb0mOEkCTAJ+XlXbVdVOwBeA16yM4F6hUcDSBKeqplfViQPU97eBJ4E3VNXOwFHAq5exr4OAH1XVmKq6p6re2rVCkiHLHOlLRgNLE5yqurqqTh+AfiVJkqRVVl8jOO8AXqiqby0pqKpZVXVjM6pxXZKZSWYn+QAsHUmZm+SCZrRjcpJ1m21/luRnSW5v2m3XlH82ybQkdyT5x94Cavq/sWk/M8mSBOF04G3N6MjfJxmf5MdNm02SXNX0/8skuzXlpya5MMnPk9yb5E8SoibGNwP/q6pebM7BvVX1k2b7p5Lc2bxO6u0cNCMqJwEfSzKlqbtklGp8kilJvg/MbvqYl+TbTd+XJnlXkpuTzE+yZ9NuzyS3NCNCtyR5Y5J1gH8CDm3Ox6FJjkpydtNm6+ba3dH8fX1TflGSs5p+7k1ySB//PiRJkqRVytp9bN8FmNHDtmeBCVX1dJJXA79McnWz7Q3A4VV1TJIfAAcDlwCXAqdX1aQkw4G1kuzf1N8TCHB1kn2ramoP+30UeHdVPZvkDcBEYBxwMvCZqjoQWglDW5t/BG6rqoOS7AdcTGuEA2AHWonchsDdSc6tqhfa2u4MzKqqxV0DSbI7cDStBCjAr5LcAPxPd+egqi5J8i1gYVV9tZtj2xPYparuSzIK+DPgL4FjgWm0Rqj2Ad5PayTtIGAesG9V/THJu4DTqurgJF8CxlXVCU2sR7Xt52zg4qr6bpKPAmc1fQFs2exjB+Bq4IpujvvYJibCxmy07rINDD29yBlzkiRJGlh9JTi9CXBakn2BF4HX8dLUtfuqalazPAMYlWRD4HVVNQmgqp4FaBKc/YHbmvob0EoOekpwhgJnJxkNLAb6cz/QPrSSLKrq+iSbJhnRbPtJVT0HPJfk0eYYHuxHn0v6nVRVv2+O5d+Bt9FKDP7kHPSjv1ur6r629fuqanbT913AdVVVSWa39TcC+G6T7BWt89OXvYAPNsvfA85o23ZVM1I1J0m3UxGr6nzgfIAha42sfuxPkiRJWin6SnDuAnqapnQEsBmwe1W9kGQBMLzZ9lxbvcXAurQSou4E+EpVndeviOHvgUeAN9GaYvdsP9p0t+8lH8y7xtr1nNwFvCnJWkumqPXR7xLdnYO+/L6XPl5sW3+xLc4vA1OqakIz6vPzfuynq/YkpX2fvR2fJEmStMrp6x6c64FhSY5ZUpBkjyRvpzVy8GiT3LwD2Lq3jqrqaalfgCwAACAASURBVODBJAc1/QxLsh7wU+CjSTZoyl+XZPNeuhoB/LZJNj4MLLkh/xla08y6M5VWQrZk6trjTTx9qqp7gOnAPyZJ08cb0rrnaCpwUJL1kqwPTABu7E+/A2gE8FCzfFRbeW/n4xbgsGb5COCmFRKZJEmStJL1muBUVdH60P7uNI9IBk4FHqZ1P824JNNpfUie14/9fRg4MckdtD5kb1FVk4HvA79opl5dQc8fzAG+CXwkyS9pTU9bMupxB/DHtB5g8Pdd2pzaxHoHrYcRfKQfsbb7GLAF8JsmxguAh6tqJnARcCvwK+DbVXVbj72sGGcAX0lyMy8lewBTgJ2WPGSgS5sTgaOb8/Fh4O9WTqiSJEnSipVWDiMtmyFrjaz1h52wTG19yIAkSZL6K8mMqhrXV70+f+hTkiRJklYXy/MUNYkxY7dg+nRHYiRJkrRqcARHkiRJUscwwZEkSZLUMUxwJEmSJHUMExxJkiRJHcMER5IkSVLHMMGRJEmS1DFMcCRJkiR1DBMcSZIkSR3DBEeSJElSxzDBkSRJktQxTHAkSZIkdQwTHEmSJEkdwwRHkiRJUscwwZEkSZLUMUxwJEmSJHUMExxJkiRJHcMER5IkSVLHMMGRJEmS1DFMcCRJkiR1DBOc1UCSLZJcluSeJHOSXJNk+5Ww34Ureh+SJEnSQDLBWcUlCTAJ+HlVbVdVOwFfAF4zuJFJkiRJqx4TnFXfO4AXqupbSwqqahZwW5LrksxMMjvJBwCSjEoyN8kFSe5KMjnJus22P0vysyS3N+22a8o/m2RakjuS/ONgHKQkSZI0ENYe7ADUp12AGd2UPwtMqKqnk7wa+GWSq5ttbwAOr6pjkvwAOBi4BLgUOL2qJiUZDqyVZP+m/p5AgKuT7FtVU3sKKMmxwLEAYWM2Wvf0ZTqwpxedvEztJEmSpJ6Y4Ky+ApyWZF/gReB1vDRt7b5mlAdaydGoJBsCr6uqSQBV9SxAk+DsD9zW1N+AVsLTY4JTVecD5wMMWWtkDeRBSZIkScvDBGfVdxdwSDflRwCbAbtX1QtJFgDDm23PtdVbDKxLKyHqToCvVNV5AxOuJEmSNHi8B2fVdz0wLMkxSwqS7AFsDTzaJDfvaNZ7VFVPAw8mOajpY1iS9YCfAh9NskFT/rokm6+gY5EkSZJWKBOcVVxVFTABeHfzmOi7gFOBa4BxSabTGs2Z14/uPgycmOQO4BZgi6qaDHwf+EWS2cAVwIYDfySSJEnSipfW52dp2QxZa2StP+yEZWrrQwYkSZLUX0lmVNW4vuo5giNJkiSpY5jgSJIkSeoYPkVNy2XM2C2YPt2pZpIkSVo1OIIjSZIkqWOY4EiSJEnqGCY4kiRJkjqGCY4kSZKkjmGCI0mSJKljmOBIkiRJ6hgmOJIkSZI6hgmOJEmSpI5hgiNJkiSpY5jgSJIkSeoYJjiSJEmSOoYJjiRJkqSOYYIjSZIkqWOY4EiSJEnqGGsPdgBavS2u2Tz1/LaDHYYkrVJGrHPvYIcgSWssR3AkSZIkdQwTHEmSJEkdwwRHkiRJUscwwekiyYQklWSHXupclOSQbsrHJ/lxN+Wjk7z3FcYxPslTSW5LMjfJKb3to599HpXk7Gb5+CRH9rH/ty7LfiRJkqTBYoLzpw4HbgIOG8A+RwOvKMFp3FhVY4BxwF8n2X2gAqqqb1XVxb1UGQ+Y4EiSJGm1YoLTJskGwN7A39CW4KTl7CRzkvwE2Lxt23uSzEtyE/DBbvpcB/gn4NAks5IcmmSTJFcluSPJL5Ps1ltcVfV7YAawXZe+90xySzPKc0uSNzblNyYZ3Vbv5q77SHJqks80yyc2x3ZHksuSjAKOB/6+iflt/Th9kiRJ0qDzMdEvdxBwbVX9OsmTScZW1UxgAvBGYFfgNcAc4MIkw4ELgP2A3wCXd+2wqp5P8iVgXFWdAJDkG8BtVXVQkv2Ai2mN8nQryabAW4AvA5u1bZoH7FtVf0zyLuA04GDg28BRwElJtgeGVdUdScb2sIuTgW2q6rkkG1fV75J8C1hYVV/tJp5jgWMBwsZsNeLYnkKXpFXW04tOHuwQJEkrgCM4L3c4cFmzfFmzDrAvMLGqFlfVw8D1TfkOwH1VNb+qCrikn/vZB/geQFVdD2yaZEQ39d6W5DZgMnB6Vd3VZfsI4IdJ7gS+BuzclP8QODDJUOCjwEV9xHMHcGmSvwb+2FfwVXV+VY2rqnHJ+n1VlyRJklYaR3AazSjJfsAuSQoYAlSSzzVVqoemPZX3urt+9nNjVR3YSz9fBqZU1YRmWtnPAarqD0n+C/gA8CFa9/D05n20krj3A/87yc591JckSZJWSY7gvOQQ4OKq2rqqRlXVVsB9tEZbpgKHJRmSZEvgHU2becA2SZbcG3P4n/Ta8gywYdv6VOAIaD2tDHi8qp5ehphHAA81y0d12fZt4CxgWlU92VMHSdYCtqqqKcDngI2BDbqJWZIkSVrlmeC85HBgUpeyK4G/asrnA7OBc4EbAKrqWVr3ovykecjA/T30PQXYaclDBoBTgXFJ7gBOBz6yjDGfAXwlyc20RpyWqqoZwNPAv/XRxxDgkiSzgduAr1XV74D/ACb4kAFJkiStTtK6dUSdJslraU1Z26GqXlxR+xmy1shaf9gJK6p7SVphfMiAJK1eksyoqr5uvXAEpxM1P+D5K+CLKzK5kSRJklY1PmSgAzU/4Nnbj3hKkiRJHckER8tlzNgtmD7daR6SJElaNThFTZIkSVLHMMGRJEmS1DFMcCRJkiR1DBMcSZIkSR3DBEeSJElSxzDBkSRJktQxTHAkSZIkdQwTHEmSJEkdwwRHkiRJUscwwZEkSZLUMUxwJEmSJHUMExxJkiRJHcMER5IkSVLHMMGRJEmS1DHWHuwAtHpbXLN56vltBzsMqWONWOfewQ5BkqTViiM4kiRJkjqGCY4kSZKkjmGCI0mSJKljmOCsAEkmJKkkO/RS56Ikh3RTPj7Jj3sofyrJrOb1sx76fX+Sk5fvCJb2dWqSzwxEX5IkSdLK4EMGVozDgZuAw4BTB7DfG6vqwJ42Jlm7qq4Grh7AfUqSJEmrDROcAZZkA2Bv4B20Eo1Tm/IA3wD2A+4D0tbmPcDXgceBma9wfxcBTwJjgJlJZgPjquqEJJsB3wJe31Q/qapuTnJqU7Zt8/frVXVW098XgSOBB4DHgBmv6ARIkiRJg8gpagPvIODaqvo18GSSsU35BOCNwK7AMcBbAZIMBy4A/gJ4G7BFL32/rW2K2hfbyrcH3lVVn+5S//8HvlZVewAHA99u27YDcACwJ3BKkqFJdqc16jQG+CCwxys7dEmSJGlwOYIz8A6nNRoDcFmzPhPYF5hYVYuBh5Nc39TZAbivquYDJLkEOLaHvnuaovbDpt+u3gXs1Bo8AmCjJBs2yz+pqueA55I8CryGVoI1qar+0MTS7VS3JMcuiTFszFYjegpX6gxPLxqQ29okSdJKYIIzgJJsSmsK2i5JChgCVJLPNVWqh6Y9lffX73soXwvYq6oWdYkT4Lm2osW89G+hz1iq6nzgfIAha41c3tglSZKkAeMUtYF1CHBxVW1dVaOqaita99vsA0wFDksyJMmWtO7RAZgHbJNku2b98AGMZzJwwpKVJKP7qD8VmJBk3Wak5y8GMBZJkiRphTPBGViHA5O6lF0J/FVTPh+YDZwL3ABQVc/Smu71kyQ3AfcPYDwnAuOS3JFkDnB8b5WraiZwOTCrifvGAYxFkiRJWuFS5QwjLbsha42s9Yed0HdFaTXmPTiSJA2+JDOqalxf9RzBkSRJktQxTHAkSZIkdQyfoqblMmbsFkyf7vQdSZLUGV544QUefPBBnn322cEOZY01fPhwRo4cydChQ5epvQmOJEmS1HjwwQfZcMMNGTVqFG2/JaiVpKp44oknePDBB9lmm22WqQ+nqEmSJEmNZ599lk033dTkZpAkYdNNN12uETQTHEmSJKmNyc3gWt7zb4IjSZIkqWN4D44kSZLUg43WPX1A++vvb6v993//NyeddBLTpk1j2LBhjBo1iq9//etsv/32AxpPVxtssAELFy5kwYIFHHjggdx55539bnvUUUdx4IEHcsghh6zACPvmCI4kSZK0CqkqJkyYwPjx47nnnnuYM2cOp512Go888shgh7ZaMMGRJEmSViFTpkxh6NChHH/88UvLRo8ezZgxY3jnO9/J2LFj2XXXXfnRj34EwIIFC9hxxx055phj2Hnnndl///1ZtGgRAL/5zW9417vexZve9CbGjh3LPffcA8CZZ57JHnvswW677cYpp5zSazyLFy/ms5/97NL65513HtBKxE444QR22mkn3ve+9/Hoo4+uiNPxipngSJIkSauQO++8k9133/1PyocPH86kSZOYOXMmU6ZM4dOf/jRVBcD8+fP5xCc+wV133cXGG2/MlVdeCcARRxzBJz7xCW6//XZuueUWttxySyZPnsz8+fO59dZbmTVrFjNmzGDq1Kk9xvOd73yHESNGMG3aNKZNm8YFF1zAfffdx6RJk7j77ruZPXs2F1xwAbfccsuKOSGvkPfgSJIkSauBquILX/gCU6dOZa211uKhhx5aOm1tm222YfTo0QDsvvvuLFiwgGeeeYaHHnqICRMmAK0ECWDy5MlMnjyZMWPGALBw4ULmz5/Pvvvu2+1+J0+ezB133MEVV1wBwFNPPcX8+fOZOnUqhx9+OEOGDOG1r30t++233wo9/v4ywZEkSZJWITvvvPPSZKLdpZdeymOPPcaMGTMYOnQoo0aNWvp7McOGDVtab8iQISxatGjp6E5XVcXnP/95jjvuuH7FU1V84xvf4IADDnhZ+TXXXLNKPlLbKWqSJEnSKmS//fbjueee44ILLlhaNm3aNO6//34233xzhg4dypQpU7j//vt77WejjTZi5MiRXHXVVQA899xz/OEPf+CAAw7gwgsvZOHChQA89NBDvd4/c8ABB3DuuefywgsvAPDrX/+a3//+9+y7775cdtllLF68mN/+9rdMmTJleQ99QDiCI0mSJPWgv491HkhJmDRpEieddBKnn346w4cPZ9SoUZx66qmceOKJjBs3jtGjR7PDDjv02df3vvc9jjvuOL70pS8xdOhQfvjDH7L//vszd+5c9tprL6D1aOhLLrmEzTffvNs+Pvaxj7FgwQLGjh1LVbHZZptx1VVXMWHCBK6//np23XVXtt9+e97+9rcP6HlYVulp6Erqj3HjxtX06dMHOwxJkqQBMXfuXHbcccfBDmON1911SDKjqsb11dYpapIkSZI6hlPUtFwW12yeen7bFb6fEevcu8L3IUmSpNWfIziSJEmSOoYJjiRJkqSOYYIjSZIkqWOY4EiSJEnqGCY4q6kkE5JUkh2a9fFJfjxAfR+UZKeB6EuSJGl19tTz2w7oq78mTZpEEubNm9dn3YsuuoiHH3546frHPvYx5syZs0zH2wlMcFZfhwM3AYetgL4PAkxwJEmSBsnEiRPZZ599uOyyy/qs2zXB+fa3v81OO616H+WqihdffHGF78cEZzWUZANgb+BveHmCs1GSSUnmJPlWkrWa+ocnmZ3kziT/p62fhW3LhyS5KMlbgfcDZyaZlWS7lXNUkiRJAli4cCE333wz3/nOd/4kwTnjjDPYddddedOb3sTJJ5/MFVdcwfTp0zniiCMYPXo0ixYtYvz48UyfPp1zzz2Xz33uc0vbXnTRRXzyk58E4JJLLmHPPfdk9OjRHHfccSxevPhP4hg1ahSPP/44ANOnT2f8+PEA3HDDDYwePZrRo0czZswYnnnmGQDOPPNM9thjD3bbbTdOOeUUABYsWMCOO+7Ixz/+ccaOHcsDDzzAUUcdxS677MKuu+7K1772tQE/f/4OzurpIODaqvp1kieTjG3K96Q18nI/cC3wwSS3AP8H2B34H2BykoOq6qruOq6qW5JcDfy4qq7ork6SY4FjAcLGbDXi2GU+kKcXnbzMbSVJkjrRVVddxXve8x623357NtlkE2bOnMnYsWP5z//8T6666ip+9atfsd566/Hkk0+yySabcPbZZ/PVr36VcePGvayfQw45hL322oszzjgDgMsvv5wvfvGLzJ07l8svv5ybb76ZoUOH8vGPf5xLL72UI488sl/xffWrX+Wcc85h7733ZuHChQwfPpzJkyczf/58br31VqqK97///UydOpXXv/713H333fzbv/0b3/zmN5kxYwYPPfQQd955JwC/+93vBvbk4QjO6upwYEk6f1mzDnBrVd1bVYuBicA+wB7Az6vqsar6I3ApsO/y7Lyqzq+qcVU1Lll/ebqSJElSFxMnTuSww1qTdA477DAmTpwIwM9+9jOOPvpo1ltvPQA22WSTXvvZbLPN2HbbbfnlL3/JE088wd13383ee+/Nddddx4wZM9hjjz0YPXo01113Hffe2/8fVd9777351Kc+xVlnncXvfvc71l57bSZPnszkyZMZM2YMY8eOZd68ecyfPx+Arbfemre85S0AbLvtttx777188pOf5Nprr2WjjTZ6xeenL47grGaSbArsB+ySpIAhQAHXNH/bFZBeumuvP3wg45QkSdIr98QTT3D99ddz5513koTFixeThDPOOIOqIunto92fOvTQQ/nBD37ADjvswIQJE0hCVfGRj3yEr3zlK722XXvttZfeM/Pss88uLT/55JN53/vexzXXXMNb3vIWfvazn1FVfP7zn+e44457WR8LFixg/fVf+kL8Va96Fbfffjs//elPOeecc/jBD37AhRde+IqOqS+O4Kx+DgEurqqtq2pUVW0F3EdrtGbPJNs0994cSushBL8C3p7k1UmG0BrtuaHp65EkOzb1J7Tt4xlgw5V1QJIkSWq54oorOPLII7n//vtZsGABDzzwANtssw033XQT+++/PxdeeCF/+MMfAHjyyScB2HDDDZfeB9PVBz/4Qa666iomTpzIoYceCsA73/lOrrjiCh599NGl/dx///1/0nbUqFHMmDEDgCuvvHJp+T333MOuu+7KP/zDPzBu3DjmzZvHAQccwIUXXsjCha1bvB966KGl/bd7/PHHefHFFzn44IP58pe/zMyZM5f1VPXIEZzVz+HA6V3KrgT+FvhFs21XYCowqapeTPJ5YAqt0ZxrqupHTbuTgR8DDwB3Ahs05ZcBFyQ5ETikqu5ZgccjSZK0yhqxTv+nbg2EiRMncvLJL79H+eCDD+b73/8+5557LrNmzWLcuHGss846vPe97+W0007jqKOO4vjjj2fdddflF7/4xcvavupVr2KnnXZizpw57LnnngDstNNO/PM//zP7778/L774IkOHDuWcc85h6623flnbU045hb/5m7/htNNO481vfvPS8q9//etMmTKFIUOGsNNOO/Hnf/7nDBs2jLlz57LXXnsBsMEGG3DJJZcwZMiQl/X50EMPcfTRRy8dGeprFGlZpKrrrCap/4asNbLWH3bCMrf3IQOSJGlVMnfuXHbcccfBDmON1911SDKjqsb10GQpp6hJkiRJ6hhOUdNyGTN2C6ZPdxRGkiRJqwZHcCRJkqQ23sIxuJb3/JvgSJIkSY3hw4fzxBNPmOQMkqriiSeeYPjwZf8FE6eoSZIkSY2RI0fy4IMP8thjjw12KGus4cOHM3LkyGVub4IjSZIkNYYOHco222wz2GFoOThFTZIkSVLHMMGRJEmS1DFMcCRJkiR1jPiECC2PJM8Adw92HFppXg08PthBaKXxeq9ZvN5rFq/3mqVTrvfWVbVZX5V8yICW191VNW6wg9DKkWS613vN4fVes3i91yxe7zXLmna9naImSZIkqWOY4EiSJEnqGCY4Wl7nD3YAWqm83msWr/eaxeu9ZvF6r1nWqOvtQwYkSZIkdQxHcCRJkiR1DBMcSZIkSR3DBEfLLMl7ktyd5DdJTh7seLRiJVmQZHaSWUmmD3Y8GlhJLkzyaJI728o2SfJfSeY3f181mDFq4PRwvU9N8lDzHp+V5L2DGaMGRpKtkkxJMjfJXUn+rin3/d2Bernea9T723twtEySDAF+DbwbeBCYBhxeVXMGNTCtMEkWAOOqqhN+KExdJNkXWAhcXFW7NGVnAE9W1enNlxivqqp/GMw4NTB6uN6nAgur6quDGZsGVpItgS2ramaSDYEZwEHAUfj+7ji9XO8PsQa9vx3B0bLaE/hNVd1bVc8DlwEfGOSYJC2jqpoKPNml+APAd5vl79L6T1IdoIfrrQ5UVb+tqpnN8jPAXOB1+P7uSL1c7zWKCY6W1euAB9rWH2QNfAOtYQqYnGRGkmMHOxitFK+pqt9C6z9NYPNBjkcr3glJ7mimsDllqcMkGQWMAX6F7++O1+V6wxr0/jbB0bJKN2XOd+xse1fVWODPgU80U1wkdY5zge2A0cBvgf9vcMPRQEqyAXAlcFJVPT3Y8WjF6uZ6r1HvbxMcLasHga3a1kcCDw9SLFoJqurh5u+jwCRa0xTV2R5p5nMvmdf96CDHoxWoqh6pqsVV9SJwAb7HO0aSobQ+7F5aVf/eFPv+7lDdXe817f1tgqNlNQ14Q5JtkqwDHAZcPcgxaQVJsn5zsyJJ1gf2B+7svZU6wNXAR5rljwA/GsRYtIIt+bDbmIDv8Y6QJMB3gLlV9a9tm3x/d6Cervea9v72KWpaZs0jBr8ODAEurKp/GeSQtIIk2ZbWqA3A2sD3vd6dJclEYDzwauAR4BTgKuAHwOuB/wv8ZVV5Y3oH6OF6j6c1faWABcBxS+7R0OoryT7AjcBs4MWm+Au07svw/d1herneh7MGvb9NcCRJkiR1DKeoSZIkSeoYJjiSJEmSOoYJjiRJkqSOYYIjSZIkqWOY4EiSJEnqGCY4kqSlkixOMivJnUl+mGS9QYrjpMHad7P/M5PcleTMwYqhqyQHJdlpsOMYDEmuSLJtkmFJrm3+fX68bfv5Sca0rZ+Q5OjBiVbSYDPBkSS1W1RVo6tqF+B54Pj+NkwyZADjOAkYtAQHOA4YW1WfHcQYujoIGNQEZ4CvcX/3uTMwpKruBQ4AZgC7Acc2298ErFVVt7U1uxA4cWXHKmnVYIIjSerJjcCfAST56yS3NqM75y35oJtkYZJ/SvIrYK8keyS5JcntTf0NkwxpRkSmJbkjyXFN2/FJft58Oz8vyaVpORF4LTAlyZSm7rlJpjejKv+4JMAk723a3pTkrCQ/bsrXT3Jhs8/bknyg68E1+zqzGQ2YneTQpvxqYH3gV0vK2tp022+So5L8ezO6MD/JGU353y5Zbqv3jX6c039pzuEvk7wmyVuB9wNnNvW36xLX1kmua87vdUle35S/Jsmkpq/bm35IcmRT9/Yk32vKLkpySFufC9uu05Qk36f144GvKPY+4ui2ny6OAH7ULL8ArEvrB4eX+DLwpfYGVfUHYEGSPbvpT1Knqypfvnz58uWLqgJY2Pxdm9aHyr8FdgT+AxjabPsmcGSzXMCHmuV1gHuBPZr1jZp+jgX+V1M2DJgObAOMB54CRtL6wu0XwD5NvQXAq9vi2qT5OwT4Oa1v8IcDDwDbNNsmAj9ulk8D/rpZ3hj4NbB+l2M9GPivps/X0Po19y3bz0M356fbfoGjmmMf0cR1P7AVsBnwm7b2/wns049z+hfN8hlt5+4i4JAe4voP4CPN8keBq5rly4GT2s7dCGBn4O4l57ft3L6s/7Z/C+OB37ed52WJvbs4euyny7HdAOza9u/y+8BtwF/RSvpO6eGcfBH49GC/p3z58rXyX+3fgEiStG6SWc3yjcB3aCUouwPTkkDrG/RHmzqLgSub5TcCv62qaQBV9TRAkv2B3dpGB0YAb6A1Be7WqnqwqTcLGAXc1E1cH0pyLK0PuFvSmqq1FnBvVd3X1JnYxAqwP/D+JJ9p1ocDrwfmtvW5DzCxqhYDjyS5AdgDuLqX89NTvwDXVdVTzbHMAbauqpuS3JvkLcD85hzdDHyCns/p88CPm+UZwLt7iWeJvYAPNsvfo5VcAOwHHAnQHOdTSY4Erqiqx5vyJ/vR/61t5/mdyxB7d3F8uJd+2m0JPNa0/SOtxIYkQ4Gf0roe/0rrOlxcVUuu36PADv04NkkdxgRHktRuUVWNbi9I69Pnd6vq893Uf7b5wAoQWt/gdxXgk1X10y79jgeeaytaTDf/LyXZBvgMrZGh/0lyEa3EIr0cR4CDq+ruPuq8Ut32m+TN9HwslwMfAuYBk6qq+jinL1RVddPPK9HddWg/hu62/5Fm6noT3zpt237fpf1AxN5bP+0W0breXX0c+C6t5O554FBao4BLEpzhTVtJaxjvwZEk9eU64JAkmwMk2STJ1t3Umwe8NskeTb0Nk6xN61v2v22+cSfJ9knW72OfzwAbNssb0fqA/VRzT8eft+1v2ySjmvX2+2V+Cnyy+aBO2p6w1WYqcGha9whtBuwL3NpHXP3pt6t/p/WAgMNpJTvQ/3Parv2cdHULcFizfAQvjYJdR2uaIc1xbtSUfSjJpkv23dRdQGtEBeADwNAe9rUssfcUR3/6mUtzL9gSSV4FHAhcTOthFC/SStraE6HtgTv7iEtSBzLBkST1qqrmAP8LmJzkDlr3rWzZTb0l36J/I8ntTb3hwLeBOcDMJHcC59H3qMT5wH8mmVJVt9O65+IuWk/HurnZ3yJa3+Jfm+Qm4BFa9/RA68bzocAdzT6/3M0+JgF3ALcD1wOfq6r/7iOu/vT7MlX1P7SOf+uqurUp69c57eIy4LNpPdxguy7bTgSObvr6MPB3TfnfAe9IMpvWlLGdq+ou4F+AG5rr9K9N3QuAtye5FXgzLx+1aT+eZYm9uzj6289PaN0H1O5LwD83o0U/BcbRegDCBW119gZ+1kdckjpQXhpJliRp9ZJkg6pa2IyonAPMr6qvDXZcGjhJ1gWmAHu3TYfsq80Y4FNV9eEVGpykVZIjOJKk+7ILcQAAAFhJREFU1dkxzcMJ7qL18ILzBjkeDbBmpO4U4HWvoNmrgf+9YiKStKpzBEeSJElSx3AER5IkSVLHMMGRJEmS1DFMcCRJkiR1DBMcSZIkSR3DBEeSJElSx/h/FfQlOfbzKfwAAAAASUVORK5CYII=
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<h5 id="Membership-duration">Membership duration<a class="anchor-link" href="#Membership-duration">&#182;</a></h5><p>Lastly, we can investigate the membership duration of users to see effect on churn event.</p>

