customer_segments.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>customer_segments</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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<style type="text/css">
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/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
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  -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 {
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}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
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}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
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  color: #000;
}
small {
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}
sub,
sup {
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  position: relative;
  vertical-align: baseline;
}
sup {
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}
sub {
  bottom: -0.25em;
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img {
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svg:not(:root) {
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figure {
  margin: 1em 40px;
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hr {
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pre {
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code,
kbd,
pre,
samp {
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button,
input,
optgroup,
select,
textarea {
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button {
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button,
select {
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}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
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}
button[disabled],
html input[disabled] {
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button::-moz-focus-inner,
input::-moz-focus-inner {
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input {
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input[type="checkbox"],
input[type="radio"] {
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input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
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input[type="search"] {
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input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
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}
fieldset {
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  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
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legend {
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textarea {
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optgroup {
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table {
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}
td,
th {
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/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
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    color: #000 !important;
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    text-shadow: none !important;
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@font-face {
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  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
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}
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}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-download:before {
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}
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}
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}
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}
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}
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}
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}
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}
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  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
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  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
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.glyphicon-circle-arrow-left:before {
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.glyphicon-globe:before {
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.glyphicon-wrench:before {
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.glyphicon-tasks:before {
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}
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}
.glyphicon-jpy:before {
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}
.glyphicon-ruble:before {
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.glyphicon-rub:before {
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.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 4.2.0 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=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#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;
}
.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;
}
@-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 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  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 {
  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:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.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 {
  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: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-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.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";
}
/*!
*
* 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;
}
/**
 * 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 {
  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;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#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#login_widget {
  float: right;
}
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;
}
@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;
}
/*!
*
* 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 {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
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 {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.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: baseline;
  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;
}
.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_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;
}
.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;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.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.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.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.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.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;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.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;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-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.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.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.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.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);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* 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;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  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 {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@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. */
  padding: 0.4em;
}
.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. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

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;
}
/* 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: 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 {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.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;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.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;
}
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.unrendered .text_cell_render {
  display: none;
}
.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;
}
/* 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;
}
.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 {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#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;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -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.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.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;
}
.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;
}
#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;
}
#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;
}
#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.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.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.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.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.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.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 {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  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;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
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<h1 id="Machine-Learning-Engineer-Nanodegree">Machine Learning Engineer Nanodegree<a class="anchor-link" href="#Machine-Learning-Engineer-Nanodegree">&#182;</a></h1><h2 id="Unsupervised-Learning">Unsupervised Learning<a class="anchor-link" href="#Unsupervised-Learning">&#182;</a></h2><h2 id="Project:-Creating-Customer-Segments">Project: Creating Customer Segments<a class="anchor-link" href="#Project:-Creating-Customer-Segments">&#182;</a></h2>
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<p>Welcome to the third project of the Machine Learning Engineer Nanodegree! In this notebook, some template code has already been provided for you, and it will be your job to implement the additional functionality necessary to successfully complete this project. Sections that begin with <strong>'Implementation'</strong> in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section and the specifics of the implementation are marked in the code block with a <code>'TODO'</code> statement. Please be sure to read the instructions carefully!</p>
<p>In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a <strong>'Question X'</strong> header. Carefully read each question and provide thorough answers in the following text boxes that begin with <strong>'Answer:'</strong>. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.</p>
<blockquote><p><strong>Note:</strong> Code and Markdown cells can be executed using the <strong>Shift + Enter</strong> keyboard shortcut. In addition, Markdown cells can be edited by typically double-clicking the cell to enter edit mode.</p>
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<h2 id="Getting-Started">Getting Started<a class="anchor-link" href="#Getting-Started">&#182;</a></h2><p>In this project, you will analyze a dataset containing data on various customers' annual spending amounts (reported in <em>monetary units</em>) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip the distributor with insight into how to best structure their delivery service to meet the needs of each customer.</p>
<p>The dataset for this project can be found on the <a href="https://archive.ics.uci.edu/ml/datasets/Wholesale+customers">UCI Machine Learning Repository</a>. For the purposes of this project, the features <code>'Channel'</code> and <code>'Region'</code> will be excluded in the analysis — with focus instead on the six product categories recorded for customers.</p>
<p>Run the code block below to load the wholesale customers dataset, along with a few of the necessary Python libraries required for this project. You will know the dataset loaded successfully if the size of the dataset is reported.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Import libraries necessary for this project</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="kn">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="kn">import</span> <span class="n">display</span> <span class="c1"># Allows the use of display() for DataFrames</span>

<span class="c1"># Import supplementary visualizations code visuals.py</span>
<span class="kn">import</span> <span class="nn">visuals</span> <span class="kn">as</span> <span class="nn">vs</span>

<span class="c1"># Pretty display for notebooks</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="c1"># Load the wholesale customers dataset</span>
<span class="k">try</span><span class="p">:</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;customers.csv&quot;</span><span class="p">)</span>
    <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;Region&#39;</span><span class="p">,</span> <span class="s1">&#39;Channel&#39;</span><span class="p">],</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="bp">True</span><span class="p">)</span>
    <span class="k">print</span><span class="p">(</span><span class="s2">&quot;Wholesale customers dataset has {} samples with {} features each.&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="o">*</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="k">except</span><span class="p">:</span>
    <span class="k">print</span><span class="p">(</span><span class="s2">&quot;Dataset could not be loaded. Is the dataset missing?&quot;</span><span class="p">)</span>
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<pre>Wholesale customers dataset has 440 samples with 6 features each.
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<h2 id="Data-Exploration">Data Exploration<a class="anchor-link" href="#Data-Exploration">&#182;</a></h2><p>In this section, you will begin exploring the data through visualizations and code to understand how each feature is related to the others. You will observe a statistical description of the dataset, consider the relevance of each feature, and select a few sample data points from the dataset which you will track through the course of this project.</p>
<p>Run the code block below to observe a statistical description of the dataset. Note that the dataset is composed of six important product categories: <strong>'Fresh'</strong>, <strong>'Milk'</strong>, <strong>'Grocery'</strong>, <strong>'Frozen'</strong>, <strong>'Detergents_Paper'</strong>, and <strong>'Delicatessen'</strong>. Consider what each category represents in terms of products you could purchase.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display a description of the dataset</span>
<span class="n">display</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">describe</span><span class="p">())</span>
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      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
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      <th>count</th>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>12000.297727</td>
      <td>5796.265909</td>
      <td>7951.277273</td>
      <td>3071.931818</td>
      <td>2881.493182</td>
      <td>1524.870455</td>
    </tr>
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      <th>std</th>
      <td>12647.328865</td>
      <td>7380.377175</td>
      <td>9503.162829</td>
      <td>4854.673333</td>
      <td>4767.854448</td>
      <td>2820.105937</td>
    </tr>
    <tr>
      <th>min</th>
      <td>3.000000</td>
      <td>55.000000</td>
      <td>3.000000</td>
      <td>25.000000</td>
      <td>3.000000</td>
      <td>3.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>3127.750000</td>
      <td>1533.000000</td>
      <td>2153.000000</td>
      <td>742.250000</td>
      <td>256.750000</td>
      <td>408.250000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>8504.000000</td>
      <td>3627.000000</td>
      <td>4755.500000</td>
      <td>1526.000000</td>
      <td>816.500000</td>
      <td>965.500000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>16933.750000</td>
      <td>7190.250000</td>
      <td>10655.750000</td>
      <td>3554.250000</td>
      <td>3922.000000</td>
      <td>1820.250000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>112151.000000</td>
      <td>73498.000000</td>
      <td>92780.000000</td>
      <td>60869.000000</td>
      <td>40827.000000</td>
      <td>47943.000000</td>
    </tr>
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<h3 id="Implementation:-Selecting-Samples">Implementation: Selecting Samples<a class="anchor-link" href="#Implementation:-Selecting-Samples">&#182;</a></h3><p>To get a better understanding of the customers and how their data will transform through the analysis, it would be best to select a few sample data points and explore them in more detail. In the code block below, add <strong>three</strong> indices of your choice to the <code>indices</code> list which will represent the customers to track. It is suggested to try different sets of samples until you obtain customers that vary significantly from one another.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Select three indices of your choice you wish to sample from the dataset</span>
<span class="n">indices</span> <span class="o">=</span> <span class="p">[</span><span class="mi">26</span><span class="p">,</span><span class="mi">176</span><span class="p">,</span><span class="mi">392</span><span class="p">]</span>

<span class="c1"># Create a DataFrame of the chosen samples</span>
<span class="n">samples</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="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">indices</span><span class="p">],</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="bp">True</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Chosen samples of wholesale customers dataset:&quot;</span><span class="p">)</span>
<span class="n">display</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span>
</pre></div>

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<pre>Chosen samples of wholesale customers dataset:
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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;
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>9898</td>
      <td>961</td>
      <td>2861</td>
      <td>3151</td>
      <td>242</td>
      <td>833</td>
    </tr>
    <tr>
      <th>1</th>
      <td>45640</td>
      <td>6958</td>
      <td>6536</td>
      <td>7368</td>
      <td>1532</td>
      <td>230</td>
    </tr>
    <tr>
      <th>2</th>
      <td>518</td>
      <td>4180</td>
      <td>3600</td>
      <td>659</td>
      <td>122</td>
      <td>654</td>
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<h3 id="Question-1">Question 1<a class="anchor-link" href="#Question-1">&#182;</a></h3><p>Consider the total purchase cost of each product category and the statistical description of the dataset above for your sample customers.</p>
<ul>
<li>What kind of establishment (customer) could each of the three samples you've chosen represent?</li>
</ul>
<p><strong>Hint:</strong> Examples of establishments include places like markets, cafes, delis, wholesale retailers, among many others. Avoid using names for establishments, such as saying <em>"McDonalds"</em> when describing a sample customer as a restaurant. You can use the mean values for reference to compare your samples with. The mean values are as follows:</p>
<ul>
<li>Fresh: 12000.2977</li>
<li>Milk: 5796.2</li>
<li>Grocery: 7951.3</li>
<li>Detergents_paper: 2881.4</li>
<li>Delicatessen: 1524.8</li>
</ul>
<p>Knowing this, how do your samples compare? Does that help in driving your insight into what kind of establishments they might be?</p>

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<p><strong>Answer:</strong><br></p>
<table>
<tr><th >mean</th></tr>
<tr><th></th><th>Fresh</th>  <th>Milk</th>  <th>Grocery</th>    <th>Frozen</th>  <th>Detergents_Paper</th> <th>Delicatessen</th></tr>
<tr><td></td><td>12000.297727</td>  <td>5796.265909</td>    <td>7951.277273</td>    <td>3071.931818</td>  <td>2881.493182</td> <td>1524.870455</td></tr>    

<tr><th>id</th><th>Fresh</th>  <th>Milk</th>    <th>Grocery</th>    <th>Frozen</th>  <th>Detergents_Paper</th> <th>Delicatessen</th></tr> 
<tr><td>0</td><td>9898</td>  <td>961</td>   <td>2861</td>    <td>3151</td>  <td>242</td> <td>833</td></tr>
<tr><td>1</td><td>45640</td>  <td>6958</td> <td>6536</td>    <td>7368</td>  <td>1532</td> <td>230</td></tr>
<tr><td>2</td><td>518</td>  <td>4180</td>   <td>3600</td>    <td>659</td>  <td>122</td> <td>654</td></tr>
</table><ul>
<li><p>My first sample customer is wholesale retailers becuse he purchase 9898 Fresh, 961 Milk, 2861 Grocery, 242 Detergents_Paper and 833 Delicatessen all these less than to mean, except 3151 Frozen more than to mean.<br></p>
</li>
<li><p>My second sample customer is wholesale retailers becuse he purchase  6536 Grocery, 1532 Detergents_Paper and 230 Delicatessen all these less than to mean, except 45640 Fresh, 6958 Milk, 7368 Frozen more than to mean.<br></p>
</li>
<li><p>My third sample customer is cafe becuse he purchase 518 Fresh, 4180 Milk, 3600 Grocery, 659 Frozen, 122 Detergents_Paper and 654 Delicatessen all these less than to mean.</p>
</li>
</ul>

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<h3 id="Implementation:-Feature-Relevance">Implementation: Feature Relevance<a class="anchor-link" href="#Implementation:-Feature-Relevance">&#182;</a></h3><p>One interesting thought to consider is if one (or more) of the six product categories is actually relevant for understanding customer purchasing. That is to say, is it possible to determine whether customers purchasing some amount of one category of products will necessarily purchase some proportional amount of another category of products? We can make this determination quite easily by training a supervised regression learner on a subset of the data with one feature removed, and then score how well that model can predict the removed feature.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign <code>new_data</code> a copy of the data by removing a feature of your choice using the <code>DataFrame.drop</code> function.</li>
<li>Use <code>sklearn.cross_validation.train_test_split</code> to split the dataset into training and testing sets.<ul>
<li>Use the removed feature as your target label. Set a <code>test_size</code> of <code>0.25</code> and set a <code>random_state</code>.</li>
</ul>
</li>
<li>Import a decision tree regressor, set a <code>random_state</code>, and fit the learner to the training data.</li>
<li>Report the prediction score of the testing set using the regressor's <code>score</code> function.</li>
</ul>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Make a copy of the DataFrame, using the &#39;drop&#39; function to drop the given feature</span>
<span class="n">new_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;Detergents_Paper&#39;</span><span class="p">],</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>

<span class="c1"># TODO: Split the data into training and testing sets(0.25) using the given feature as the target</span>
<span class="c1"># Set a random state.</span>
<span class="kn">from</span> <span class="nn">sklearn.cross_validation</span> <span class="kn">import</span> <span class="n">train_test_split</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">new_data</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="s1">&#39;Detergents_Paper&#39;</span><span class="p">],</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>

<span class="c1"># TODO: Create a decision tree regressor and fit it to the training set</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeRegressor</span>
<span class="n">regressor</span> <span class="o">=</span> <span class="n">DecisionTreeRegressor</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">75</span><span class="p">)</span>
<span class="n">regressor</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
<span class="c1"># TODO: Report the score of the prediction using the testing set</span>
<span class="n">score</span> <span class="o">=</span> <span class="n">regressor</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">score</span><span class="p">)</span>
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<pre>0.5800925978481628
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<pre>/home/marie/anaconda2/lib/python2.7/site-packages/sklearn/cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  &#34;This module will be removed in 0.20.&#34;, DeprecationWarning)
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<h3 id="Question-2">Question 2<a class="anchor-link" href="#Question-2">&#182;</a></h3><ul>
<li>Which feature did you attempt to predict? </li>
<li>What was the reported prediction score? </li>
<li>Is this feature necessary for identifying customers' spending habits?</li>
</ul>
<p><strong>Hint:</strong> The coefficient of determination, <code>R^2</code>, is scored between 0 and 1, with 1 being a perfect fit. A negative <code>R^2</code> implies the model fails to fit the data. If you get a low score for a particular feature, that lends us to beleive that that feature point is hard to predict using the other features, thereby making it an important feature to consider when considering relevance.</p>

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<p><strong>Answer:</strong></p>
<ul>
<li>I attemped to predict 'Detergents_Paper'</li>
<li>prediction score = 0.58</li>
<li>No, this feature 'Detergents_Paper' necessary to get good score compare with other featuers.</li>
</ul>

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<h3 id="Visualize-Feature-Distributions">Visualize Feature Distributions<a class="anchor-link" href="#Visualize-Feature-Distributions">&#182;</a></h3><p>To get a better understanding of the dataset, we can construct a scatter matrix of each of the six product features present in the data. If you found that the feature you attempted to predict above is relevant for identifying a specific customer, then the scatter matrix below may not show any correlation between that feature and the others. Conversely, if you believe that feature is not relevant for identifying a specific customer, the scatter matrix might show a correlation between that feature and another feature in the data. Run the code block below to produce a scatter matrix.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Produce a scatter matrix for each pair of features in the data</span>
<span class="n">pd</span><span class="o">.</span><span class="n">scatter_matrix</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">alpha</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span><span class="mi">8</span><span class="p">),</span> <span class="n">diagonal</span> <span class="o">=</span> <span class="s1">&#39;kde&#39;</span><span class="p">);</span>
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<pre>/home/marie/anaconda2/lib/python2.7/site-packages/ipykernel_launcher.py:2: FutureWarning: pandas.scatter_matrix is deprecated. Use pandas.plotting.scatter_matrix instead
  
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<div class="prompt input_prompt">In&nbsp;[7]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">cor_matrix</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="kn">as</span> <span class="nn">sns</span>
<span class="n">sns</span><span class="o">.</span><span class="n">heatmap</span><span class="p">(</span><span class="n">cor_matrix</span><span class="p">)</span>
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<div class="prompt output_prompt">Out[7]:</div>


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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f700ec09810&gt;</pre>
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<h3 id="Question-3">Question 3<a class="anchor-link" href="#Question-3">&#182;</a></h3><ul>
<li>Using the scatter matrix as a reference, discuss the distribution of the dataset, specifically talk about the normality, outliers, large number of data points near 0 among others. If you need to sepearate out some of the plots individually to further accentuate your point, you may do so as well.</li>
<li>Are there any pairs of features which exhibit some degree of correlation? </li>
<li>Does this confirm or deny your suspicions about the relevance of the feature you attempted to predict? </li>
<li>How is the data for those features distributed?</li>
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<p><strong>Hint:</strong> Is the data normally distributed? Where do most of the data points lie? You can use <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html">corr()</a> to get the feature correlations and then visualize them using a <a href="http://seaborn.pydata.org/generated/seaborn.heatmap.html">heatmap</a>(the data that would be fed into the heatmap would be the correlation values, for eg: <code>data.corr()</code>) to gain further insight.</p>

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<p><strong>Answer:</strong></p>
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<li>There is <strong>high correlation</strong> between (Grocery and Detergents_paper), there is <strong>medium correlation</strong> between (Grocery and Milk) and there is <strong>small correlation</strong> between (Detergents_paper and Milk)</li>
<li>That confirm my suspicions about 'Detergents_paper', it has high correlation with Grocery and small correlation with Milk.</li>
<li>This data is not normally distributed and  most of the data points lie on left skewed because it have outliers for all features to solve it we can use methods of data preprocessing ( make drop for outliers and make data normalization ) . </li>
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<h2 id="Data-Preprocessing">Data Preprocessing<a class="anchor-link" href="#Data-Preprocessing">&#182;</a></h2><p>In this section, you will preprocess the data to create a better representation of customers by performing a scaling on the data and detecting (and optionally removing) outliers. Preprocessing data is often times a critical step in assuring that results you obtain from your analysis are significant and meaningful.</p>

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<h3 id="Implementation:-Feature-Scaling">Implementation: Feature Scaling<a class="anchor-link" href="#Implementation:-Feature-Scaling">&#182;</a></h3><p>If data is not normally distributed, especially if the mean and median vary significantly (indicating a large skew), it is most <a href="http://econbrowser.com/archives/2014/02/use-of-logarithms-in-economics">often appropriate</a> to apply a non-linear scaling — particularly for financial data. One way to achieve this scaling is by using a <a href="http://scipy.github.io/devdocs/generated/scipy.stats.boxcox.html">Box-Cox test</a>, which calculates the best power transformation of the data that reduces skewness. A simpler approach which can work in most cases would be applying the natural logarithm.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign a copy of the data to <code>log_data</code> after applying logarithmic scaling. Use the <code>np.log</code> function for this.</li>
<li>Assign a copy of the sample data to <code>log_samples</code> after applying logarithmic scaling. Again, use <code>np.log</code>.</li>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Scale the data using the natural logarithm</span>
<span class="n">log_data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

<span class="c1"># TODO: Scale the sample data using the natural logarithm</span>
<span class="n">log_samples</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span>

