From b5a9b0653b735c08b8569b354bacfb5aedbb5793 Mon Sep 17 00:00:00 2001 From: Renato Vimieiro Date: Mon, 28 May 2018 15:54:54 -0300 Subject: [PATCH] atualizacoes dos slides conforme semestre 2018.1 --- aula02-intro-pandas.ipynb | 93 +- aula03-intro-pandas-part2.ipynb | 239 +- aula05-data-scraping-com-beautifulsoup.ipynb | 864 +++-- aula06-data-scraping-api-twitter.ipynb | 2464 ++++++------ aula07-preprocessamento.ipynb | 804 ++-- aula08-eda.ipynb | 673 ++-- aula09-datavis-parte01.ipynb | 512 ++- aula10-datavis-parte02.ipynb | 3666 ++++++++---------- aula11-datavis-parte03.ipynb | 2337 ++++------- aula12-datavis-parte04.ipynb | 300 +- aula13-regressao-linear.ipynb | 143 +- aula14-regressao-linear-parte02.ipynb | 38 +- aula15-regressao-logistica.ipynb | 396 +- aula16-LDA-naiveBayes.ipynb | 385 +- aula17-arvores-decisao.ipynb | 90 +- aula18-knn-avaliacao.ipynb | 62 +- aula19-clustering.ipynb | 66 +- 17 files changed, 6044 insertions(+), 7088 deletions(-) diff --git a/aula02-intro-pandas.ipynb b/aula02-intro-pandas.ipynb index ff286f9..2ec681b 100644 --- a/aula02-intro-pandas.ipynb +++ b/aula02-intro-pandas.ipynb @@ -4,7 +4,6 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "skip" } @@ -94,7 +93,6 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -125,7 +123,6 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -159,7 +156,6 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -188,7 +184,6 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -220,7 +215,6 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -258,7 +252,6 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -292,9 +285,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 2, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -325,7 +317,6 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -335,9 +326,9 @@ "name": "stdout", "output_type": "stream", "text": [ - " [0, 1, 4, 9, 16, 25]\n", - " [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)]\n", - " [0, 2, 4, 6, 8]\n" + " [0, 1, 4, 9, 16, 25]\n", + " [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)]\n", + " [0, 2, 4, 6, 8]\n" ] } ], @@ -376,7 +367,6 @@ "cell_type": "code", "execution_count": 10, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -418,7 +408,6 @@ "cell_type": "code", "execution_count": 11, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -462,7 +451,6 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -499,7 +487,6 @@ "cell_type": "code", "execution_count": 13, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -594,9 +581,8 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -613,6 +599,19 @@ "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -678,7 +677,7 @@ "4 5 33 F other 15213" ] }, - "execution_count": 24, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -709,9 +708,8 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 21, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -728,6 +726,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -913,7 +924,7 @@ "[5 rows x 24 columns]" ] }, - "execution_count": 26, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -922,7 +933,8 @@ "filmes = pd.read_csv(\n", " \"http://files.grouplens.org/datasets/movielens/ml-100k/u.item\",\n", " sep='|',header=None, names=[\"movie_id\", \"movie_title\", \"release_date\", \"video_release_date\", \"IMDb_URL\", \"unknown\", \"Action\", \"Adventure\", \"Animation\", \n", - " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \"Horror\", \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"])\n", + " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \"Horror\", \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"],\n", + " encoding='latin1')\n", "print(filmes.shape)\n", "filmes.head()" ] @@ -945,9 +957,8 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -964,6 +975,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1023,7 +1047,7 @@ "4 166 346 1 886397596" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1053,9 +1077,8 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -1091,9 +1114,8 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -1134,6 +1156,13 @@ "source": [ "print(filmes.dtypes)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -1153,7 +1182,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula03-intro-pandas-part2.ipynb b/aula03-intro-pandas-part2.ipynb index 3dc0430..6757bf8 100644 --- a/aula03-intro-pandas-part2.ipynb +++ b/aula03-intro-pandas-part2.ipynb @@ -4,7 +4,6 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "collapsed": true, "slideshow": { "slide_type": "skip" } @@ -55,7 +54,6 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "collapsed": true, "slideshow": { "slide_type": "skip" } @@ -67,8 +65,11 @@ " sep='|',header=None, names=[\"user_id\", \"age\", \"gender\", \"occupation\", \"zip_code\"])\n", "filmes = pd.read_csv(\n", " \"http://files.grouplens.org/datasets/movielens/ml-100k/u.item\",\n", - " sep='|',header=None, names=[\"movie_id\", \"movie_title\", \"release_date\", \"video_release_date\", \"IMDb_URL\", \"unknown\", \"Action\", \"Adventure\", \"Animation\", \n", - " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \"Horror\", \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"])\n", + " sep='|',header=None, names=[\"movie_id\", \"movie_title\", \"release_date\", \"video_release_date\", \"IMDb_URL\", \n", + " \"unknown\", \"Action\", \"Adventure\", \"Animation\", \n", + " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \"Horror\", \n", + " \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"],\n", + "encoding='latin1')\n", "avaliacoes = pd.read_csv(\n", " \"http://files.grouplens.org/datasets/movielens/ml-100k/u.data\",\n", " sep='\\t',header=None, names=[\"user_id\", \"movie_id\", \"rating\", \"timestamp\"])\n" @@ -89,7 +90,6 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -124,7 +124,6 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -134,6 +133,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -196,7 +208,6 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -206,6 +217,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -277,9 +301,8 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -292,10 +315,10 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Nao e possivel combinar selecao de linha e coluna diretamente via []\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mavaliacoes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'rating'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m/usr/local/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2057\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2058\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2059\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2060\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2061\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2064\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2065\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2066\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2067\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2068\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.5/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1382\u001b[0m \u001b[0;34m\"\"\"Return the cached item, item represents a label indexer.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1383\u001b[0m \u001b[0mcache\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_item_cache\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1384\u001b[0;31m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1385\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1386\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Nao e possivel combinar selecao de linha e coluna diretamente via []\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mavaliacoes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'rating'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2138\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2141\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2144\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2145\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2148\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1838\u001b[0m \u001b[0;34m\"\"\"Return the cached item, item represents a label indexer.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1839\u001b[0m \u001b[0mcache\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_item_cache\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1840\u001b[0;31m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1841\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1842\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mTypeError\u001b[0m: unhashable type: 'slice'" ] } @@ -307,9 +330,8 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 23, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -332,6 +354,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -407,9 +442,8 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 9, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -419,6 +453,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -484,7 +531,7 @@ "13 14 45 M scientist 55106" ] }, - "execution_count": 25, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -513,9 +560,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 27, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -529,7 +575,7 @@ "174 175 26 F scientist 21911\n", "729 730 31 F scientist 32114\n", "929 930 28 F scientist 07310\n", - "28.3333333333\n" + "28.333333333333332\n" ] } ], @@ -542,9 +588,8 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 29, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -580,9 +625,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -592,6 +636,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -639,7 +696,7 @@ "929 930 28 F scientist None" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -653,9 +710,8 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -665,6 +721,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -718,7 +787,7 @@ "4 Copycat (1995) 01-Jan-1995 1995" ] }, - "execution_count": 4, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -747,9 +816,8 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -774,7 +842,7 @@ "Name: rating, dtype: int64" ] }, - "execution_count": 5, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -782,7 +850,8 @@ "source": [ "print(\"Mediana de idade dos usuarios \", usuarios.age.median())\n", "\n", - "piorAvaliacao = avaliacoes.rating.argmin()\n", + "# piorAvaliacao = avaliacoes.rating.argmin()\n", + "piorAvaliacao = avaliacoes.rating.values.argmin()\n", "print(filmes[filmes.movie_id == avaliacoes.movie_id.iloc[piorAvaliacao]].movie_title.iloc[0])\n", "\n", "avaliacoes.rating.value_counts()" @@ -807,7 +876,6 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -817,6 +885,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -910,9 +991,8 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -922,6 +1002,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1000,7 +1093,7 @@ "99999 Dadetown (1995) 1996 " ] }, - "execution_count": 18, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1029,9 +1122,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1040,17 +1132,17 @@ { "data": { "text/plain": [ - "(3.8215246636771298, 1.0184489421764065)" + "(3.82152466367713, 1.0184489421764038)" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "avaliacaoFilmes.release_year.fillna(value=-1,inplace=True)\n", - "avaliacaoFilmes['release_year'] = \n", + "avaliacaoFilmes['release_year'] = \\\n", "avaliacaoFilmes.release_year.astype(np.int)\n", "avalFilmUsu = pd.merge(avaliacaoFilmes,usuarios[[\"user_id\",\"occupation\"]], \n", " on=\"user_id\")\n", @@ -1120,9 +1212,8 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 31, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1132,6 +1223,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1281,7 +1385,7 @@ "writer 495.711111 36.311111" ] }, - "execution_count": 21, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1295,9 +1399,8 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 19, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "subslide" } @@ -1322,6 +1425,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1560,7 +1676,7 @@ "90s 195 70 208 42 13 " ] }, - "execution_count": 34, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1591,9 +1707,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 20, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1618,6 +1733,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1870,7 +1998,7 @@ "Western 0.009819 " ] }, - "execution_count": 11, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1881,6 +2009,13 @@ "print(sizes)\n", "b.T/sizes" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -1900,7 +2035,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula05-data-scraping-com-beautifulsoup.ipynb b/aula05-data-scraping-com-beautifulsoup.ipynb index 06ff7dd..44518a5 100644 --- a/aula05-data-scraping-com-beautifulsoup.ipynb +++ b/aula05-data-scraping-com-beautifulsoup.ipynb @@ -14,10 +14,8 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true - }, + "execution_count": 1, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -42,10 +40,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [ { "ename": "UnicodeDecodeError", @@ -54,9 +50,9 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"../2017.1/data/scraping/buscape/7\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mparsed_page\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBeautifulSoup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"html.parser\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;31m#print(parsed_page)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.5/site-packages/bs4/__init__.