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<div class="prompt input_prompt">In&nbsp;[53]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_pandas_lifetime</span> <span class="o">=</span> <span class="n">df</span>\
    <span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span><span class="s1">&#39;registration&#39;</span><span class="p">,</span><span class="s1">&#39;ts&#39;</span><span class="p">,</span><span class="s1">&#39;churn&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">,(</span><span class="n">df</span><span class="o">.</span><span class="n">ts</span><span class="o">-</span><span class="n">df</span><span class="o">.</span><span class="n">registration</span><span class="p">))</span> \
    <span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span><span class="s1">&#39;churn&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">agg</span><span class="p">({</span><span class="s1">&#39;lifetime&#39;</span><span class="p">:</span><span class="s1">&#39;max&#39;</span><span class="p">})</span> \
    <span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;max(lifetime)&#39;</span><span class="p">,</span><span class="s1">&#39;lifetime&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="p">(</span><span class="n">col</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">)</span><span class="o">/</span><span class="mi">1000</span><span class="o">/</span><span class="mi">3600</span><span class="o">/</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">))</span> \
    <span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
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<div class="prompt input_prompt">In&nbsp;[54]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ax</span> <span class="o">=</span> <span class="n">sns</span><span class="o">.</span><span class="n">boxplot</span><span class="p">(</span><span class="n">data</span> <span class="o">=</span> <span class="n">df_pandas_lifetime</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="s1">&#39;churn&#39;</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;lifetime&#39;</span><span class="p">,</span> <span class="n">orient</span> <span class="o">=</span> <span class="s1">&#39;h&#39;</span><span class="p">,</span> <span class="n">palette</span> <span class="o">=</span> <span class="s2">&quot;Set2&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Days since registration when churn&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Has customer churned&#39;</span><span class="p">)</span>
<span class="n">title</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Churned customer use the service for a shorter period of time&#39;</span><span class="p">)</span>
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<h1 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h1><p>Once you've familiarized yourself with the data, build out the features you find promising to train your model on. To work with the full dataset, you can follow the following steps.</p>
<ul>
<li>Write a script to extract the necessary features from the smaller subset of data</li>
<li>Ensure that your script is scalable, using the best practices discussed in Lesson 3</li>
<li>Try your script on the full data set, debugging your script if necessary</li>
</ul>
<p>If you are working in the classroom workspace, you can just extract features based on the small subset of data contained here. Be sure to transfer over this work to the larger dataset when you work on your Spark cluster.</p>