<span class="c1"># Produce a scatter matrix for each pair of newly-transformed features</span>
<span class="n">pd</span><span class="o">.</span><span class="n">scatter_matrix</span><span class="p">(</span><span class="n">log_data</span><span class="p">,</span> <span class="n">alpha</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span><span class="mi">8</span><span class="p">),</span> <span class="n">diagonal</span> <span class="o">=</span> <span class="s1">&#39;kde&#39;</span><span class="p">);</span>
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<pre>/home/marie/anaconda2/lib/python2.7/site-packages/ipykernel_launcher.py:8: FutureWarning: pandas.scatter_matrix is deprecated. Use pandas.plotting.scatter_matrix instead
  
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<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>After applying a natural logarithm scaling to the data, the distribution of each feature should appear much more normal. For any pairs of features you may have identified earlier as being correlated, observe here whether that correlation is still present (and whether it is now stronger or weaker than before).</p>
<p>Run the code below to see how the sample data has changed after having the natural logarithm applied to it.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display the log-transformed sample data</span>
<span class="n">display</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>
</pre></div>

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      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
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      <th>0</th>
      <td>9.200088</td>
      <td>6.867974</td>
      <td>7.958926</td>
      <td>8.055475</td>
      <td>5.488938</td>
      <td>6.725034</td>
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      <th>1</th>
      <td>10.728540</td>
      <td>8.847647</td>
      <td>8.785081</td>
      <td>8.904902</td>
      <td>7.334329</td>
      <td>5.438079</td>
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      <th>2</th>
      <td>6.249975</td>
      <td>8.338067</td>
      <td>8.188689</td>
      <td>6.490724</td>
      <td>4.804021</td>
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<h3 id="Implementation:-Outlier-Detection">Implementation: Outlier Detection<a class="anchor-link" href="#Implementation:-Outlier-Detection">&#182;</a></h3><p>Detecting outliers in the data is extremely important in the data preprocessing step of any analysis. The presence of outliers can often skew results which take into consideration these data points. There are many "rules of thumb" for what constitutes an outlier in a dataset. Here, we will use <a href="http://datapigtechnologies.com/blog/index.php/highlighting-outliers-in-your-data-with-the-tukey-method/">Tukey's Method for identfying outliers</a>: An <em>outlier step</em> is calculated as 1.5 times the interquartile range (IQR). A data point with a feature that is beyond an outlier step outside of the IQR for that feature is considered abnormal.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign the value of the 25th percentile for the given feature to <code>Q1</code>. Use <code>np.percentile</code> for this.</li>
<li>Assign the value of the 75th percentile for the given feature to <code>Q3</code>. Again, use <code>np.percentile</code>.</li>
<li>Assign the calculation of an outlier step for the given feature to <code>step</code>.</li>
<li>Optionally remove data points from the dataset by adding indices to the <code>outliers</code> list.</li>
</ul>
<p><strong>NOTE:</strong> If you choose to remove any outliers, ensure that the sample data does not contain any of these points!<br>
Once you have performed this implementation, the dataset will be stored in the variable <code>good_data</code>.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">all_outliers</span> <span class="o">=</span> <span class="p">[]</span>
<span class="c1"># For each feature find the data points with extreme high or low values</span>
<span class="k">for</span> <span class="n">feature</span> <span class="ow">in</span> <span class="n">log_data</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
    
    <span class="c1"># TODO: Calculate Q1 (25th percentile of the data) for the given feature</span>
    <span class="n">Q1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">],</span> <span class="mi">25</span><span class="p">)</span>
    
    <span class="c1"># TODO: Calculate Q3 (75th percentile of the data) for the given feature</span>
    <span class="n">Q3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">],</span> <span class="mi">75</span><span class="p">)</span>
    
    <span class="c1"># TODO: Use the interquartile range to calculate an outlier step (1.5 times the interquartile range)</span>
    <span class="n">step</span> <span class="o">=</span> <span class="p">(</span><span class="n">Q3</span> <span class="o">-</span> <span class="n">Q1</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.5</span>
    
    <span class="c1"># Display the outliers</span>
    <span class="k">print</span><span class="p">(</span><span class="s2">&quot;Data points considered outliers for the feature &#39;{}&#39;:&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">feature</span><span class="p">))</span>
    <span class="n">newoutliers</span> <span class="o">=</span> <span class="n">log_data</span><span class="p">[</span><span class="o">~</span><span class="p">((</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">Q1</span> <span class="o">-</span> <span class="n">step</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">Q3</span> <span class="o">+</span> <span class="n">step</span><span class="p">))]</span>
    <span class="n">display</span><span class="p">(</span><span class="n">newoutliers</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">newoutliers</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
        <span class="n">all_outliers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">i</span><span class="p">)</span>
        
<span class="c1"># OPTIONAL: Select the indices for data points you wish to remove</span>
<span class="n">outliers</span>  <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">all_outliers</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">all_outliers</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
        <span class="n">outliers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">i</span><span class="p">)</span>
<span class="k">print</span> <span class="s1">&#39;repeated outliers = &#39;</span><span class="p">,</span> <span class="n">outliers</span>
<span class="c1"># Remove the outliers, if any were specified</span>
<span class="n">good_data</span> <span class="o">=</span> <span class="n">log_data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">log_data</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">outliers</span><span class="p">])</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="bp">True</span><span class="p">)</span>
</pre></div>

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<pre>Data points considered outliers for the feature &#39;Fresh&#39;:
</pre>
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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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>65</th>
      <td>4.442651</td>
      <td>9.950323</td>
      <td>10.732651</td>
      <td>3.583519</td>
      <td>10.095388</td>
      <td>7.260523</td>
    </tr>
    <tr>
      <th>66</th>
      <td>2.197225</td>
      <td>7.335634</td>
      <td>8.911530</td>
      <td>5.164786</td>
      <td>8.151333</td>
      <td>3.295837</td>
    </tr>
    <tr>
      <th>81</th>
      <td>5.389072</td>
      <td>9.163249</td>
      <td>9.575192</td>
      <td>5.645447</td>
      <td>8.964184</td>
      <td>5.049856</td>
    </tr>
    <tr>
      <th>95</th>
      <td>1.098612</td>
      <td>7.979339</td>
      <td>8.740657</td>
      <td>6.086775</td>
      <td>5.407172</td>
      <td>6.563856</td>
    </tr>
    <tr>
      <th>96</th>
      <td>3.135494</td>
      <td>7.869402</td>
      <td>9.001839</td>
      <td>4.976734</td>
      <td>8.262043</td>
      <td>5.379897</td>
    </tr>
    <tr>
      <th>128</th>
      <td>4.941642</td>
      <td>9.087834</td>
      <td>8.248791</td>
      <td>4.955827</td>
      <td>6.967909</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>171</th>
      <td>5.298317</td>
      <td>10.160530</td>
      <td>9.894245</td>
      <td>6.478510</td>
      <td>9.079434</td>
      <td>8.740337</td>
    </tr>
    <tr>
      <th>193</th>
      <td>5.192957</td>
      <td>8.156223</td>
      <td>9.917982</td>
      <td>6.865891</td>
      <td>8.633731</td>
      <td>6.501290</td>
    </tr>
    <tr>
      <th>218</th>
      <td>2.890372</td>
      <td>8.923191</td>
      <td>9.629380</td>
      <td>7.158514</td>
      <td>8.475746</td>
      <td>8.759669</td>
    </tr>
    <tr>
      <th>304</th>
      <td>5.081404</td>
      <td>8.917311</td>
      <td>10.117510</td>
      <td>6.424869</td>
      <td>9.374413</td>
      <td>7.787382</td>
    </tr>
    <tr>
      <th>305</th>
      <td>5.493061</td>
      <td>9.468001</td>
      <td>9.088399</td>
      <td>6.683361</td>
      <td>8.271037</td>
      <td>5.351858</td>
    </tr>
    <tr>
      <th>338</th>
      <td>1.098612</td>
      <td>5.808142</td>
      <td>8.856661</td>
      <td>9.655090</td>
      <td>2.708050</td>
      <td>6.309918</td>
    </tr>
    <tr>
      <th>353</th>
      <td>4.762174</td>
      <td>8.742574</td>
      <td>9.961898</td>
      <td>5.429346</td>
      <td>9.069007</td>
      <td>7.013016</td>
    </tr>
    <tr>
      <th>355</th>
      <td>5.247024</td>
      <td>6.588926</td>
      <td>7.606885</td>
      <td>5.501258</td>
      <td>5.214936</td>
      <td>4.844187</td>
    </tr>
    <tr>
      <th>357</th>
      <td>3.610918</td>
      <td>7.150701</td>
      <td>10.011086</td>
      <td>4.919981</td>
      <td>8.816853</td>
      <td>4.700480</td>
    </tr>
    <tr>
      <th>412</th>
      <td>4.574711</td>
      <td>8.190077</td>
      <td>9.425452</td>
      <td>4.584967</td>
      <td>7.996317</td>
      <td>4.127134</td>
    </tr>
  </tbody>
</table>
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<pre>Data points considered outliers for the feature &#39;Milk&#39;:
</pre>
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    .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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>86</th>
      <td>10.039983</td>
      <td>11.205013</td>
      <td>10.377047</td>
      <td>6.894670</td>
      <td>9.906981</td>
      <td>6.805723</td>
    </tr>
    <tr>
      <th>98</th>
      <td>6.220590</td>
      <td>4.718499</td>
      <td>6.656727</td>
      <td>6.796824</td>
      <td>4.025352</td>
      <td>4.882802</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
    <tr>
      <th>356</th>
      <td>10.029503</td>
      <td>4.897840</td>
      <td>5.384495</td>
      <td>8.057377</td>
      <td>2.197225</td>
      <td>6.306275</td>
    </tr>
  </tbody>
</table>
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<pre>Data points considered outliers for the feature &#39;Grocery&#39;:
</pre>
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    .dataframe tbody tr th:only-of-type {
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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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>75</th>
      <td>9.923192</td>
      <td>7.036148</td>
      <td>1.098612</td>
      <td>8.390949</td>
      <td>1.098612</td>
      <td>6.882437</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
  </tbody>
</table>
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<pre>Data points considered outliers for the feature &#39;Frozen&#39;:
</pre>
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    .dataframe tbody tr th:only-of-type {
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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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>38</th>
      <td>8.431853</td>
      <td>9.663261</td>
      <td>9.723703</td>
      <td>3.496508</td>
      <td>8.847360</td>
      <td>6.070738</td>
    </tr>
    <tr>
      <th>57</th>
      <td>8.597297</td>
      <td>9.203618</td>
      <td>9.257892</td>
      <td>3.637586</td>
      <td>8.932213</td>
      <td>7.156177</td>
    </tr>
    <tr>
      <th>65</th>
      <td>4.442651</td>
      <td>9.950323</td>
      <td>10.732651</td>
      <td>3.583519</td>
      <td>10.095388</td>
      <td>7.260523</td>
    </tr>
    <tr>
      <th>145</th>
      <td>10.000569</td>
      <td>9.034080</td>
      <td>10.457143</td>
      <td>3.737670</td>
      <td>9.440738</td>
      <td>8.396155</td>
    </tr>
    <tr>
      <th>175</th>
      <td>7.759187</td>
      <td>8.967632</td>
      <td>9.382106</td>
      <td>3.951244</td>
      <td>8.341887</td>
      <td>7.436617</td>
    </tr>
    <tr>
      <th>264</th>
      <td>6.978214</td>
      <td>9.177714</td>
      <td>9.645041</td>
      <td>4.110874</td>
      <td>8.696176</td>
      <td>7.142827</td>
    </tr>
    <tr>
      <th>325</th>
      <td>10.395650</td>
      <td>9.728181</td>
      <td>9.519735</td>
      <td>11.016479</td>
      <td>7.148346</td>
      <td>8.632128</td>
    </tr>
    <tr>
      <th>420</th>
      <td>8.402007</td>
      <td>8.569026</td>
      <td>9.490015</td>
      <td>3.218876</td>
      <td>8.827321</td>
      <td>7.239215</td>
    </tr>
    <tr>
      <th>429</th>
      <td>9.060331</td>
      <td>7.467371</td>
      <td>8.183118</td>
      <td>3.850148</td>
      <td>4.430817</td>
      <td>7.824446</td>
    </tr>
    <tr>
      <th>439</th>
      <td>7.932721</td>
      <td>7.437206</td>
      <td>7.828038</td>
      <td>4.174387</td>
      <td>6.167516</td>
      <td>3.951244</td>
    </tr>
  </tbody>
</table>
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<pre>Data points considered outliers for the feature &#39;Detergents_Paper&#39;:
</pre>
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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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>75</th>
      <td>9.923192</td>
      <td>7.036148</td>
      <td>1.098612</td>
      <td>8.390949</td>
      <td>1.098612</td>
      <td>6.882437</td>
    </tr>
    <tr>
      <th>161</th>
      <td>9.428190</td>
      <td>6.291569</td>
      <td>5.645447</td>
      <td>6.995766</td>
      <td>1.098612</td>
      <td>7.711101</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

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<pre>Data points considered outliers for the feature &#39;Delicatessen&#39;:
</pre>
</div>
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<div class="output_html rendered_html output_subarea ">
<div>
<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>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>66</th>
      <td>2.197225</td>
      <td>7.335634</td>
      <td>8.911530</td>
      <td>5.164786</td>
      <td>8.151333</td>
      <td>3.295837</td>
    </tr>
    <tr>
      <th>109</th>
      <td>7.248504</td>
      <td>9.724899</td>
      <td>10.274568</td>
      <td>6.511745</td>
      <td>6.728629</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>128</th>
      <td>4.941642</td>
      <td>9.087834</td>
      <td>8.248791</td>
      <td>4.955827</td>
      <td>6.967909</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>137</th>
      <td>8.034955</td>
      <td>8.997147</td>
      <td>9.021840</td>
      <td>6.493754</td>
      <td>6.580639</td>
      <td>3.583519</td>
    </tr>
    <tr>
      <th>142</th>
      <td>10.519646</td>
      <td>8.875147</td>
      <td>9.018332</td>
      <td>8.004700</td>
      <td>2.995732</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
    <tr>
      <th>183</th>
      <td>10.514529</td>
      <td>10.690808</td>
      <td>9.911952</td>
      <td>10.505999</td>
      <td>5.476464</td>
      <td>10.777768</td>
    </tr>
    <tr>
      <th>184</th>
      <td>5.789960</td>
      <td>6.822197</td>
      <td>8.457443</td>
      <td>4.304065</td>
      <td>5.811141</td>
      <td>2.397895</td>
    </tr>
    <tr>
      <th>187</th>
      <td>7.798933</td>
      <td>8.987447</td>
      <td>9.192075</td>
      <td>8.743372</td>
      <td>8.148735</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>203</th>
      <td>6.368187</td>
      <td>6.529419</td>
      <td>7.703459</td>
      <td>6.150603</td>
      <td>6.860664</td>
      <td>2.890372</td>
    </tr>
    <tr>
      <th>233</th>
      <td>6.871091</td>
      <td>8.513988</td>
      <td>8.106515</td>
      <td>6.842683</td>
      <td>6.013715</td>
      <td>1.945910</td>
    </tr>
    <tr>
      <th>285</th>
      <td>10.602965</td>
      <td>6.461468</td>
      <td>8.188689</td>
      <td>6.948897</td>
      <td>6.077642</td>
      <td>2.890372</td>
    </tr>
    <tr>
      <th>289</th>
      <td>10.663966</td>
      <td>5.655992</td>
      <td>6.154858</td>
      <td>7.235619</td>
      <td>3.465736</td>
      <td>3.091042</td>
    </tr>
    <tr>
      <th>343</th>
      <td>7.431892</td>
      <td>8.848509</td>
      <td>10.177932</td>
      <td>7.283448</td>
      <td>9.646593</td>
      <td>3.610918</td>
    </tr>
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<pre>repeated outliers =  [128, 154, 65, 66, 75]
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<h3 id="Question-4">Question 4<a class="anchor-link" href="#Question-4">&#182;</a></h3><ul>
<li>Are there any data points considered outliers for more than one feature based on the definition above? </li>
<li>Should these data points be removed from the dataset? </li>
<li>If any data points were added to the <code>outliers</code> list to be removed, explain why.</li>
</ul>
<p><strong> Hint: </strong> If you have datapoints that are outliers in multiple categories think about why that may be and if they warrant removal. Also note how k-means is affected by outliers and whether or not this plays a factor in your analysis of whether or not to remove them.</p>

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<p><strong>Answer:</strong></p>
<ul>
<li>Yes, there are 5 outliers [128, 154, 65, 66, 75]</li>
<li>Yes, these data points should be removed from the dataset </li>
<li>It will affect badly on data variance and K-means algorithm.</li>
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<h2 id="Feature-Transformation">Feature Transformation<a class="anchor-link" href="#Feature-Transformation">&#182;</a></h2><p>In this section you will use principal component analysis (PCA) to draw conclusions about the underlying structure of the wholesale customer data. Since using PCA on a dataset calculates the dimensions which best maximize variance, we will find which compound combinations of features best describe customers.</p>

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<h3 id="Implementation:-PCA">Implementation: PCA<a class="anchor-link" href="#Implementation:-PCA">&#182;</a></h3><p>Now that the data has been scaled to a more normal distribution and has had any necessary outliers removed, we can now apply PCA to the <code>good_data</code> to discover which dimensions about the data best maximize the variance of features involved. In addition to finding these dimensions, PCA will also report the <em>explained variance ratio</em> of each dimension — how much variance within the data is explained by that dimension alone. Note that a component (dimension) from PCA can be considered a new "feature" of the space, however it is a composition of the original features present in the data.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Import <code>sklearn.decomposition.PCA</code> and assign the results of fitting PCA in six dimensions with <code>good_data</code> to <code>pca</code>.</li>
<li>Apply a PCA transformation of <code>log_samples</code> using <code>pca.transform</code>, and assign the results to <code>pca_samples</code>.</li>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="kn">import</span> <span class="n">PCA</span>
<span class="c1"># TODO: Apply PCA by fitting the good data with the same number of dimensions as features</span>
<span class="n">pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">()</span>
<span class="n">pca</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>

<span class="c1"># TODO: Transform log_samples using the PCA fit above</span>
<span class="n">pca_samples</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>

<span class="c1"># Generate PCA results plot</span>
<span class="n">pca_results</span> <span class="o">=</span> <span class="n">vs</span><span class="o">.</span><span class="n">pca_results</span><span class="p">(</span><span class="n">good_data</span><span class="p">,</span> <span class="n">pca</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[12]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">display</span><span class="p">(</span><span class="n">pca_results</span><span class="p">)</span>
<span class="n">display</span><span class="p">(</span><span class="n">pca_results</span><span class="p">[</span><span class="s1">&#39;Explained Variance&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cumsum</span><span class="p">())</span>
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      <th></th>
      <th>Explained Variance</th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
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      <th>Dimension 1</th>
      <td>0.4430</td>
      <td>0.1675</td>
      <td>-0.4014</td>
      <td>-0.4381</td>
      <td>0.1782</td>
      <td>-0.7514</td>
      <td>-0.1499</td>
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      <th>Dimension 2</th>
      <td>0.2638</td>
      <td>-0.6859</td>
      <td>-0.1672</td>
      <td>-0.0707</td>
      <td>-0.5005</td>
      <td>-0.0424</td>
      <td>-0.4941</td>
    </tr>
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      <th>Dimension 3</th>
      <td>0.1231</td>
      <td>-0.6774</td>
      <td>0.0402</td>
      <td>-0.0195</td>
      <td>0.3150</td>
      <td>-0.2117</td>
      <td>0.6286</td>
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      <th>Dimension 4</th>
      <td>0.1012</td>
      <td>-0.2043</td>
      <td>0.0128</td>
      <td>0.0557</td>
      <td>0.7854</td>
      <td>0.2096</td>
      <td>-0.5423</td>
    </tr>
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      <th>Dimension 5</th>
      <td>0.0485</td>
      <td>-0.0026</td>
      <td>0.7192</td>
      <td>0.3554</td>
      <td>-0.0331</td>
      <td>-0.5582</td>
      <td>-0.2092</td>
    </tr>
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      <th>Dimension 6</th>
      <td>0.0204</td>
      <td>0.0292</td>
      <td>-0.5402</td>
      <td>0.8205</td>
      <td>0.0205</td>
      <td>-0.1824</td>
      <td>0.0197</td>
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<pre>Dimension 1    0.4430
Dimension 2    0.7068
Dimension 3    0.8299
Dimension 4    0.9311
Dimension 5    0.9796
Dimension 6    1.0000
Name: Explained Variance, dtype: float64</pre>
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<h3 id="Question-5">Question 5<a class="anchor-link" href="#Question-5">&#182;</a></h3><ul>
<li>How much variance in the data is explained<em> <strong>in total</strong> </em>by the first and second principal component? </li>
<li>How much variance in the data is explained by the first four principal components? </li>
<li>Using the visualization provided above, talk about each dimension and the cumulative variance explained by each, stressing upon which features are well represented by each dimension(both in terms of positive and negative variance explained). Discuss what the first four dimensions best represent in terms of customer spending.</li>
</ul>
<p><strong>Hint:</strong> A positive increase in a specific dimension corresponds with an <em>increase</em> of the <em>positive-weighted</em> features and a <em>decrease</em> of the <em>negative-weighted</em> features. The rate of increase or decrease is based on the individual feature weights.</p>