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, markup, features, builder, parse_only, from_encoding, exclude_encodings, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 190\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmarkup\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'read'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# It's a file-type object.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 191\u001b[0;31m \u001b[0mmarkup\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmarkup\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 192\u001b[0m elif len(markup) <= 256 and (\n\u001b[1;32m 193\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmarkup\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbytes\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34mb'<'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmarkup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/Cellar/python3/3.5.2_1/Frameworks/Python.framework/Versions/3.5/lib/python3.5/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 319\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 321\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 322\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 323\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"../2017.1/data/scraping/buscape/7\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mparsed_page\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBeautifulSoup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"html.parser\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;31m#print(parsed_page)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.6/site-packages/bs4/__init__.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, markup, features, builder, parse_only, from_encoding, exclude_encodings, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 190\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmarkup\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'read'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# It's a file-type object.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 191\u001b[0;31m \u001b[0mmarkup\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmarkup\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 192\u001b[0m elif len(markup) <= 256 and (\n\u001b[1;32m 193\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmarkup\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbytes\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34mb'<'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmarkup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/Cellar/python3/3.6.3/Frameworks/Python.framework/Versions/3.6/lib/python3.6/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 319\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 321\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 322\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 323\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0xe1 in position 138816: invalid continuation byte" ] } @@ -84,9 +80,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": { - "collapsed": false, "scrolled": false }, "outputs": [ @@ -100,17 +95,17 @@ "\n", "\n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " Celular e Smartphone 7 iPhone - Preços no Buscapé" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -159,9 +152,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -187,10 +178,8 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -198,30 +187,11 @@ "text": [ "\"Buscapé\"\n" ] - }, - { - "data": { - "text/plain": [ - "[\"Buscapé\",\n", - " Navegue por categorias ,\n", - " Celulares,\n", - " Iphones ,\n", - " Smartphones Android,\n", - " Smartphones Samsung,\n", - " Smartphones com 2 chips,\n", - " Smartphones LG,\n", - " Smartphones até 600 reais,\n", - " Smartphones Motorola]" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ "print(parsed_page.find('a'))\n", - "parsed_page.find_all('a')[:10]\n" + "#parsed_page.find_all('a')[:10]\n" ] }, { @@ -233,17 +203,15 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/\n", - "{'data-gacategory': 'topo', 'class': ['brand__thumb'], 'data-gaevent': 'event', 'href': '/', 'data-gaaction': 'logo', 'title': 'Buscapé', 'itemprop': 'url'}\n", + "{'itemprop': 'url', 'data-gaaction': 'logo', 'data-gacategory': 'topo', 'data-gaevent': 'event', 'class': ['brand__thumb'], 'title': 'Buscapé', 'href': '/'}\n", "['brand__thumb']\n" ] } @@ -269,10 +237,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -354,7 +320,7 @@ " 'modelo': 'iPhone 6'}]" ] }, - "execution_count": 8, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -392,10 +358,8 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -416,6 +380,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -571,7 +548,7 @@ "14 iPhone 6 128 3799.00 3799.00 1" ] }, - "execution_count": 28, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -592,22 +569,33 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", " \n", @@ -620,48 +608,48 @@ " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", + " \n", " \n", " \n", "
capacidademaiorPrecomenorPrecomaiorPreco
modelo
iPhone 5S16, 322559.991381.252559.99
iPhone 616, 64, 1284599.002249.104599.00
iPhone 6S16, 32, 64, 1285305.002464.415305.00
iPhone 732, 128, 2564899.002931.654899.00
iPhone 7 Plus32, 128, 2564899.003499.004899.00
\n", "
" ], "text/plain": [ - " capacidade maiorPreco menorPreco\n", + " capacidade menorPreco maiorPreco\n", "modelo \n", - "iPhone 5S 16, 32 2559.99 1381.25\n", - "iPhone 6 16, 64, 128 4599.00 2249.10\n", - "iPhone 6S 16, 32, 64, 128 5305.00 2464.41\n", - "iPhone 7 32, 128, 256 4899.00 2931.65\n", - "iPhone 7 Plus 32, 128, 256 4899.00 3499.00" + "iPhone 5S 16, 32 1381.25 2559.99\n", + "iPhone 6 16, 64, 128 2249.10 4599.00\n", + "iPhone 6S 16, 32, 64, 128 2464.41 5305.00\n", + "iPhone 7 32, 128, 256 2931.65 4899.00\n", + "iPhone 7 Plus 32, 128, 256 3499.00 4899.00" ] }, - "execution_count": 29, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -697,10 +685,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -750,9 +736,7 @@ { "cell_type": "code", "execution_count": 242, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -849,10 +833,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -912,15 +894,26 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -1107,7 +1100,7 @@ "23 Casas Bahia 1999.00 http://www.buscape.com.br/redirect_prod?pagina..." ] }, - "execution_count": 15, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1140,15 +1133,26 @@ }, { "cell_type": "code", - "execution_count": 216, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1164,7 +1168,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1172,7 +1176,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1228,7 +1232,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1236,7 +1240,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1244,7 +1248,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1252,7 +1256,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1308,7 +1312,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1324,7 +1328,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1332,7 +1336,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1359,28 +1363,28 @@ ], "text/plain": [ " vendedor preco \\\n", - "0 Wal-Mart 1549.00 \n", - "1 Mercado Livre 1699.00 \n", + "0 Wal-Mart 1498.98 \n", + "1 Mercado Livre 1599.00 \n", "2 DouGShoP 1381.25 \n", "3 KaBuM! 1529.90 \n", "4 Carrefour 1549.00 \n", "5 Casas Bahia 1495.12 \n", "6 PontoFrio.com 1580.07 \n", "7 Extra.com.br 1550.00 \n", - "8 Magazine Luiza 1529.91 \n", - "9 Americanas.com 1614.05 \n", - "10 Submarino 1599.00 \n", - "11 Shoptime 1614.05 \n", + "8 Magazine Luiza 1439.91 \n", + "9 Americanas.com 1519.05 \n", + "10 Submarino 1439.10 \n", + "11 Shoptime 1599.00 \n", "12 Wal-Mart 1599.00 \n", "13 Mercado Livre 1635.29 \n", "14 KaBuM! 1554.56 \n", "15 Casas Bahia 1495.12 \n", "16 Extra.com.br 1550.00 \n", "17 PontoFrio.com 1495.12 \n", - "18 Magazine Luiza 1529.91 \n", + "18 Magazine Luiza 1439.91 \n", "19 Americanas.com 1439.10 \n", - "20 Submarino 1614.05 \n", - "21 Shoptime 1439.10 \n", + "20 Submarino 1519.05 \n", + "21 Shoptime 1599.00 \n", "22 Mercado Livre 1549.00 \n", "23 Casas Bahia 1999.00 \n", "\n", @@ -1411,7 +1415,7 @@ "23 http://www.buscape.com.br/redirect_prod?pagina... iPhone 5S 16 " ] }, - "execution_count": 216, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -1431,15 +1435,26 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
0Wal-Mart1549.001498.98http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
1Mercado Livre1699.001599.00http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
8Magazine Luiza1529.911439.91http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
9Americanas.com1614.051519.05http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
10Submarino1599.001439.10http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
11Shoptime1614.051599.00http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
18Magazine Luiza1529.911439.91http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
20Submarino1614.051519.05http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
21Shoptime1439.101599.00http://www.buscape.com.br/redirect_prod?pagina...iPhone 5S16
\n", " \n", " \n", @@ -1702,7 +1717,7 @@ "23 http://www.buscape.com.br/redirect_prod?pagina... " ] }, - "execution_count": 16, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -1742,10 +1757,8 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1758,6 +1771,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1772,242 +1798,242 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -2022,240 +2048,240 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -2264,68 +2290,68 @@ "" ], "text/plain": [ - " modelo capacidade vendedor preco \\\n", - "0 iPhone 7 32 Peixe Urbano 3149.90 \n", - "1 iPhone 7 32 Wal-Mart 3499.00 \n", - "2 iPhone 7 32 Mercado Livre 3699.90 \n", - "3 iPhone 7 32 Fnac.com 3499.00 \n", - "4 iPhone 7 32 DouGShoP 2931.65 \n", - "5 iPhone 7 32 KaBuM! 3149.10 \n", - "6 iPhone 7 32 Saraiva.com.br 3324.05 \n", - "7 iPhone 7 32 Casas Bahia 3079.12 \n", - "8 iPhone 7 32 Extra.com.br 3079.12 \n", - "9 iPhone 7 32 PontoFrio.com 3079.12 \n", - "10 iPhone 7 32 Magazine Luiza 3104.91 \n", - "11 iPhone 7 32 Fast Shop.com.br 3047.92 \n", - "12 iPhone 7 32 Americanas.com 3324.05 \n", - "13 iPhone 7 32 Submarino 3149.10 \n", - "14 iPhone 7 32 Shoptime 3324.05 \n", - "15 iPhone 7 32 Peixe Urbano 3399.90 \n", - "16 iPhone 7 32 Mercado Livre 3288.09 \n", - "17 iPhone 7 32 Fnac.com 3499.00 \n", - "18 iPhone 7 32 Wal-Mart 3299.00 \n", - "19 iPhone 7 32 KaBuM! 3149.10 \n", - "20 iPhone 7 32 Saraiva.com.br 3324.05 \n", - "21 iPhone 7 32 Casas Bahia 3079.12 \n", - "22 iPhone 7 32 Extra.com.br 3079.12 \n", - "23 iPhone 7 32 PontoFrio.com 3079.12 \n", - "24 iPhone 7 Plus 256 Fnac.com 4899.00 \n", - "25 iPhone 7 Plus 256 Wal-Mart 4899.00 \n", - "26 iPhone 7 Plus 256 NoteTec 4199.00 \n", - "27 iPhone 7 Plus 256 KaBuM! 