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<h6 id="Dataset-Features:">Dataset Features:<a class="anchor-link" href="#Dataset-Features:">&#182;</a></h6><p>In the dataset, we have below features:</p>
<p><u>Categorical features</u></p>
<ul>
<li>Currently listening artists</li>
<li>Authorization</li>
<li>First/Last name of user</li>
<li>Gender of user</li>
<li>The payment level of membership (Paid/Free)</li>
<li>Location</li>
<li>Method</li>
<li>Current page</li>
<li>Currently listening song</li>
<li>User agent, (MacOs, Windows, etc.)</li>
</ul>
<p><u>Numerical features</u></p>
<ul>
<li>Item in session</li>
<li>Length</li>
<li>Registration date in timestamp format</li>
<li>SessionId</li>
<li>Status</li>
<li>Time as ts in timestamp format</li>
<li>Userid</li>
</ul>
<p>For the analysis, we will add the below features according to the data exploration that we have performed in the previous section.</p>
<ol>
<li>Gender feature as numerical/binary variable</li>
<li>Number of played/listened songs</li>
<li>Number of liked songs according to thumbs up/down</li>
<li>Number of songs added to playlist</li>
<li>Number of songs listened per session</li>
<li>Number of listened artists</li>
<li>Number of added friends.</li>
<li>Total time duration/lenght of listening event</li>
<li>Membership duration</li>
<li>Churn label</li>
<li>Downgrade label</li>
</ol>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Gender feature as numerical/binary variable</span>
<span class="n">feature_1</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s2">&quot;userId&quot;</span><span class="p">,</span> <span class="s2">&quot;gender&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span><span class="o">.</span><span class="n">replace</span><span class="p">([</span><span class="s1">&#39;M&#39;</span><span class="p">,</span> <span class="s1">&#39;F&#39;</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;0&#39;</span><span class="p">,</span> <span class="s1">&#39;1&#39;</span><span class="p">],</span> <span class="s1">&#39;gender&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="n">col</span><span class="p">(</span><span class="s1">&#39;gender&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="s1">&#39;int&#39;</span><span class="p">))</span>
<span class="n">feature_1</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+------+
|userId|gender|
+------+------+
|    44|     1|
|    46|     1|
|    41|     1|
|    72|     1|
|300023|     1|
+------+------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of played/listened songs</span>
<span class="n">feature_2</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;song&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="s1">&#39;total_songs&#39;</span><span class="p">)</span>
<span class="n">feature_2</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+-----------+
|userID|total_songs|
+------+-----------+
|100010|        381|
|200002|        474|
|   125|         11|
|    51|       2464|
|   124|       4825|
+------+-----------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of liked songs according to thumbs up/down</span>
<span class="n">feature_3</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;page&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">page</span> <span class="o">==</span> <span class="s1">&#39;Thumbs Up&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_up&#39;</span><span class="p">)</span>
<span class="n">feature_3</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+---------+
|userID|thumbs_up|
+------+---------+
|100010|       17|
|200002|       21|
|    51|      100|
|   124|      171|
|     7|        7|
+------+---------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of liked songs according to thumbs up/down</span>
<span class="n">feature_4</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;page&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">page</span> <span class="o">==</span> <span class="s1">&#39;Thumbs Down&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_down&#39;</span><span class="p">)</span>
<span class="n">feature_4</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+-----------+
|userID|thumbs_down|
+------+-----------+
|100010|          5|
|200002|          6|
|    51|         21|
|   124|         41|
|     7|          1|
+------+-----------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of songs added to playlist</span>
<span class="n">feature_5</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;page&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">page</span> <span class="o">==</span> <span class="s1">&#39;Add to Playlist&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="s1">&#39;add_to_playlist&#39;</span><span class="p">)</span>
<span class="n">feature_5</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+---------------+
|userID|add_to_playlist|
+------+---------------+
|100010|              7|
|200002|              8|
|    51|             52|
|   124|            118|
|     7|              5|
+------+---------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of songs listened per session</span>
<span class="n">feature_6</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="s1">&#39;page == &quot;NextSong&quot;&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="s1">&#39;sessionId&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;userId&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">agg</span><span class="p">({</span><span class="s1">&#39;count&#39;</span><span class="p">:</span><span class="s1">&#39;avg&#39;</span><span class="p">})</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;avg(count)&#39;</span><span class="p">,</span> <span class="s1">&#39;avg_songs_played&#39;</span><span class="p">)</span>
<span class="n">feature_6</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<pre>+-------+------------------+-----------------+
|summary|            userId| avg_songs_played|
+-------+------------------+-----------------+
|  count|               225|              225|
|   mean|65391.013333333336|70.78971233958933|
| stddev|105396.47791907164| 42.6153697543817|
|    min|                10|              3.0|
|    max|                99|286.6666666666667|
+-------+------------------+-----------------+