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<p><strong>Answer:</strong></p>
<ul>
<li>Explained Variance in the first and second principal component = 0.70.</li>
<li>Explained Variance in the first four principal component = 0.93.</li>
<li><ul>
<li>In Dimension 1 : large increases in Milk, Grocery and Detergents_Paper .The best represent in terms of customer spending.</li>
<li>In Dimension 2 : large increases in Fresh, Frozen and Delicatessen.</li>
<li>In Dimension 3 : large increases in Fresh and decreases in Frozen nd Delicatessen.</li>
<li>In Dimension 4 : large increases in Fresh, Delicatessen and decreases in Frozen.</li>
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<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Run the code below to see how the log-transformed sample data has changed after having a PCA transformation applied to it in six dimensions. Observe the numerical value for the first four dimensions of the sample points. Consider if this is consistent with your initial interpretation of the sample points.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display sample log-data after having a PCA transformation applied</span>
<span class="n">display</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">pca_results</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">values</span><span class="p">))</span>
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      <th>Dimension 5</th>
      <th>Dimension 6</th>
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      <th>0</th>
      <td>1.9083</td>
      <td>-0.3765</td>
      <td>0.1924</td>
      <td>0.1502</td>
      <td>-0.3852</td>
      <td>0.5367</td>
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      <th>1</th>
      <td>-0.0349</td>
      <td>-1.6819</td>
      <td>-1.7115</td>
      <td>1.6613</td>
      <td>0.5394</td>
      <td>-0.1548</td>
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      <th>2</th>
      <td>0.9955</td>
      <td>2.3169</td>
      <td>1.7454</td>
      <td>-0.4569</td>
      <td>1.2462</td>
      <td>-0.0669</td>
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<h3 id="Implementation:-Dimensionality-Reduction">Implementation: Dimensionality Reduction<a class="anchor-link" href="#Implementation:-Dimensionality-Reduction">&#182;</a></h3><p>When using principal component analysis, one of the main goals is to reduce the dimensionality of the data — in effect, reducing the complexity of the problem. Dimensionality reduction comes at a cost: Fewer dimensions used implies less of the total variance in the data is being explained. Because of this, the <em>cumulative explained variance ratio</em> is extremely important for knowing how many dimensions are necessary for the problem. Additionally, if a signifiant amount of variance is explained by only two or three dimensions, the reduced data can be visualized afterwards.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign the results of fitting PCA in two dimensions with <code>good_data</code> to <code>pca</code>.</li>
<li>Apply a PCA transformation of <code>good_data</code> using <code>pca.transform</code>, and assign the results to <code>reduced_data</code>.</li>
<li>Apply a PCA transformation of <code>log_samples</code> using <code>pca.transform</code>, and assign the results to <code>pca_samples</code>.</li>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Apply PCA by fitting the good data with only two dimensions</span>
<span class="n">pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">pca</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>
<span class="c1"># TODO: Transform the good data using the PCA fit above</span>
<span class="n">reduced_data</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>

<span class="c1"># TODO: Transform log_samples using the PCA fit above</span>
<span class="n">pca_samples</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>

<span class="c1"># Create a DataFrame for the reduced data</span>
<span class="n">reduced_data</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="n">reduced_data</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Dimension 1&#39;</span><span class="p">,</span> <span class="s1">&#39;Dimension 2&#39;</span><span class="p">])</span>
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<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Run the code below to see how the log-transformed sample data has changed after having a PCA transformation applied to it using only two dimensions. Observe how the values for the first two dimensions remains unchanged when compared to a PCA transformation in six dimensions.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display sample log-data after applying PCA transformation in two dimensions</span>
<span class="n">display</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Dimension 1&#39;</span><span class="p">,</span> <span class="s1">&#39;Dimension 2&#39;</span><span class="p">]))</span>
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<h2 id="Visualizing-a-Biplot">Visualizing a Biplot<a class="anchor-link" href="#Visualizing-a-Biplot">&#182;</a></h2><p>A biplot is a scatterplot where each data point is represented by its scores along the principal components. The axes are the principal components (in this case <code>Dimension 1</code> and <code>Dimension 2</code>). In addition, the biplot shows the projection of the original features along the components. A biplot can help us interpret the reduced dimensions of the data, and discover relationships between the principal components and original features.</p>
<p>Run the code cell below to produce a biplot of the reduced-dimension data.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Create a biplot</span>
<span class="n">vs</span><span class="o">.</span><span class="n">biplot</span><span class="p">(</span><span class="n">good_data</span><span class="p">,</span> <span class="n">reduced_data</span><span class="p">,</span> <span class="n">pca</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f700c3dd110&gt;</pre>
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<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Once we have the original feature projections (in red), it is easier to interpret the relative position of each data point in the scatterplot. For instance, a point the lower right corner of the figure will likely correspond to a customer that spends a lot on <code>'Milk'</code>, <code>'Grocery'</code> and <code>'Detergents_Paper'</code>, but not so much on the other product categories.</p>
<p>From the biplot, which of the original features are most strongly correlated with the first component? What about those that are associated with the second component? Do these observations agree with the pca_results plot you obtained earlier?</p>

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<h2 id="Clustering">Clustering<a class="anchor-link" href="#Clustering">&#182;</a></h2><p>In this section, you will choose to use either a K-Means clustering algorithm or a Gaussian Mixture Model clustering algorithm to identify the various customer segments hidden in the data. You will then recover specific data points from the clusters to understand their significance by transforming them back into their original dimension and scale.</p>

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<h3 id="Question-6">Question 6<a class="anchor-link" href="#Question-6">&#182;</a></h3><ul>
<li>What are the advantages to using a K-Means clustering algorithm? </li>
<li>What are the advantages to using a Gaussian Mixture Model clustering algorithm? </li>
<li>Given your observations about the wholesale customer data so far, which of the two algorithms will you use and why?</li>
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<p><strong> Hint: </strong> Think about the differences between hard clustering and soft clustering and which would be appropriate for our dataset.</p>

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<p><strong>Answer:</strong></p>
<ul>
<li>The advantages to using a K-Means clustering algorithm :-<ul>
<li>Easy to implement </li>
<li>With a large number of variables, K-Means may be computationally faster than hierarchical clustering (if  K is small).</li>
<li>k-Means may produce Hghter clusters than hierarchical clustering</li>
<li>An instance can change cluster (move to another cluster) when the centroids are recomputed.</li>
</ul>
</li>
<li>The advantages to using a Gaussian Mixture Model clustering algorithm :-<ul>
<li>GMM is a lot more flexible in terms of cluster covariance</li>
<li>GMM model accommodates mixed membership</li>
<li>The GMM algorithm is a good algorithm to use for the classification of static postures and non-temporal pattern recognition.</li>
</ul>
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<li><p>which of the two algorithms will you use and why?</p>
<ul>
<li>I'll use K-means clustering algorithm, because it easy and faster and it will help me to get high score in data.</li>
</ul>
</li>
<li><p><strong>Ref :-</strong></p>
<ul>
<li><a href="http://stp.lingfil.uu.se/~santinim/ml/2016/Lect_10/10c_UnsupervisedMethods.pdf">http://stp.lingfil.uu.se/~santinim/ml/2016/Lect_10/10c_UnsupervisedMethods.pdf</a></li>
<li><a href="https://www.quora.com/What-are-the-advantages-to-using-a-Gaussian-Mixture-Model-clustering-algorithm">https://www.quora.com/What-are-the-advantages-to-using-a-Gaussian-Mixture-Model-clustering-algorithm</a></li>
<li><a href="http://www.nickgillian.com/wiki/pmwiki.php/GRT/GMMClassifier#Advantages">http://www.nickgillian.com/wiki/pmwiki.php/GRT/GMMClassifier#Advantages</a>    </li>
</ul>
</li>
</ul>

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<h3 id="Implementation:-Creating-Clusters">Implementation: Creating Clusters<a class="anchor-link" href="#Implementation:-Creating-Clusters">&#182;</a></h3><p>Depending on the problem, the number of clusters that you expect to be in the data may already be known. When the number of clusters is not known <em>a priori</em>, there is no guarantee that a given number of clusters best segments the data, since it is unclear what structure exists in the data — if any. However, we can quantify the "goodness" of a clustering by calculating each data point's <em>silhouette coefficient</em>. The <a href="http://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html">silhouette coefficient</a> for a data point measures how similar it is to its assigned cluster from -1 (dissimilar) to 1 (similar). Calculating the <em>mean</em> silhouette coefficient provides for a simple scoring method of a given clustering.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Fit a clustering algorithm to the <code>reduced_data</code> and assign it to <code>clusterer</code>.</li>
<li>Predict the cluster for each data point in <code>reduced_data</code> using <code>clusterer.predict</code> and assign them to <code>preds</code>.</li>
<li>Find the cluster centers using the algorithm's respective attribute and assign them to <code>centers</code>.</li>
<li>Predict the cluster for each sample data point in <code>pca_samples</code> and assign them <code>sample_preds</code>.</li>
<li>Import <code>sklearn.metrics.silhouette_score</code> and calculate the silhouette score of <code>reduced_data</code> against <code>preds</code>.<ul>
<li>Assign the silhouette score to <code>score</code> and print the result.</li>
</ul>
</li>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Apply your clustering algorithm of choice to the reduced data </span>
<span class="kn">from</span> <span class="nn">sklearn.cluster</span> <span class="kn">import</span> <span class="n">KMeans</span>
<span class="n">clusterer</span> <span class="o">=</span> <span class="n">KMeans</span><span class="p">(</span><span class="n">n_clusters</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span> <span class="mi">42</span><span class="p">)</span>
<span class="n">clusterer</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">)</span>

<span class="c1"># TODO: Predict the cluster for each data point</span>
<span class="n">preds</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">)</span>

<span class="c1"># TODO: Find the cluster centers</span>
<span class="n">centers</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">cluster_centers_</span>

<span class="c1"># TODO: Predict the cluster for each transformed sample data point</span>
<span class="n">sample_preds</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">)</span>

<span class="c1"># TODO: Calculate the mean silhouette coefficient for the number of clusters chosen</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">silhouette_score</span>
<span class="n">score</span> <span class="o">=</span> <span class="n">silhouette_score</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">preds</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">score</span><span class="p">)</span>
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<pre>0.3318412760093694
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<h3 id="Question-7">Question 7<a class="anchor-link" href="#Question-7">&#182;</a></h3><ul>
<li>Report the silhouette score for several cluster numbers you tried. </li>
<li>Of these, which number of clusters has the best silhouette score?</li>
</ul>