4409.10 \n", - "28 iPhone 7 Plus 256 Saraiva.com.br 4654.05 \n", - "29 iPhone 7 Plus 256 Casas Bahia 4311.12 \n", - ".. ... ... ... ... \n", - "261 iPhone 6S 32 Submarino 2849.99 \n", - "262 iPhone 6S 32 Shoptime 2849.99 \n", - "263 iPhone 6S 32 Casas Bahia 2699.10 \n", - "264 iPhone 6S 32 Extra.com.br 2699.10 \n", - "265 iPhone 6S 32 PontoFrio.com 2699.10 \n", - "266 iPhone 6S 32 Magazine Luiza 2609.91 \n", - "267 iPhone 6S 128 Mercado Livre 3399.90 \n", - "268 iPhone 6S 128 Fnac.com 3059.10 \n", - "269 iPhone 6S 128 Wal-Mart 2999.00 \n", - "270 iPhone 6S 128 Saraiva.com.br 3229.05 \n", - "271 iPhone 6S 128 Carrefour 3999.00 \n", - "272 iPhone 6S 128 Casas Bahia 4599.00 \n", - "273 iPhone 6S 128 Extra.com.br 4599.00 \n", - "274 iPhone 6S 128 PontoFrio.com 4599.00 \n", - "275 iPhone 6S 128 Magazine Luiza 3059.91 \n", - "276 iPhone 6S 128 Fast Shop.com.br 2960.81 \n", - "277 iPhone 6S 128 Americanas.com 3229.05 \n", - "278 iPhone 6S 128 Submarino 3229.05 \n", - "279 iPhone 6S 128 Shoptime 3229.05 \n", - "280 iPhone 6S 128 Mercado Livre 3399.00 \n", - "281 iPhone 6S 128 Fnac.com 3399.00 \n", - "282 iPhone 6S 128 Wal-Mart 3099.00 \n", - "283 iPhone 6S 128 Saraiva.com.br 3229.05 \n", - "284 iPhone 6S 128 Carrefour 3999.00 \n", - "285 iPhone 6S 128 Casas Bahia 4599.00 \n", - "286 iPhone 6S 128 Extra.com.br 4599.00 \n", - "287 iPhone 6S 128 PontoFrio.com 4599.00 \n", - "288 iPhone 6S 128 Magazine Luiza 3059.91 \n", - "289 iPhone 6S 128 Fast Shop.com.br 2960.81 \n", - "290 iPhone 6S 128 Americanas.com 3229.05 \n", + " modelo capacidade vendedor preco \\\n", + "0 iPhone 5S 16 Wal-Mart 1498.98 \n", + "1 iPhone 5S 16 Mercado Livre 1599.00 \n", + "2 iPhone 5S 16 DouGShoP 1381.25 \n", + "3 iPhone 5S 16 KaBuM! 1529.90 \n", + "4 iPhone 5S 16 Carrefour 1549.00 \n", + "5 iPhone 5S 16 Casas Bahia 1495.12 \n", + "6 iPhone 5S 16 PontoFrio.com 1580.07 \n", + "7 iPhone 5S 16 Extra.com.br 1550.00 \n", + "8 iPhone 5S 16 Magazine Luiza 1439.91 \n", + "9 iPhone 5S 16 Americanas.com 1519.05 \n", + "10 iPhone 5S 16 Submarino 1439.10 \n", + "11 iPhone 5S 16 Shoptime 1599.00 \n", + "12 iPhone 5S 16 Wal-Mart 1599.00 \n", + "13 iPhone 5S 16 Mercado Livre 1635.29 \n", + "14 iPhone 5S 16 KaBuM! 1554.56 \n", + "15 iPhone 5S 16 Casas Bahia 1495.12 \n", + "16 iPhone 5S 16 Extra.com.br 1550.00 \n", + "17 iPhone 5S 16 PontoFrio.com 1495.12 \n", + "18 iPhone 5S 16 Magazine Luiza 1439.91 \n", + "19 iPhone 5S 16 Americanas.com 1439.10 \n", + "20 iPhone 5S 16 Submarino 1519.05 \n", + "21 iPhone 5S 16 Shoptime 1599.00 \n", + "22 iPhone 5S 16 Mercado Livre 1549.00 \n", + "23 iPhone 5S 16 Casas Bahia 1999.00 \n", + "24 iPhone 7 128 Casas Bahia 3431.12 \n", + "25 iPhone 7 128 Wal-Mart 3899.00 \n", + "26 iPhone 7 128 NoteTec 3349.00 \n", + "27 iPhone 7 128 PontoFrio.com 3431.12 \n", + "28 iPhone 7 128 Mercado Livre 4499.88 \n", + "29 iPhone 7 128 Fnac.com 3899.00 \n", + ".. ... ... ... ... \n", + "261 iPhone 6S 32 PontoFrio.com 2699.10 \n", + "262 iPhone 6S 32 Magazine Luiza 2609.91 \n", + "263 iPhone 6S 64 Wal-Mart 5305.00 \n", + "264 iPhone 6S 64 Carrefour 3499.00 \n", + "265 iPhone 6S 64 Casas Bahia 4299.00 \n", + "266 iPhone 6S 64 Extra.com.br 3998.00 \n", + "267 iPhone 6S 64 PontoFrio.com 4299.00 \n", + "268 iPhone 6S 64 Magazine Luiza 2969.91 \n", + "269 iPhone 6S 64 Carrefour 3499.00 \n", + "270 iPhone 6S 64 PontoFrio.com 4299.00 \n", + "271 iPhone 6S 64 Magazine Luiza 2969.91 \n", + "272 iPhone 6S 64 Carrefour 3499.00 \n", + "273 iPhone 6S 64 PontoFrio.com 3997.98 \n", + "274 iPhone 6S 64 Magazine Luiza 2969.91 \n", + "275 iPhone 6S 64 PontoFrio.com 4299.00 \n", + "276 iPhone 6S 64 Magazine Luiza 2969.91 \n", + "277 iPhone 6 64 Magazine Luiza 2249.91 \n", + "278 iPhone 6 64 Americanas.com 3039.05 \n", + "279 iPhone 6 64 Submarino 3039.05 \n", + "280 iPhone 6 64 Shoptime 3039.05 \n", + "281 iPhone 6 64 Magazine Luiza 2249.91 \n", + "282 iPhone 6 64 Americanas.com 3039.05 \n", + "283 iPhone 6 64 Submarino 3039.05 \n", + "284 iPhone 6 64 Shoptime 3039.05 \n", + "285 iPhone 5S 32 Casas Bahia 2149.00 \n", + "286 iPhone 5S 32 PontoFrio.com 2149.00 \n", + "287 iPhone 5S 32 Casas Bahia 2149.00 \n", + "288 iPhone 5S 32 PontoFrio.com 2149.00 \n", + "289 iPhone 6 128 Casas Bahia 3799.00 \n", + "290 iPhone 6 128 Casas Bahia 3799.00 \n", "\n", " link \n", "0 http://www.buscape.com.br/redirect_prod?pagina... \n", @@ -2393,7 +2419,7 @@ "[291 rows x 5 columns]" ] }, - "execution_count": 22, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -2419,9 +2445,7 @@ { "cell_type": "code", "execution_count": 244, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "dadosCelulares.to_csv('../2017.1/data/scraping/dadosConsolidadosIPhone7.csv', index=False)\n", @@ -2469,7 +2493,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula06-data-scraping-api-twitter.ipynb b/aula06-data-scraping-api-twitter.ipynb index fab13eb..0a550fd 100644 --- a/aula06-data-scraping-api-twitter.ipynb +++ b/aula06-data-scraping-api-twitter.ipynb @@ -15,9 +15,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -186,9 +184,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# As chaves estao armazenadas em um arquivo de configuracoes\n", @@ -222,9 +218,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "api = tweepy.API(auth, wait_on_rate_limit=False)" @@ -242,9 +236,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -3531,268 +3523,278 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 34, "metadata": { - "collapsed": false, "scrolled": true }, "outputs": [ { "data": { "text/plain": [ - "[{'as_of': '2017-08-29T16:59:36Z',\n", - " 'created_at': '2017-08-29T16:53:52Z',\n", - " 'locations': [{'name': 'Recife', 'woeid': 455824}],\n", - " 'trends': [{'name': 'III Guerra Mundial',\n", + "[{'as_of': '2018-03-22T16:39:37Z',\n", + " 'created_at': '2018-03-22T16:32:28Z',\n", + " 'locations': [{'name': 'Brazil', 'woeid': 23424768}],\n", + " 'trends': [{'name': '#LulaLivre',\n", " 'promoted_content': None,\n", - " 'query': '%22III+Guerra+Mundial%22',\n", - " 'tweet_volume': 92235,\n", - " 'url': 'http://twitter.com/search?q=%22III+Guerra+Mundial%22'},\n", - " {'name': '#OProblemaDaMinhaVidaÉ',\n", + " 'query': '%23LulaLivre',\n", + " 'tweet_volume': 21890,\n", + " 'url': 'http://twitter.com/search?q=%23LulaLivre'},\n", + " {'name': '#DiaMundialDaÁgua',\n", " 'promoted_content': None,\n", - " 'query': '%23OProblemaDaMinhaVida%C3%89',\n", + " 'query': '%23DiaMundialDa%C3%81gua',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23OProblemaDaMinhaVida%C3%89'},\n", - " {'name': '#TercaDetremuraSDV',\n", - " 'promoted_content': None,\n", - " 'query': '%23TercaDetremuraSDV',\n", - " 'tweet_volume': 16989,\n", - " 'url': 'http://twitter.com/search?q=%23TercaDetremuraSDV'},\n", - " {'name': 'PARABÉNS LUCERO',\n", + " 'url': 'http://twitter.com/search?q=%23DiaMundialDa%C3%81gua'},\n", + " {'name': '#MamitaCNCOFtLuan',\n", " 'promoted_content': None,\n", - " 'query': '%22PARAB%C3%89NS+LUCERO%22',\n", + " 'query': '%23MamitaCNCOFtLuan',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22PARAB%C3%89NS+LUCERO%22'},\n", - " {'name': '#VisibilidadeLésbica',\n", + " 'url': 'http://twitter.com/search?q=%23MamitaCNCOFtLuan'},\n", + " {'name': '#QuintaDetremuraSdv',\n", " 'promoted_content': None,\n", - " 'query': '%23VisibilidadeL%C3%A9sbica',\n", - " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23VisibilidadeL%C3%A9sbica'},\n", - " {'name': '#MelhorCoisaEh',\n", + " 'query': '%23QuintaDetremuraSdv',\n", + " 'tweet_volume': 18810,\n", + " 'url': 'http://twitter.com/search?q=%23QuintaDetremuraSdv'},\n", + " {'name': 'Marcelo Miranda',\n", " 'promoted_content': None,\n", - " 'query': '%23MelhorCoisaEh',\n", + " 'query': '%22Marcelo+Miranda%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23MelhorCoisaEh'},\n", - " {'name': '#FlickerSessionsDublin',\n", + " 'url': 'http://twitter.com/search?q=%22Marcelo+Miranda%22'},\n", + " {'name': '#HAPPYRENJUNDAY',\n", " 'promoted_content': None,\n", - " 'query': '%23FlickerSessionsDublin',\n", - " 'tweet_volume': 10695,\n", - " 'url': 'http://twitter.com/search?q=%23FlickerSessionsDublin'},\n", - " {'name': 'Fufuca',\n", + " 'query': '%23HAPPYRENJUNDAY',\n", + " 'tweet_volume': 88883,\n", + " 'url': 'http://twitter.com/search?q=%23HAPPYRENJUNDAY'},\n", + " {'name': 'Deadpool 2',\n", " 'promoted_content': None,\n", - " 'query': 'Fufuca',\n", - " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=Fufuca'},\n", - " {'name': 'Kenarik Boujikian',\n", + " 'query': '%22Deadpool+2%22',\n", + " 'tweet_volume': 84822,\n", + " 'url': 'http://twitter.com/search?q=%22Deadpool+2%22'},\n", + " {'name': 'Paula Toller',\n", " 'promoted_content': None,\n", - " 'query': '%22Kenarik+Boujikian%22',\n", + " 'query': '%22Paula+Toller%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Kenarik+Boujikian%22'},\n", - " {'name': 'Pasadena',\n", + " 'url': 'http://twitter.com/search?q=%22Paula+Toller%22'},\n", + " {'name': 'Sidão e Jean',\n", " 'promoted_content': None,\n", - " 'query': 'Pasadena',\n", - " 'tweet_volume': 10697,\n", - " 'url': 'http://twitter.com/search?q=Pasadena'},\n", - " {'name': 'Sonic Mania',\n", + " 'query': '%22Sid%C3%A3o+e+Jean%22',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=%22Sid%C3%A3o+e+Jean%22'},\n", + " {'name': 'Marquinhos Cipriano',\n", " 'promoted_content': None,\n", - " 'query': '%22Sonic+Mania%22',\n", + " 'query': '%22Marquinhos+Cipriano%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Sonic+Mania%22'},\n", - " {'name': 'Kim Jong-un',\n", + " 'url': 'http://twitter.com/search?q=%22Marquinhos+Cipriano%22'},\n", + " {'name': 'Bozo',\n", " 'promoted_content': None,\n", - " 'query': '%22Kim+Jong-un%22',\n", - " 'tweet_volume': 16925,\n", - " 'url': 'http://twitter.com/search?q=%22Kim+Jong-un%22'},\n", + " 'query': 'Bozo',\n", + " 'tweet_volume': 14511,\n", + " 'url': 'http://twitter.com/search?q=Bozo'},\n", " {'name': 'Bear',\n", " 'promoted_content': None,\n", " 'query': 'Bear',\n", - " 'tweet_volume': 99228,\n", + " 'tweet_volume': 103612,\n", " 'url': 'http://twitter.com/search?q=Bear'},\n", - " {'name': 'Vadão',\n", + " {'name': 'Borussia Dortmund',\n", " 'promoted_content': None,\n", - " 'query': 'Vad%C3%A3o',\n", + " 'query': '%22Borussia+Dortmund%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=Vad%C3%A3o'},\n", - " {'name': 'Lea Michele',\n", + " 'url': 'http://twitter.com/search?q=%22Borussia+Dortmund%22'},\n", + " {'name': 'Ipsos',\n", " 'promoted_content': None,\n", - " 'query': '%22Lea+Michele%22',\n", + " 'query': 'Ipsos',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Lea+Michele%22'},\n", - " {'name': 'Quixeré',\n", + " 'url': 'http://twitter.com/search?q=Ipsos'},\n", + " {'name': 'Bale',\n", " 'promoted_content': None,\n", - " 'query': 'Quixer%C3%A9',\n", - " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=Quixer%C3%A9'},\n", - " {'name': 'Erika Miranda',\n", + " 'query': 'Bale',\n", + " 'tweet_volume': 20617,\n", + " 'url': 'http://twitter.com/search?q=Bale'},\n", + " {'name': 'Mauro Carlesse',\n", " 'promoted_content': None,\n", - " 'query': '%22Erika+Miranda%22',\n", + " 'query': '%22Mauro+Carlesse%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Erika+Miranda%22'},\n", - " {'name': 'Emre Mor',\n", + " 'url': 'http://twitter.com/search?q=%22Mauro+Carlesse%22'},\n", + " {'name': 'Denatran',\n", " 'promoted_content': None,\n", - " 'query': '%22Emre+Mor%22',\n", - " 'tweet_volume': 24936,\n", - " 'url': 'http://twitter.com/search?q=%22Emre+Mor%22'},\n", - " {'name': 'Moro e Bretas',\n", + " 'query': 'Denatran',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=Denatran'},\n", + " {'name': 'Círculo de Fogo',\n", " 'promoted_content': None,\n", - " 'query': '%22Moro+e+Bretas%22',\n", + " 'query': '%22C%C3%ADrculo+de+Fogo%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Moro+e+Bretas%22'},\n", - " {'name': 'Mamadou Sakho',\n", + " 'url': 'http://twitter.com/search?q=%22C%C3%ADrculo+de+Fogo%22'},\n", + " {'name': 'Balsas',\n", " 'promoted_content': None,\n", - " 'query': '%22Mamadou+Sakho%22',\n", + " 'query': 'Balsas',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Mamadou+Sakho%22'},\n", - " {'name': \"'Chiclete'\",\n", + " 'url': 'http://twitter.com/search?q=Balsas'},\n", + " {'name': 'Salgado Filho',\n", " 'promoted_content': None,\n", - " 'query': '%27Chiclete%27',\n", + " 'query': '%22Salgado+Filho%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%27Chiclete%27'},\n", - " {'name': 'What Lovers Do',\n", + " 'url': 'http://twitter.com/search?q=%22Salgado+Filho%22'},\n", + " {'name': 'HOJE TEM CORINTHIANS',\n", " 'promoted_content': None,\n", - " 'query': '%22What+Lovers+Do%22',\n", + " 'query': '%22HOJE+TEM+CORINTHIANS%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22What+Lovers+Do%22'},\n", - " {'name': 'Giovanni