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of listened artists</span>
<span class="n">feature_7</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">filter</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">page</span><span class="o">==</span><span class="s2">&quot;NextSong&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s2">&quot;userId&quot;</span><span class="p">,</span> <span class="s2">&quot;artist&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s2">&quot;userId&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s2">&quot;count&quot;</span><span class="p">,</span> <span class="s2">&quot;artist_count&quot;</span><span class="p">)</span>
<span class="n">feature_7</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+------------+
|userId|artist_count|
+------+------------+
|100010|         252|
|200002|         339|
|   125|           8|
|    51|        1385|
|   124|        2232|
+------+------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of added friends</span>
<span class="n">feature_8</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;page&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">page</span> <span class="o">==</span> <span class="s1">&#39;Add Friend&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;count&#39;</span><span class="p">,</span> <span class="s1">&#39;add_friend&#39;</span><span class="p">)</span> 
<span class="n">feature_8</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+----------+
|userID|add_friend|
+------+----------+
|100010|         4|
|200002|         4|
|    51|        28|
|   124|        74|
|     7|         1|
+------+----------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Total time duration/lenght of listening event</span>
<span class="n">feature_9</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;length&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;sum(length)&#39;</span><span class="p">,</span> <span class="s1">&#39;listen_time&#39;</span><span class="p">)</span>
<span class="n">feature_9</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+------------------+
|userID|       listen_time|
+------+------------------+
|100010| 66940.89735000003|
|200002| 94008.87593999993|
|   125|2089.1131000000005|
|    51| 523275.8428000004|
|   124|1012312.0927899999|
+------+------------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Membership duration</span>
<span class="n">feature_10</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span><span class="s1">&#39;registration&#39;</span><span class="p">,</span><span class="s1">&#39;ts&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">,(</span><span class="n">df</span><span class="o">.</span><span class="n">ts</span><span class="o">-</span><span class="n">df</span><span class="o">.</span><span class="n">registration</span><span class="p">))</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">agg</span><span class="p">({</span><span class="s1">&#39;lifetime&#39;</span><span class="p">:</span><span class="s1">&#39;max&#39;</span><span class="p">})</span><span class="o">.</span><span class="n">withColumnRenamed</span><span class="p">(</span><span class="s1">&#39;max(lifetime)&#39;</span><span class="p">,</span><span class="s1">&#39;lifetime&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="p">(</span><span class="n">col</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">)</span><span class="o">/</span><span class="mi">1000</span><span class="o">/</span><span class="mi">3600</span><span class="o">/</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">&#39;lifetime&#39;</span><span class="p">))</span>
<span class="n">feature_10</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+------------------+
|userId|          lifetime|
+------+------------------+
|100010|  55.6436574074074|
|200002| 70.07462962962963|
|   125| 71.31688657407408|
|    51|19.455844907407407|
|   124|131.55591435185184|
+------+------------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Churn label</span>
<span class="n">churn_label</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="n">col</span><span class="p">(</span><span class="s1">&#39;churn&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">&#39;label&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span>
<span class="n">churn_label</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+-----+
|userId|label|
+------+-----+
|100010|    0|
|200002|    0|
|   125|    1|
|   124|    0|
|    51|    1|
+------+-----+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Downgrade label</span>
<span class="n">downgrade_label</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s1">&#39;userId&#39;</span><span class="p">,</span> <span class="n">col</span><span class="p">(</span><span class="s1">&#39;downgrade&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">&#39;downgrade_label&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">dropDuplicates</span><span class="p">()</span>
<span class="n">downgrade_label</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+---------------+
|userId|downgrade_label|
+------+---------------+
|100010|              0|
|200002|              0|
|   125|              0|
|   124|              0|
|    51|              0|
+------+---------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data</span> <span class="o">=</span> <span class="n">feature_1</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_2</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_3</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_4</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_5</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_6</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_7</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_8</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_9</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">feature_10</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">churn_label</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">downgrade_label</span><span class="p">,</span><span class="s1">&#39;userID&#39;</span><span class="p">,</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;userID&#39;</span><span class="p">)</span> \
    <span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>