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<p><strong>Answer:</strong></p>
<ul>
<li>I tried this numbes<ul>
<li>when i put n_clusters=2 get 0.42</li>
<li>when i put n_clusters=3 get 0.39</li>
<li>when i put n_clusters=4 get 0.33</li>
<li>so the best n_clusters=2 </li>
</ul>
</li>
<li>the best silhouette score = 0.42</li>
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<h3 id="Cluster-Visualization">Cluster Visualization<a class="anchor-link" href="#Cluster-Visualization">&#182;</a></h3><p>Once you've chosen the optimal number of clusters for your clustering algorithm using the scoring metric above, you can now visualize the results by executing the code block below. Note that, for experimentation purposes, you are welcome to adjust the number of clusters for your clustering algorithm to see various visualizations. The final visualization provided should, however, correspond with the optimal number of clusters.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display the results of the clustering from implementation</span>
<span class="n">vs</span><span class="o">.</span><span class="n">cluster_results</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">preds</span><span class="p">,</span> <span class="n">centers</span><span class="p">,</span> <span class="n">pca_samples</span><span class="p">)</span>
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pgRvDYdf/c8nyOCc/1N/BisnfGD+VcFrxc61xYAhwa/E7c759YA/x8+KHsFH3j+kSI5P7D+ePxx+HXQzsfw6V/LnHPb8APfD8OP4XoN/7u9S8yPuAIfqG8ysy/naMPT+Iv1a4Ptn4YvsPCPLKt/C3+8XsAXIrgx9NoO+PPhNXy63p707dnI9vlvOOd+G0l5DH/e4cBmfPBd6PsOb3cTPsA6ycwujXEs8+1bLnfgz+8VQfu2l593zq3D/z1w9PRAxmn3C8Fnh3sJb8QXeXgxaNstfd/Zbw/hf79+i0+R/VWwPN/fZpGGZtn/TomI1Keg92odfiDyA4XWFxHJMLOfABuccxcXXFlEUk8TZ4lI3TNfTncZvvfqK/gxCVXrlRKR2mdmY/E9mO9PtiUiUi5KjRORRnAEvix2Jk3ojGg1KxGRXMzsUnwq6beDVDcRqQNKjRMRERERkYajHiEREREREWk4CoREpCGZ2VFm9lfzE2Pmm4S26szsADNLfXe9mV1mZguTbkfamNnxZvZimbZ1k5ldkuO1z5jZg+X4nBjtKPm7rpXzWkQahwIhEamaIOjI/HSb2duh5+dUuTmXAVcFE2NGS0Gnmpl92MweNbPNZvaGmT1sZocn3a7+MLN1oe9/k5n90cw+a2ZZJzLN8v6SLqqDeYucmW0wP0lxZvm7zOx1M+sqdtu1KDiHOoLvY7OZPRTMR5Nkm4ab2TVm9lLQrr+a2f9YMO+WiEipFAiJSNUEQcdQ59xQ4CX83CaZZYui65uf2LNS3gM8WcwbK9yuQp+9K35OkP8BdgX2wQd12eaISbuTgnNhLH6+o4vwcylVUzvw0dDzU/FFNYqS5LlRBhcE38fu+LmUfppUQ8xsMPA74L3472dn4EP4eZmas6xfy8ddRBKiQEhEUiNIv7nFzH4eTPx3rpkdYWZ/CnoN2szsu2bWFKyfuas/K7hb/Hcz+25oeweZ2e+DO9yvmdnNwfIXgTHAvcGd5oFmto+Z3RX0sDxrZp8u0K7LzGxxsGyLma00s/3N7GIz2xjcxT4+tI3hZnZDsA/rzOw/gzmNCD7/qqAn4jn8JLm5HAx0Oef+1znX7Zzb6py7zzm3OtjWgWb2QLCt18zsRjPbPlln8NlfNrPVQbuvN7N3m9n9Zvammf3KzIYH6x4QHN9/DXpONpjZF/N8f0eGvqsVZvbhON+7c26Tc+524BPATDN7b7C904PttAfH85uht/0+WCfTo/iBQvuew43AeaHn5+EnZQ3v12fMbG3QjufM7DOh1443sxfN7CIzexn4UZbj8sXgeI8K7dfK4Dg9bGbjQ+tOCu3zz/GTmuYzwMy+H5zja83sI8F2PmFmyyLt+KqZLS2wPZxzXcBi/OTDfZjZADNbamYvB/vwoJkdEnp9SHA+vxS06/dm1mc/zGxacOyyfc4MYC9gqnPuqeBcf9U5d4lz7v7g/evM7CtmtgrYGiwbZ743a5OZrTKzU0Kfd2roe1yXOZfNbE8zuyd4zxtm9vtCx0hE6oMCIRFJm6nAzfjZ4W8BuoB/B/YAjsQHCbMi7zkZmISf3+PcUADyX/jZ4TM9J9cBOOfGAhsIeiSCGepvwc9APwqYDswzs6PztAvg4/iZ54fje5d+E7R3JHAF8IPQ+2/Cz2O0P/6O9inA+cFrn8Pf9Z4ITAam5Tk+TwMDg6DqY5mgJcTwPUQj8Rey+wHfjKzzz8Cx+LvtZwbHaC6wJ/7C+/OR9T8MHACcBFxsZsdEG2Vmo/E9Vf8P2A34GvAL60cak3PuUeBl4Khg0RbgXPwxPw34d+sZz/Xh4D2ZHsXHY+571C+AY81s56CtHwSiqZKv4L+vnYF/Ba41s/eFXt8HGIoPrv8t/EYz+xZwDnCMc26DmX0AHyx9Bt/z8hPgDvMpeTsAdwTLdgv+fUaB9n8IeAr/+3EpcFtwTtwOHGxmB4bWPRcf+OVlZu8K2pxvrq27gAPxwcrqyHavAt4HTAn24yKgO/IZn8H/fh7rnFuTZfvHA/c657YWaO5Z+PNyl6Ddd+HP5xHAF4FbzOyAYN0bgJnOuWFB+x4Kln8FeD54z14UPmdEpE4oEBKRtHnYOXdncAf4befc4865Zc65Lufc8/jUqaMj77nCObfZOfci8CBwWLC8E592NdI51+Gc+2O2DzSzffEByNeC9Z7AXzR9Mle7gmUPOud+E9xB/1/8Rd+80B31A8xsqJntDRwHfDHowXkZuBp/EQc+8LnKObfOOfc6cGWug+Oc+zvwT/i/3wuAjWZ2u5mNCF5/xjn3W+fcP5xzr+IvSqPH65rg7vo64GHgUefcSudcB/4COjph5LeCdq/Ep0t9IkvTzgN+6Zy7PzhG9wEryd+7lc0G/HHEOfc759zqYHsr8cc0ui/bxdz3qK3AvcC/BPt1G/BOZLt3Oueed97vgN/SE6yBD34vCT43c26YmV0DfAR/sZ9Jt/ss8P3gvN7mnPtJsPwD+EDfAdc65zqdc4uBPxdof1to/ZvxF/QnBe34X3zwg5kdhg8Q78mzre+b2SZ8APpZ4D+zrRR8Hwudc+3BOXMJMMnMdjI/3moGcKFzri3Yx4edc52Z95vZl4A5wNHB73Q2uwf7Vsg1we/N2/jj9y78XD+dzrnf4L/bzO9ZJ3ComQ1zzr0R/J5nlo8CxgTf4UPRDxGR+qRASETSpjX8xMzea2Z3B2k4b+IvzvaIvOfl0L+34u/OA3wJaAJagjSZT+X4zFHAa865t0LL/gbsnatdgVdC/34b2Oic6w49J2jLe/A9La8E6Teb8L1T7w59fnj7f8vRTgCcc0865z7lnNsbf2d7DH7MEGa2l5ktMbP1wfFaSN/jFW139PnQ3qv3aduoLM16D/CJzP4F+/jBHOvmszfwRrAvRwRpVxvNbDO+FyW6L9vF3PdsfoYP5PqkxQXbPdXMlgVpU5vwvXfh7b7inIuO0do9aO9lzrk3Q8vfA3w1cpxGBvs9Cljnek/wl/dcyLF+5pj/FN+zAz4guiUckGTxb8654cBgfE/U7ZalYIL5VM55ZvZ8cJz/Gry0B/6cfhd+AuNc5uKDtw151nkdf1wKCZ+bo4CXshyPzO/xVOB04KXgvJoSLL8yWO+35lMfvxLjc0WkDigQEpG0iVYCm49PvTnAObcz8H/xKVCFN+TvSH/GOTcSn+51fdD7E7UB2MPMdgotGwOsz9Ou/mjFB2i7OeeGBz87O+cy6VVtwOjIZ8finFuLv3jPjDP5b3yPxoTgeM0g5vHKI9q2bBewrcANof0b7pzbyTn37bgfYmYfxF9IPxwsWgzcCox2zu0C/Jiefcn2fRS77w/gA5ThQXpeuE07AkvxqY7vDgKFX0W2m60tr+Evum8K9iujFd/DFj5OQ5xzS/DnwT6R7RQ6F7KtvwHAOfdwsA9H4nu7CqbFBe/rDnpFXgBOyLLKefh01GPxaYuZ1DPDB9X/wKeA5nIC8C0zy5f29xvgJDMbUqi5oX9vAEab9ao8uP33OOhZPh2fAnoX/vzCOfemc+6LzqfMnoEPVAv1JIpIHVAgJCJpNwzYDLwVDMiOjg/KKRiMnbkbvAl/0bQtup5z7gWgBbjczHYI0ojOB/pUsiuGc64VPx7hO8FYlAHmCxFkigksAeaY2d7BOJWv5tmnQ83sPzL7ZWZj8Kk/mfEcw4C3gM3BuJ0vl2EXvmlmO5rZBOBT9IyRCrsRmGpmJwQ9BoPN7CMWFAjIx8x2MbPT8WOwFgbBXWZf3nDOdQTBxFmht70KODPbL7SsqH0PehBOJft4nB3wPRwbgW3BGKXjYm73t/ig4Q4zy1Q6ux74vPniDhakTp4WBOEP44sffMF8IZB/AQqVRR8ZWv8sfAByX+j1G/Fj1d5yzuUb89NLEDy9l+yVFYfhA87XgSH4sT6Zfd6G74m7OuihG2i+iEZTaJ2/4AOp+RYqZhCxEN/Tu9TMDg6O1R5m9k0zOzHHex7Bpyl+ycyazOzY4HOWBOfv2Wa2c9Ar1k7wtyA4/vsHAdTmYHmfvxMiUn8UCIlI2n0Jf/Hdju8dynYRnssU4HEzews/KP7zzrmXcqw7HT/4+2V8D8BFzrkHim51X+cCOwFrgL/jx2/sFbz2A/y4k1XA48Hn59IOHEHPfj0CrMCnG4EvVjAZf0H3S3yPSqkexo89+RV+PNbvois4Pz5rKn6g+UZ8efQvkf//mXvNbEuw7tfwJbQ/E3r9c8AV5iv1XYQPGDOf147vpVkWpJg1U8K+B2OR+gzad85twg+6vw2fsvd/6FtMId9278MXWLjLzA5zzi0L9usH+PPgGYJxPM65d/DH8F+D1/4ZP2Yrn0eAcUHbLgHOdH4cWUamtzBOb9APLajChw9Evuqc+3WW9W7A975swAdKj0Re/yKwFlgetOtyIj1zwfic04AbzOyjkfcTjD06Fp929xv8ef8nfA/U49kaHxy/0/BFTF4Dvguc7Zx7JljlU8DfgnS+mfSMATwYX6p7C75s+DWZ3jQRqW/WO5VWRETEM19t61nnXKmpdZKQoKfpVWB80PMpIiIB9QiJiIjUr88Df1QQJCLSl2ZiFhERqUNmtg5fGvrjSbdFRCSNlBonIiIiIiINR6lxIiIiIiLScBQIiYiIiIhIw6mpMUJ77LGHGzt2bNLNEBERERGRlFq+fPlrzrkRhdarqUBo7NixtLS0JN0MERERERFJKTP7W5z1lBonIiIiIiINR4GQiIiIiIg0HAVCIiIiIiLScGpqjJCIiIiISL3o7Oxk3bp1dHR0JN2UmjR48GD22Wcfmpqainq/AiERERERkQSsW7eOYcOGMXbsWMws6ebUFOccr7/+OuvWrWPfffctahtKjRMRERERSUBHRwe77767gqAimBm77757Sb1pCoRERERERBKiIKh4pR47BUIiIiIiIg3q5Zdf5qyzzmL//ffn0EMP5eSTT+aZZ57hxRdfZPz48UVtc+HChWzYsKGkdjnnuPDCCznggAN43/vexxNPPFHS9rJRICQiIiIi0oCcc0ydOpVjjjmG5557jjVr1nD55ZfzyiuvlLTdYgKhrq6uXs/vvfdenn32WZ599lmuv/56Pve5z5XUpmwUCImIiIiI1ILWNph9GUye7h9b20ra3AMPPEBTUxMXXHDB9mWHHXYYRx11VK/1Fi5cyBe+8IXtz0899VQefPBBtm3bxowZMxg/fjwTJkzgqquuYunSpbS0tHDOOedw2GGH8fbbb7N8+XKOPvpoJk2axIknnkhbm2/3Mcccw0UXXcTRRx/NNddc0+sz77jjDs477zzMjA9+8INs2rRp+/vKRVXjRERERETSrrUNJk6FLVuhswtWrIVFd8HK22D0yKI2uXr1aiZNmlR0k1asWMH69etZvXo1AJs2bWL48OF873vf4zvf+Q7Nzc10dnYye/Zs7rjjDkaMGMEtt9zCN77xDX7yk59sf89DDz3UZ9vr169n9OjR25/vs88+rF+/npEji9vXbBQIiYiIiIik3bwFPUEQ+MctW/3yay9OpEn77bcfzz//PLNnz+aUU07hox/9aJ91nn76aVavXs0JJ5wAwLZt23oFM9OnT8+6bedcn2XlLiyhQEhEREREJO2WreoJgjI6u+CxVUVvcty4cSxdurTgeoMGDaK7u3v780zJ6l133ZWVK1dy//33c91117FkyZLtPT0ZzjnGjRvHo48+mnXbO+20U9bl++yzD62trdufr1u3jlGjRhVsa39ojJCIiIiISNpNmQBNkT6MpkEweULRmzz22GN55513+NGPfrR92eOPP94nVW3s2LGsWLGC7u5uWltbeeyxxwB47bXX6O7u5swzz+TSSy/dXtlt2LBhtLe3A3DwwQezcePG7YFQZ2cnTz75ZMG2nX766fzsZz/DOcef/vQndtlll7KmxYF6hERERERE0m/uTD8mKJMe1zQIhg7xy4tkZtx2223MmTOHK6+8ksGDBzN27FiuvvrqXusdeeSR7LvvvkyYMIHx48dz+OGHA34cz/nnn7+9t+iKK64AYMaMGVxwwQXsuOOOPProoyxdupQLL7yQzZs309XVxZw5cxg3blzetp188sncc889HHDAAQwZMoQbbrih6P3Muf/Z8u/Sqrm52bW0tCTdDBERERGRkq1du5ZDDjkk/hta2/yYoMdW+Z5JsTwWAAAgAElEQVSguTOLLpRQL7IdQzNb7pxrLvRe9QiJiIiIiNSC0SMTK4xQjxIdI2Rmw81sqZk9ZWZrzeyIJNsjIlIzWjtg9jMwebl/bO1IukUiIiI1JekeoWuA+5xz/8fM3gUMSbg9IiLp19oBE1tgSxd0AivaYdGrsLIZRg9OunUiIiI1IbEeITPbGfgwsADAOfcP59ympNojIlIz5r3UEwSBf9yyzS8XERGRWJJMjdsP2AjcYGZ/NrMfm1n2QuIiItJjWXtPEJTR6eCx9kSaU/Na22D2ZTB5un9sbUu6RSIiUgVJBkKDgMOBHzjn3g+8BXwtupKZfdbMWsysZePGjdVuo4hI+kwZBk2RZU0Gk4cl0pya1toGE6fC/CXw+Cr/OHGqgiERkQaQZCC0DljnnFsWPF+KD4x6cc5d75xrds41jxgxoqoNFBFJpbljYOignmCoyWDoQL9c+mfegp45OcA/btnql4uINICXX36Zs846i/33359DDz2Uk08+mWeeeYYXX3yR8ePHF7XNhQsXsmHDhpLa9dRTT3HEEUewww478J3vfKekbeWSWCDknHsZaDWzg4NFxwFrkmqPiEjNGD3YF0aYNcr3As0aqUIJxVq2qicIyujs8nN0iIjUOeccU6dO5ZhjjuG5555jzZo1XH755bzyyislbbeYQKirq/ff4t12243vfve7fPnLXy6pLfkkWj4bmA0sMrO/AIcBlyfcHhGR2jB6MFx7ECyb5B8VBBVnygQ/O3tY0yA/UaGISNqUeeqEBx54gKamJi644ILtyw477DCOOuqoXustXLiQL3zhC9ufn3rqqTz44INs27aNGTNmMH78eCZMmMBVV13F0qVLaWlp4ZxzzuGwww7j7bffZvny5Rx99NFMmjSJE088kbY2n358zDHHcNFFF3H00UdzzTXX9PrMPffckw984AM0NUVzwcsn0fLZzrkVQMFZX0VERCpi7kxYdFdPelzTIBg6xC8XEUmTCkydsHr1aiZNmlR0k1asWMH69etZvXo1AJs2bWL48OF873vf4zvf+Q7Nzc10dnYye/Zs7rjjDkaMGMEtt9zCN77xDX7yk59sf89DDz1UdBtKkfQ8QiIiIskZPRJW3ubHBD22yvcEzZ3pl4uIpEm+qROuPSiRJu233348//zzzJ49m1NOOYWPfvSjfdZ5+umnWb16NSeccAIA27ZtY+TInr+x06dPr1p7oxQIiYhIYxs9Eq69OOlWiIjkV4GpE8aNG8fSpUsLrjdo0CC6u7u3P+/o8Cl5u+66KytXruT+++/nuuuuY8mSJdt7ejKcc4wbN45HH30067Z32im52XOSHiMkItmUOQdYREREalwFpk449thjeeedd/jRj360fdnjjz/eJ1Vt7NixrFixgu7ublpbW3nssccAeO211+ju7ubMM8/k0ksv5YknngBg2LBhtLf7AO3ggw9m48aN2wOhzs5OnnzyyaLbXE7qERJJmwrkAIuIiEiNmzvGXw9krg/KMHWCmXHbbbcxZ84crrzySgYPHszYsWO5+uqre6135JFHsu+++zJhwgTGjx/P4Yf7GW/Wr1/P+eefv7236IorrgBgxowZXHDBBey44448+uijLF26lAsvvJDNmzfT1dXFnDlzGDduXN62vfzyyzQ3N/Pmm28yYMAArr76atasWcPOO+9c9P722X/nXNk2VmnNzc2upaUl6WaIVNbsZ2D+ht7d303mSyQnlAMsIiIi5bd27VoOOeSQ+G9o7fBjgh5r9z1Bc8c0/E3SbMfQzJY75woWZFOPkEjaVCAHuI/MH9Jl7b6rXX9IRURE0i8zdYKUhQIhkbSZMsynw0V7hErIAe5FqXciIiIiKpYgkjpzx8DQQT0DIsuQA9xLvvKbIiIiIg1CgZBI2owe7HtnZo3yvUCzRpa3t6YaqXciIiISSy2N10+bUo+dUuNE0qiSOcCVTr0TERGRWAYPHszrr7/O7rvvjpkl3Zya4pzj9ddfZ/Dg4m8UKxASaTQVKL8pIiIi/bfPPvuwbt06Nm7cmHRTatLgwYPZZ599in6/AiGRRpNJvVP5TRERkUQ1NTWx7777Jt2MhqVASKQRqfymiIiINDgVSxCR+Fo7/ISvk5f7x9aOpFskIiIiUhT1CIlIPJp/SEREROqIeoREJB7NPyQiIiJ1RIGQiMSj+YdERESkjigQEpF4pgyDpsgyzT8kIiIiNUqBkIjEM3cMDB3UEwxp/iERERGpYQqERCSezPxDs0b5XqBZI1UoQURERGqWqsaJSHyaf0hERETqhHqERERERESk4SgQEhERERGRhqNASEREREREGo4CIRERERERaTgKhEREREREpOEoEBIRERERkYajQEhERERERBqOAiEREREREWk4CoRERERERKThKBASEREREZGGo0BIREREREQajgIhERERERFpOAqEREREpHG1tsHsy2DydP/Y2pZ0i0SkSgYl3QARERGRRLS2wcSpsGUrdHbBirWw6C5YeRuMHpl060SkwtQjJCIiIo1p3oKeIAj845atfrmI1D0FQiIiItKYlq3qCYIyOrvgsVXJtEdEqkqBkIiIiDSmKROgKTJKoGkQTJ6QTHtEpKoUCImIiEhjmjsThg7pCYaaBvnnc2cm2y4RqQoFQiIiImmmqmaVM3qkL4wwa5rvBZo1TYUSRBqIOeeSbkNszc3NrqWlJelmiIiIVEe0qlmmx0IX6yIiOZnZcudcc6H11CMkIiKSVqpqJiJSMQqERERE0kpVzUREKkaBkIiISFqpqpmISMUoEBIREUkrVTUTEakYBUIiIiJppapmIiIVM6jwKiIiInWstc0XH1i2yqeizZ2ZrkBj9Ei49uKkWyEiUncUCImISOOKlqdesRYW3aVeFxGRBqDUOBERaVwqTy0i0rAUCImISONSeWoRkYalQEhERBqXylOLiDQsBUIiItK4VJ5aRKRhKRASEZHGpfLUIiINS1XjRESksak8tYhIQ1KPkIiIiEgta22D2ZfB5On+sbUt6RaJ1AT1CImIiIjUKs2FJVI09QiJiIiI1CrNhSVSNAVCIiIiIrVKc2GJFE2BkIiIiEit0lxYIkVTICQiIiJSqzQXlkjREg+EzGygmf3ZzO5Kui0iIiIiNUVzYYkULQ1V4/4dWAvsnHRDRERERGqO5sISKUqiPUJmtg9wCvDjJNshIiIiIiKNJenUuKuBuUB3wu0QEREREZEGklggZGanAq8655YXWO+zZtZiZi0bN26sUutERERERKSeJdkjdCRwupm9CCwGjjWzm6IrOeeud841O+eaR4wYUe02iohII2htg9mXweTp/rG1LekWiYhIhZlzLuk2YGbHAF92zp2ab73m5mbX0tJSnUaJiEhjaG2DiVNhy1Y/EWWm/LAqb4mI1CQzW+6cay60XtJjhERE6ktrB8x+BiYv94+tHUm3SAqZt6AnCAL/uGWrXy4iInUrDeWzcc49CDyYcDNERErT2gETW2BLF3QCK9ph0auwshlGD066dZLLslU9QVBGZxc8tiqZ9oiISFWoR0hEpFzmvdQTBIF/3LLNL5f0mjLBp8OFNQ3yk1OKiEjdUiAkIlIuy9p7gqCMTgePtSfSHIlp7kw/JigTDGXGCM2dmWy7RESkohQIiYiUy5Rh0BRZ1mQweVgizZGYRo/0hRFmTfO9QLOmqVCC1B9VRhTpIxVV4+JS1TgRSbXoGKEmg6EDNUYoSa1tvujBslU+BW7uTAU40nhUGVEajKrGiYhU2+jBPuiZNcr3As0aqSAoSZmLv/lL4PFV/nHiVN0Jl8ajyogiWaWiapxITWvt8IPhl7X71Ki5Y3Th28hGD4ZrD0q6FQL5L/6uvTjZtolUkyojimSlQEikFCqXLJJe1bz4UwqepNmUCbBibe/fB1VGFFFqnEhJVC5ZJL2qVRZbKXiSdqqMKJKVAiGRUqhcskh6VeviT+MvJO1UGVEkK6XGiZRiyjCfDhcOhlQuWSQdMhd/8xb4dLjJFUpZ0/gLqQWjR2psnEiEAiGRUswd48cERcslzx2TdMtEBKpz8afxFyIiNUmpcSKlULlkEdH4CxGRmqQeIZFSqVyySGOrVgqeiIiUlQIhERGRUmn8hYhIzVFqnIiIiIiINBwFQiIiIiIi0nAUCImIiIiISMNRICQiIiIiIg1HgZCIiIiIiDQcBUJSH1o7YPYzMHm5f2ztSLpFIiIiIpJiKp8tta+1Aya2wJYu6ARWtMOiVzWxqYiIiIjkpB4hqX3zXuoJgsA/btnml4uIiIiIZKFASGrfsvaeICij08Fj7Yk0R0RERETST4GQ1L4pw6ApsqzJYPKwRJojIiIiIumnQEhq39wxMHRQTzDUZDB0oF8uIiIiIpKFAiGpfaMH+8IIs0b5XqBZI1UoQURERETyUtU4qQ+jB8O1ByXdChERERGpEeoREhERkcprbYPZl8Hk6f6xtS3pFolIg1OPkIiIiMTX2gbzFsCyVTBlAsydCaNHFn7PxKmwZSt0dsGKtbDoLlh5W+H3iohUiHqEREREJJ5MQDN/CTy+yj9OnFq4d2fegp4gCPzjlq1+uYhIQhQIiTSq1g6Y/QxMXu4fWzuSbpGIpF2xAc2yVT3vyejsgsdWVaadIiIxKDVOpBG1dsDEFtjS5SejXdEOi15VtT0Rya/YgGbKBJ8OF35v0yCYPKH8bRQRiUk9QiKNaN5LPUEQ+Mct2/xyEZFcpkzwAUxYnIBm7kwYOqTnvU2D/PO5MyvTThGRGBQIiVRC2tPOlrX3BEEZnQ4ea0+kOSJSI4oNaEaP9IURZk3zQdOsaSqUICKJU2qcSGuH7wlZ1g5ThsHcMaWlh9VC2tmUYb5d4WCoyfyEtCIiuWQCmnkLfDrc5JhV4zLvvfbiyrdRRCQmc84l3YbYmpubXUtLS9LNkHoSDVqagKGDSgtaZj8D8zf0DTJmjUzPpK999ttg6MB0BWsiIiIiRTCz5c655kLrKTVOGlslxsrUQtrZ6ME+6Jk1yvcCzRqpIEhEREQailLjpLGVM2jJpNj9rcPfYugOvZbGtLPRg9PTQyUiIiJSZQqEpLGVa6xMNNUsLJN2NndMqa0VERERkTJRapw0trlj/JigpuB5sUFLNMUOwIA9m6qTdpb2KnUiIiIiKaMeIWlsmbEy817y6XCTi6waly3FzgFjq5B+VgtV6kRE0qK1zVe9W7bKz4sUt+qdiNQdBUIi5RgrU81y1NFy3+3bchd80BggEZEerW0wcSps2QqdXbBiLSy6S3MaiTQopcaJlEO5UuwKyfT+zN8Aj7f7x5teSX+VOhGRNJi3oCcIAv+4ZatfXk2tbTD7Mpg83T+2tlX380UEUI+QSHmUK8WukGzlvgfgxyOFpwTL1xtV7glkRURqxbJVPUFQRmeXnxy2WtQrJZIaCoREyqUa5aizjUXqBgbiA6Lw5KjZeqM0nkhEGtmUCT7wCAdDTYNg8oTqtSFfr9S1F1evHSKi1DiRVClU/W3KsJ70u4wmg3PfHW9y1EpMICvFU7U/keqaOxOGDvHBD/jHoUP88mpJQ6+UiADqERLJr5ppZHF6a+aO8csy62R6fy7dN167yjmBrJRGvXOp5ZzDzMq2nqTI6JE+BW3eAh94TE6galwaeqVEBFCPkEhu2QoTTGyp3F37OL01mbFI0d4fiNezkKtHqRLV7SQ/9c6lUkdHB6eeeiqLFy/Ou97ixYs59dRT6ehQL17NGT3Sp6Atu8U/VntcThp6pUQEUI+QSG75LlQrMRYobm9NdCxSf3oWcvUolbu6nRSm3rnU6ejo4IwzzuD+++/nvvvuA+Css87qs97ixYs555xz6O7u5owzzuD2229n8GD14klMaeiVEhFAPUIiuVX7QrXY3pr+9Czk6lFSKlb1qXcuVZxznHnmmdx///0AdHd3c8455/TpGQoHQQD3338/Z555Js65PtsUySnpXikRARQIieRW7QvVYuci6m/AlulRWjbJPyoISka15p6SWMyMT37ykwwY0PPfYjQYigZBAAMGDOCTn/ykxgqJiNQgBUIiuVT7QrXY3hr1LNQm9c6lzllnncWiRYv6BkNnn80Zu+7NOWef3ScIWrRoUdb0ORERST+rpe785uZm19LSknQzpFG0dsA3X4B73/DPT9otfnW2aoqOEcoEbMVeVGvC1cag7zmnbD0/UQqCRETSy8yWO+eaC66nQEgkiz7BBb53KK137DMXtY+1+96FYi9qa2G/dQFfulr4nhO2ePFi3wOU5f/IAWYsuvlmBUEiIikVNxBSapxINrVW2rhc437Svt/VLmler9L+PefT2gazL4PJ0/1ja1tFPuass87itF2yD2A/bZeRCoJEROqAAiGRbNJU2ri1I94cQeWQpv3OppYv4NMk7d9zLq1tMHEqzF8Cj6/yjxOnViQYWrx4MXduzr7dOze3FZxnSERE0k+BkEg2aSlAUO0ekLTsdy61egFfSDWDXUj/95zLvAWwZSt0dvnnnV3++bwF/nmZeou2jxHKkTre7VzW0toiIlJbFAiJZJOW0sbV7gFJy37nUqsX8Pkkke6Xhu+5mKBl2aqeICijs8tPSlmm3qKsJbLN+PjwUQwIlcjONc+QiIjUDgVCItlUsrRxf+7+V7sHJO0lndNwAV9uSaT7Jf09Fxu0TJkATYN6L2saBJMnFO4tiiHXPEGLbr6Z2/++nkU335x3niEREaktgwqvIlIlaasGlilAUE7Ral0r2mHRq7kvQqcM8+uEg6FK94BUYr/LJXMBX44KeWmRVLpfkt9zvqDl2otzv2/uTFh0V897mwbB0CF++ZlzcvcWxeCc48Ybb8w7T1DmMRwsdXd3c+ONNzJ9+nRNqioiUmPUIyTp0CjVwOLe/c/0Gv1+MwywnlsW9dADUqpyVchLi3pM9yskX4pbPqNHwr3z4b37wU47+sd75/vl+XqLYjAzbr31Vk488UQg9zxB0UlXTzzxRG699VYFQSIiNSixQMjMRpvZA2a21syeNLN/T6otkgJpqQZW6UHrce7+h4PCv7wF2xwMNJi4U/pS1aR09ZjuV0ixQUtrG5w0C556Ht562z+eNMsvnzvT9w5lthvuLYpp8ODB3H777Zx88sl5J0vNBEMnn3wyt99+O4MHV/n3sUolxEVE6l1iE6qa2UhgpHPuCTMbBiwHznDOrcn1Hk2oWscmL/c9QX2WD/N3/quhGpNMzn7GBzjRVLdZI3vSlOKsU4/SlhpZTeWaELdWZMYIRVPcVt7me3dymX2ZH08U7k1qGgSzpvmUutY2n1732CofVM2dmX97OTjnYvXwxF2vrIo9diIiDSTuhKqJjRFyzrUBbcG/281sLbA3kDMQkjqWxFiYqHy9UuUKQOaO8WOCtgdbWe7+12uJ6Hz6O3aq3qR5XFYljB7pL9z7G7QUSqkbPTL/GKOY4gY3iaTDFTu+SkRE+kjFGCEzGwu8H1iWbEskMWlID6pGABKnWlctjBkpdwphWlIjpa9KpWFlgpZlt/jHOL0ZJY4DqgvFjq8SEZE+Eq8aZ2ZDgVuBOc65N7O8/lngswBjxtRxznyjS0M1sGr1ShW6+x+n1yhJlei9acResFoQTcNasdZXbUsqDStf1bhGMWWC/x6i6YGNFAyKiJRJoj1CZtaED4IWOed+kW0d59z1zrlm51zziBEjqttAqa6kq4GloVcKkp/jJZdML1DzcthU5t6bWugFa0RlmJunrDIpdbOm+Qv/WdMab2xMGYpCiIiIl2SxBAN+CrzhnJsT5z0qliAV12iD1uOK9gJlU0phiz6FKoIgNA0BYCObPN1PeNpn+QSf0ia9ZYo1LFvle26KLNYQ+3NKLAohIlKvUl8sATgS+CSwysxWBMsucs7dk2CbpNE12qD1uKJjeKJK7b1JQ2qk9KU0rPiqmUZYpqIQIiKNLsmqcQ8DmoFO6ls9lIRu7YAlG/MHQeVIIayXILQevvMMjcmJT9XcRERqTuLFEkTqVj2UhM7sw6auvq8NAPZogmkjavtiv5zq4TsPK7bMdSNSNTcRkZqjQEikUkqdlygNPQuZfYgOJRwA7DIIWiYld4GfhuMTVY25qKqtUmlY1RpPUy1KIxQRqTkKhETi6u+FdyklodPSs5BtH8D3BCUdBKXh+ESpDHg8aSvLXQ5KIxQRqTmpmFBVJPUyF97zN8Dj7f5xYkv+iURLKQmdlglGc+3DtBHJBhxpOT5RKgMeT9rKcpeDSnuLiNQcBUIicRRz4V3KvERp6VlIy9xKUWk5PlFpPV5pU6/jaTJphMtu8Y8KgkREUk2BkEgcxVx4lzIxalp6FtI6uWtajk9UWo9X2kyZ0DMhaIbG04iISJUlNqFqMTShqiRm9jM+HS4cDDWZv9Dt7yD4OGONNMFofjo+tS06RigznkapZCIiUgZxJ1RVICQSR7kuvPtsB59KlW07mYBJE4xmV4njk8ZKdPUqUzVOZbl71FslPelL37FIVSgQEim3clx4l7NnScqrP0GqSLmpl6z+6TsWqZq4gZDGCInENXqwD1aWTfKPxVwc92esUWuHD5wmL/eP+SrUSenSWolOyqO1DWZfBpOn+8fWtqRb1Fs9VtKT3mrpO07774tImWgeIZFqmjLMz3kT7RHKDPLP9Dr9YTM8tRW2OegiPfPkFKNW0s3SWolOSlcL8xbVayU96VEr33Et/L6IlIl6hESqKV955fBcRSvfgneCIAhqt3eimPmXkpLWSnRSulq4E69KevWvVr7jWvh9ESkTBUIipepPClu+8srR1KyoWuydqKV0M80BVL9q4U783Jl+vEjmQjkzfmTuzGTbJeVTK99xLfy+iJSJUuNEShEdYB8nhS0z1igqW2pWWC32TtRSulkmSK2nSn21kpZYaVMm+PSe8MVdUnfic1UNGz3Spx6pkl79qpXvOE2/LyIVpqpxIqUoZxW4bNsKb7MW58lRlbzkqApej2Ur4ejz4J3gREyqWpeqhkkt0HkqdUBV40SqoZw9Hn1Ss4AdDCbu1DuFrhyqVZFO6WbJqaW0xEpqbYOTZsG27p5lAwzunV/9i7q0jL1QRTDJZ/RI//vx3v1gpx39YxK/LyJVoNQ4kVIUqgLXH9VKzSomna9Y9ZhuVitqKS2xEjIpaEvug83t0B3Kfuh2cNOdMGVidduUhrEXaasIpglGi1PJ45a5eZA5R5563j9Xj5DUIQVCUh31OlZh7hgfRGxPPyqxxyPX+KFyytdTUInPrsY+1aNSf2fKGaTXmujFflRSA7/TMPYiX6/UtRdXrx1QvaCs3oKtSh+3NJ0jIhWm1Dgpj3ypVrVUQrm/8lWBS6t8PQW1MIlrLbSxVOX4nWnktMTohVxUUgO/01A1LA29UhnVSBXMBA3zl8Djq/zjxKm1nQ5Y6eOWpnMkbZRWWncUCEnpCl201ftYhUyPx7JJ/jHNQRDkni/nkCHpD1jrOagOK8fvTC0G6eWS7UIuI8mSxZmqYbOm+UBs1rSeu/jlusAqtJ1yz2VTSrurccGdlnFZhfTnOFb6uNXKfEfVVo9BtSg1TsqgUKpVo49VSJtc6XxQ3ZS5YlQ7rS8p5fqdadS0xGwpaGYwYjeYdmKyqVGjR/ZNLypXqlOc7cyd6ZdFK4IVExiW2u5qpArWQu9Gf49jpY9bOc+ReqKUwbqUs0fIzHY2syvM7EYzOzvy2vcr3zSpGYUu2nL1QDTCWIU0ytVTsGZr+gPWRgmqC/3ONEJ6YCmypaANHwYtS/wFS9rGh5Sr1yLOdvL1SlW73eVKFczXm1ILvRv9PY6VTrEs5zlST2ohqJZ+y9cjdAPwLHAr8GkzOxM42zn3DvDBajROakShQdnlLiggpcvWU1ALg+troY3lkO93pppV/2pVJSeurMTA+3JdYMXdTrZeqbjC+/+39aW1uxzfU6HelFro3ejv91+NiVlLOUfqVRqKnUjZ5QuE9nfOnRn8+3Yz+wbwOzM7vQrtklpSKNBRCeXaUAsBaznaWAsVDPP9zsx+pjHSA0tViQu5SlXrKtcFVqUv1KL7P8D6rtPfzyv1eyqUrlSNoKFUxXxvClSqrxaCauk3c85lf8FsLTDOOdcdWvYpYC4w1Dn3nuo0sUdzc7NraWmp9sdKHJmLy3oKdGrhgrncauF7LKWN0d6UJnxltVrqTZm83BeK6LN8mC/YIcWJ09Mz+zI/QDp6wTprWmkXpdEAI3OBVeoYobjbidvLlW3/wY+/cq74dpdi8nQ/cL3P8gmw7JbqtKFU5fr+pfIyvytpDaplOzNb7pxrLrhenkBoHvAr59xvIss/BlzrnDuwLC3tBwVCUjX1cMEsfc1+xleai6bWzRpZO70p2fbBgBFNMG1EOoPXtIt7IVrJi+5yXWD1dzv9uQjPtf977g5jRyVzYVip4LTakr7Arre5lqThlRwIpZECIamaerhglr7qoTclGqSHKWAvTtyL6Xq56A7L1csz4SC4+we9L4bTuP/qTSmdjqHUobiBkOYREsmmUaqTNZp6qGAYrvq3Z1Pvv+L1NkdXf1RjPps41bqKbUdSEzXmmnNp1TN950hJw4SwUapwVrpamWtJpAI0j5BINo1SnazR1EJBiDi2T+LbDq9GIvZKBOxpT5vpbxGD6P4cul+8weqFBt4XW0yhUkUY4sg2UD8jOkdKWgsPqHBAaVQWWhqYAiGRbOrlgll6q7cKhtUI2JO8SI+rPxMdZtufIYP9z9aOwtWg8l10FzvhYpITNWYqYf39zb6vlbv0tqSTykJLA4uVGmdmHzKzs83svMxPpRsmkqhck47254JZk16m0/belEn+sVaDIPBB3NBBPel+lQjYayFtpj93tLPtz9YOOOO40tOrir2znuQd+Uwvz4QsYx91MVxYUimN5ZTGlEeRKinYI2RmNwL7AyuAbcFiB/ysgu0Sia9SZa6zTTranzZp0kuplPA5f/ruftnarZXp4XYx1TgAACAASURBVErqIr0/6Xj9uaOda3/WPl965bdi76xX8458ruN69w+yD5jXxXButdBbGkdaUx5FqiBOalwzcKirpfJy0jjSGnDMe0mTXkplZDvnK1kpLom0mf5eYPZnosO4+xMnEIuuc+5pxU24WK2JGgsdV10M90+SKY3lppRHaVBxUuNWA3tVuiEiRckXcCRJVeekUqp9zieRNtPfdLz+VA6LW/lt4lRfKvrxVf4xWkEt2zonzYJ75/c/xa6/lc+KTccqdFwzF8PLbvGPjRAEVaPaoIikVpweoT2ANWb2GPBOZqFz7vSKtUokrrQGHKo6l16VSqWslmqf80n0FBRzgRn3jnac/Ylzpz/XOjfdWdyd9bjtLyUdSxfuvZWa2qYiAyI1L04gdEmlGyFStLQGHKo6l13SQUi1Uykrsb9JnPPVTpup9AVmof2JEzAkFVSUko5VjxfupZR2LzW1rVopjSJSMQVT45xzDwFPAcOCn7XBMpHkVaNqVjHKUXWu3mSCkPkb4PF2/zixpbrV9KqZVlap/U3rOR9WaiWtpKtYTZnQ89kZ0YAhzjqVUEoAlvRxLbe4KYy5zsVSg1lN5ipS8+JUjZsGfBt4EDDgWjP7inNuaYXbJlJYmueFKaXqXLVVo6cmDQUkqplWVqn9rcY5X8pd9mzpRjf+0penXvN8vO0lPXA/zp3+UnoDijm+mff8bT2YQbh+UdwALOnjWm6FenQKpb6Vo4dMRQZEapoVKgZnZiuBE5xzrwbPRwC/cc5NrEL7emlubnYtLS3V/liR+hZNF2uiMlXIJi/3PSN9lg/zc/pUw+xnfM9MNK1s1sjyB2O59nfPJmiZVJ5jW4kANnrxmLnAj3une/Zl/s589E77AINu1//tJSUTeOQLGOKsk2274eNr5o/NuafBpRdmf3/0PWG1cjwrYfJ03xPUZ/kEX/Ah27nYNMj33GQLlBr5WIrUGTNb7pxrLrRenKpxAzJBUOD1mO8TkVpQrXSxKcN60rkyqj2eq5ppZdn2F2BjZ3lS5CqVelfqBKp/WN73Yh18EFTM9qotk0p15hz/fOnVuSuoFVNlLXp8nYNt3b7XLJrWles94IOnPXfrnY5Vrsk9a2WS0ELpiYVS35TaJtLw4hRLuM/M7gd+HjyfDtxTuSaJSFVVK10sDQUkqplKmdnfzV3QHVruKE+KXCmpd/lSs0oZN9HaBk89X3i9tFYqq8YEmdmOL/hAMddA/Wzv6XYwdu+edcvV9mocg1JSL8MKpSfGSX1TaptIQ4tTLOErwPXA+4CJwPXOua9WumEiNau1w6dgTV7uH6tZDKAY/e2pKXb/0lJAIjN2a9kk/1ipz8/s7x5ZuoUygWYp50qxAWyhAealFAGYt8D3bhRSaHtxeyTK3XNRam9YHNmOb0Y4QAzvW8c7MGhg73Wjx7Bcba/0MYief9f9HPY9AWZ8vf/fX6EenXorDiEiZVdwjFCaaIyQpF5/x9skXU46a5uDnppsbS52PFEa9jMpucYlnb0n/PL14sdmFTveqZLjJnKN2Rg4AAYMiLe9uJ9fifEdhcaclEOm3Zvaexc8gJ7vYe7M3vs2aCBs2wYDB0LXtuz7WmrbW9vgm9/1PSxd24rfTiH5xpDtMqz8qWnFjOPqz3ZL7dUSkYooeYyQmT0cPLab2Zuhn3Yze7OcjRWpG/0Zb5OGctLQv56aYsYTpWU/k5JrXBKUNjar2PFOlRw3ceh+2ZdPPT7+9uL2SFSi56IaJbEzx/e804MA0Xo+J9NbEd23riAIOmT/3scQ+tdrlEtrG0z4OPz0juxBUNMgOGS/8vS+xUkNLKdixnEVEqdst4jUhJxjhJxz/xQ8JjwzpUgN6U+6UhrKSWfELfVdTDpWmvYzCbnGJZ35ZGljs4od75TEuImddoy/vThjlFrbYMl95Z/QtFoTZI4eCQuv8FXisvVWZDsGXdt80DR5gn/9m9+F238LWzt69xoNivQaxWn7vAXQ/lb21wYYDBnc+7NKGTeU7fzLSOvYsahSJ2IVkdSIM4/Q/sA659w7ZnYMfqzQz5xzmyrdOJGaM2UYrIgEC7nG21RzTpty6c/+ZdTifvZHnLS/bIFmMccyqpi5qip5sb8mR6GEtTEKKGQUCtQyd+M3Zzl/Su29qfY8O7kCzmzHYNBAX4hizXN++fLVPZX4wAc/g4Jeox138D044KvfFUrdWraq97bC9tgVTjoKbr67PBf+mfMvV2pgpSekLYdSJ2IVkdSIUwb7VmCbmR0ALAD2BW6uaKtEalV/0pXSUE66v4pJx6rF/YyrlLS/apbyDutP6lt/ixGUI7Ws0AD3zN346IW7WXkCukqkUvVXtmMwcIAvRJG5AM8WuHRt80HQ0qvhlw/44CVO6taUCT0pemFmMO1jPsAt14V/nNTAtKtGCqWIVEWcCVWfcM4dbmZfATqcc9ea2Z+dc++vThN7qFhCiRp5wHo1ZY5zoXSl/hQpSJO4+xdevxb3M45SJ2jt77GspmKKEZSrgEG+Ae65igLsuTu0LKmfAevRY/CH5bDy6fzvyRRbgPwFMbJ91oSPw+YtvZfvMhRW3eHb0Z/txZXZxz8s94HdAIOjJpWnF66SxQw0EatI6sUtlhAnEFoGXA18AzjNOfeCma12zo0vT1PjUyBUgmKrfUllFXMhXIsBbZov+EsxebnvCeqzfJgvz13LClWXy6VSVbpKbVeaFHORnqvamuHnpgpfjJ85p/8V5DJV4+592G/wpKP8GKbMRK2VuvAvd/C8bJUv2hEe01SJQKXS57mIlKScgdChwAXAo865n5vZvsB059yV5WlqfAqESlDqnWtJBwW06VLPv1eFyjFX6o57oe3Wyt34XPtRbPtz9dq8axAccgAcdXjPZ2QLmsx8OtrCK0rbn3Jf+JcacGcLfMxylybPlIhX6WuRula2QChNFAiVoJ7vXDeCTI/Kko2wsdPfAc4o9cK7FnuY0qKu0/7yXKBG57lpGuQri51xnB9PUuzFZX/mEErz3fh8+1FKmtmMr8PPftn7Ij/bewuluqXpWBUz/1H0+A6w3MUeottcenVtBNIiUpK4gVCcqnFHApcA7wnWN8A553JMGCGpVI4KVZKM6MV2VKEKbPkCnei2V7TDolf7XMh3dXVx991309LSwpYtWxg6dCjNzc2ccsopDBpU8M9I/Sq2hHUtyFddLlv54M1b4MZf+gvSYssrxy1LXO7y3uWWbz9yVRz7w3IffObrpVjzfN+ejmxFC0aP9EFp5vvI2NqRvhLPccq5R0WPb5wgKLNNlb4WkZA4VzALgC8Cy4EsM61JTZg7xl/gRu9cV7pClZQuOg9PVL6AtlCgU2COn7feeourrrqK+fPns27duj6b36fp3cw6/Cy++NNvstPBu5dhZyugHD1e+bZRTAnrWpCvlHS+STGh+IvLeilLnG8/4pTGzhVI9idoWPN83wAhjceymHLuuc6/qExPUXibZ86pj3NMRMoiTiC02Tl3b8VbIpVVz3eua1mci/Rs8/BkFApoC01mmmeOn1dffZVTTjmFTDrqgQceyLRp09htt9144403WLJkCc8++yzfXHYNd4y7n7sfv58935+ywDpmj1fFt1Gr+jPPTVQxF5fF9A6kUb79yHbhP8B8aeyu4F5jrkCyP0FDrRzLYuZuynX+ZcYGhVM11z7fe5u1clwkHTSerO7FKZZwJTAQ+AXwTma5c+6JyjatL40RkroSp/BBawec8hdYtbX3ewcAezTBtBH5A9pCY8NyDPZ/69O7cMzyf6WlpYV9992XBdf9D8d0/g576VF44wXo7qT7+G/x27fHMWvWLF544QWadx/Pg//nRnZ6Ylt6xhqVo5hBPRdEKFZ0jEahwenFbrdWx28U2o+4pbGzjZOJMz4qUwHupjv99xLuFanUsdxede4P/nm46lwlPivXGLVo4BPnvbV4jknl6VypaWUbIwRMCR7DG3PAscU0TEQChXprMoFSe+SuZyZgaplUONAoNDYsR8rkVcNu3x4EPfLII+zV+RL85CbAwcAm6IYBb2/ihBNO4JFHHuFDH/oQLS+s5uoffY9vdJ+bnl6TPD1eVd1GvYnexT8kR7ni/k6OWUzvQBoV2o9oT9vsy3rS4jJy9VIUGh8Vvnjb1u2D1IED4OxTKhuYRIsz/PQOf05UojhDKedJvZxjUnkaT9YQCgZCzrmPVKMhIg2n0AV2JlCKZh+9dwjc/b54AUahsWFZUia7/mMU8z/8CQDmz5/PXnvtBW86OOhjMOow+NMPoGt75zB77bUXP/zhDznxxBOZ330nX+UTDOoc2DuoS0o5ioSo0Eh20QvyclVyS3shhLjy7Uc03ebc0/o/TiaX6MWbczBgIAzbqXIX+/MWwJtv9V3e/lblLhpLOU/q5RyTyqqXMYuSV5yqce8GLgdGOedOCuYVOsI5t6DirROpZ4UusHONDdpxYP4gKDru6N4JcNMruceGRQb7333HHaxbt46DDjqI4447zi/ceSR84mb/7yd+Bm+/0esjjz/+eA488ECeffZZ7uFPnM6RxfealLOcdzmKhJSr0Ei9lynXxWU80XSbTGGEe+f7VLZSA8kkLt6WreqbGgk+JU8XjVKrNJ6sIQyIsc7/3979x8lV1/cef3/3h4QkawRJMMCmgpVfGmObJak/kFqr/AgEMCVsibG1udf19pIWe73xWuqjP8yl98bHvaLYSvzRKiE0BKn8ChDFizbWurCpiREDxKJkQwIBgbBJWMjufu8f3znZ2bPnnDln5pw5Z2Zez8cjj2VnZ898z8yQnM98P9/39+uSNks6qfT945KuyWpAQMtYNce1uHWWvvdfYC/sGv+Zyu4TNRPhtdOt3evWBq3dK124wx2zf74reCpcfHvr8K644gq1tcX5K0Jqa2vTFVdc4X5fj8Uba9zxzxtwt1fDm/HqO8mNpW928nY9/zGumiUtfr205BG3fijO2LzzurF0Xl/cK725X+o/UN15NZLBfa71a8GV7uvgvrxHlK81X3MzJf52m5vvdoVk/63ua7WzNwvnuou1cllfvC2c61rw/NpM/MdthfdJs59js53fqhVuZtb7/6mWmVoUVpw1QidYazcaYz4lSdbaEWMMMdpArSol+VUzE1Fp3VEMBw+6Pv/jjz8+0el49x/Sy9XPmqQw/knSiLf2jlFtgtya3W6tV/kH9a9Y6bxt0q6FzTUzVC5o9mPdXdVtvNos6U1bto6nw3mOjEhbQvKHkp53NXHUtVq1wr2u/g1cu6bFe9ywWbJmWpTe7OfYjOfHerKWEKcQOmSMeb1Ke9kbY35LUiofYxpjLpD0eblUuq9aa/9XGscFGkbURXo1kecpLOyfPn26JOn555+vcM+JvPt3nfQ66YOzq2v9KnowQZJCrbwV7snhyWu9JFcM1XsdVT0LirCNV2+6y7VSxb1YaqaLrLDNP8fGJPk2L973jKav36SeI51aNHqsOuKcd7UXb7W8L7pnu1CEo6lxRrrw3fHDGVphUXoa51jkDwOa9TWk5bfpxSmE/kzSXZLeZIz5V0kzJf1erQ9sjGmX9HeS3i9pj6SHjTF3WWt/VuuxgaMafV1G0tmMFBb29/S4gMiNGzfqb/7mb2K1x42Njem2225zv/+lS6TFVV7Ynz1V2jokjZXdVoRgAu999I9PxyvU/DNHAV1DR9WzyKt3QRG28aVNuPFq0EXWi0NSzxXS0gsqXxDmcQEZ9phBLWSSDtlRfW716vDNi9WhviPH6eNDszSt0vOVJKjBm7Gp9X3RPVv6+t/Gu69/DFu2Nv+i9FrXbvn/3/3xz6Sv3CadeZp07vz8iyKCBdCg4qTG/bsx5jxJZ8j9c/6YtTZse8ckFkj6ubX2CUkyxmyQdKkkCiGkI+uNMItYZKWwsH/RokU65ZRTtGvXLn33u9/V+9//fveDoaelI4elsdL//sMvSs8/IU09QQ/8y4+0a9cudXd366KLLqpu7IPD0h3PTSyCJGlqW/IWuzT530d+QYWaf+YobLu2DtW3yKvHp7beRe6WrdLg05XvH+diKegiy1pp//PS2o3RF+1pFH9JC6mox3zPfOmRXS7aumR/25gW7f+xBj59j6SIzYv1rO4cGdKmf31Ys+KNPN64Fr+3fp/mB42hzUgd7RNbBpttUXqtC+/9/++OjLo/2x9z0et5z5ASLIAGVfGj3tLMzUWS3ifpA5JWGmP+LIXHPlnSYNn3e0q3AemIamOqVdqL+tOSQjhAR0eH+vr6JEl9fX16+umnpdEj0v89W7rx3dLLpc7YHRulv3+HXrlpyYT7d3TEmWgOsGa3dNi3dsJIuuyEfAtM//uoXFihGZb4V65DUldHfYu8rD+19S5yb7zVXaA97+uiDpoM6exw+xBFLbIOCgDwlF+0B4kq/pKc09qN0sM73Nd5l0cvBI96zA9dcrQNTpIOaUyLxp7UwP6ndOqpp+rb3/62vvujH+u5My7Tl351pm7Tu/TBv71N/7xps0499VQNaFiLntqqQ4cC4qorCRvXfVvq92l+0BhGx9xeR828KL3Whfdhs6tS8vd0FggWaBzNFmpRoziRUHdL+kNJr5fUVfanVkH/JE763NQY81FjzIAxZuDZZ59N4WHRMrJcb5JlkVUrr50uZkpckI9//OPq6enRL37xC73zne/Udx54QLbjGOnVQ9LIy+5Orx6SRob1g/4f65e//KXOOeccXXNNDYGS/3Jg8utlJe08XP0x0xBW1ExrCy80wxL//uBE6epSkfqxk+qz4Wz5P3rDr7hP3ieMK8VPbb2LXH8YgOf0U6UZ0ydeLE2d4jbejCo0/BdZflEX7bUWf9UUUlGPefPdUvv4a/A5Pa8BDR/dvPgd73mvLvv7H2rzI89obEw6MjqmWwf26EuPHaMtP/hXVwztf0rXX3/95MetdIETNi6Z+iXNBY1hZNS1ePUtdY/Zt7Qx139F8dZuVXuOUR8GSPm3odV6fqiPaj7YiXPMBi6s4nx0e4q19m0ZPPYeSd3ljyNpr/9O1tovS/qyJPX09IQ1mACTZbkRZtEX9ddo2rRp2rRpkxYtWqSBgQF94IKL9OY3v1lXXPFHR9t1brvtNu3atUuSdM4552jTpk2aNm1adQ84OCw9FlDw1Lt1LEjY++gjbwhfvxXWoviZU+s7u+VvQ+pol0ZHx9uQ0v7UNupTa8kVQd/56sSF/EOHpFs2RbdllQcAbLxfeu6FiaEDURfttbbsVFNIRT1m/46jheKIrNbqBUnjmxd/44e/0NDLIzqms023fvQdev7wq+pbt1V7XnhZjw+1j29evHatPvnJT47PwMZpAQwb14Xvlu56sD5Jc2FjOHd+8y9Kr2XhvT8N0K8IbWgECxRf2u3RTRBkE2dG6D5jzAcyeOyHJb3ZGHOqMeY1knrlQhmAdFTap6cW1ezx02BmzZql733ve1q9evXRNUPXXXedPvGJT+i66647uiZo9erVevDBBzVz5szqH2zNbmk04HOOdpPv+iCpuvdRGvsXpSFoXUFHh3TWm7L51DbqU2vvQs27WPL2y/nZE/EKDe/3Bm6TZnTFb8GptWWnmn15oh6z7HibdFB7NDJh8+IHH31Wr46O6d2/foLmdb9O7z1jln7t+Kk6/Oqofvjz545uXjw4OKh77713/DEDE/pKgRLep7Rh4/rMn9Tv03xaqKpTPuMy7wzpmM7x2V2eQ8SVdnt0ra3HBRBnRuhHkr5ljGnTeP6Rtda+tpYHLu1HdLXcZq3tkv7BWvtILccEJqgmfjquFEIJchUz6GHatGm69tpr9clPflL33nuvBgYGNDQ0pK6uLvX09Oiiiy6qfk1Quf6h4HjpM6fmH0BR7fsojf2LahX2j96xx7hCJG3ep9ZDhya2x3W0h1+oJZ2xKZ8d2vLvbr2NMe77oBCDJHHSQaEI1ezLE/WYZccbOOLaTMs3L/7ZvpckSXNPnnH0cKef2KVd+w9q65MvHt28+LrrrtPAwIAWL17s7hT0Wo8FBEpEPRf1+DQ/6Ln50CXFjYUukvIZF++9yv42SCLtUIsmSAuMcwXzfyS9Q9IOa22qrWnW2nsl3VvxjkC1sroYzbLIyloVaXodHR1avHjx+EVX2uMZDlhT0mmkc2dMvj0PRShqqpFHktPi97rF92Nj0uuPk6a8Jjret9pCw/97OyOSs+K07ES1eFSzL0/YY5YVAgdvu0l65lcTNi9+ZWRMHW1GXVPGp5yPm+b++/Cr7nU8unnxUFkrbtBr7fG3v9zwF+MX0kuuqX/x4b1+XrrgV25zgQkjo+PP+31r3XqqRiuO6hXVThsaqpH2hstNkBYYpxDaJemnaRdBQMNr1IvjJJuCZs0ryoZ8F2+daqwZtqKK+49eGhdv/kKis8Nd3FZqsUo6w+NJu9e90vHSvOgsXcROf90r0urVEzYvPqajTQdethoaHl+U9sIh999TX+NaoY5uXtxV1opbaQ3JkRHZ/p+4lKIKff3WWpmQ/Y5S4X983zg1dEg678NuRquR1h00wXoJNLlqN1wOk3ZhlYM4a4T2SfqeMeZTxpg/8/5kPTCgoQ0OSysflxZsdV/zjtUuV6SgB68o81+3nTk1nzU1zSZOklNaKUK19Ip7MwS790qPPiH95LHK4whrydi4ubr0otDj3Z9ZGlL55sVjpUjts2a7rvMdT41Hjz/+jPt/8zfnHDdx8+LS70ua+FrPev2kjVuHO9p08f7t2rBhQ/Br9cJL0qL/og1/9yVdfPHFGh4u+zsr7VQo/+P7jYxKrxxpvHUHTbBeAi3Av06zliK9CdIC48wI/aL05zWlP0A2irhBaTWiWs+k6s8xrecnyzS9pMKiqY9tb8zXvogqtdCkNbMSVUjEmWlKOo6wVrBnn5f2/yr5p/Fhx3vuBbfOJoNP94M2L/6dM2fq3/7jV/rBz5/T9sEX9fzhV/Xk84d17Gva9a43n6AHHnggfPNi77VetWLCzMRwR5su0x5tfvKA7l+2THrjAvUGFCEbdjysZVffqTFJl112me644w5NefYFae6lbpZmzEpbfyqtu0vacWf1z0OldMEgjbDuoAnWSwCJNXibZsUZIWvtXwf9qcfg0EKKukGpN7YkszthrWef/kX155jm85Nlml5SjZa+V+SZvmqldfEWlhj33AvxZpqSjsOfPtZWmgHxuriTfhrvP543ozJW5fFiCNq8eMn8bnUd26FXjozpg3//Q634+sM6Mjqm7uOO1RmvHY23eXHZp7T2nLdqyclHtHnEzTCNjY1p2S/6taH94IRf2aADWqa98rZ63bx5s5YsWSL7F5+XDhwcfx7GrPv+01+o/sQrpQuWJ6KV3170dQfVJAwCyFVoIWSMub709W5jzF3+P/UbIlpCUTcoraYACWs9u+/56s8xzeenKNHOUrGKskqKWqzXWpyldfFWayGRdBz+lowTjpt8H6+QitPa5T/ezIjjpci/efEPv///dMcfv1Pnv/UNamuTOtvb1Ntzij52+rDe/a53uc2L57298ubFpU9pzUMbtfx//fXRVDpJGrNWy0YHtUGuOPIXQZLU1tam5cuXy9z/g+Dj3xdyexxBEdrHdLpY6L6l0vdvkrqmNV7ENtHgQMMxYRkIxpj51tqtxpjzgn5urf1+piML0NPTYwcGBur9sKiHBVvdxeWk27uk/vn1H49n5ePugtffRtY3OzxYIPB35PbEGQ74/y3OORb1+UmD1/JX9PS9sPfCVbOkrvZ8Wjr9bZidcoVlksI2KORg+tTqWsDKI31/+ZRrKfNbMDc4urvWcaxc7Wad/OlFVy0K3iy00nHDjte3NHkbSIUwiv379x/dvFhSafPiK4I3LzbHatMf/almfvVvE4VcbNiwQcuWLTu6Fklyn4Reoum6WwcnFkGS1v/TP6m3t1c68d3Br+Os46VnaiiGKsU/N2o8dKOOG2gyxpit1tqeiveLEwZnjJkpSdbaZ1MYW9UohJpYNQVHPVRTgARdnHrXUv7/3eKeY1GfnyDNstbLL+y90C535VhtIVKLtN4XWVy8VVNI1DKOsEJq8XulWzYlL2hqLcy8c9my1QVAePHQIcc5dOiQrr/+et14443as2fPpMN1q0N9Ok7X6HhNWzBP+ub1bnzlezYd0+lmUxbOCxxSUDHk1yZp/Zwe9T75sLvhDz8lfePOyXf8g0ulr/9t5ecBAHJQcyFkXHbmX0q6Wm4T1Ta5y7kbrLV/k+JYY6MQamKTiodSi1TeyWHVXmiWz3K8PCrtPDw5Gc1Iel3Mi+aiPj9+acxQFFXQe8GU/pRfV9azQC3yTGGaM01JHtNfSC25xq1R8gubmap0vLhFUFg8tBRZiI2MjIxvXnzXA+ra8R/qGXuNLtJ0dciM/64k3XjrxI1rJVcM7bo/emboqqs0FvBvf5uk9W2nqPeP+yZu3Dn3UumlQ279lTHSa6fVFpYAABlLoxD6uKSLJH3UWvuL0m2nSfqSpPuttZ9LcbyxUAg1uSK2SKVRgIRdrM7qlAbmJ0+NK9LzUz6u/iG3Maq/6CvqzFVSQe+FMSsF7AUbqxBJY+YsrDib2SktnVnnNr2ANi0p/zahNFvcanlMv7iFWFgxGVbgSdLVV0We22XHnaw7X9w76fZLNV13HPeWycVq/3bpP/+l9MSgdFq39JW/Dp11mjD2emwsCgAB0iiEfizp/dba53y3z5T0bWvtb6Qy0gQohJCLWguQRmprS8pfHIQpwgxFGvzvhaFR6ZZnqpsxTGPmLOr5r+dsXB6zP0UbW/mF/5Mh66M8SQqxsFmplaulL94S/DsRRVbFGaEv/r16/+t/mfj4SZ+/Ir8fALSEuIVQVHx2p78Iko6uE/IH3gLNq3uKu6jtn+++Jr2oLGIyWlox0P40uyBFjsNOyv9e+Myp1b22aaUAlicAzuqc+Dd6PZMXk2wkmfbmnJVUs+Ff0jH6N6V99oXw+yZNEgvb4dn3MwAAIABJREFU/HDVCtcGF3T8kKS9o2uEQj4AHZO07E+udpuueqrZJDTLjUXr/f4B0NSiNlR9tcqfASjnXawWpa0tasPXpGMK2xDVU6kwaPRghWpf27CI9YcCWijjjOGG090x9/sOWu0xk4q7B5B/piCDTUojVc4Gqm6M/gt/r9BoK7VPdna4/z7zNOntZ7qfLbmmtpax7tkuGOG8D0uvlF73iCIrMDXOGF0yY7buPrDvaHE0NjamZcuWSZJLjatmn6msNhbN+/0DoOlEFULzjDEvBdxuJDXQlQpQAN7FahFEzUYEjTGqWFnY5Qqp8uvvDklnTZWObY8uDNIsyLJUqVir5rUNet5qnTnL4pixH3uuuyj1r8Pxz0xEzRRktV4n6cVz0jEO7pM23h+8HuiE46Q3njze0ibVfiHvX3vz/Zukm++OXIcVWAS1tWn9+vXq7e2d9PMJxVDc17ZcNb8TRx7vHwBNLbQQsta2h/0MQANLMhtRqVhZNcd97w+T2PS2ysVM0oIsD1kVa2HPWy3tklkcM/Zjr3AX9P41If6ZiaxmCqIkvXhOMkavyHox4P+dzg5p6QUTH2Pl6tou5KuYEbHWat26daFFkKSjX/3F0Lp163Tll74iE+e1LRf3/ZBUHu8fAE0tao0Q0FjSWvfSqOKe/8Kuyav8wmYOKq1lKV+jsqDLhQTELRLSbA/LSlprefxqed7qeczYjx1zHc7Cue6iuFwaMwVRkl48JxmjV2T519y0mWwKwSrW3hhjdPvtt+v8837bDU1G6393iXrfNXGv9N7eXq1fv15tbe6y4Pzzz9ftt98uM+ek5GusqlmXFUce7x8ATS3WhqpFQWocQjXz/jVxJDn/JJHgWe5TU7Q0vaAWuCWPFHefnkaUR5pY0vjsJGNccGVwhPWs46WB2ybfv9Yo77DHK0+JC4kxH37bpVpy4FEtt13q7Xx96Dlt2LBB69at0+23364pUwr2dydpdABiSiM1DmgcWX1yXw9pzGQlOf8kMwdJZo+iBJ1jkdL0vOJw7V5X+Kzd674/e2o65w8ni5mCSiliq1a4i2VvJqFSm1aSMZ59WvAxLjx34v29MW7Z6maLOtrDxxJ2PoP7pOFXJj9WR/v4jIg/vW7tRvf9p7+gKYeGdY89Wb2aETmT1Nvbq3vuuad4RZCU3UwTgJYVFZYANI5GaLMKktYalKTnH3eBf6V1J3FS36LOsShpemGFpOSKtTzW3TQrLw46jkqbcsZZM+NdPCfZ2DXJGOOcQ/kYO9ql9jbpLb8unTt/4ljCzue+tdKFfdJLBycff3RU+tAl7r/DWufu2yIdGZGRGf+9iJY8Y8ruV7SNUdN8bQC0PAohNIesErOyjndOKzAgq/OPiof2Fzg/HpK+sk86c6p07ozx+1U6xyIEI4QVkjsPF6dYazVxipy4QQhZXTz/7Ing23eW3e4f48ioZIwrgvxjCjuf//yX7uvomCbp6HCpcQvnha9BknGzT0lT3LKMqy5agQWgJVEIoTlkkZhVj3jntGayskwMC5s98hc4I5JGrLT9kLTjkPSlvdKHTpS2HSz+bF1UIVmk6PNWEqfIyTtFLE5MdNQY/cXAlq3B931iMDieu/xYUeO58N3SXQ8mT3HLKq6a/YAAFARrhNAcskjMqse6o7TW4OSRGBa1meqYpFFJNz0jPXp48kcu/nNMuk4q7YTAIq1Xqgf/OpT+7dHrbPIQp8jJO0UszvqjsDGeddrk9TyPPjG+fqj8vqd1Tz5G+c+98w0bz2f+JHptjfd+ePvl0tsuc+NauVr6l5DCrNZCs4r0u9xVWosGoCGRGodiyLoFrRpZJqZ5vFmnoRE3oyJJxxjp+2+XFs6I9/t5PW9BqW9BOiS1G2nMBqfUJU38yyoh0Hsum70FLmjNyuio1N7u2raKksQVJ2GtCCli3qxO2PqjsDEufq90y6aJ5+etHxqzE+/rrREaOuReo/Lnw3++lcYTNP55l08+tjeW0bHJjxk35S5MnPS7IinC+wxAInFT42iNQ/6StqDV6+I/q3U35bqnSPfNlc7b5trKJGnUShfuqHxhX4/WvSj+drwwI5LeMlV6+3TpvufdbRceP/7zpOukstqItVVa4ILWrJR/Tav9qVZxNuWsJgghbZXWH4WNcck1k2dbRkbHQxT85+MdY8tWVyi1tUnn/ubk8026Hsp7P5QXO95YjHHFkDG1b4xa3gY4/IortPwFVnn6XZHWD1VqESzaeAHExowQ8pdkP5l67heUZL+dWlS7n04R9uHxitItB1wL3KtW8v+V0mmkq2ZJd/0q+HVLuldP2EzdvGnStnNqO48izUhmZd7l0k8eq3y/Inw6n3R2o5HUuqdQWsJmZzzzznQFVy2vQZJZSKl4sy9RM1jfvL544wXAPkJoIEkCA+q5X1CSdTe1rFmpNjAhraCFWsbuzaJsO0fatVD68IlSu3Q0pdcrHqXw1y3pOqmFXcFz2Y8ejjd2//n2H5i4h9Df7ZVO/ZH0hztrX3tUNIP7pMdCks7K1bLOJs21FN7sRv+t7mszXVjGWV9Uj3UpQWuYPJ0drgiq9TUImoXs6JDOetPkNUtFXD8UtRatiOMFEButcchfkha0eu8XFKddqtYWtWpb8NJo3Uuzva57ivT1s6TPnDp5rc2SR8Jft2++JVni3ao5LqZ7xDf1NGort8cFne+XS7Nq3uGsXNDDumfcLFa9Wg3rYc3XgiOYpfFWpVrbn0gDi6dSW1+9nkuvBTFojVC17wO/sOCLY4+ZPOuYdxJgkKg2zaAWx7zHCyA2ZoSQvySJXWmlrKWp1lmqahPL0kg6y2KGzSse++e7r91Tgl+3NklnTU2eeNc9RTpj6uTbR1S5IA4631c1uZ1Pcsl3Wc025qV/x+S1IJL7ZP5jVwYniiXRaJ+OR8241GM2JmrGq17PpVeQfexK1wY393Rp3hnu+7SKriTpfnknAQbxnqOg1L0ijhdAbKwRQjHETexKum6nHms/0kiXqzaxrNaks6Rjr/b5HByW5j4sHfBdhM9ol3ack/w1qXZ9VNj5RkkzJTBvWa9LaaQ0sKgkMCn/dR+N9FxWkiR1rdES2hptvECLIDUOjSVuYpc3e1BN0eRv+yq/qD+7NMPws8PJC6Y0WtSqTSyrNeksydhraaPrniJddoLbV6j8s5fDY9WlvVXaQDasYAs63yh5zzamLU4SWy3ibDBaFJVmXLLYSDSJoOeyzbj9hxpNknS/IiQBJtFo4wUwATNCaF5Rswar5ky8qC+XNImuXulyWUgy9lpT6tLelylsNiwqWVCa+DOj4LY479xqfR2LmEaXZRJbI306HjXjYlWf2Zio2OXBfdLcS6UDByf+zozp0o474z+fg/ukT39Bum+L+/7Cc90Gq0V7PQAgRcwIAVHBCv61IhPuo2T70iSZpSqaJGOvNagi7X2ZwmbDKu0zVH6+Z02V7nhOOjw6XjS1GenMqdK5M2p7Hf0F2Y+HXMjDGVOl99R47Fok3Wcm6bHr9el4rXu3VJq9ynpmq1IYQvds6bL3STfdJZV/YHl4OP7MVFAx9Y07pTu+m6yYqif25AFQRxRCaF5RF95BF/XlkibR5bEZZ1qzDXHHXmshU6mdLS2VCjb/+da6ziqMvyAbkUu6+8khaeeh+m5+W09ZFlqeNBLVKrUJRv0sjYv1Spt0StLPnphYBHn3i5tItuZrLg3O76VDk4upuOeUZaFC6iCAOiM1Ds0rKlUtKMWsXNHXhnizDd7eN2v3uu+z3Pem1pS6pOlw1UqaLBiUcpeGqGI7y/2vWkEaiWpRSWBRP/Mu1tdudO1zaze675OmysWJia41kax/hzQW0Ptp7cTHiXtOaZ17mEZLHQTQ8CiE0LyiLrz9F/XlspqpSFM9N5b1pFHIpFl0hG0Em0aseBoqFdtZ7n/V7NLaayYqvjrsZ2ldrMcpcuJsulrpMdrM5NuNmfg4cc8p60KliHsIAWhqtMahuYW1ffnXxpxVSo3bebgx1vhUav/KapF+Hi2AQSol2BVhzZa/FdCv6LOOeYjbdpVnOl1aF+txEvzK11xt2epmd9qM+z5OS9qqFdK6uyYHLrx22sQ2v433Vz6nuPerRSOlDgJoCqTGAY0oSSJe0hQ8TxETzzy1JtjVi/ccbjkgPXpYGrVurVAjJQvWS6PsNZPmXkxxE/xqOd+jqXE/kGQnpsZ5xz0wNLmFrvycvPu9ODR5zVKa+1A1UupgERAsAYSKmxpHIQQ0oqjY6zW7ay8SoiKoi3DhnnYUdz1kFcrQLJIWGFnGgEfJ42I9q41wg44ruda513WNn1PY/dqMNKMr3XPP63VtNBSNQCTis4FmFtX+VWvMtVQ5grpaac0ypR3FXQ9FaSssqqQtZ/VIpwt73HpHhP/jt7JpSQt6ziVp5vHSwMbxcwq73wnHSQO3pXvueb2ujSZO6iCAiiiEgEqK2iIWdmGdRpGQRjHlV2ldTxL1iuJG/TTS+pA8IsL90nhuwp7zpedPLG5C73cBsw95IVgCSAWpcUCUPGKqa5VGalrSCOo40ky6q1cUtycsoQ7pqTUhrdn4P/EvV+tzM7jPtbtt2era2zrao4/La1M8tUarA5DEGiEgWqMsyverdT1K1BqkaouNeq3rSWMGr/wYZ0+V7nhOOjxazPVSzYT1IeMWXOn26vGbdqz0kcurf278M00d7VJ7m3TmadK58ytvpMprUwysEQIisUYISEMWLWL1UOt6lCwiqOuxrieN9jv/MbYOSWNlPz8i6cURqWertHTm5OelqK2UjaCI60PiJHNlkd4V1o72kctre478M00joy4c4dz50cct4mvTyuq5Vg1oYswIAVEadUaoiLKYZfJL4/UKOkYY/+xQ0dP2kEycT93j3iduoeTdd8tW6dEnpNExV6zU8ol/+eM/+ZS0//nJ91kw120eCwBNIO6MEGuEgChprLeBU491PWnM4AUdI4x/nVOa66CQv6hkrrj38QqltRtdq9vaje77wX2TH6/8vtsfc0VQe5s07wwXlV1tEVT++EFFEGtLALQoCiEk02qLxuu9KL/ZeS17/fPd17SfxzRCHoKOIUkm5P7lhVajtlIiWJxkrkr3iVNMeYLa1sbseNtaNW1PUaELEsEHAFoahRDia8QEtTRkffGO9KQxgxd0jBnt0odPlGZ1Tv5bs7zQyiJtD/mJk8xV6T5JYo6ziEQO2wPIc+ZpLLAH0LIohBAfbT8oujRm8IKOseMc6etnSQPzpRkRhVacQizvWVUvOnnBle5rUItWSdw1pI201jSROLHRle6TJOY4i0jkoGOWO/YYiiAALYuwBMRXr/hjoMgqRZNH/TzvMIUEkbvDw8NasmSJli9frt7e3tBDbtiwQevWrdPtt9+uKVOacLY0Tmx01H2SxBxnEYnsHfPFIcn/731nh1t7RBocgCYTNyyBQgjxkaCGIEniols9Wjrv/4dWrnaL5v2RzL6L4eHhYV122WXavHmz2tratH79+sBiaMOGDVq2bJnGxsZ0/vnn64477phcDGURLV0E1STBxYk5zmK/nsF90qe/IN18tyuGxiz7zgBoahRCSF894o/RWJLMcOQ9G1IEec+qhm3SWRadbK3VxRdfrHvvvffoj4OKofIiyHPRRRfpnnvukTGlZIlm3fSxEc4rqFCT2HcGQEsgPhvpI0ENfknWjSVdY5b3Wpos5B2mEGMNijFGy5cvV1vb+D8PY2NjWrZsmTZs2CApuAhqa2vT8uXLx4sgKVliWiMp+nmFRXZLbuav/9bqU+gAoIlQCCEZEtRQLklcdJL7BiUUzn1Y+sOdjV0Y5b0vVdDC/qlTpKFDE8ITent7tX79+snF0O//vi6bMVvLrrpqUhEU2D6XRgpagnCHuski3S1NRSrUivj6AUBJRJQMAFSwsEvaNjR5zUvQDEeS+wbNHh0YldY9I43JHWf9/sabkfRmVaPCFjJ9/NmufctrjzrrNOmO70q3bHIXy9t2SuvvkbZ/yxU1v3pBy67+Y3klz5ikO196esIho9YQaeFcd0z/mqS4KWj+FrSy8eU6m1HreWWtKIVaUV8/AChhRghoZbW2nyWZ4Uhy36DZI0lHr8gbObo971nV7tnj7VFd06TDw6EzB72P/krr27tD/6FoMya8CJLixU9HKdLMRrlazytrWcRwV6Oorx8AlFAIAa0qjQ1yk6wbS3LfoLU0fmFtdYiv0sxB/w71jk7XJZoe+OuXzJgdGa19dAaqb6m7CO9bmmw2oCgzG361nlfWilKohb1+G++nRQ5AIdAaB7SqqPCCJFHO3gxHmvddNce1vnnjM5L8AZdJQgZaPbY7TFSL1+A+afgVbdAB3a2Dgb9+94F92rBhQ+ViqNp9avJsQasUj13LeWXN3wKZV0Jc0OsnSc+94FrmilQ8AmhJxGcDrSrvKOdKyjcmPWuqdMdz0uHR5NHtxHaHC4uBvm+tdGGfNhx4SsvG9mgs4hCRa4SyGl/WF9De4w4dkkZG3W3HdErfv0laOC+7x202bOYKICfEZwOIlneUcyXla2m+fpa045zqotuTxna3krAWr5vv1oaX9k4qgtokXfraN6itLCLbH61dl/FlPYuw5msTiyBJeuWIdN6HaelKwnv9Zh43+WdFaHEE0PKYEaoWrTZodK2yQW7WM19N+HfBhl87R8t2D0wqgta/6bfU+/N/C95HyBitP3Whei9a1PgbdYZtPCtJV1/FLEZSK1e7vYz8LY7MCAHICDNCWUpjkTmQt1bZIDfLma8m/LvA7t6rdXsem1wEtZ2i3gsXSVLwPkPWat0TO2RvvNW1QzXSzIl/r5uzTwu/by2zGK26p05RwhsAwIewhGqktcgcyFuSoING5Q9eSHMT0yb8u8B89h90u+nWZXpSm3XIFUE6Sb2dx0+4cPXWBC276iqNWavzNU236xSZkdHxiOSiftpfHoRwdmkvJS9GfNtOt8nsazqkV32L/GsJamjlPXWKEt5Qq0oBGgAaTi6FkDHms5IukfSqpP+Q9BFr7Yt5jKUqQXucEOULFFOWm5g2498F/Ts0ZdTqDp2iJdqj5ZqhXs2QznzTpIu+3t5e6drPa90TO3S7TtEUr8mgyOs//AXJwE8nLuQ/MuKKokt/R7r7Qbc2SKp9FiNqT52iFoxpKnLKXhytXMgCTSyv1rjvSHqrtfZtkh6X9KmcxlGdoi8yBzBRVpuYNuPfBaXNOKeoTfeo2xVBnR3Sub8ZePfeixbpno5Tx4sgqb4R10lbzfwFSdA62SMj0u590q773ZqgNIIaironUpBWbeGLwuawQFPKZUbIWvvtsm9/JOn38hhH1bJstQFQXP5ghA+dWJy/C9Jq21m1Qlp3lzR0SGZMUptxrWJhMyGrVsisv2dyxLV3/6zaiar9hD6oIPHzCrk0ZzHy3BMpCWY+gjVSIQsgtiKEJfyRpPvyHkQirbLIHMC4oGCEC3dI983N/+8C7+J17UaXdrZ2Y+2BBdb3NUxUxHUW4/JU+wl9acZrkrZSJHhWC/kbJTCAmY9gQe+bIhayABLJrBAyxjxgjPlpwJ9Ly+5zraQRSesjjvNRY8yAMWbg2WefzWq4yWXVagPUanBYWvm4i41e+XhDJ5gVSlgwws3P5P93QZoXr2u+5tbIeC1j1rrvo47lzZz03+q+ejMHWV5UV/sJfVBBMmO6tHxxtnsVpb0nUtz2taRtbsx8BGuUQhZAIpm1xllrfzfq58aYP5B0saT32YjNjKy1X5b0ZcntI5TqIIFm498baNuQa91ixrJ2RQ5GSPPiNa9jJW2hq7bVLIsEs7hjT6vVLm77WjVtbo3SwldvzZJ8B2CCXFrjjDEXSPqkpMXW2sN5jAE5YKYie1FxzqhNkYMR0mzbyeNY1bTQ1fIJfdgMVjWybP8LE3emrZoZOWY+wqX5vgFQCHmtEfqipC5J3zHGbDPG3JjTOFAvTbjxZCEVedai0a2aI03vGC+GihSSkubFax7HquaCPe1Ws2rlsaYm7kxbNbN7RXleAaAO8kqN+/U8Hhc5qrTxpD+NK619XlrNwi7XDldeDBVl1qLRZbkfUc1jS7FtJ49jVduOV4S9afJYUxO3fa2W9sG8n1cAqAMTsTyncHp6euzAwEDew0A1Fmx1M0GTbu+SvvmWietaOuU+eWddS3L+NULerAXPZX4o8itbudq1lPkv2PuWFv+CPI+x+9f+eDNtldYIhd0PAJqMMWartban4v0ohFAXKx937XDlMxUdks6aKj1zRHruiDRW9rNO46KIbzi9zgNtAt6Fd9FmLVrRpMJUFPlBGvmCPa+xewENlWbt4t4PAJoIhRCKxX9B2CFpVFK7XIB6kAVdLpIYaFRBHwBQ5Adr5Av2Rh47ADShuIVQLmuE0IL86yteHpV2Hg4vgljXgmZAeEV8jbwupZHH3iiSxqsDQAwUQqgfbxNaya0ZiiqCipLGBdSC8AqgdtXshwQAMeQVn41WF7Qni5E0q9O1DbGGAs0gLHL7Qyeyp1aQwX0ufGDBle5rlnvxoHHEjSjn/QMgIdYIIR+km6FV+MMrPnSidOEOAhT8ihCYQPtVMS240m1WO+n2uW5zU6kY7x8AhRF3jRAzQsiHt2ao7yR3ccgsEJqV1xLaP999vfmZ8D21WllaG5NWOyvgXUiv3eguutdudN8zq5C/hXPHN+X1+PdDymNjWwANjzVCyE/5miGgVRCgECyNjUlrWUsSdSFNEEK+Vq1wr6N/tmfVivH75LGxLYCGx4wQgNoMDrPeJYmg9XEEKMT71L+SWmYFuJAuru7ZrpjtW+reD31LJxe3abx/ALQcZoQAVM+/1mvbkLR+P22OUVbNcc+Rf31cq6ckxvnUv5JaipmFc90MUvnvcyFdHJUiytN4/wBoOcwIAajemt2sd0mK9XHB4nzqX0ktswKrVrgLZ+/3uZBuLGm8fwC0HFLjAFRvwVbp4YC1LQu6XDgAUE+1Jod5qXEP7XAX06TGtQ4SA4GmEjc1jtY4ANVjw1AUiTcrUG0xU6n9Cs2JDVuBlkUhBKB6rHdBlqr5lJ5iBkmRGAi0LAohANXz1ruUbxi6ag7rXVA7PqVHvZAYCLQswhIA1Ma/YShFENLABpmoF6K3gZZFIQQAKB4+pUe9kBgItCwKIVTGhpkA6o1P6VEvRG8DLYv4bETzb5jZKWl6B/ueoPgGh93apf4hl27H2qV4ihIjXGsUNgCgZcWNz6YQQrSVj0tr906OR+6b7daDAEVEAV+dLIqPWgor9vUBAFSBfYSQjn7fHjGSdMS6hDCgqNbsHi+CJPf14Ki7nQI+XFRAwaoVyQuaWpPfiMIGAGSINUKItrDLfZpejg0zUXQU8NUJCyjYstUVNGs3Sg/vcF/nXe4KnSj1Tn4b3CetXC0tuNJ9rTQ+AEBLoxBCtFVzXEuRVwyxYSYaAQV8dcICCsZsdQVNPZPfvNmnSsUaxRIAoIRCCNG8DTP7TnIXkX2zWWeB4qOAr05YjHCbqa6gqWfyW5zZp7jFEgCgJVAIoTI2zESjoYCvTliM8Lnzqyto6rk/S5zZJzZpBQCUITUOABCtljS5eiW/rVztZnjKi6HODumqRVLXNFcoPfmUtP/5yb+7YK7Uf2v6YwIA5IL4bABAeooeZR1UrE0tzQAeHna3GSP5/83r7HAzX6TTAUDToBACALQWf7E2dEi6ZdPklrk24wIg2KQVAJoS+wgBAIqtls1Wg/j3HVpw5eQiSJJOOE5648nFnNkCANQNhRAAoP5q3Ww1joVz3XH964aWXkArHACA1DgAQA7qkeBWz9Q6AEDDoRACAKQrzqal9dhsNSwOnFY4AIBojQMApCluy1tY21ram6361w0BAFDCjBAAID1xW95oWwMA5IxCCACQnrgtb7StAQByRmscACA9SVreaFsDAOSIGSEAQHpoeQMANAgKIQBAemh5AwA0CFrjAACVDe5zgQf9O1z726oV4cUNLW8AgAZAIQQAiBY3EhsAgAZCaxwAIFrcSGwAABoIhRAAIFrcSGwAABoIhRAAINrCueMpcJ6wSGwAABoEhRAAIBqR2ACAJkQhBACIRiQ2AKAJkRoHAEUyOCyt2S31D0kLu6RVc6TuKXmPikhsAEDToRACgKIYHJbmDUgHR6QjkrYNSev3S9t7ilEMAQDQRGiNA4CiWLN7vAiS3NeDo+52AACQKgohoGgGh6WVj0sLtrqvg8N5jwj10j80XgR5jljpoaFchgMAQDOjNQ4oElqjWtvCLvealxdDnUZa0JXbkAAAaFbMCAFFQmtUa1s1R5reIXWWvu800vR2dzsAAEgVhRBQJLRGtbbuKW72r+8kNwvUN5vZQAAAMkJrHFAktEahe4p0w+l5jwIAgKbHjBBQJLRGAQAA1AWFEFAktEYBAADUBa1xQNHQGgUAAJA5ZoQAAAAAtBwKIQAAAAAth0IIAAAAQMvJtRAyxnzCGGONMSfkOQ5EGByWVj4uLdjqvg4O5z0iAAAAoGa5hSUYY7olvV/S7rzGgAoGh6V5A9LBEbevzbYhaf1+UswAAADQ8PKcEfqcpFWSbI5jQJQ1u8eLIMl9PTjqbgcAAAAaWC6FkDFmsaSnrLXb83h8xNQ/NF4EeY5Y6aGhXIYDAAAApCWz1jhjzAOS3hDwo2sl/bmkD8Q8zkclfVSS5syZk9r4EMPCLtcOV14MdRq30ScAAADQwIy19e1MM8bMlfRdSYdLN50iaa+kBdbap6N+t6enxw4MDGQ8QhzlXyPUaaTp7awRAgAAQGEZY7Zaa3sq3a/uYQnW2h2SZnnfG2N+KanHWvtcvceCCrqnuKJnzW7XDregS1o1hyIIAAAADS+31Dg0iO4p0g2n5z0KAAAAIFW5F0LW2jfmPQYAAAAArSXXDVUBAAAAIA8UQgAAAABaDoUQAORtcFha+bi0YKv7Ojic94gAAGh6ua8RAoCW5o+p3za5KyvWAAAJr0lEQVQkrd9PTD0AABljRggA8rRm93gRJLmvB0fd7QAAIDMUQgCQp/6h8SLIc8S6vbsAAEBmKIQAIE8Lu6RO322dxm1gDAAAMkMhBAB5WjVHmt4xXgx1Gml6u7sdAABkhkIIAPLUPcUFI/Sd5GaB+mYTlAAAQB2QGgcAeeueIt1wet6jAACgpTAjBAAAAKDlUAgBAAAAaDkUQgAAAABaDoUQAAAAgJZDIQQAAACg5VAIAQAAAGg5FEIAAAAAWg6FEAAAAICWQyEEAAAAoOVQCAEAAABoORRCAAAAAFoOhRAAAACAlkMhBKCywWFp5ePSgq3u6+Bw3iMCAACoSUfeAwBQcIPD0rwB6eCIdETStiFp/X5pe4/UPSXv0QEAAFSFGSEA0dbsHi+CJPf14Ki7HQAAoEFRCAGI1j80XgR5jljpoaFchgMAAJAGCiEA0RZ2SZ2+2zqNtKArl+EAAACkgUIIQLRVc6TpHePFUKeRpre72wEAABoUhRCAaN1TXDBC30luFqhvNkEJAACg4ZEaB6Cy7inSDafnPQoAAIDUMCMEAAAAoOVQCAEAAABoORRCAAAAAFoOhRAAAACAlkMhBAAAAKDlUAgBAAAAaDkUQgAAAABaDoUQADSLwX3SytXSgivd18F9eY8IAIDCYkNVAGgGg/ukeZdLBw9LR0akbTul9fdI278ldc/Oe3QAABQOM0IA0AzWfG28CJLc14OH3e0AAGASCiEAaAb9O8aLIM+REemhHfmMBwCAgqMQAoBmsHCu1Onrdu7skBbMzWc8AAAUHIUQADSDVSuk6VPHi6HODvf9qhX5jgsAgIKiEAKAZtA92wUj9C11s0B9SwlKAAAgAqlxANAsumdLN/xF3qMAAKAhMCMEAAAAoOVQCAEAAABoORRCAAAAAFoOhRAAAACAlkMhBAAAAKDlUAgBAAAAaDkUQgAAAABaDoUQAAAAgJZDIQQAAACg5VAIAQAAAGg5FEIAAAAAWg6FEAAAAICWQyEEAAAAoOVQCAEAAABoORRCAAAAAFqOsdbmPYbYjDHPSnoy73EgVSdIei7vQSATvLbNjde3ufH6Njde3+bFa+v8mrV2ZqU7NVQhhOZjjBmw1vbkPQ6kj9e2ufH6Njde3+bG69u8eG2ToTUOAAAAQMuhEAIAAADQciiEkLcv5z0AZIbXtrnx+jY3Xt/mxuvbvHhtE2CNEAAAAICWw4wQAAAAgJZDIYTCMMZ8whhjjTEn5D0WpMMY81ljzKPGmJ8YY75ljHld3mNC7YwxFxhjHjPG/NwY8z/yHg/SYYzpNsY8aIzZaYx5xBjzp3mPCekzxrQbY35sjLkn77EgXcaY1xljvln6d3enMeYdeY+p6CiEUAjGmG5J75e0O++xIFXfkfRWa+3bJD0u6VM5jwc1Msa0S/o7SRdKOlvS7xtjzs53VEjJiKT/Zq09S9JvSfqvvLZN6U8l7cx7EMjE5yXdb609U9I88TpXRCGEovicpFWSWLTWRKy137bWjpS+/ZGkU/IcD1KxQNLPrbVPWGtflbRB0qU5jwkpsNbus9b+e+m/h+Quok7Od1RIkzHmFEmLJH0177EgXcaY10p6j6SvSZK19lVr7Yv5jqr4KISQO2PMYklPWWu35z0WZOqPJN2X9yBQs5MlDZZ9v0dcLDcdY8wbJf2GpP58R4KUXS/3oeNY3gNB6k6T9Kykfyy1Pn7VGDMt70EVXUfeA0BrMMY8IOkNAT+6VtKfS/pAfUeEtES9ttbaO0v3uVau7WZ9PceGTJiA25jJbSLGmOmSbpd0jbX2pbzHg3QYYy6WtN9au9UY89t5jwep65D0m5JWWmv7jTGfl/Q/JH0632EVG4UQ6sJa+7tBtxtj5ko6VdJ2Y4zkWqf+3RizwFr7dB2HiCqFvbYeY8wfSLpY0vssef3NYI+k7rLvT5G0N6exIGXGmE65Imi9tfaf8x4PUvUuSYuNMRdJmiLptcaYm621H8p5XEjHHkl7rLXeLO435QohRGAfIRSKMeaXknqstc/lPRbUzhhzgaT/K+k8a+2zeY8HtTPGdMgFX7xP0lOSHpZ0lbX2kVwHhpoZ92nUNyQ9b629Ju/xIDulGaFPWGsvznssSI8xZouk/2StfcwY81eSpllr/3vOwyo0ZoQAZOmLko6R9J3SjN+PrLUfy3dIqIW1dsQYc7WkzZLaJf0DRVDTeJek5ZJ2GGO2lW77c2vtvTmOCUB8KyWtN8a8RtITkj6S83gKjxkhAAAAAC2H1DgAAAAALYdCCAAAAEDLoRACAAAA0HIohAAAAAC0HAohAAAAAC2HQggAUDNjzKgxZpsx5hFjzHZjzJ8ZY9pKP+sxxnwhp3H9MKXjXFE6tzFjTE8axwQA5Iv4bABAzYwxB62100v/PUvSLZL+1Vr7l/mOLB3GmLMkjUlaK7cR5UDOQwIA1IgZIQBAqqy1+yV9VNLVxvltY8w9kmSM+StjzDeMMd82xvzSGPNBY8waY8wOY8z9xpjO0v3mG2O+b4zZaozZbIyZXbr9e8aY/22MecgY87gx5tzS7W8p3bbNGPMTY8ybS7cfLH01xpjPGmN+WnqsK0u3/3bpmN80xjxqjFlvSrv/+s5pp7X2sXo8fwCA+qAQAgCkzlr7hNy/MbMCfvwmSYskXSrpZkkPWmvnSnpZ0qJSMXSDpN+z1s6X9A+S/mfZ73dYaxdIukaSN+P0MUmft9a+XVKPpD2+x/ygpLdLmifpdyV91iuuJP1G6VhnSzpN0ruqPW8AQOPoyHsAAICmNWlmpeQ+a+0RY8wOSe2S7i/dvkPSGyWdIemtkr5Tmpxpl7Sv7Pf/ufR1a+n+kvRvkq41xpwi6Z+ttbt8j/luSf9krR2V9Iwx5vuSzpH0kqSHrLV7JMkYs610zB8kPVkAQGNhRggAkDpjzGmSRiXtD/jxK5JkrR2TdMSOL1Ydk/uAzkh6xFr79tKfudbaD/h/v3T8jtKxbpG0WG5WabMx5nf8Q4oY7itl/330mACA5kYhBABIlTFmpqQbJX3RVpfI85ikmcaYd5SO12mMeUuFxzxN0hPW2i9IukvS23x3+RdJVxpj2kvje4+kh6oYGwCgSVAIAQDScKwXny3pAUnflvTX1RzIWvuqpN+T9L+NMdslbZP0zgq/dqWkn5Za286UdJPv59+S9BNJ2yX9P0mrrLVPxx2TMeZyY8weSe+QtMkYsznu7wIAion4bAAAAAAthxkhAAAAAC2HQggAAABAy6EQAgAAANByKIQAAAAAtBwKIQAAAAAth0IIAAAAQMuhEAIAAADQciiEAAAAALSc/w+DSV1X/+CQ7wAAAABJRU5ErkJggg==
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<h3 id="Implementation:-Data-Recovery">Implementation: Data Recovery<a class="anchor-link" href="#Implementation:-Data-Recovery">&#182;</a></h3><p>Each cluster present in the visualization above has a central point. These centers (or means) are not specifically data points from the data, but rather the <em>averages</em> of all the data points predicted in the respective clusters. For the problem of creating customer segments, a cluster's center point corresponds to <em>the average customer of that segment</em>. Since the data is currently reduced in dimension and scaled by a logarithm, we can recover the representative customer spending from these data points by applying the inverse transformations.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Apply the inverse transform to <code>centers</code> using <code>pca.inverse_transform</code> and assign the new centers to <code>log_centers</code>.</li>
<li>Apply the inverse function of <code>np.log</code> to <code>log_centers</code> using <code>np.exp</code> and assign the true centers to <code>true_centers</code>.</li>
</ul>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># TODO: Inverse transform the centers</span>
<span class="n">log_centers</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">inverse_transform</span><span class="p">(</span><span class="n">centers</span><span class="p">)</span>