Augusto',\n", + " 'url': 'http://twitter.com/search?q=%22HOJE+TEM+CORINTHIANS%22'},\n", + " {'name': 'Ceasa',\n", " 'promoted_content': None,\n", - " 'query': '%22Giovanni+Augusto%22',\n", + " 'query': 'Ceasa',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Giovanni+Augusto%22'},\n", - " {'name': 'ISAC',\n", + " 'url': 'http://twitter.com/search?q=Ceasa'},\n", + " {'name': 'Liam Payne',\n", " 'promoted_content': None,\n", - " 'query': 'ISAC',\n", - " 'tweet_volume': 28669,\n", - " 'url': 'http://twitter.com/search?q=ISAC'},\n", - " {'name': 'Arena Grêmio',\n", + " 'query': '%22Liam+Payne%22',\n", + " 'tweet_volume': 16093,\n", + " 'url': 'http://twitter.com/search?q=%22Liam+Payne%22'},\n", + " {'name': 'Basquete Cearense',\n", " 'promoted_content': None,\n", - " 'query': '%22Arena+Gr%C3%AAmio%22',\n", + " 'query': '%22Basquete+Cearense%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Arena+Gr%C3%AAmio%22'},\n", - " {'name': 'Contorno Leste',\n", + " 'url': 'http://twitter.com/search?q=%22Basquete+Cearense%22'},\n", + " {'name': 'Vingadores 4',\n", " 'promoted_content': None,\n", - " 'query': '%22Contorno+Leste%22',\n", + " 'query': '%22Vingadores+4%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Contorno+Leste%22'},\n", - " {'name': 'Presidente da Câmara',\n", + " 'url': 'http://twitter.com/search?q=%22Vingadores+4%22'},\n", + " {'name': 'Vettel',\n", " 'promoted_content': None,\n", - " 'query': '%22Presidente+da+C%C3%A2mara%22',\n", + " 'query': 'Vettel',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Presidente+da+C%C3%A2mara%22'},\n", - " {'name': 'Lollapalooza 2018',\n", + " 'url': 'http://twitter.com/search?q=Vettel'},\n", + " {'name': 'Araguaia',\n", " 'promoted_content': None,\n", - " 'query': '%22Lollapalooza+2018%22',\n", + " 'query': 'Araguaia',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Lollapalooza+2018%22'},\n", - " {'name': 'Van Dijk',\n", + " 'url': 'http://twitter.com/search?q=Araguaia'},\n", + " {'name': 'CNMP',\n", " 'promoted_content': None,\n", - " 'query': '%22Van+Dijk%22',\n", - " 'tweet_volume': 52376,\n", - " 'url': 'http://twitter.com/search?q=%22Van+Dijk%22'},\n", - " {'name': 'Pato Fu',\n", - " 'promoted_content': None,\n", - " 'query': '%22Pato+Fu%22',\n", + " 'query': 'CNMP',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Pato+Fu%22'},\n", - " {'name': 'São João Batista',\n", + " 'url': 'http://twitter.com/search?q=CNMP'},\n", + " {'name': 'ANAC',\n", " 'promoted_content': None,\n", - " 'query': '%22S%C3%A3o+Jo%C3%A3o+Batista%22',\n", + " 'query': 'ANAC',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22S%C3%A3o+Jo%C3%A3o+Batista%22'},\n", - " {'name': 'Rever',\n", - " 'promoted_content': None,\n", - " 'query': 'Rever',\n", - " 'tweet_volume': 10952,\n", - " 'url': 'http://twitter.com/search?q=Rever'},\n", - " {'name': 'Ucker',\n", + " 'url': 'http://twitter.com/search?q=ANAC'},\n", + " {'name': 'Alexandre de Moraes',\n", " 'promoted_content': None,\n", - " 'query': 'Ucker',\n", + " 'query': '%22Alexandre+de+Moraes%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=Ucker'},\n", - " {'name': 'Robinho e Fred',\n", + " 'url': 'http://twitter.com/search?q=%22Alexandre+de+Moraes%22'},\n", + " {'name': 'Alianza Lima',\n", " 'promoted_content': None,\n", - " 'query': '%22Robinho+e+Fred%22',\n", + " 'query': '%22Alianza+Lima%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%22Robinho+e+Fred%22'},\n", - " {'name': '#5HonGMA',\n", + " 'url': 'http://twitter.com/search?q=%22Alianza+Lima%22'},\n", + " {'name': 'MUITO BOM DIA',\n", " 'promoted_content': None,\n", - " 'query': '%235HonGMA',\n", - " 'tweet_volume': 41421,\n", - " 'url': 'http://twitter.com/search?q=%235HonGMA'},\n", - " {'name': '#VELHAPRA',\n", + " 'query': '%22MUITO+BOM+DIA%22',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=%22MUITO+BOM+DIA%22'},\n", + " {'name': 'David Byrne',\n", " 'promoted_content': None,\n", - " 'query': '%23VELHAPRA',\n", + " 'query': '%22David+Byrne%22',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23VELHAPRA'},\n", - " {'name': '#HappyDLDay',\n", + " 'url': 'http://twitter.com/search?q=%22David+Byrne%22'},\n", + " {'name': 'Organização',\n", " 'promoted_content': None,\n", - " 'query': '%23HappyDLDay',\n", + " 'query': 'Organiza%C3%A7%C3%A3o',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23HappyDLDay'},\n", + " 'url': 'http://twitter.com/search?q=Organiza%C3%A7%C3%A3o'},\n", " {'name': '#Encontro',\n", " 'promoted_content': None,\n", " 'query': '%23Encontro',\n", " 'tweet_volume': None,\n", " 'url': 'http://twitter.com/search?q=%23Encontro'},\n", - " {'name': '#bbdebate',\n", + " {'name': '#EmNomeDeQuê',\n", + " 'promoted_content': None,\n", + " 'query': '%23EmNomeDeQu%C3%AA',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=%23EmNomeDeQu%C3%AA'},\n", + " {'name': '#JinAppreciationDay',\n", + " 'promoted_content': None,\n", + " 'query': '%23JinAppreciationDay',\n", + " 'tweet_volume': 54058,\n", + " 'url': 'http://twitter.com/search?q=%23JinAppreciationDay'},\n", + " {'name': '#DePlaca',\n", " 'promoted_content': None,\n", - " 'query': '%23bbdebate',\n", + " 'query': '%23DePlaca',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23bbdebate'},\n", - " {'name': '#SeOTwitterFosseBanidoEu',\n", + " 'url': 'http://twitter.com/search?q=%23DePlaca'},\n", + " {'name': '#11AnosDeQuaseAnjos',\n", " 'promoted_content': None,\n", - " 'query': '%23SeOTwitterFosseBanidoEu',\n", + " 'query': '%2311AnosDeQuaseAnjos',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23SeOTwitterFosseBanidoEu'},\n", - " {'name': '#fsradiobrasil',\n", + " 'url': 'http://twitter.com/search?q=%2311AnosDeQuaseAnjos'},\n", + " {'name': '#FLAxFLU',\n", " 'promoted_content': None,\n", - " 'query': '%23fsradiobrasil',\n", + " 'query': '%23FLAxFLU',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23fsradiobrasil'},\n", - " {'name': '#MichaelJacksonDay',\n", + " 'url': 'http://twitter.com/search?q=%23FLAxFLU'},\n", + " {'name': '#bomdiafoxquinta',\n", " 'promoted_content': None,\n", - " 'query': '%23MichaelJacksonDay',\n", + " 'query': '%23bomdiafoxquinta',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23MichaelJacksonDay'},\n", - " {'name': '#MalhaçãoNoVIVA',\n", + " 'url': 'http://twitter.com/search?q=%23bomdiafoxquinta'},\n", + " {'name': '#trchuvaRJ',\n", " 'promoted_content': None,\n", - " 'query': '%23Malha%C3%A7%C3%A3oNoVIVA',\n", + " 'query': '%23trchuvaRJ',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23Malha%C3%A7%C3%A3oNoVIVA'},\n", - " {'name': '#JornalAssombrado',\n", + " 'url': 'http://twitter.com/search?q=%23trchuvaRJ'},\n", + " {'name': '#cartolafc',\n", " 'promoted_content': None,\n", - " 'query': '%23JornalAssombrado',\n", + " 'query': '%23cartolafc',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23JornalAssombrado'},\n", - " {'name': '#economiaG1',\n", + " 'url': 'http://twitter.com/search?q=%23cartolafc'},\n", + " {'name': '#sbtrio',\n", " 'promoted_content': None,\n", - " 'query': '%23economiaG1',\n", + " 'query': '%23sbtrio',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23economiaG1'},\n", - " {'name': '#ConexãoEI',\n", + " 'url': 'http://twitter.com/search?q=%23sbtrio'},\n", + " {'name': '#redacaosportv',\n", " 'promoted_content': None,\n", - " 'query': '%23Conex%C3%A3oEI',\n", + " 'query': '%23redacaosportv',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23Conex%C3%A3oEI'},\n", - " {'name': '#BemEstar',\n", + " 'url': 'http://twitter.com/search?q=%23redacaosportv'},\n", + " {'name': '#BBbomdia',\n", " 'promoted_content': None,\n", - " 'query': '%23BemEstar',\n", + " 'query': '%23BBbomdia',\n", " 'tweet_volume': None,\n", - " 'url': 'http://twitter.com/search?q=%23BemEstar'},\n", - " {'name': '#VMAs',\n", + " 'url': 'http://twitter.com/search?q=%23BBbomdia'},\n", + " {'name': '#DragRace',\n", " 'promoted_content': None,\n", - " 'query': '%23VMAs',\n", - " 'tweet_volume': 392329,\n", - " 'url': 'http://twitter.com/search?q=%23VMAs'}]}]" + " 'query': '%23DragRace',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=%23DragRace'},\n", + " {'name': '#ConferênciaOABJovem',\n", + " 'promoted_content': None,\n", + " 'query': '%23Confer%C3%AAnciaOABJovem',\n", + " 'tweet_volume': None,\n", + " 'url': 'http://twitter.com/search?q=%23Confer%C3%AAnciaOABJovem'},\n", + " {'name': '#InMyBlood',\n", + " 'promoted_content': None,\n", + " 'query': '%23InMyBlood',\n", + " 'tweet_volume': 469178,\n", + " 'url': 'http://twitter.com/search?q=%23InMyBlood'},\n", + " {'name': '#apagao',\n", + " 'promoted_content': None,\n", + " 'query': '%23apagao',\n", + " 'tweet_volume': 45731,\n", + " 'url': 'http://twitter.com/search?q=%23apagao'}]}]" ] }, - "execution_count": 6, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "trendtopics = api.trends_place(455824)\n", - "#trendtopics = api.trends_place(455821)\n", + "#trendtopics = api.trends_place(455824)\n", + "#trendtopics = api.trends_place(455823)\n", + "trendtopics = api.trends_place(23424768)\n", "trendtopics" ] }, @@ -3805,10 +3807,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 35, + "metadata": {}, "outputs": [], "source": [ "dfTrendTopics = pd.DataFrame(trendtopics[0]['trends'])" @@ -3816,15 +3816,26 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 36, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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0gp_pulipakaDr. GP PulipakaGanapathi Pulipaka | Founder and CEO @deepsing...Los Angeles, CA290981632233305IainLJBrownIain Brown, PhDLead #DataScientist @SASSoftware | Adjunct Pro...London54038527296551
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2kdnuggetsKDnuggetsCovering #Analytics, #BigData, #DataMining, #D...Brookline, MA, USA9238439440731reach2ratanRatan Jyoti#CyberSecurity Researcher & Leader, #influence...Bangalore9060116513726
3pinakinariwalaPinakin AriwalaProject Manager @marutitech, sharing data scie...Ahmedabad4531408316KirkDBorneKirk BorneThe Principal Data Scientist at @BoozAllen, Ph...Booz Allen Hamilton1904344240483963
4paulalbrightPaul AlbrightLeadership, growth, and getting things done at...Silicon Valley, CA735542715979MikeQuindazziMike Quindazzi ✨Managing Director @StrategyAnd / @PwC • EC @LA...Los Angeles, CA73636517034403
5ipfconline1ipfconlineCréation de Sites Internet Formation et Consei...Marseille, France669316479783172PwCPwCLatest news and insights from and about the Pw...Global786446398511
6evankirstelEvan Kirstel#Influencer #ThoughtLeader Helping #B2B client...Boston, MA141111137632548280kdnuggetsKDnuggetsCovering #AI, #Analytics, #BigData, #DataMinin...Brookline, MA, USA10977740746364
7cloudpreacherDavid HolmFuturist, CloudEvangelist, Influencer, Entrepr...Oslo, Norway802663383408omgitsBenHayesBen HayesSolving problems, making big data seem small. 🔍Pittsburgh, PA3836512188
8Ronald_vanLoonRonald van LoonHelping data driven companies generating value...#NL. Also connect on LinkedIn1001739607033068IHDPscotIHDP ScotlandInnovative Healthcare Delivery Programme | Har...Edinburgh, Scotland5326161093
9jblefevre60J-Baptiste Lefevre#digital #innovation #banque #fintech #disrupt...Paris, France14634282250882Ronald_vanLoonRonald van LoonHelping data driven companies generating value...#NL. Also follow Linkedin Puls12552111985544526