<span class="n">data</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
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<pre>+------+-----------+---------+-----------+---------------+------------------+------------+----------+------------------+------------------+-----+---------------+
|gender|total_songs|thumbs_up|thumbs_down|add_to_playlist|  avg_songs_played|artist_count|add_friend|       listen_time|          lifetime|label|downgrade_label|
+------+-----------+---------+-----------+---------------+------------------+------------+----------+------------------+------------------+-----+---------------+
|     1|        381|       17|          5|              7|39.285714285714285|         252|         4| 66940.89735000003|  55.6436574074074|    0|              0|
|     0|        474|       21|          6|              8|              64.5|         339|         4| 94008.87593999993| 70.07462962962963|    0|              0|
|     0|         11|        0|          0|              0|               8.0|           8|         0|2089.1131000000005| 71.31688657407408|    1|              0|
|     1|       4825|      171|         41|            118|145.67857142857142|        2232|        74|1012312.0927899999|131.55591435185184|    0|              0|
|     0|       2464|      100|         21|             52|             211.1|        1385|        28| 523275.8428000004|19.455844907407407|    1|              0|
+------+-----------+---------+-----------+---------------+------------------+------------+----------+------------------+------------------+-----+---------------+
only showing top 5 rows

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Saving as SPARK format</span>
<span class="n">data</span><span class="o">.</span><span class="n">write</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">&#39;SparkFile_10.CSV&#39;</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s1">&#39;csv&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_pandas</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">toPandas</span><span class="p">()</span>
<span class="n">data_pandas</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<style scoped>
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      <th>artist_count</th>
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      <td>4825</td>
      <td>171</td>
      <td>41</td>
      <td>118</td>
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      <td>2232</td>
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      <td>211.100000</td>
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      <td>7.113449e+05</td>
      <td>110.751690</td>
      <td>1</td>
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      <td>1</td>
      <td>1002</td>
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      <td>24</td>
      <td>136.666667</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_pandas</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s1">&#39;PandasFile_71.CSV&#39;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<h1 id="Modeling">Modeling<a class="anchor-link" href="#Modeling">&#182;</a></h1><p>Split the full dataset into train, test, and validation sets. Test out several of the machine learning methods you learned. Evaluate the accuracy of the various models, tuning parameters as necessary. Determine your winning model based on test accuracy and report results on the validation set. Since the churned users are a fairly small subset, I suggest using F1 score as the metric to optimize.</p>

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<h5 id="Notes-on-F1-Score">Notes on F1 Score<a class="anchor-link" href="#Notes-on-F1-Score">&#182;</a></h5><p>According to Wikipedia, F1 Score is defined as a weighted average of the precision and recall where an F1 score reached its best value at 1 and worst at 0. But first lets define the precision and recall:</p>
<ul>
<li><p>The precision is the number of correct positive results divided by the number of all positive results. Precision talks about how precise/accurate your model is out of those predicted positive, how many of them are actual positive. Precision is a good measure to determine, when the costs of False Positive is high. For instance, email spam detection. In email spam detection, a false positive means that an email that is non-spam (actual negative) has been identified as spam (predicted spam). The email user might lose important emails if the precision is not high for the spam detection model.</p>
</li>
<li><p>The recall is the number of correct positive results divided by the number of positive results that should have been returned. Recall actually calculates how many of the Actual Positives our model capture through labeling it as Positive (True Positive). Applying the same understanding, we know that Recall shall be the model metric we use to select our best model when there is a high cost associated with False Negative.</p>
</li>
</ul>
<p>And accuracy is one of the more obvious metrics, it is the measure of all the correctly identified cases. It is most used when all the classes are equally important.</p>
<p>F1 Score is defined as the harmonic mean of Precision and Recall and gives a better measure of the incorrectly classified cases than the Accuracy Metric. And the use case differences of accuracy and F1 Score can be summarized as below:</p>
<ol>
<li><p>Accuracy is used when the True Positives and True negatives are more important while F1-score is used when the False Negatives and False Positives are crucial</p>
</li>
<li><p>Accuracy can be used when the class distribution is similar while F1-score is a better metric when there are imbalanced classes as in the above case.</p>
</li>
<li><p>In most real-life classification problems, imbalanced class distribution exists and thus F1-score is a better metric to evaluate our model on.</p>
</li>
</ol>
<p>[1] <a href="https://towardsdatascience.com/accuracy-precision-recall-or-f1-331fb37c5cb9">https://towardsdatascience.com/accuracy-precision-recall-or-f1-331fb37c5cb9</a></p>
<p>[2] <a href="https://adamyedidia.files.wordpress.com/2014/11/f_score.pdf">https://adamyedidia.files.wordpress.com/2014/11/f_score.pdf</a></p>
<p>[3] <a href="https://medium.com/analytics-vidhya/accuracy-vs-f1-score-6258237beca2">https://medium.com/analytics-vidhya/accuracy-vs-f1-score-6258237beca2</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_pandas</span><span class="o">.</span><span class="n">columns</span>
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<pre>Index([&#39;gender&#39;, &#39;total_songs&#39;, &#39;thumbs_up&#39;, &#39;thumbs_down&#39;, &#39;add_to_playlist&#39;,
       &#39;avg_songs_played&#39;, &#39;artist_count&#39;, &#39;add_friend&#39;, &#39;listen_time&#39;,
       &#39;lifetime&#39;, &#39;label&#39;, &#39;downgrade_label&#39;],
      dtype=&#39;object&#39;)</pre>
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<p>We will use the saved features as the inputs except the churn event, indicated as label. Because the churn label will be the feature that we want to predict by using the related features.</p>
<p>After defining the features, we will create the feature vector and perform transformation.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># The input features are all features except the Churn Label and the output is the churn event.</span>