<span class="c1"># TODO: Exponentiate the centers</span>
<span class="n">true_centers</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">log_centers</span><span class="p">)</span>

<span class="c1"># Display the true centers</span>
<span class="n">segments</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Segment {}&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">centers</span><span class="p">))]</span>
<span class="n">true_centers</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="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">true_centers</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<span class="n">true_centers</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">segments</span>
<span class="n">display</span><span class="p">(</span><span class="n">true_centers</span><span class="p">)</span>
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    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
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    <tr>
      <th>Segment 0</th>
      <td>8867.0</td>
      <td>1897.0</td>
      <td>2477.0</td>
      <td>2088.0</td>
      <td>294.0</td>
      <td>681.0</td>
    </tr>
    <tr>
      <th>Segment 1</th>
      <td>4005.0</td>
      <td>7900.0</td>
      <td>12104.0</td>
      <td>952.0</td>
      <td>4561.0</td>
      <td>1036.0</td>
    </tr>
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<h3 id="Question-8">Question 8<a class="anchor-link" href="#Question-8">&#182;</a></h3><ul>
<li>Consider the total purchase cost of each product category for the representative data points above, and reference the statistical description of the dataset at the beginning of this project(specifically looking at the mean values for the various feature points). What set of establishments could each of the customer segments represent?</li>
</ul>
<p><strong>Hint:</strong> A customer who is assigned to <code>'Cluster X'</code> should best identify with the establishments represented by the feature set of <code>'Segment X'</code>. Think about what each segment represents in terms their values for the feature points chosen. Reference these values with the mean values to get some perspective into what kind of establishment they represent.</p>