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Also connect on LinkedIn 100173 96070 33068 \n", - "9 Paris, France 14634 2822 50882 " + " location followers_count friends_count no_tweets \n", + "0 London 54038 52729 6551 \n", + "1 96347 93698 29797 \n", + "2 Bangalore 9060 1165 13726 \n", + "3 Booz Allen Hamilton 190434 42404 83963 \n", + "4 Los Angeles, CA 73636 5170 34403 \n", + "5 Global 78644 639 8511 \n", + "6 Brookline, MA, USA 109777 407 46364 \n", + "7 Pittsburgh, PA 3836 512 188 \n", + "8 Edinburgh, Scotland 532 616 1093 \n", + "9 #NL. Also follow Linkedin Puls 125521 119855 44526 " ] }, - "execution_count": 35, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -6176,7 +6072,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula07-preprocessamento.ipynb b/aula07-preprocessamento.ipynb index 55b65e7..7b1f274 100644 --- a/aula07-preprocessamento.ipynb +++ b/aula07-preprocessamento.ipynb @@ -72,7 +72,7 @@ "source": [ "#### Atributos binários\n", "\n", - "Atributos binários são um caso particular de atributos nominais em que existem apenas duas categorias. Em geral representamos tais atributos por **0** e **1**. Também frequentemente associamos 0 com a ausência do atributo e 1 com a presença. Exemplos de atributos numéricos são: *fumante* (numa base de dados médicos, indicando se a pessoa é ou não fumante), genêro (0 indicando feminino e 1 masculino). Esses atributos podem ser **simétricos** ou **assimétricos**. Em atributos simétricos ambos os códigos possuem o mesmo 'peso' e igualmente prováveis. Por exemplo, o gênero masculino e feminino são igualmente prováveis e, nesse caso, tanto faz associar masculino a 0 ou 1. Atributos assimétricos, por outro lado, não são igualmente prováveis. Por exemplo, a indicação de um resultado de um teste de câncer. Proporcionalmente temos mais eventos negativos que positivos. Isto é, os eventos positivos são mais raros que os negativos, logo associamos 1 à presença (evento positivo) e 0 à ausência (evento negativo)." + "Atributos binários são um caso particular de atributos nominais em que existem apenas duas categorias. Em geral representamos tais atributos por **0** e **1**. Também frequentemente associamos 0 com a ausência do atributo e 1 com a presença. Exemplos de atributos binários são: *fumante* (numa base de dados médicos, indicando se a pessoa é ou não fumante), genêro (0 indicando feminino e 1 masculino). Esses atributos podem ser **simétricos** ou **assimétricos**. Em atributos simétricos ambos os códigos possuem o mesmo 'peso' e são igualmente prováveis. Por exemplo, o gênero masculino e feminino são igualmente prováveis e, nesse caso, tanto faz associar masculino a 0 ou 1. Atributos assimétricos, por outro lado, não são igualmente prováveis. Por exemplo, a indicação de um resultado de um teste de câncer. Proporcionalmente temos mais eventos negativos que positivos. Isto é, os eventos positivos são mais raros que os negativos, logo associamos 1 à presença (evento positivo) e 0 à ausência (evento negativo)." ] }, { @@ -81,7 +81,7 @@ "source": [ "#### Atributos ordinais\n", "\n", - "Atributos ordinais são aqueles em que existe uma ordem (total) definida entre suas possíveis categorias. Por exemplo, tamanho de roupas divididos P, M, e G. Sabemos que existe uma ordem entre as possíveis categorias, mas não sabemos quantificar tal diferença. Não sabemos quão grande é a diferença de tamanho entre o P e o G. Atributos desse tipo surgem com frequência em questionários associados a números (por exemplo, pesquisa de satisfação). Embora exista uma ordem entre as categorias e essas estejam relacionadas a números, não podemos executar certas operações algébricas com tais atributos. Por exemplo, não faz sentido subtrair duas categorias ou, ainda, calcular a média de um atributo ordinal. Em outras palavras, esses ainda continuando sendo descrições qualitativas de objetos." + "Atributos ordinais são aqueles em que existe uma ordem (total) definida entre suas possíveis categorias. Por exemplo, tamanho de roupas divididos P, M, e G. Sabemos que existe uma ordem entre as possíveis categorias, mas não sabemos quantificar tal diferença. Não sabemos quão grande é a diferença de tamanho entre o P e o G. Atributos desse tipo surgem com frequência em questionários associados a números (por exemplo, pesquisa de satisfação). Embora exista uma ordem entre as categorias e essas estejam relacionadas a números, não podemos executar certas operações algébricas com tais atributos. Por exemplo, não faz sentido subtrair duas categorias ou, ainda, calcular a média de um atributo ordinal. Em outras palavras, esses ainda continuam sendo descrições qualitativas de objetos." ] }, { @@ -115,9 +115,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -134,9 +132,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "usuarios = pd.read_csv(\n", @@ -145,7 +141,9 @@ "filmes = pd.read_csv(\n", " \"http://files.grouplens.org/datasets/movielens/ml-100k/u.item\",\n", " sep='|',header=None, names=[\"movie_id\", \"movie_title\", \"release_date\", \"video_release_date\", \"IMDb_URL\", \"unknown\", \"Action\", \"Adventure\", \"Animation\", \n", - " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \"Horror\", \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"])\n", + " \"Children\", \"Comedy\", \"Crime\", \"Documentary\", \"Drama\", \"Fantasy\",\"FilmNoir\", \n", + " \"Horror\", \"Musical\", \"Mystery\", \"Romance\", \"SciFi\",\"Thriller\", \"War\", \"Western\"],\n", + "encoding='latin1')\n", "avaliacoes = pd.read_csv(\n", " \"http://files.grouplens.org/datasets/movielens/ml-100k/u.data\",\n", " sep='\\t',header=None, names=[\"user_id\", \"movie_id\", \"rating\", \"timestamp\"])\n" @@ -161,9 +159,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -181,6 +177,19 @@ "data": { "text/html": [ "
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\n", " \n", " \n", @@ -899,9 +922,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -918,6 +939,19 @@ "data": { "text/html": [ "
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Isso é feito em Pandas através da função `fillna`, tal como havíamos feito anteriormente quando extraímos o ano da data de lançamento e o convertemos para inteiro. A função espera um valor que será assinalado ao atributo. Esse valor pode ser arbitrário ou uma medida de tendência computado sobre os dados presentes. Por exemplo, podemos preencher a data de lançamento do filme descoberto acima com a moda." + "Podemos preencher todos os dados ausentes com um único valor. Isso é feito em Pandas através da função `fillna`, tal como havíamos feito anteriormente quando extraímos o ano da data de lançamento e o convertemos para inteiro. A função espera um valor que será assinalado ao atributo. Esse valor pode ser arbitrário ou uma medida de tendência computada sobre os dados presentes. Por exemplo, podemos preencher a data de lançamento do filme descoberto acima com a moda." ] }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { @@ -1350,7 +1453,7 @@ "Timestamp('1995-01-01 00:00:00')" ] }, - "execution_count": 18, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1403,10 +1506,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 46, + "metadata": {}, "outputs": [ { "data": { @@ -1472,11 +1573,11 @@ "1679 90s\n", "1680 90s\n", "1681 90s\n", - "Name: decada, dtype: category\n", + "Name: decada, Length: 1682, dtype: category\n", "Categories (7, object): [20s < 40s < 50s < 60s < 70s < 80s < 90s]" ] }, - "execution_count": 19, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" } @@ -1487,7 +1588,7 @@ " labels=[\"20s\"]+list(map(lambda x: '{}s'.format(x%100),\n", " np.linspace(1940,2000,7,dtype=np.int32)[:6])))\n", "\n", - "filmes.decada" + "filmes.decada\n" ] }, { @@ -1509,86 +1610,87 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 51, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 [1, 3]\n", - "1 [1, 3]\n", - "2 [1, 3]\n", - "3 [1, 3]\n", - "4 [1, 3]\n", - "5 (3, 4]\n", - "6 [1, 3]\n", - "7 (4, 5]\n", - "8 [1, 3]\n", - "9 [1, 3]\n", - "10 [1, 3]\n", - "11 (4, 5]\n", - "12 (4, 5]\n", - "13 [1, 3]\n", - "14 [1, 3]\n", - "15 [1, 3]\n", - "16 (4, 5]\n", - "17 [1, 3]\n", - "18 (3, 4]\n", - "19 [1, 3]\n", - "20 (3, 4]\n", - "21 (3, 4]\n", - "22 (3, 4]\n", - "23 [1, 3]\n", - "24 (3, 4]\n", - "25 [1, 3]\n", - "26 (4, 5]\n", - "27 [1, 3]\n", - "28 (3, 4]\n", - "29 (4, 5]\n", - " ... \n", - "99970 [1, 3]\n", - "99971 [1, 3]\n", - "99972 [1, 3]\n", - "99973 (3, 4]\n", - "99974 [1, 3]\n", - "99975 [1, 3]\n", - "99976 [1, 3]\n", - "99977 [1, 3]\n", - "99978 (4, 5]\n", - "99979 [1, 3]\n", - "99980 (3, 4]\n", - "99981 [1, 3]\n", - "99982 [1, 3]\n", - "99983 [1, 3]\n", - "99984 [1, 3]\n", - "99985 (3, 4]\n", - "99986 [1, 3]\n", - "99987 [1, 3]\n", - "99988 (3, 4]\n", - "99989 (3, 4]\n", - "99990 (3, 4]\n", - "99991 (3, 4]\n", - "99992 [1, 3]\n", - "99993 [1, 3]\n", - "99994 [1, 3]\n", - "99995 [1, 3]\n", - "99996 (4, 5]\n", - "99997 [1, 3]\n", - "99998 [1, 3]\n", - "99999 [1, 3]\n", - "Name: rating, dtype: category\n", - "Categories (3, object): [[1, 3] < (3, 4] < (4, 5]]" + "0 (0.999, 3.0]\n", + "1 (0.999, 3.0]\n", + "2 (0.999, 3.0]\n", + "3 (0.999, 3.0]\n", + "4 (0.999, 3.0]\n", + "5 (3.0, 4.0]\n", + "6 (0.999, 3.0]\n", + "7 (4.0, 5.0]\n", + "8 (0.999, 3.0]\n", + "9 (0.999, 3.0]\n", + "10 (0.999, 3.0]\n", + "11 (4.0, 5.0]\n", + "12 (4.0, 5.0]\n", + "13 (0.999, 3.0]\n", + "14 (0.999, 3.0]\n", + "15 (0.999, 3.0]\n", + "16 (4.0, 5.0]\n", + "17 (0.999, 3.0]\n", + "18 (3.0, 4.0]\n", + "19 (0.999, 3.0]\n", + "20 (3.0, 4.0]\n", + "21 (3.0, 4.0]\n", + "22 (3.0, 4.0]\n", + "23 (0.999, 3.0]\n", + "24 (3.0, 4.0]\n", + "25 (0.999, 3.0]\n", + "26 (4.0, 5.0]\n", + "27 (0.999, 3.0]\n", + "28 (3.0, 4.0]\n", + "29 (4.0, 5.0]\n", + " ... \n", + "99970 (0.999, 3.0]\n", + "99971 (0.999, 3.0]\n", + "99972 (0.999, 3.0]\n", + "99973 (3.0, 4.0]\n", + "99974 (0.999, 3.0]\n", + "99975 (0.999, 3.0]\n", + "99976 (0.999, 3.0]\n", + "99977 (0.999, 3.0]\n", + "99978 (4.0, 5.0]\n", + "99979 (0.999, 3.0]\n", + "99980 (3.0, 4.0]\n", + "99981 (0.999, 3.0]\n", + "99982 (0.999, 3.0]\n", + "99983 (0.999, 3.0]\n", + "99984 (0.999, 3.0]\n", + "99985 (3.0, 4.0]\n", + "99986 (0.999, 3.0]\n", + "99987 (0.999, 3.0]\n", + "99988 (3.0, 4.0]\n", + "99989 (3.0, 4.0]\n", + "99990 (3.0, 4.0]\n", + "99991 (3.0, 4.0]\n", + "99992 (0.999, 3.0]\n", + "99993 (0.999, 3.0]\n", + "99994 (0.999, 3.0]\n", + "99995 (0.999, 3.0]\n", + "99996 (4.0, 5.0]\n", + "99997 (0.999, 3.0]\n", + "99998 (0.999, 3.0]\n", + "99999 (0.999, 3.0]\n", + "Name: rating, Length: 100000, dtype: category\n", + "Categories (3, interval[float64]): [(0.999, 3.0] < (3.0, 4.0] < (4.0, 5.0]]" ] }, - "execution_count": 20, + "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.qcut(avaliacoes.rating.astype(int),3)" + "pd.qcut(avaliacoes.rating.astype(int),3)\n", + "#pd.qcut(avaliacoes.rating.astype(int),3).cat.rename_categories(\n", + "# {pd.Interval(left=0.999, right=3.0,closed='right'):'ruim'})\n", + "#pd.qcut(avaliacoes.rating.astype(int),3).cat.rename_categories(['ruim','media','boa'])" ] }, { @@ -1597,11 +1699,11 @@ "source": [ "## Normalização\n", "\n", - "Em várias situações devemos ajustar valores em difentes escalas para uma escala comum (em geral [0,1] ou [-1,1]). Isso ocorre porque os algoritmos de mineração/aprendizado podem atribuir pesos maiores aos atributos com valores maiores. Por exemplo, algoritmos de clustering usam distância euclidiana entre objetos computada sobre os atributos. Atributos com grandezas maiores podem 'dominar' outros com grandezas menores.\n", + "Em várias situações devemos ajustar valores em diferentes escalas para uma escala comum (em geral [0,1] ou [-1,1]). Isso ocorre porque os algoritmos de mineração/aprendizado podem atribuir pesos maiores aos atributos com valores maiores. Por exemplo, algoritmos de clustering usam distância euclidiana entre objetos computada sobre os atributos. Atributos com grandezas maiores podem 'dominar' outros com grandezas menores.\n", "\n", "O processo de normalização é uma tentativa de conferir pesos iguais a todos os atributos. As técnicas mais comuns de normalização são *min-max* e *z-score*.\n", "\n", - "Usaremos como exemplo de normalização os dados sobre qualidade de vinhos disponível em http://mlr.cs.umass.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv.\n", + "Usaremos, como exemplo de normalização, os dados sobre qualidade de vinhos disponível em http://mlr.cs.umass.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv.\n", "Veremos como as duas técnicas podem ser facilmente computadas em Python, usando Pandas e Scikit-Learn.\n", "\n", "Logo, antes de iniciarmos as discussões sobre as técnicas, precisamos carregar os dados." @@ -1609,10 +1711,8 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 34, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1642,6 +1742,19 @@ "data": { "text/html": [ "
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\n", " \n", " \n", @@ -1763,7 +1876,7 @@ "4 9.9 6 " ] }, - "execution_count": 21, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -1799,15 +1912,26 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 35, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1823,7 +1947,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -1840,7 +1963,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -1855,7 +1977,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -1870,7 +1991,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -1885,7 +2005,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -1900,7 +2019,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", "
pHsulphatesalcoholquality
0.2545450.2674420.1290320.5
10.5272730.3139530.2419350.5
20.4909090.2558140.3387100.5
30.4272730.2093020.3064520.5
40.4272730.2093020.3064520.5