<span class="n">features_labels</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="s1">&#39;total_songs&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_up&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_down&#39;</span><span class="p">,</span> <span class="s1">&#39;add_to_playlist&#39;</span><span class="p">,</span>
                   <span class="s1">&#39;avg_songs_played&#39;</span><span class="p">,</span> <span class="s1">&#39;artist_count&#39;</span><span class="p">,</span> <span class="s1">&#39;add_friend&#39;</span><span class="p">,</span> <span class="s1">&#39;listen_time&#39;</span><span class="p">,</span> <span class="s1">&#39;lifetime&#39;</span><span class="p">,</span> <span class="s1">&#39;downgrade_label&#39;</span> <span class="p">]</span>

<span class="c1"># Define the vector assembler for all input columns</span>
<span class="n">features_vector</span>  <span class="o">=</span> <span class="n">VectorAssembler</span><span class="p">(</span><span class="n">inputCols</span> <span class="o">=</span> <span class="n">features_labels</span><span class="p">,</span> <span class="n">outputCol</span> <span class="o">=</span> <span class="s2">&quot;features&quot;</span><span class="p">)</span>

<span class="n">input_data</span> <span class="o">=</span> <span class="n">features_vector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
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<p>As a next step, we will perform standardization. Standardization is performed because using these variables without standardization in effect gives the variable with the larger range a weight of 100 in the analysis. Typical data standardization procedures equalize the range and/or data variability. Therefore we standardize the features by taking off the mean and divided by the standard deviation of each feature.</p>
<p>[1] <a href="https://spark.apache.org/docs/latest/ml-features">https://spark.apache.org/docs/latest/ml-features</a></p>
<p>[2] <a href="https://scikit-learn.org/stable/modules/preprocessing.html">https://scikit-learn.org/stable/modules/preprocessing.html</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># standard scaler</span>
<span class="n">features_scaler</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">(</span><span class="n">inputCol</span> <span class="o">=</span> <span class="s2">&quot;features&quot;</span><span class="p">,</span> <span class="n">outputCol</span><span class="o">=</span><span class="s2">&quot;scaled_features&quot;</span><span class="p">,</span> <span class="n">withMean</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">features_scaler_fit</span> <span class="o">=</span> <span class="n">features_scaler</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>
<span class="n">scaled_inputs</span> <span class="o">=</span> <span class="n">features_scaler_fit</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>
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<p>After standardize our features, we can divide our dataset in to test, train, and validation. We can use randomSplit function to divide our dataset.</p>
<p>RandomSplit is performing the randomly splits this DataFrame with the provided weights. When we perform random splitting we are splitting the data randomly to generate two sets: one to use during training of the ML algorithm (training set), and the second to check whether the training is working (test set). This is widely done and a very good idea, as it catches overfitting which otherwise can make it seem like you have a great ML solution when it's actually effectively just memorized the answer for each data point and can't interpolate or generalize.</p>
<p>And one of the main problem is selecting the seed which is defined according to reference 4.</p>
<p>[1] <a href="https://spark.apache.org/docs/2.2.0/api/python/pyspark.sql.html">https://spark.apache.org/docs/2.2.0/api/python/pyspark.sql.html</a></p>
<p>[2] <a href="https://stackoverflow.com/questions/40606456/randomsplit-dont-respect-specific-weights-pyspark">https://stackoverflow.com/questions/40606456/randomsplit-dont-respect-specific-weights-pyspark</a></p>
<p>[3] <a href="https://stackoverflow.com/questions/24857650/issue-understanding-splitting-data-in-scala-using-randomsplit-for-machine-lear">https://stackoverflow.com/questions/24857650/issue-understanding-splitting-data-in-scala-using-randomsplit-for-machine-lear</a></p>
<p>[4] <a href="https://medium.com/@ODSC/properly-setting-the-random-seed-in-ml-experiments-not-as-simple-as-you-might-imagine-219969c84752">https://medium.com/@ODSC/properly-setting-the-random-seed-in-ml-experiments-not-as-simple-as-you-might-imagine-219969c84752</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Creating train, test, and validation</span>
<span class="n">train</span><span class="p">,</span> <span class="n">rest</span> <span class="o">=</span> <span class="n">scaled_inputs</span><span class="o">.</span><span class="n">randomSplit</span><span class="p">([</span><span class="mf">0.8</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">],</span> <span class="n">seed</span> <span class="o">=</span> <span class="mi">45</span><span class="p">)</span>
<span class="n">validation</span><span class="p">,</span> <span class="n">test</span> <span class="o">=</span> <span class="n">rest</span><span class="o">.</span><span class="n">randomSplit</span><span class="p">([</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">],</span> <span class="n">seed</span> <span class="o">=</span> <span class="mi">45</span><span class="p">)</span>
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<p>Use baseline model to observe accuracy and F1-Score.</p>

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<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Test set metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_1</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_1</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>Test set metrics:
Accuracy: 0.20588235294117646
F-1 Score:0.07030129124820661
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Test set metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_0</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_0</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>Test set metrics:
Accuracy: 0.7941176470588235
F-1 Score:0.7029893924783028
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<p>As a next step, we will perform classification with different algorithms to observe the result.</p>
<p>[1] <a href="https://spark.apache.org/docs/latest/ml-classification-regression.html">https://spark.apache.org/docs/latest/ml-classification-regression.html</a></p>

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<h5 id="Gradient-Boost-and-Random-Forest">Gradient Boost and Random Forest<a class="anchor-link" href="#Gradient-Boost-and-Random-Forest">&#182;</a></h5>
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<p>The idea of boosting came out of the idea of whether a weak learner can be modified to become better. A weak hypothesis or weak learner is defined as one whose performance is at least slightly better than random chance.
Gradient Boost Trees is the modified and improved version of AdaBoost.</p>
<p>AdaBoost, which is the abbreviation of the Adaptive Boosting, is the first practical boosting algorithm proposed by Freund and Schapire in 1996. AdaBoost is an algorithm for constructing a “strong” classifier as linear combination of “simple” “weak” classifier. In other words, the main working principle is to convert a set of weak classifiers into a strong one. Weak classifier is described as less than 50% error over any distribution and strong classifier is thresholded linear combination of the weak classifier outputs. AdaBoost works by weighting the observations, putting more weight on difficult to classify instances and less on those already handled well. New weak learners are added sequentially that focus their training on the more difficult patterns. Predictions are made by majority vote of the weak learners’ predictions, weighted by their individual accuracy.</p>
<p>Gradient boosting involves three elements:</p>
<ul>
<li>A loss function to be optimized. The loss function used depends on the type of problem being solved. It must be differentiable, but many standard loss functions are supported and you can define your own. For example, regression may use a squared error and classification may use logarithmic loss</li>
<li>A weak learner to make predictions. Decision trees are used as the weak learner in gradient boosting</li>
<li>An additive model to add weak learners to minimize the loss function. Trees are added one at a time, and existing trees in the model are not changed. A gradient descent procedure is used to minimize the loss when adding trees.</li>
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<p>GBT build trees one at a time, where each new tree helps to correct errors made by previously trained tree. A great application of GBM is anomaly detection in supervised learning settings where data is often highly unbalanced such as DNA sequences, credit card transactions or cybersecurity.</p>
<p>The differences between the GBT and RF can be explained as Gradient boosting uses regression trees for prediction purpose where a random forest use decision tree. ... The random forest is easy to parallelize but boosted trees are hard to do. Random forests overfit a sample of the training data and then reduces the overfit by simple averaging the predictors. If you carefully tune parameters, gradient boosting can result in better performance than random forests. However, gradient boosting may not be a good choice if you have a lot of noise, as it can result in overfitting. They also tend to be harder to tune than random forests.</p>
<p>[1] <a href="https://machinelearningmastery.com/gentle-introduction-gradient-boosting-algorithm-machine-learning/">https://machinelearningmastery.com/gentle-introduction-gradient-boosting-algorithm-machine-learning/</a></p>
<p>[2] <a href="https://medium.com/@aravanshad/gradient-boosting-versus-random-forest-cfa3fa8f0d80">https://medium.com/@aravanshad/gradient-boosting-versus-random-forest-cfa3fa8f0d80</a></p>
<p>[3] <a href="https://www.datasciencecentral.com/profiles/blogs/decision-tree-vs-random-forest-vs-boosted-trees-explained">https://www.datasciencecentral.com/profiles/blogs/decision-tree-vs-random-forest-vs-boosted-trees-explained</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># initialize the GBT classifier</span>
<span class="n">gbt</span> <span class="o">=</span> <span class="n">GBTClassifier</span><span class="p">(</span><span class="n">maxIter</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span> <span class="n">seed</span> <span class="o">=</span> <span class="mi">45</span><span class="p">)</span>