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<p><strong>Answer:</strong></p>
<p><table></p>
<p><tr><th >mean</th></tr></p>
<p><tr><th></th><th>Fresh</th>  <th>Milk</th>  <th>Grocery</th>    <th>Frozen</th>  <th>Detergents_Paper</th> <th>Delicatessen</th></tr></p>
<p><tr><td></td><td>12000.297727</td>  <td>5796.265909</td>    <td>7951.277273</td>    <td>3071.931818</td>  <td>2881.493182</td> <td>1524.870455</td></tr><br>
 &lt;/table&gt;</p>
<ul>
<li>Segment 0 : All features less than mean. So it's small wholesale retailers.</li>
<li>Segment 1 : Fresh = 4005, Frozen = 2088, Detergents_Paper = 294, Delicatessen = 681 less than mean, Milk = 7900, Grecery = 12104 more than mean.So it's wholesale retailers.</li>
</ul>

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<h3 id="Question-9">Question 9<a class="anchor-link" href="#Question-9">&#182;</a></h3><ul>
<li>For each sample point, which customer segment from<em> <strong>Question 8</strong> </em>best represents it? </li>
<li>Are the predictions for each sample point consistent with this?*</li>
</ul>
<p>Run the code block below to find which cluster each sample point is predicted to be.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display the predictions</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">pred</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sample_preds</span><span class="p">):</span>
    <span class="k">print</span><span class="p">(</span><span class="s2">&quot;Sample point&quot;</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;predicted to be in Cluster&quot;</span><span class="p">,</span> <span class="n">pred</span><span class="p">)</span>
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<pre>(&#39;Sample point&#39;, 0, &#39;predicted to be in Cluster&#39;, 0)
(&#39;Sample point&#39;, 1, &#39;predicted to be in Cluster&#39;, 0)
(&#39;Sample point&#39;, 2, &#39;predicted to be in Cluster&#39;, 0)
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<p><strong>Answer:</strong></p>
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<li>It represent wholesale retailers.</li>
<li>The predictions like my predictions for each sample point 0, 1.</li>
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<h2 id="Conclusion">Conclusion<a class="anchor-link" href="#Conclusion">&#182;</a></h2>
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<p>In this final section, you will investigate ways that you can make use of the clustered data. First, you will consider how the different groups of customers, the <strong><em>customer segments</em></strong>, may be affected differently by a specific delivery scheme. Next, you will consider how giving a label to each customer (which <em>segment</em> that customer belongs to) can provide for additional features about the customer data. Finally, you will compare the <strong><em>customer segments</em></strong> to a hidden variable present in the data, to see whether the clustering identified certain relationships.</p>

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<h3 id="Question-10">Question 10<a class="anchor-link" href="#Question-10">&#182;</a></h3><p>Companies will often run <a href="https://en.wikipedia.org/wiki/A/B_testing">A/B tests</a> when making small changes to their products or services to determine whether making that change will affect its customers positively or negatively. The wholesale distributor is considering changing its delivery service from currently 5 days a week to 3 days a week. However, the distributor will only make this change in delivery service for customers that react positively.</p>
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<li>How can the wholesale distributor use the customer segments to determine which customers, if any, would react positively to the change in delivery service?*</li>
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<p><strong>Hint:</strong> Can we assume the change affects all customers equally? How can we determine which group of customers it affects the most?</p>

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<p><strong>Answer:</strong></p>
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<li>when we make delivery service from currently 5 days a week to 3 days a week, that will affect negatively for  customers.</li>
<li>we cam use A/B test of both groups of customers by selecting a small but statistically significant sample of customers from each cluster and using the remainder of their cluster as the control group. That test will determine this change helpful or damaging to one group or the other.</li>
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<h3 id="Question-11">Question 11<a class="anchor-link" href="#Question-11">&#182;</a></h3><p>Additional structure is derived from originally unlabeled data when using clustering techniques. Since each customer has a <strong><em>customer segment</em></strong> it best identifies with (depending on the clustering algorithm applied), we can consider <em>'customer segment'</em> as an <strong>engineered feature</strong> for the data. Assume the wholesale distributor recently acquired ten new customers and each provided estimates for anticipated annual spending of each product category. Knowing these estimates, the wholesale distributor wants to classify each new customer to a <strong><em>customer segment</em></strong> to determine the most appropriate delivery service.</p>
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<li>How can the wholesale distributor label the new customers using only their estimated product spending and the <strong>customer segment</strong> data?</li>
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<p><strong>Hint:</strong> A supervised learner could be used to train on the original customers. What would be the target variable?</p>

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<p><strong>Answer:</strong></p>
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<li>He could used classifier to classify the new clients based on their features.</li>
<li>Target variable would be the cluster group.</li>
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<h3 id="Visualizing-Underlying-Distributions">Visualizing Underlying Distributions<a class="anchor-link" href="#Visualizing-Underlying-Distributions">&#182;</a></h3><p>At the beginning of this project, it was discussed that the <code>'Channel'</code> and <code>'Region'</code> features would be excluded from the dataset so that the customer product categories were emphasized in the analysis. By reintroducing the <code>'Channel'</code> feature to the dataset, an interesting structure emerges when considering the same PCA dimensionality reduction applied earlier to the original dataset.</p>
<p>Run the code block below to see how each data point is labeled either <code>'HoReCa'</code> (Hotel/Restaurant/Cafe) or <code>'Retail'</code> the reduced space. In addition, you will find the sample points are circled in the plot, which will identify their labeling.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Display the clustering results based on &#39;Channel&#39; data</span>
<span class="n">vs</span><span class="o">.</span><span class="n">channel_results</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">outliers</span><span class="p">,</span> <span class="n">pca_samples</span><span class="p">)</span>
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<h3 id="Question-12">Question 12<a class="anchor-link" href="#Question-12">&#182;</a></h3><ul>
<li>How well does the clustering algorithm and number of clusters you've chosen compare to this underlying distribution of Hotel/Restaurant/Cafe customers to Retailer customers? </li>
<li>Are there customer segments that would be classified as purely 'Retailers' or 'Hotels/Restaurants/Cafes' by this distribution? </li>
<li>Would you consider these classifications as consistent with your previous definition of the customer segments?</li>
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<p><strong>Answer:</strong></p>
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<li>The number of clusters react with the number of channels</li>
<li>Yes, there are customer segments that would be classified as purely 'Retailers' or 'Hotels/Restaurants/Cafes' by this distribution.</li>
<li>Yes, i would consider these classifications as consistent with my previous definition of the customer segments.</li>
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<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations and successfully answered each question above, you may finalize your work by exporting the iPython Notebook as an HTML document. You can do this by using the menu above and navigating to<br>
<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
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