\n", @@ -1921,30 +2039,28 @@ "3 0.156794 0.410673 0.163678 0.427273 0.209302 \n", "4 0.156794 0.410673 0.163678 0.427273 0.209302 \n", "\n", - " alcohol quality \n", - "0 0.129032 0.5 \n", - "1 0.241935 0.5 \n", - "2 0.338710 0.5 \n", - "3 0.306452 0.5 \n", - "4 0.306452 0.5 " + " alcohol \n", + "0 0.129032 \n", + "1 0.241935 \n", + "2 0.338710 \n", + "3 0.306452 \n", + "4 0.306452 " ] }, - "execution_count": 22, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "wine.apply(lambda x: (x-x.min())/(x.max()-x.min())).head()\n", + "wine.drop('quality',axis=1).apply(lambda x: (x-x.min())/(x.max()-x.min())).head()\n", "#wine.iloc[:,:-1].apply(lambda x: (x-x.min())/(x.max()-x.min()))" ] }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 36, + "metadata": {}, "outputs": [], "source": [ "from sklearn.preprocessing import StandardScaler, MinMaxScaler" @@ -1952,204 +2068,26 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": { - "collapsed": false - }, + "execution_count": 52, + "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:321: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/usr/local/lib/python3.5/site-packages/sklearn/preprocessing/data.py:356: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n" - ] - }, { "data": { "text/html": [ "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcohol
00.3076920.1862750.2168670.3082820.1068250.1498260.3735500.2677850.2545450.2674420.129032
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" - ], - "text/plain": [ - " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", - "0 0.307692 0.186275 0.216867 0.308282 0.106825 \n", - "1 0.240385 0.215686 0.204819 0.015337 0.118694 \n", - "2 0.413462 0.196078 0.240964 0.096626 0.121662 \n", - "3 0.326923 0.147059 0.192771 0.121166 0.145401 \n", - "4 0.326923 0.147059 0.192771 0.121166 0.145401 \n", + "\n", "\n", " \n", " \n", @@ -3220,31 +3158,28 @@ "[4898 rows x 11 columns]" ] }, - "execution_count": 32, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "scaler = MinMaxScaler()\n", + "#scaler.fit_transform(wine.drop('quality',axis=1))\n", "pd.DataFrame(scaler.fit_transform(wine.drop('quality',axis=1)), columns=wine.drop('quality',axis=1).columns)" ] }, { "cell_type": "markdown", - "metadata": { - "collapsed": false - }, + "metadata": {}, "source": [ "Veja que o resultado da transformação é um vetor de numpy. Podemos criar um novo data frame a partir desse vetor e assinalar as colunas do data frame original, ou podemos substituir os valores no data frame original." ] }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, + "execution_count": 39, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -3276,6 +3211,19 @@ "data": { "text/html": [ "
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\n", " \n", " \n", @@ -3465,17 +3424,17 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -3568,7 +3527,7 @@ "text/plain": [ " fixed acidity volatile acidity citric acid residual sugar \\\n", "count 4.898000e+03 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean -3.481630e-16 4.468092e-16 2.321087e-17 -1.109770e-16 \n", + "mean 2.653755e-14 -1.053431e-14 5.344610e-14 -2.538326e-15 \n", "std 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n", "min -3.619982e+00 -1.966784e+00 -2.761461e+00 -1.141827e+00 \n", "25% -6.574340e-01 -6.770318e-01 -5.304215e-01 -9.249530e-01 \n", @@ -3578,7 +3537,7 @@ "\n", " chlorides free sulfur dioxide total sulfur dioxide density \\\n", "count 4.898000e+03 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean 1.160543e-17 -1.378145e-17 -4.642174e-17 3.256485e-14 \n", + "mean -1.419036e-15 6.210721e-18 -1.387439e-16 2.148461e-12 \n", "std 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 \n", "min -1.683102e+00 -1.958477e+00 -3.043919e+00 -2.312802e+00 \n", "25% -4.472890e-01 -7.237012e-01 -7.144009e-01 -7.706280e-01 \n", @@ -3588,7 +3547,7 @@ "\n", " pH sulphates alcohol \n", "count 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean -1.195360e-15 -8.218098e-16 -3.713739e-16 \n", + "mean 1.316599e-14 -1.280696e-14 -2.846868e-14 \n", "std 1.000000e+00 1.000000e+00 1.000000e+00 \n", "min -3.101091e+00 -2.364468e+00 -2.043089e+00 \n", "25% -6.507699e-01 -6.996389e-01 -8.241915e-01 \n", @@ -3597,7 +3556,7 @@ "max 4.183648e+00 5.171074e+00 2.995020e+00 " ] }, - "execution_count": 34, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -3608,15 +3567,26 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 41, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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mean-3.481630e-164.468092e-162.321087e-17-1.109770e-161.160543e-17-1.378145e-17-4.642174e-173.256485e-14-1.195360e-15-8.218098e-16-3.713739e-162.653755e-14-1.053431e-145.344610e-14-2.538326e-15-1.419036e-156.210721e-18-1.387439e-162.148461e-121.316599e-14-1.280696e-14-2.846868e-14
std
\n", " \n", " \n", @@ -3651,17 +3621,17 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -3754,7 +3724,7 @@ "text/plain": [ " fixed acidity volatile acidity citric acid residual sugar \\\n", "count 4.898000e+03 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean -3.481630e-16 4.497106e-16 1.160543e-17 -1.066249e-16 \n", + "mean 7.584333e-17 5.196832e-16 6.019639e-16 -1.024542e-16 \n", "std 1.000102e+00 1.000102e+00 1.000102e+00 1.000102e+00 \n", "min -3.620351e+00 -1.966985e+00 -2.761743e+00 -1.141944e+00 \n", "25% -6.575011e-01 -6.771010e-01 -5.304757e-01 -9.250474e-01 \n", @@ -3764,7 +3734,7 @@ "\n", " chlorides free sulfur dioxide total sulfur dioxide density \\\n", "count 4.898000e+03 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean 2.321087e-17 -1.015476e-17 -4.642174e-17 3.256485e-14 \n", + "mean 6.482723e-17 -4.671641e-17 1.057636e-16 3.212112e-14 \n", "std 1.000102e+00 1.000102e+00 1.000102e+00 1.000102e+00 \n", "min -1.683274e+00 -1.958677e+00 -3.044230e+00 -2.313038e+00 \n", "25% -4.473347e-01 -7.237750e-01 -7.144739e-01 -7.707066e-01 \n", @@ -3774,7 +3744,7 @@ "\n", " pH sulphates alcohol \n", "count 4.898000e+03 4.898000e+03 4.898000e+03 \n", - "mean -1.183754e-15 -8.218098e-16 -3.713739e-16 \n", + "mean -1.203860e-15 -7.572999e-16 -2.178784e-15 \n", "std 1.000102e+00 1.000102e+00 1.000102e+00 \n", "min -3.101408e+00 -2.364709e+00 -2.043297e+00 \n", "25% -6.508363e-01 -6.997104e-01 -8.242757e-01 \n", @@ -3783,7 +3753,7 @@ "max 4.184075e+00 5.171602e+00 2.995326e+00 " ] }, - "execution_count": 35, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -3821,7 +3791,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula08-eda.ipynb b/aula08-eda.ipynb index b38b0c3..87f0dc4 100644 --- a/aula08-eda.ipynb +++ b/aula08-eda.ipynb @@ -32,9 +32,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -51,14 +49,25 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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\n", " \n", " \n", @@ -1153,7 +1149,7 @@ "2014 2.762845e+12 5.797893e+10" ] }, - "execution_count": 19, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -1175,15 +1171,26 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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1960[50, 70)[50.0, 70.0)
1961[50, 70)[50.0, 70.0)
1962[50, 70)[50.0, 70.0)
1963[50, 70)[50.0, 70.0)
1964[50, 70)[50.0, 70.0)
1965[50, 70)[50.0, 70.0)
1966[50, 70)[50.0, 70.0)
1967[50, 70)[50.0, 70.0)
1968[50, 70)[50.0, 70.0)
1969[50, 70)[50.0, 70.0)
1970[50, 70)[50.0, 70.0)
1971[50, 70)[50.0, 70.0)
1972[50, 70)[50.0, 70.0)
1973[50, 70)[50.0, 70.0)
1974[50, 70)[50.0, 70.0)
1975[50, 70)[50.0, 70.0)
1976[50, 70)[50.0, 70.0)
1977[50, 70)[50.0, 70.0)
1978[50, 70)[50.0, 70.0)
1979[50, 70)[50.0, 70.0)
1980[50, 70)[50.0, 70.0)
1981[50, 70)[50.0, 70.0)
1982[50, 70)[50.0, 70.0)
1983[50, 70)[50.0, 70.0)
1984[50, 70)[50.0, 70.0)
1985[50, 70)[50.0, 70.0)
1986[50, 70)[50.0, 70.0)
1987[50, 70)[50.0, 70.0)
1988[50, 70)[50.0, 70.0)
1989[50, 70)[50.0, 70.0)
1990[50, 70)[50.0, 70.0)
1991[50, 70)[50.0, 70.0)
1992[50, 70)[50.0, 70.0)
1993[50, 70)[50.0, 70.0)
1994[50, 70)[50.0, 70.0)
1995[50, 70)[50.0, 70.0)
1996[50, 70)[50.0, 70.0)
1997[50, 70)[50.0, 70.0)
1998[50, 70)[50.0, 70.0)
1999[70, inf)[70.0, inf)
2000[70, inf)[70.0, inf)
2001[70, inf)[70.0, inf)
2002[70, inf)[70.0, inf)
2003[70, inf)[70.0, inf)
2004[70, inf)[70.0, inf)
2005[70, inf)[70.0, inf)
2006[70, inf)[70.0, inf)
2007[70, inf)[70.0, inf)
2008[70, inf)[70.0, inf)
2009[70, inf)[70.0, inf)
2010[70, inf)[70.0, inf)
2011[70, inf)[70.0, inf)
2012[70, inf)[70.0, inf)
2013[70, inf)[70.0, inf)
2014[70, inf)[70.0, inf)
\n", "
" ], "text/plain": [ - " 0\n", - "1960 [50, 70)\n", - "1961 [50, 70)\n", - "1962 [50, 70)\n", - "1963 [50, 70)\n", - "1964 [50, 70)\n", - "1965 [50, 70)\n", - "1966 [50, 70)\n", - "1967 [50, 70)\n", - "1968 [50, 70)\n", - "1969 [50, 70)\n", - "1970 [50, 70)\n", - "1971 [50, 70)\n", - "1972 [50, 70)\n", - "1973 [50, 70)\n", - "1974 [50, 70)\n", - "1975 [50, 70)\n", - "1976 [50, 70)\n", - "1977 [50, 70)\n", - "1978 [50, 70)\n", - "1979 [50, 70)\n", - "1980 [50, 70)\n", - "1981 [50, 70)\n", - "1982 [50, 70)\n", - "1983 [50, 70)\n", - "1984 [50, 70)\n", - "1985 [50, 70)\n", - "1986 [50, 70)\n", - "1987 [50, 70)\n", - "1988 [50, 70)\n", - "1989 [50, 70)\n", - "1990 [50, 70)\n", - "1991 [50, 70)\n", - "1992 [50, 70)\n", - "1993 [50, 70)\n", - "1994 [50, 70)\n", - "1995 [50, 70)\n", - "1996 [50, 70)\n", - "1997 [50, 70)\n", - "1998 [50, 70)\n", - "1999 [70, inf)\n", - "2000 [70, inf)\n", - "2001 [70, inf)\n", - "2002 [70, inf)\n", - "2003 [70, inf)\n", - "2004 [70, inf)\n", - "2005 [70, inf)\n", - "2006 [70, inf)\n", - "2007 [70, inf)\n", - "2008 [70, inf)\n", - "2009 [70, inf)\n", - "2010 [70, inf)\n", - "2011 [70, inf)\n", - "2012 [70, inf)\n", - "2013 [70, inf)\n", - "2014 [70, inf)" + " 0\n", + "1960 [50.0, 70.0)\n", + "1961 [50.0, 70.0)\n", + "1962 [50.0, 70.0)\n", + "1963 [50.0, 70.0)\n", + "1964 [50.0, 70.0)\n", + "1965 [50.0, 70.0)\n", + "1966 [50.0, 70.0)\n", + "1967 [50.0, 70.0)\n", + "1968 [50.0, 70.0)\n", + "1969 [50.0, 70.0)\n", + "1970 [50.0, 70.0)\n", + "1971 [50.0, 70.0)\n", + "1972 [50.0, 70.0)\n", + "1973 [50.0, 70.0)\n", + "1974 [50.0, 70.0)\n", + "1975 [50.0, 70.0)\n", + "1976 [50.0, 70.0)\n", + "1977 [50.0, 70.0)\n", + "1978 [50.0, 70.0)\n", + "1979 [50.0, 70.0)\n", + "1980 [50.0, 70.0)\n", + "1981 [50.0, 70.0)\n", + "1982 [50.0, 70.0)\n", + "1983 [50.0, 70.0)\n", + "1984 [50.0, 70.0)\n", + "1985 [50.0, 70.0)\n", + "1986 [50.0, 70.0)\n", + "1987 [50.0, 70.0)\n", + "1988 [50.0, 70.0)\n", + "1989 [50.0, 70.0)\n", + "1990 [50.0, 70.0)\n", + "1991 [50.0, 70.0)\n", + "1992 [50.0, 70.0)\n", + "1993 [50.0, 70.0)\n", + "1994 [50.0, 70.0)\n", + "1995 [50.0, 70.0)\n", + "1996 [50.0, 70.0)\n", + "1997 [50.0, 70.0)\n", + "1998 [50.0, 70.0)\n", + "1999 [70.0, inf)\n", + "2000 [70.0, inf)\n", + "2001 [70.0, inf)\n", + "2002 [70.0, inf)\n", + "2003 [70.0, inf)\n", + "2004 [70.0, inf)\n", + "2005 [70.0, inf)\n", + "2006 [70.0, inf)\n", + "2007 [70.0, inf)\n", + "2008 [70.0, inf)\n", + "2009 [70.0, inf)\n", + "2010 [70.0, inf)\n", + "2011 [70.0, inf)\n", + "2012 [70.0, inf)\n", + "2013 [70.0, inf)\n", + "2014 [70.0, inf)" ] }, - "execution_count": 28, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1504,14 +1511,25 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -1932,15 +1950,26 @@ }, { "cell_type": "code", - "execution_count": 32, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1970,7 +1999,7 @@ "pib 6.379557e+11 4.750014e+22" ] }, - "execution_count": 32, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -2007,15 +2036,26 @@ }, { "cell_type": "code", - "execution_count": 36, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -2052,6 +2092,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -2101,15 +2154,26 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -2513,7 +2577,7 @@ "2014 7.863009e+13 7.863013e+13 3.725969e+07" ] }, - "execution_count": 9, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -2535,15 +2599,26 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -2947,7 +3022,7 @@ "2014 65.951683 72.936854 76.986146" ] }, - "execution_count": 10, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -2965,10 +3040,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { @@ -3031,7 +3104,7 @@ "dtype: float64" ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -3049,15 +3122,26 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -3798,7 +3882,7 @@ "2014 83.980488 " ] }, - "execution_count": 12, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -3818,15 +3902,26 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -3843,22 +3938,22 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3871,42 +3966,55 @@ "" ], "text/plain": [ - " expvida pib\n", - "country \n", - "Aruba [50, 70) NaN\n", - "Afghanistan [0, 50) [0.0012, 0.0673]\n", - "Angola [0, 50) NaN\n", - "Albania [50, 70) NaN\n", - "Andorra NaN NaN" + " expvida pib\n", + "country \n", + "Aruba [50.0, 70.0) NaN\n", + "Afghanistan [0.0, 50.0) (0.0002, 0.0673]\n", + "Angola [0.0, 50.0) NaN\n", + "Albania [50.0, 70.0) NaN\n", + "Andorra NaN NaN" ] }, - "execution_count": 21, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df = pd.DataFrame({'expvida':pd.cut(expv_pib[expv_pib.variable.str.contains('1960_ev')].value,bins=[0,50,70,np.infty],right=False),\\\n", - " 'pib':pd.qcut(expv_pib[expv_pib.variable.str.contains('1960_pib')].value/10E9,q=3)})\n", + "df = pd.DataFrame({'expvida':pd.cut(expv_pib[expv_pib.variable.str.contains('1960_ev')].value,\n", + " bins=[0,50,70,np.infty],right=False),\n", + " 'pib':pd.qcut(expv_pib[expv_pib.variable.str.contains('1960_pib')].value/10E9,\n", + " q=3)})\n", "df.head()" ] }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