<span class="c1"># set evaluator</span>
<span class="n">f1_evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">metricName</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>

<span class="c1"># build paramGrid</span>
<span class="n">paramGrid</span> <span class="o">=</span> <span class="n">ParamGridBuilder</span><span class="p">()</span><span class="o">.</span><span class="n">build</span><span class="p">()</span>

<span class="n">gbt_crossvalidation</span> <span class="o">=</span> <span class="n">CrossValidator</span><span class="p">(</span><span class="n">estimator</span> <span class="o">=</span> <span class="n">gbt</span><span class="p">,</span>
                                    <span class="n">estimatorParamMaps</span> <span class="o">=</span> <span class="n">paramGrid</span><span class="p">,</span>
                                    <span class="n">evaluator</span> <span class="o">=</span> <span class="n">f1_evaluator</span><span class="p">,</span>
                                    <span class="n">numFolds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
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<p>Fit the training data:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">start</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_gbt</span> <span class="o">=</span> <span class="n">gbt_crossvalidation</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
<span class="n">end</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_gbt</span><span class="o">.</span><span class="n">avgMetrics</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The training process took </span><span class="si">{}</span><span class="s1"> seconds&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">end</span> <span class="o">-</span> <span class="n">start</span><span class="p">))</span>
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<pre>The training process took 1140.1361155509949 seconds
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span> <span class="o">=</span> <span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Gradient Boosted Trees Metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">gbt_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">gbt_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>Gradient Boosted Trees Metrics:
Accuracy: 0.8333333333333334
F-1 Score:0.838095238095238
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># initialize the random forest classifier</span>
<span class="n">randomforest</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">()</span>

<span class="c1"># set evaluator</span>
<span class="n">f1_evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">metricName</span> <span class="o">=</span> <span class="s1">&#39;f1&#39;</span><span class="p">)</span>

<span class="c1"># build paramGrid</span>
<span class="n">paramGrid</span> <span class="o">=</span> <span class="n">ParamGridBuilder</span><span class="p">()</span><span class="o">.</span><span class="n">build</span><span class="p">()</span>

<span class="n">randomforest_crossval</span> <span class="o">=</span> <span class="n">CrossValidator</span><span class="p">(</span><span class="n">estimator</span> <span class="o">=</span> <span class="n">randomforest</span><span class="p">,</span>
                              <span class="n">estimatorParamMaps</span> <span class="o">=</span> <span class="n">paramGrid</span><span class="p">,</span>
                              <span class="n">evaluator</span> <span class="o">=</span> <span class="n">f1_evaluator</span><span class="p">,</span>
                              <span class="n">numFolds</span> <span class="o">=</span> <span class="mi">3</span><span class="p">)</span>
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<span class="n">cvModel_rf</span> <span class="o">=</span> <span class="n">randomforest_crossval</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
<span class="n">end</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_rf</span><span class="o">.</span><span class="n">avgMetrics</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The training process took </span><span class="si">{}</span><span class="s1"> seconds&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">end</span> <span class="o">-</span> <span class="n">start</span><span class="p">))</span>
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<pre>The training process took 520.41619181633 seconds
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Random Forest Metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">randomforest_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">randomforest_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>Random Forest Metrics:
Accuracy: 1.0
F-1 Score:1.0
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<h5 id="Support-Vector-Machines">Support Vector Machines<a class="anchor-link" href="#Support-Vector-Machines">&#182;</a></h5><p>The working principle of the support vector machines is to find or create the hyperplane in an N-dimensional space that distinctly classifies the data points. The dimension of the hyperplane is depending on the number of the features. Hyperplanes are basicly the desicion boundaries that helps the classification of the data such that data points which are locating at te different side of the hyperplane are classified as different classes. Support vector machines are commonly used in face detection, text and hypertext categorization, classification of images, bioinformatics and, handwriting recognition. One of the real world example is performed in the article "Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes".</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># initialize classifier</span>
<span class="n">svm</span> <span class="o">=</span> <span class="n">LinearSVC</span><span class="p">(</span><span class="n">maxIter</span> <span class="o">=</span> <span class="mi">10</span><span class="p">)</span>

<span class="c1"># set evaluator</span>
<span class="n">f1_evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">metricName</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>

<span class="c1"># build paramGrid</span>
<span class="n">paramGrid</span> <span class="o">=</span> <span class="n">ParamGridBuilder</span><span class="p">()</span><span class="o">.</span><span class="n">build</span><span class="p">()</span>

<span class="n">svm_crossval</span> <span class="o">=</span> <span class="n">CrossValidator</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">svm</span><span class="p">,</span>
                          <span class="n">estimatorParamMaps</span><span class="o">=</span><span class="n">paramGrid</span><span class="p">,</span>
                          <span class="n">evaluator</span><span class="o">=</span><span class="n">f1_evaluator</span><span class="p">,</span>
                          <span class="n">numFolds</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">start</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_svm</span> <span class="o">=</span> <span class="n">svm_crossval</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
<span class="n">end</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_svm</span><span class="o">.</span><span class="n">avgMetrics</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The training process took </span><span class="si">{}</span><span class="s1"> seconds&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">end</span> <span class="o">-</span> <span class="n">start</span><span class="p">))</span>
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<pre>The training process took 709.1884164810181 seconds
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">svm_result</span> <span class="o">=</span> <span class="n">cvModel_svm</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">validation</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;SVM Metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">svm_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">svm_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>SVM Metrics:
Accuracy: 0.6666666666666666
F-1 Score:0.5333333333333333
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<h5 id="Decision-Tree-Classifier">Decision Tree Classifier<a class="anchor-link" href="#Decision-Tree-Classifier">&#182;</a></h5><p>In decision analysis, one of the visual and explicit representation of decision and decision making procedure can be performed by using decision trees. The decision tree is using a tree-like model of decisions such that a flowchart like tree structure in which each node internal node denotes a test and each branch represents an outcome of the test and each leaf node holds a corresponding class label. Decision tree is the one of the most powerfull and popular tool for classification and prediction. Decision trees are commonly using in medical diagnosis, failure prediction, credit scroing and crime risk investigation. Several business analysis examples can be found but one of the widely used one is the detection of the raudulent Financial Statements.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dt</span> <span class="o">=</span> <span class="n">DecisionTreeClassifier</span><span class="p">()</span>

<span class="c1"># set evaluator</span>
<span class="n">f1_evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">metricName</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>

<span class="c1"># build paramGrid</span>
<span class="n">paramGrid</span> <span class="o">=</span> <span class="n">ParamGridBuilder</span><span class="p">()</span><span class="o">.</span><span class="n">build</span><span class="p">()</span>

<span class="n">dt_crossval</span> <span class="o">=</span> <span class="n">CrossValidator</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">dt</span><span class="p">,</span>
                          <span class="n">estimatorParamMaps</span><span class="o">=</span><span class="n">paramGrid</span><span class="p">,</span>
                          <span class="n">evaluator</span><span class="o">=</span><span class="n">f1_evaluator</span><span class="p">,</span>
                          <span class="n">numFolds</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">start</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_dt</span> <span class="o">=</span> <span class="n">dt_crossval</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
<span class="n">end</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<span class="n">cvModel_dt</span><span class="o">.</span><span class="n">avgMetrics</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The training process took </span><span class="si">{}</span><span class="s1"> seconds&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">end</span> <span class="o">-</span> <span class="n">start</span><span class="p">))</span>
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<pre>The training process took 595.8720190525055 seconds
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dt_result</span> <span class="o">=</span> <span class="n">cvModel_dt</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">validation</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Decision Trees Metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">dt_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">dt_result</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>SVM Metrics:
Accuracy: 0.8333333333333334
F-1 Score:0.838095238095238
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<h4 id="Model-Comparision-and-Decision">Model Comparision and Decision<a class="anchor-link" href="#Model-Comparision-and-Decision">&#182;</a></h4><p>Gradient Boost Trees, Random Forest, Support Vector Machines, and Decision Tree algorithms are selected and used for training. Below is the summary of obtained accuracy, F1 Score during a recorded training time</p>
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<li><p><strong>Gradient Boost Trees</strong> gave the accuracy of <strong>0.833</strong>, F1 Score of <strong>0.830</strong> with <strong>1140.13 secs</strong> of training duration.</p>
</li>
<li><p><strong>Random Forest</strong> gave the accuracy of <strong>1.00</strong>, F1 Score of <strong>1.00</strong> with <strong>520.41 secs</strong> of training duration.</p>
</li>
<li><p><strong>Support Vector Machines</strong> gave the accuracy of <strong>0.666</strong>, F1 Score of <strong>0.5333</strong> with <strong>709.8 secs</strong> of training duration.</p>
</li>
<li><p><strong>Decision Trees</strong> gave the accuracy of <strong>0.833</strong>, F1 Score of <strong>0.830</strong> with <strong>595.87 secs</strong> of training duration.</p>
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<p>Since the accuracy and F1 Score are the most important results for selecting the algorithm, training duration time has also an effect while working with large dataset. Since we have a relatively small dataset, I will choose the GBT algorithm because it has the 0.833% accuracy.</p>
<p>Note: Random Forest algorithm provides 1.0 accuracy and F1 results which is interesting and can be sign of overfitting.</p>

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<h5 id="Model-Tuning">Model Tuning<a class="anchor-link" href="#Model-Tuning">&#182;</a></h5>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#gbt = GBTClassifier(maxIter = 10, seed = 45)</span>

<span class="c1"># build paramGrid</span>
<span class="c1">#paramGrid_gbt = ParamGridBuilder() \</span>
<span class="c1">#    .addGrid(gbt.maxDepth,[5, 10]) \</span>
<span class="c1">#    .addGrid(gbt.maxIter, [10,15]) \</span>
<span class="c1">#    .build()</span>

<span class="c1"># set evaluator</span>
<span class="c1">#f1_evaluator = MulticlassClassificationEvaluator(metricName=&#39;f1&#39;)</span>

<span class="c1">#gbt_crossval = CrossValidator(estimator=gbt,</span>
<span class="c1">#                          estimatorParamMaps=paramGrid_gbt,</span>
<span class="c1">#                          evaluator=f1_evaluator,</span>
<span class="c1">#                          numFolds=3)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#start = time()</span>
<span class="c1">#cvModel_gbt = gbt_crossval.fit(train)</span>
<span class="c1">#end = time()</span>
<span class="c1">#cvModel_gbt.avgMetrics</span>
<span class="c1">#print(&#39;The training process took {} seconds&#39;.format(end - start))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#best_model = GBTClassifier(maxIter=10,seed=45, maxDepth=5)</span>
<span class="c1">#best_model = best_model.fit(train)</span>
<span class="c1">#results = best_model.transform(test)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#evaluator = MulticlassClassificationEvaluator(predictionCol=&quot;prediction&quot;)</span>
<span class="c1">#print(&#39;Best Model Metrics:&#39;)</span>
<span class="c1">#print(&#39;Accuracy: {}&#39;.format(evaluator.evaluate(results, {evaluator.metricName: &quot;accuracy&quot;})))</span>
<span class="c1">#print(&#39;F-1 Score:{}&#39;.format(evaluator.evaluate(results, {evaluator.metricName: &quot;f1&quot;})))</span>
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<pre>Best Model Metrics:
Accuracy: 0.7647058823529411
F-1 Score:0.7492997198879553
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># The Gradient-Boosted Trees (GBTs) model</span>

<span class="c1">#model = GBTClassifier(seed = 45)</span>
<span class="c1">#param_grid = ParamGridBuilder().addGrid(model.maxDepth,[3, 5, 10]).addGrid(model.maxBins ,[10, 5]) \</span>
<span class="c1">#    .addGrid(model.maxIter ,[20, 5]).build()</span>

<span class="c1">#gbt_crossval = CrossValidator(estimator=model,</span>
<span class="c1">#                          estimatorParamMaps=param_grid,</span>
<span class="c1">#                          evaluator=f1_evaluator,</span>
<span class="c1">#                          numFolds=3)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#start = time()</span>
<span class="c1">#cvModel_gbt = gbt_crossval.fit(train)</span>
<span class="c1">#end = time()</span>
<span class="c1">#cvModel_dt.avgMetrics</span>
<span class="c1">#print(&#39;The training process took {} seconds&#39;.format(end - start))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#gbt_result = cvModel_gbt.transform(validation)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#evaluator = MulticlassClassificationEvaluator(predictionCol=&quot;prediction&quot;)</span>
<span class="c1">#print(&#39;GBT Metrics:&#39;)</span>
<span class="c1">#print(&#39;Accuracy: {}&#39;.format(evaluator.evaluate(gbt_result, {evaluator.metricName: &quot;accuracy&quot;})))</span>
<span class="c1">#print(&#39;F-1 Score:{}&#39;.format(evaluator.evaluate(gbt_result, {evaluator.metricName: &quot;f1&quot;})))</span>
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<h5 id="Feature-Importance-Observation">Feature Importance Observation<a class="anchor-link" href="#Feature-Importance-Observation">&#182;</a></h5>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gbt_best</span> <span class="o">=</span> <span class="n">GBTClassifier</span><span class="p">(</span><span class="n">maxIter</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span><span class="n">seed</span><span class="o">=</span><span class="mi">45</span><span class="p">)</span>
<span class="n">gbt_best_model</span> <span class="o">=</span> <span class="n">gbt_best</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
<span class="n">results_final</span> <span class="o">=</span> <span class="n">gbt_best_model</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">test</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">MulticlassClassificationEvaluator</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Test set metrics:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_final</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">})))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;F-1 Score:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">results_final</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;f1&quot;</span><span class="p">})))</span>
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<pre>Test set metrics:
Accuracy: 0.7647058823529411
F-1 Score:0.7492997198879553
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">features</span> <span class="o">=</span> <span class="n">gbt_best_model</span><span class="o">.</span><span class="n">featureImportances</span><span class="o">.</span><span class="n">values</span>
<span class="n">features_labels</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">,</span> <span class="s1">&#39;total_songs&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_up&#39;</span><span class="p">,</span> <span class="s1">&#39;thumbs_down&#39;</span><span class="p">,</span> <span class="s1">&#39;add_to_playlist&#39;</span><span class="p">,</span>
                   <span class="s1">&#39;avg_songs_played&#39;</span><span class="p">,</span> <span class="s1">&#39;artist_count&#39;</span><span class="p">,</span> <span class="s1">&#39;add_friend&#39;</span><span class="p">,</span> <span class="s1">&#39;listen_time&#39;</span><span class="p">,</span> <span class="s1">&#39;lifetime&#39;</span><span class="p">,</span> <span class="s1">&#39;downgrade_label&#39;</span> <span class="p">]</span>
<span class="n">y_pos</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">features_labels</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span> 
<span class="n">plt</span><span class="o">.</span><span class="n">barh</span><span class="p">(</span><span class="n">y_pos</span><span class="p">,</span> <span class="n">features</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s1">&#39;center&#39;</span><span class="p">,</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;magenta&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">yticks</span><span class="p">(</span><span class="n">y_pos</span><span class="p">,</span> <span class="n">features_labels</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Importance Score&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Feature Importances&#39;</span><span class="p">);</span>
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<p>Feature importance is utilized for Gradient Boost Tree model. From the above Figure, it is seen that thumbs down feature has a very important role. And second important feature is lifetime. It is reasonable that lifetime is an indicator because it is known that churned users have a shorter lifetime.</p>

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<h3 id="Conclusion">Conclusion<a class="anchor-link" href="#Conclusion">&#182;</a></h3><p>The machine learning modeling has a success in predicting the customer's churn activity. That can help the application owners to improve the user lifetime. Despite the relatively good results of other selected machine learning models such as SVM and Decision Trees, the GBT algorithm is selected and tuned with hyperparameters. For a future work, the Random Forest algorithm can be adjusted with different settings to overcome the over-fitting.</p>
<h6 id="Possible-Improvements-for-Current-Model">Possible Improvements for Current Model<a class="anchor-link" href="#Possible-Improvements-for-Current-Model">&#182;</a></h6><p>Even if we have almost 80% accuracy in current model, there is still a chance to improve it by</p>
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<li>Working with more observations by increasing the dataset size.</li>
<li>Investigating the different parameter settings to have more accuracy.</li>
<li>Analyzing location information effect on the churned user since location can provide us a information about life style and give company owner a chance to provide location based promotions to keep the users.</li>
<li>Used environment can also provide a usefull information. If android users are more likely to churned, this means the application needs an improvement for that environment.</li>
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<h1 id="Final-Steps">Final Steps<a class="anchor-link" href="#Final-Steps">&#182;</a></h1><p>Clean up your code, adding comments and renaming variables to make the code easier to read and maintain. Refer to the Spark Project Overview page and Data Scientist Capstone Project Rubric to make sure you are including all components of the capstone project and meet all expectations. Remember, this includes thorough documentation in a README file in a Github repository, as well as a web app or blog post.</p>

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