Aruba[50, 70)[50.0, 70.0)NaN
Afghanistan[0, 50)[0.0012, 0.0673][0.0, 50.0)(0.0002, 0.0673]
Angola[0, 50)[0.0, 50.0)NaN
Albania[50, 70)[50.0, 70.0)NaN
\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3919,19 +4027,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3941,14 +4049,14 @@ "" ], "text/plain": [ - "pib [0.0012, 0.0673] (0.0673, 0.818] (0.818, 135.293]\n", - "expvida \n", - "[0, 50) 26 16 20\n", - "[50, 70) 12 21 16\n", - "[70, inf) 1 3 6" + "pib (0.0002, 0.0673] (0.0673, 0.818] (0.818, 135.293]\n", + "expvida \n", + "[0.0, 50.0) 26 16 20\n", + "[50.0, 70.0) 12 21 16\n", + "[70.0, inf) 1 3 6" ] }, - "execution_count": 22, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -3959,20 +4067,31 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
pib[0.0012, 0.0673](0.0002, 0.0673](0.0673, 0.818](0.818, 135.293]
[0, 50)[0.0, 50.0)261620
[50, 70)[50.0, 70.0)122116
[70, inf)[70.0, inf)136
\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3985,19 +4104,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4007,14 +4126,14 @@ "" ], "text/plain": [ - "pib [0.00318, 1.283] (1.283, 23.769] (23.769, 6585.316]\n", - "expvida \n", - "[0, 50) 6 0 0\n", - "[50, 70) 40 27 26\n", - "[70, inf) 27 54 56" + "pib (0.00218, 1.283] (1.283, 23.769] (23.769, 6585.316]\n", + "expvida \n", + "[0.0, 50.0) 6 0 0\n", + "[50.0, 70.0) 40 27 26\n", + "[70.0, inf) 27 54 56" ] }, - "execution_count": 23, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -4028,9 +4147,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -4051,7 +4168,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula09-datavis-parte01.ipynb b/aula09-datavis-parte01.ipynb index e89d2a9..5bda51a 100644 --- a/aula09-datavis-parte01.ipynb +++ b/aula09-datavis-parte01.ipynb @@ -13,7 +13,7 @@ "Renato Vimieiro\n", "rv2 {em} cin.ufpe.br\n", "\n", - "setembro 2017" + "abril 2018" ] }, { @@ -41,7 +41,9 @@ "source": [ "## Exemplo processamento pré-atentivo\n", "\n", - "
\n", + "\n", + "
\n", + "
\n", "
\n", "67830958779870871254

\n", "14098349857690874124

\n", @@ -62,7 +64,8 @@ "source": [ "## Exemplo processamento pré-atentivo\n", "\n", - "
\n", + "
\n", + "
\n", "
\n", "67830958779870871254

\n", "14098349857690874124

\n", @@ -86,7 +89,7 @@ "- Visualização **exploratória**\n", " - Usar elementos visuais para se familiarizar com os dados antes de iniciar a análise\n", "- Visualização **explanatória**\n", - " - Usar elementos visuais para contar uma estória, explicar os resultados da análise" + " - Usar elementos visuais para contar uma história, explicar os resultados da análise" ] }, { @@ -106,9 +109,8 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 27, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -119,8 +121,8 @@ "text/html": [ "\n", "
\n", - " \n", - " Loading BokehJS ...\n", + " \n", + " Loading BokehJS ...\n", "
" ] }, @@ -131,23 +133,143 @@ "data": { "application/javascript": [ "\n", - "(function(global) {\n", + "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", - " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", - " window._bokeh_onload_callbacks = [];\n", - " window._bokeh_is_loading = undefined;\n", + " if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id !== undefined) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var element_id = msg.content.text.trim();\n", + " Bokeh.index[element_id].model.document.clear();\n", + " delete Bokeh.index[element_id];\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(`.${CLASS_NAME.split(' ')[0]}`);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[0]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", " }\n", "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", "\n", " \n", - " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", - " window._bokeh_timeout = Date.now() + 5000;\n", - " window._bokeh_failed_load = false;\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", @@ -167,23 +289,33 @@ " \"
\"}};\n", "\n", " function display_loaded() {\n", - " if (window.Bokeh !== undefined) {\n", - " var el = document.getElementById(\"36287bce-0afb-440a-8a5e-575e99809163\");\n", - " el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n", - " } else if (Date.now() < window._bokeh_timeout) {\n", + " var el = document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", + "\n", " function run_callbacks() {\n", - " window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", - " delete window._bokeh_onload_callbacks\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", + " }\n", + " finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", " console.info(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(js_urls, callback) {\n", - " window._bokeh_onload_callbacks.push(callback);\n", - " if (window._bokeh_is_loading > 0) {\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", @@ -192,15 +324,15 @@ " return null;\n", " }\n", " console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " window._bokeh_is_loading = js_urls.length;\n", + " root._bokeh_is_loading = js_urls.length;\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", " var s = document.createElement('script');\n", " s.src = url;\n", " s.async = false;\n", " s.onreadystatechange = s.onload = function() {\n", - " window._bokeh_is_loading--;\n", - " if (window._bokeh_is_loading === 0) {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", " run_callbacks()\n", " }\n", @@ -211,13 +343,13 @@ " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", - " };var element = document.getElementById(\"36287bce-0afb-440a-8a5e-575e99809163\");\n", + " };var element = document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\");\n", " if (element == null) {\n", - " console.log(\"Bokeh: ERROR: autoload.js configured with elementid '36287bce-0afb-440a-8a5e-575e99809163' but no matching script tag was found. \")\n", + " console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c340c936-9d20-4e36-bf46-2eabc5dd60a8' but no matching script tag was found. \")\n", " return false;\n", " }\n", "\n", - " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.js\"];\n", + " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n", "\n", " var inline_js = [\n", " function(Bokeh) {\n", @@ -227,39 +359,36 @@ " function(Bokeh) {\n", " \n", " },\n", - " \n", - " function(Bokeh) {\n", - " \n", - " document.getElementById(\"36287bce-0afb-440a-8a5e-575e99809163\").textContent = \"BokehJS is loading...\";\n", - " },\n", " function(Bokeh) {\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " \n", - " if ((window.Bokeh !== undefined) || (force === true)) {\n", + " if ((root.Bokeh !== undefined) || (force === true)) {\n", " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i](window.Bokeh);\n", + " inline_js[i].call(root, root.Bokeh);\n", " }if (force === true) {\n", " display_loaded();\n", - " }} else if (Date.now() < window._bokeh_timeout) {\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", - " } else if (!window._bokeh_failed_load) {\n", + " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " window._bokeh_failed_load = true;\n", + " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"36287bce-0afb-440a-8a5e-575e99809163\")).parents('.cell').data().cell;\n", + " var cell = $(document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", "\n", " }\n", "\n", - " if (window._bokeh_is_loading === 0) {\n", + " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", @@ -268,8 +397,9 @@ " run_inline_js();\n", " });\n", " }\n", - "}(this));" - ] + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n }\n finally {\n delete root._bokeh_onload_callbacks\n }\n console.info(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(js_urls, callback) {\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = js_urls.length;\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var s = document.createElement('script');\n s.src = url;\n s.async = false;\n s.onreadystatechange = s.onload = function() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: all BokehJS libraries loaded\");\n run_callbacks()\n }\n };\n s.onerror = function() {\n console.warn(\"failed to load library \" + url);\n };\n console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.getElementsByTagName(\"head\")[0].appendChild(s);\n }\n };var element = document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\");\n if (element == null) {\n console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c340c936-9d20-4e36-bf46-2eabc5dd60a8' but no matching script tag was found. \")\n return false;\n }\n\n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n \n function(Bokeh) {\n \n },\n function(Bokeh) {\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n }\n ];\n\n function run_inline_js() {\n \n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"c340c936-9d20-4e36-bf46-2eabc5dd60a8\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(js_urls, function() {\n console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" @@ -283,6 +413,8 @@ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", + "matplotlib.style.use('ggplot')\n", + "\n", "from bokeh.plotting import figure, show\n", "from bokeh.io import output_notebook\n", "\n", @@ -292,9 +424,8 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -316,9 +447,8 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -328,6 +458,19 @@ "data": { "text/html": [ "
\n", + "\n", "
pib[0.00318, 1.283](0.00218, 1.283](1.283, 23.769](23.769, 6585.316]
[0, 50)[0.0, 50.0)600
[50, 70)[50.0, 70.0)402726
[70, inf)[70.0, inf)275456
\n", " \n", " \n", @@ -491,7 +634,7 @@ "10 5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -502,9 +645,8 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -514,6 +656,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -569,7 +724,7 @@ "media 9.0 7.5 9.0 7.5 9.0 7.5 9.0 7.5" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -582,9 +737,8 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -592,9 +746,9 @@ "outputs": [ { "data": { - "image/png": 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xM2tJZtdsljYeeo4JBULc7Bw4nN6eoCeqGn6kWvIu/ufrZt2yrO8Ffhi4bNv2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qzQsXpwkFnEIy3RCEpUyO3/+rmzQEHUbni3e3Cjpw7GBToSzlyN4GNfARqTIl\n5XJPXNeF4UGvNvxcP7x7CXIlLXw6unBO9OGc7IUHj+OEteBHRMQPY8k0jSGH2aUMC+kci+ncup1S\n9jUGOZPfKeV0Z5Rog+5gitSSkvJd7va2hhMzk+Ra43ddNOkuLcLF11fLUm6VNOgLheGRU6uz4W2d\nNfgKRERkI5mcy6WJRQZGkswuZxhPrd8CuSkc4O8c209fIsZ9+yMENBsu4hsl5bvY2gZATqwFZmdw\nv/YsuXwDINd1YWx4daeUt9+ATPGCHw605bto9sLDp3AiEX++GBERYWYxw9n8doWvjaZIpYvvYDpA\nczhAQ9AhFHT4hfd1bLjYU0RqT0n5LuZ++3mvI2ek0asVjDSCu4j7/JfJ3d47fKJk44ZgEB541EvE\nT/VBxyHVGYqI+CSbc3lneim/SDPFlemlddccbY3Ql4gRbQjQP5xkPJW56+4rIuIPJeW72eQYRPdA\nJk0uNQ+peVhaBNfFvTG4et3eVq8c5WQfPHoap6nZt5BFRHa7+eUsr741wUuXRjk7mmJueX0Dn9Od\nzfQlYpxJRDnQvLqe52OPHqh1uCKySUrKdyE3k4ErF72FmSNDkMmQK73o/kdWE/HDRzfcL1xERKrP\ndV0Gby0zMJyifyTJW5PrG/h0tTTQl4jS2xXj0YPNhIO6gymy3Sgp3yXcW9P5dvYDcPE1WCzZnjgQ\ngIYIhBrgp54m+MQP+xOoiIiwkM7y+s0FBoa9+vDpxeL1PA3BACfbm+hNeHuHd+xpuMNnEpHtoi6S\ncmPMIDAPZIGMtbav5LwD/B7wYWAB+Blr7dlax7mduLksXH17daeUa1fWX3TkPmjvgrFhnMUF3P0H\n1bJeRN6TxuzKc12X4bkV+keSDAyneHNigUzJLcy2aJi+Lq+L5lOPHiY5O+NPsCJSFXWRlOd9wFo7\neYdzPwE8mP/314D/kH8ra7jJOdw3XoXz+QY+yfniCxqbvJrwk31eacq+/YVT8Xicyck7vfwiIuto\nzN6i5UyOC2MLDOR3S7mZLG7gEwrAowebC500u1pWG/g0hoMk/QhaRKqmnpLyu/ko8BVrrQu8YozZ\nZ4zptNaO+h2Yn1zXhevvrm5Z+O5lcEumVjoPe/uGn+yDB47hhOqjgc/t/dGZHIN4u2boRXYWjdl3\nMJZcoX84xcBIkvNjC6xki4vDW5tC9OYb+DzW2UxzWA18RHaLeknKXeA7xhgXeNZa+1zJ+S7g+pqP\nb+SPFQ3wxpingacBrLXE4/XXyj0UCm0prtxCipXXf8Dy2ZdZGXiZ3EzJRFVDhIaTvUTOPEmk90mC\n7YmaxFWOpYGXSX7jP3rNhvZDhjV1AAAgAElEQVS2QnIOvvEfibW00Nj7pG9xlUNxlUdx7Tgaszcp\nnc1xbmSOlwdneHlwmsHpxaLzAQeOd+zhyZ79PHm0lQfj0btuM/vy4DRfGxhmdG6QzpYIn+zt4sme\n/Xe8vtbq9XdKcZVHcfmjXpLy91trh40xbcCLxphL1trvlvtJ8n8Ybv9xcOuxHKPcMhHXdWH0+ups\n+DtvQrZ4+ysOdhRKUnj4BNmGCAt4hZxs8rlqWb6S/U9fAifgJeXZbOHt7H/6EsnuB32LqxyKqzyK\nqzyJxOb+M+0jjdl3MbWQ5uyIt1PKa6MLLJUUh7dEgpzpjHImEeXxRIyWyO3Z8CWmptbvM37bwHCS\nZ/vHCAUc9kTCjM0t8tt//jbP9LXXzX7j9fo7pbjKo7jKU6kxuy6ScmvtcP7tuDHmBeAJYO0APwwc\nXvPxofyxHcldXobL53HP9XuJ+NR48QXBEDx0fDUR7+jaXg18bu+PvlZDxDsuInVPY3axbM7l8tRi\nYcvCqzPL6665f3+jV5bSFeOB/Y0EA+WP2S9cnCYUcGgMBXAc7+1SJscLF6frJikXkXvne1JujIkC\nAWvtfP79DwKfLbnsW8AvGmP+GG+x0OxOq010J26u7pTy1nlIrxRfsG9/vp19Hxw7hdO4jRv4xNth\ndsbrIHrbyrJ3XETqmsZsz9xShrOjKQaGU7w6mmR+pXg2vDkc4HRnlN6Et1tKa9PW/9yOJdPEGop7\nRkSCDmMlC0RFZHvyPSkH2oEXjDHgxfM1a+2fGWM+BWCt/QLwp3hba72DV5Xxsz7FWjFuJg1vv7ma\niN+8UXyBE4D7H15NxA/1bDgbvh0XTDof+jju154FlrwZ8pVlyGRwPvRxv0MTkfe2K8fsnOvy7vRy\nfqeUJJcnlyjp38PhvQ30JWL0dkU5drCZ0D3Mht9NeyzM9GKGxtDq513OurTH6mMBv4hsjeO6pcPK\njuGOjIz4HUMRd2aK6OBbzP/lS3DxdVguXvBDrAXnxBk42Ydz/HGc0hKPErnzA15yGwoVJ7effKbs\nxLzWdVqb/c9EvdaPKa7yKK7y5OsTt1FNWkXU3ZidWsnybirI/7g0ytmRJDNLxet5IkGHUx3N+QY+\nMdqqnByvrSmPRsKkltNkcq5qyjdBcZVHcZWnUmN2PcyU71huNgtX3/IWaZ7rhxtXmS+9qPsBnFP5\n2fDuB8pqZ+9++3kvIb9dBhJpBJa843U+Wx442Vv3MYrI7uK6LtdnV+gf9mbDL04sUrJjIR2xML1d\nMfoSUU60N9MQ3PyYvVW9XTGewastn1zMEG8K8bFj++smIReRrVFSXmHu/CzuhbP5Bj6vwkJxewen\nOYZ77BTOyffhnDyD09J670+mBZMiIluylMlx7maKgZEUA8NJJhaK29mHgw7HDzblE/EYiRZ/29n3\ndsXo7YrV7YyhiNw7JeVb5OZycO3K6paFg29DaUlQV7fXQfNUH/En3s/UrVuVeXItmBQRKdvo/AoD\nI0n6h1NcGFsgnSsesw80h7za8ESUDxw/wsKc2tmLSPUpKb8H7kIK3nzVS8QvDMBcSZLdEIFjj3mJ\n+Mk+nAMHC6ecUOVeci2YFBF5b+lsjjfGF+kfSTIwnGJkvnh3q4ADxw42cSbhlaV074sUFtY3NwS9\nng8iIlWmpHwTXNeFkWurO6W88ybkStrZt3Wu7pTy0HGccPVvcQZO9pL75DPbbvcVEZFqm0itNvA5\ndzPFUqZ4NnxvY5DeRJQznTEe74wSi6idvYj4S0n5HbjLS3Dp3GoiPj1RfEEoBA+dxDnZ682Id3T5\nEqcWTIqIeA18Lk3kZ8NHUgzdKm7g4wAPHGikr8srS7l/fyOB7dR0TUR2PCXla7jjI/kumgNw+Txk\nihf8sD+Oc6IP52QvPHIKp7HJn0BFRIRbSxlvNnw4yWujKVLp4juY0YYAZzq95j2PJ6Lsa9SfPBGp\nX7t6hHLTaXj7wuqWheMle+QGAvDAsdWylMSR7dXOXkRkB8m5Lleml/JbFqZ4Z2p9A5+efZHCbPjD\n8aZ7amcvIuKHXZeUu1MTuBfyO6VcOgfLS8UX7Nlb2CmFR0/jNGv/VxERvySXs7w6mmJgJMnZkRSz\ny8UNfBpDDo91ROnrinEmESXeXP/dLQeGk7xwcZqxZJr2WFh7jYsIsAuScjeTgXcvrW5ZODxUfIHj\nQM+Dq4n4kfvLauAjIiKV47ouQ7eW6c/vG35pcpFc6S6zLQ2cSUTpS8Q43tZEuIYNfLZqbVfOWEOA\n6cUMz/aP8QwoMRfZ5XZ0Up579v/0GvgspopPNMdwjj8OJ3pxTpzBadnnT4AiIlLw+98fZWA4xdRi\n8XqehqDDyfZmziS8+vDOPf428NmKFy5OEwo4NIa8/0g0hhyWMjleuDitpFxkl9vRSbnb/z9XPzh8\n1KsNP9EL9z2ME9T2VyIi9eQ778wW3m+LhuhNxOhNxDjV0UwktH1mw+9mLJkm1lD8tUSCDmPJtE8R\niUi92NFJOY//0GoDn9YDfkcjIiJ3cbK9md78bPjhvQ07cmF9eyzM9GKGxtDq17acdWmP1X8tvIhU\nl69JuTHmMPAVoB1wgeestb9Xcs1TwDeBq/lDz1trP7uZzx/8R79auWBFRKSq4/Zv/NiRygZbhz52\nbD/P9o+xlMkRCTosZ10yOZePHdvvd2gi4jO/Z8ozwD+11p41xuwBBowxL1pr3yy57nvW2o/4EJ+I\niBTTuL0FvV0xngHtviIi6/ialFtrR4HR/PvzxpiLQBdQOriLiEgd0Li9db1dMSXhIrKO3zPlBcaY\nHuBx4PsbnH7SGPM6MAL8M2vtG3f4HE8DTwNYa4nH41WK9t6FQiHFVQbFVR7FVZ56jWu72Oq4rTH7\n3imu8iiu8iguf9RFUm6MiQH/Bfgn1tq5ktNngW5rbdIY82HgT4AHN/o81trngOfyH7qTk5PVCvme\nxeNxFNfmKa7yKK7y1GtciUTC7xDeUyXGbY3Z905xlUdxlUdxladSY7bve0wZY8J4A/tXrbXPl563\n1s5Za5P59/8UCBtjdu5/k0RE6pzGbRGRyvM1KTfGOMAfAhettf/uDtd05K/DGPMEXsxTtYtSRERu\n07gtIlIdfpev/A3gfwfOG2Neyx/7VeAIgLX2C8BPAr9gjMkAi8AnrLXuRp9MRESqTuO2iEgV+L37\nyv8E7todwlr7eeDztYlIRETuRuO2iEh1+F5TLiIiIiKy2ykpFxERERHxmZJyERERERGfKSkXERER\nEfGZknIREREREZ8pKRcRERER8ZmSchERERERnykpFxERERHxmZJyERERERGfKSkXEREREfGZknIR\nEREREZ8pKRcRERER8ZmSchERERERn4X8DsAY8+PA7wFB4A+stZ8rOR8BvgL0AlPA37PWDtY6ThER\n8WjcFhGpPF9nyo0xQeD3gZ8AHgV+yhjzaMllPw/MWGsfAH4H+K3aRikiIrdp3BYRqQ6/y1eeAN6x\n1r5rrV0B/hj4aMk1HwW+nH//PwM/aoxxahijiIis0rgtIlIFfiflXcD1NR/fyB/b8BprbQaYBQ7U\nJDoRESmlcVtEpAp8rymvJGPM08DTANZaEomEzxFtTHGVR3GVR3GVp17j2g00Zm+N4iqP4iqP4qo9\nv2fKh4HDaz4+lD+24TXGmBCwF2/h0DrW2uestX3W2j5jzADg1Ns/xaW4FFf9/KvzuOpVxcZtjdmK\nS3Eprh0U15b5PVP+A+BBY8xRvEH8E8AnS675FvDTwMvATwL/3Vrr1jRKERG5TeO2iEgV+DpTnq81\n/EXg28BF75B9wxjzWWPM385f9ofAAWPMO8AvAb/iT7QiIqJxW0SkOvyeKcda+6fAn5Yc+/U17y8B\nf/cePvVzWwytWhRXeRRXeRRXeRTXPajSuF2vX7PiKo/iKo/iKs+OjstxXd1RFBERERHxk98LPUVE\nREREdj3fy1e2oh5bPRtjDuefsx1wgeestb9Xcs1TwDeBq/lDz1trP1vNuNY89yAwD2SBjLW2r+S8\ng/eafhhYAH7GWnu2yjE9DHxjzaH7gF+31v7ummueogavmTHmi8BHgHFr7Yn8sf35+HqAQcBYa2c2\neOxPA/8i/+FvWGu/XOW4fhv4W8AKcAX4WWvtrQ0eO8hdvudViOtfAf8QmMhf9qv5cofSx97197cK\ncX0DeDh/yT7glrX29AaPHaR6r9eG40M9/IzVisbtsmMbRGP23WLRmL31uP4VGrPvFFdNx+xtO1Ne\nx62eM8A/tdY+CvwQ8I83iAvge9ba0/l/NUnI1/hA/nk3+sH9CeDB/L+ngf9Q7WCstW/dfi3w/hAv\nAC9scGktXrMvAT9ecuxXgD+31j4I/DkbLFrL/4J+BvhreB0PP2OMaa1yXC8CJ6y1p4DLwKfv8vi7\nfc8rHRfA76z5Xm00uG/m97eicVlr/96an7P/Ajx/l8dX6/W60/hQDz9jVadx+55pzL6zL6Exe6tx\ngcbsO6npmL1tk3LqtNWztXb09iyFtXYeb3eC0m539eyjwFesta619hVgnzGms4bP/6PAFWvtUA2f\ns8Ba+11guuTw2p+jLwN/Z4OHfgh40Vo7nf/f8otsPPBVLC5r7XestxMGwCt4+0XX1B1er83YzO9v\nVeLKjwEG+Hqlnm+z7jI++P4zViMatytPY7bG7C3FtUkas2swZm/npLzuWz0bY3qAx4Hvb3D6SWPM\n68aY/2aMOV6rmPBuv3zHGDOQ76ZXajOvazV9gjv/4vn1mrVba0fz79/Eu41Vyu/X7eeA/3aHc+/1\nPa+GXzTGnDPGfPEOMwN+vl4/DIxZa9++w/mavF4l48N2+BmrBI3b5dOYXb7t8PukMXvzds2YvZ2T\n8rpmjInh3W75J9bauZLTZ4Fua+1jwP8N/EkNQ3u/tfYM3i2of2yM+V9q+Nx3ZYxpAP428J82OO3n\na1ZgvQYodbVlkTHm1/BusX31DpfU+nv+H4D7gdPAKPB/Vfn5yvVT3H3Gpeqv193Gh3r8Gdst6nTc\n1pi9BfX4+6Qxu2y7Zszezkl5xVo9V5oxJoz3zfuqtXZdDZS1ds5am8y//6dA2BgTr3Zc+ecbzr8d\nx6sBfKLkks28rtXyE8BZa+1Y6Qk/XzNg7Pbt4Pzb8Q2u8eV1M8b8DN7imL9v79AxcRPf84qy1o5Z\na7PW2hzwH+/wfH69XiHg4xQvUitS7dfrDuND3f6MVZjG7TJpzL4ndfv7pDG7PLttzN7Ou6/UZavn\nfO3THwIXrbX/7g7XdODdinGNMU/g/eeoFn90okDAWjuff/+DQOnim2/h3cb6Y7zFCbNrbtFU2x3/\nN+zXa5Z3++foc/m339zgmm8Dv7nmtt8Hufsini3Lr4T/58CPWGsX7nDNZr7nlY6rc83PzMeACxtc\ntpnf32r4MeCStfbGRier/XrdZXyoy5+xKtC4XV5cGrPvTV3+PmnMvie7asze1s2DjDEfBn4Xb3ue\nL1pr/40x5rNAv7X2W8aYRuCP8GqApoFPWGvfrXJM7we+B5wHcvnDvwocAbDWfsEY84vAL+DdvloE\nfsla+5fVjCsf232srpAPAV/Lv2afWhObA3webzHCAt6WTf01iC0KXAPus9bO5o+tjasmr5kx5uvA\nU0AcGMNbOf0ngMX7Hg7hbX00bYzpAz5lrf0H+cf+HN73GuDfWGv/nyrH9WkgwuofulestZ8yxiTw\ntqv68J2+51WO6ym826Au3lZRz1hrR9fGlX/sut/fasZlrf1DY8yX8F6nL6y5tpav153Gh+/j889Y\nrWjcLisujdnvHYfG7K3H9RQas+8UV03H7G2dlIuIiIiI7ATbuaZcRERERGRHUFIuIiIiIuIzJeUi\nIiIiIj5TUi4iIiIi4jMl5SIiIiIiPlNSLiIiIiLiMyXlIiIiIiI+U1IuIiIiIuKzkN8BVJG6IonI\ndub4HUCNacwWke1sy2P2Tk7KGRkZ8TuEdeLxOJOTk36HsY7iKo/iKo/iKk8ikfA7BF9ozN48xVUe\nxVUexVWeSo3ZKl8REREREfGZknIREREREZ8pKRcRERER8ZmSchERERERnykpFxERERHxmZJyEZE6\n4ua0M6CIyHbhupUbs3f0logiAmOjK1y5tMJCKktzNMj9jzTQ3tngd1iyxvJSjvGbGcZH00zczPBz\n/7jL75BEROQOVlZWuH79OoODgwwODvIv/+W/rMjnVVIusoONja5wYWAJJwDhsMPSYo4LA0vQixJz\nH7muy+xMlvHRDGMjaW5NZ/0OSURE7sB1XWZmZgpJ+MjICLlcruLPU5Ok3BjzReAjwLi19kT+2G8D\nfwtYAa4AP2utvbXBYweBeSALZKy1fbWIWWQnuHJpBScAoZDXaCwUgkzG5cqlFSXlNZZeyTExlmF8\nJMP4zTTLS8W3PINBiLeHaOsM+xRhMY3bIrIbDA4OcvbsWebm5mhpaeHMmTP09PSQTqcZHh7m6tWr\nDA0NMTc3V/S4QCBAV1cX3d3dFYulVjPlXwI+D3xlzbEXgU9bazPGmN8CPg388h0e/wFrbf21cBKp\ncwupLOFwceffYNA7LtXlui7zsznGR9OMjaaZmcxSWnoYjQVo6wzRlghz4GCIYHDLXZor6Uto3BaR\nHWxwcJCXXnqJYDBIJBJhbm6O73znO7S0tDA1NUU2W/y3MhqN0tPTQ09PD4cPH6ahobKTWzVJyq21\n3zXG9JQc+86aD18BfrIWsYjsJs3RIEuLOUJrftOzWe+4VF4m7TI5nikk4ksLxVl4IAAH2rzZ8LbO\nELE99ft90LgtIjvdwMAAuVyOdDrNyspKIQlfWloCwHEcOjo6Col4PB7Hcao3eVIvNeU/B3zjDudc\n4DvGGBd41lr73J0+iTHmaeBpAGst8Xi84oFuVSgUUlxlUFzlKY3rzBNNvPLdCXAdgiGHbMYl4Lic\neeIg8XjUt7jqRSXimr21wo2hBW4Mpbg5vEhpmWE0FuJQdzOHuqN0HmoiHN4xm15tedzWmH3vFFd5\nFFd5dnJcc3NzvP3221y+fJnh4eF15wOBAMFgkI9+9KM88MADNDc3b+n5yuF7Um6M+TUgA3z1Dpe8\n31o7bIxpA140xlyy1n53owvzA//twd+dnKy/O6fxeBzFtXmKqzylcTVG4djphvzuK5nC7iuN0UUm\nJxd9i6te3Etc2azL1ESG8ZE046MZUsniLNxxoDUepL0zTHsiTKwlkJ9ZWWR2dnOveSKRKCumWqvU\nuK0x+94prvIorvLspLhyuRw3b94sLNLc6PGhUIiGhgYikQiu6xKLxUgkEiwsLLCwsPCez1GpMdvX\npNwY8zN4C4l+1Fq74UaP1trh/NtxY8wLwBPAhkm5iKzX3qktELdqIeXVho+Pppkcy1BSZkik0aGt\nI0xbIsTB9hDhhh0zG76Oxm0RqXcLCwsMDQ0V/i0vLxedb2ho4MiRI8RiMd555x3C4TChUIhMJkMu\nl+PMmTO+xO1bUm6M+XHgnwM/Yq3d8L8hxpgoELDWzuff/yDw2RqGKSK7UC7nMj2ZYXzUmxGfn1u/\n9VXrgWChNnxva7CqdYb1QuO2iNQj13UZHx8vzIaPjY2tu+bAgQOF2vCOjg6CQW9Nz5EjRzbcfcUP\ntdoS8evAU0DcGHMD+Azeqv0I3q1NgFestZ8yxiSAP7DWfhhoB17Inw8BX7PW/lktYhaR3WVp8fZs\neIaJsTSZdPH5cINDW4e3SPNgZ4hIZOfOhoPGbRGpb8vLy1y7do3BwUGGhobWlZmEQiEOHz5cSMT3\n7Nmz4ee5fb4eOJVsD1pn3JGREb9jWGcn1WnVguIqj+LaPDfn4ub2cPniBOOjGWZn1m8T2bIvSHvC\nS8Rb9wdxArWZDc/XJ+78qfdiGrPLoLjKo7jKU49xua5LLpfjtddeKzTwKc1h9+7dy9GjR+nu7qar\nq4tQqDYFIZUas31f6CkiUisryzkmbmYYy8+Ip1dmi86HQhDvCNPWEaI9EaaxaWfPhouI1LN0Ol3U\nzj6ZTBadDwQCHDp0iJ6eHrq7u2ltbfUp0spQUi4iO5bruszdyjKWrw2fmc56m/WtEWsJ0NYZpr0z\nxP54iEB9NfAREdlVbt26VUjCb9y4sa6dfSwWK8yGHz58mHC4ProgV4KSchHZUdJpl8mxNOMj3ox4\naTv7QBDibSHaO8M8fLyN5ZLZchERqZ1MJsPw8DBDQ0NcvXqV2dniMdlxHDo7Ozl69CinT58mEAjs\n2IX1SspFZFtzXZfkfK6wb/jUZAa3ZLOU5miA9kSIg51h4gdDBEPegL6nJcxyfZVNiojsePPz84XZ\n8OvXr5PJZIrONzc3093dTU9PD0eOHCESiQD1WeteSUrKRWTbyWRcpgrt7DMspkoa+ATgwMEQbZ3e\nIs3Ynp07syIiUu+y2Syjo6MMDQ0xODjI1NTUumva29vp6enh6NGjHDx4cFeO2UrKRWRbSCWz3r7h\no2kmxzPkSjZLaWxyCvuGH2wPEwrvvgFdRKReLCwsFGbDr127xsrKStH5SCRCd3d34V8t29nXKyXl\nIlKXslmX6Qmvgc/YaJrUfElNigP7Cw18wrTs02y4iIhfcrlcUQOf8fHxddfE4/GiBj6BgHa4WktJ\nuYjUjcWF4gY+2eIyQxoi+QY+iTAHO0I07OB29iIi9W5paYlr165x9epVhoaGWFpaKjofDoc5cuRI\noT48Fov5FOn2oKRcRHyTy7nMTGW9RHwkzdzs+nb2e1tXG/js27872tmLiNQj13WZnJwszIbfvHlz\nXQOf1tbWwmx4IpEotLOX96akXERqankpV6gNn7iZIZ0uHtDDYYeD+Xb2bZ0hIo2aDRcR8cvKykpR\nA59UKlV0PhgMcvjw4cJs+N69e32KdPtTUi4iVeW6LhNjS1y+uMT4aJpb0+vb2e/ZG6A94dWGtx4I\nEqhRO3sRESnmui4TExO8+uqrDA0NMTw8vK6BT0tLS2E2/NChQzVrZ7/T6VUUkYpbWfHa2d+uD19Z\nLm4GEQxBvN1r4NPWGaapWbPhIiJ+yWQy3LhxozAbPjc3V3Q+EAiQSCQKiXhra6tKCatASbmIbJnr\nuszP5hgbTTM+mmZmMktJmSHRPWva2R8MEVQ7exER38zOzjI4OMjQ0BDXr18nmy2+ixmNRunu7ubo\n0aMcOnSo0MBHqqdmSbkx5ovAR4Bxa+2J/LH9wDeAHmAQMNbamQ0e+9PAv8h/+BvW2i/XImYRubNM\n2mViLF2oD19aLGlnH4ADa9rZr6TVzn470ZgtsrNks1lGRkYKs+EzM8W/uo7j0NHRQU9PD6dPnyYU\nCmk2vMZqOVP+JeDzwFfWHPsV4M+ttZ8zxvxK/uNfXvug/B+BzwB9gAsMGGO+tdEfAhGpHtd1Sc3f\nng3PMDWxvp19U7PXwKc9EeZAW4hQvp19y94wO7gz8k71JTRmi2xryWSyMBt+7do10ul00fnGxsbC\nAs3u7m4aGxuBnd/Ovl7VLCm31n7XGNNTcvijwFP5978MvETJAA98CHjRWjsNYIx5Efhx4OvVilVE\nPNnsmnb2IxkWStvZO7A/386+vTNMrEUNfHYKjdki208ul+PmzZuF2fCNEuu2trZCEt7e3q4GPnXE\n75rydmvtaP79m0D7Btd0AdfXfHwjf0xEqmAhtdrOfmJsfTv7SGNxO/twg5LwXURjtkidWVxcZGho\nqDAjvry8XHS+oaGBI0eOFBLxaDTqU6TyXvxOygusta4xxn3vK+/MGPM08HT+8xGPxysSWyWFQiHF\nVQbFVZ57iSuXdRkbXeTG0AI3hha4NbOy7pqDHY0c6m7mUHczB+KRsmfDd9LrJR6N2f5SXOXZSXHd\nng2/fPkyly9fZnh4eF0Dn7a2Nh566CEefPBBjhw5UnYDn530em0nfiflY8aYTmvtqDGmExjf4Jph\nVm+XAhzCu2W6jrX2OeC5/IduPdZD1WudluIqz3aPa2mxuJ19prjMkHCDQ1tniLaOMAc7Q0QiASAH\nJJmaSlYtrlqr17gSiYTfIdyJxuw6objKs93jWl5e5tq1a4XZ8IWFhaLzoVCIQ4cOcfToUbq7u2lp\naSmcK13QWcm4aq1e46rUmO13Uv4t4KeBz+XffnODa74N/KYxpjX/8QeBT9cmPJGdwc25zExnC7Xh\nc7fWN/DZ2xr0EvHOMK37gzhq4CPracwWqQHXdZmeni7Uho+MjKybDd+7d29h3/Curi418NkBarkl\n4tfxZk/ixpgbeKvzPwdYY8zPA0OAyV/bB3zKWvsPrLXTxph/Dfwg/6k+e3sBkYjc2cryajv78ZsZ\n0ivFA3ooDAfbw4VEvLFJi31klcZskdpKp9Ncv369UB8+Pz9fdD4QCHDo0KHC3uH79u3zKVKpFqf0\nf147iDsyMuJ3DOvU660XxVWeeozLdV0c9nD5zUmvgc/UBu3sW7wGPm2JEPvjoZq1s6/H1wvqN678\nrdDddqtCY3YZFFd56jUux3F49dVXGRwcZHh4eF0Dn1gsVtTOvqGhoSZx1evrVa9xVWrM1r0OkW0s\nvVLcwGd5qbhBTyAIB9tD+d1SwjRHNRsuIuKXTCZT1MDn1q1bRecdx6Gzs5Oenh6OHj3K/v37tc3s\nLqKkXGQbcV2X5NxqA5/picy6dvbNsQDt+ZKUA21qZy8i4qf5+flCEn7jxo11DXyampoK2xV2d3er\nnf0upqRcpM5lMi6TY/na8NE0iwvr29nvPxiivTPEw8fbSGfmKvr8Y6MrXLm0wkIqS3M0yP2PNNDe\nWZtbqCKyMwwODnL27Fnm5uZoaWnhzJkz9PT0+B1WVWSz2aIGPlNTU+uuaW9vL7Szb2ho0Gy4AErK\nRepSaj7LWL4kZWo8Q66knX1jk0N7witJibeFCIW9AX3vvoaKtrMfG13hwsASTgDCYYelxRwXBpag\nFyXmIrIpg4ODvPTSSwSDQSKRCKlUipdeeomnnnpqxyTmCwsLDA0NcfXqVa5du8bKSnG/h0gkUpgJ\n7+7uprm5GajfGmnxh+lpJIAAACAASURBVJJykTqQzbpMT2QYG/HKUlLJ9e3sW+NB2vO14Xv21qad\n/ZVLKzgBCIW85wqFvJn7K5dWlJSLyKacPXuWYDBIOBwGKLw9e/bstk3Kc7kc4+Pjhdnw8fH1W/bH\n4/HCIs2Ojg61s5f3pKRcxCcLqVyhJGVyLEPJonsaIl4Dn/bOMAc7QoQbaj+gL6SyhMPFyX8w6B0X\nEdmMuTmvpC6ZTJLNZgkGgzQ1NRWObxdLS0uFBj6Dg4MsLS0VnQ+Hwxw+fLiQiMdiMZ8ile1KSblI\njeRyLjOT+QY+o2nmZ3Prrtm3P1hIxPfuD/peZ9gcDbK0mGNtT4ps1jsuIrIZ4XCYmZkZHMfBcRxy\nuRzJZJLW1tb3frCPXNdlcnKy0EVzdHR0XQOf1tbWQhKeSCTKbmcvspaScpEqWl5abeAzcTNDOl08\noIfDDgc7bm9ZGCLSWF+3N+9/pIELA0tkMi7BoJeQuznvuIjIZrmuW0jKXdddl9zWi5WVFa5fv16Y\nDU+lUkXng8Eghw4dKiTie/fu9SlS2YmUlItUkOu63Mq3sx8fzXBren2ZR8u+QGHf8NYDwU018PFr\nB5T2zgboRbuviMg9S6fT7Nmzh8XFxUL5SjQaXbc1oB9c12VmZqYwGz48PEyuZGV9S0tLYcvCQ4cO\nFWriRSpNSbnIFq2s5Ji4mWF8xGtnv7JcPAMUDBW3s29qLm823O8dUNo7lYSLyL1raWkhlUoVlauk\n02mi0agv8WQyGW7cuFGYDS+tbQ8EAiQSiUIirgY+UitKykXK5Lou05PLvP3mEuOjaaanslByJza2\nJ1AoSdl/cGsNfLQDiohsZ2fOnOHFF19kfn6eXC5HIBAgHA7zwz/8wzWLYWZmhnPnzjE4OMj169fX\ntbOPRqN0d3fT09PD4cOH1cBHfKGkXGQTMunidvZLi+vb2cfbVmvDo7H1i33utQRFO6CIyHa3tpb8\ndn15NWWz2aJ29jMzM+vi6ejoKMyGHzx4ULPh4jsl5SIbcF2X5HyuUBs+NZHBLdkspSla3M7+9kz2\nRrZSgqIdUERkOzt79iyO4xAIBHBdl0DA67NQ6X3Kk8kkQ0NDDA4Ocu3atXU1642NjYXZ8CNHjtDU\n1FSx5xapBF+TcmPMw8A31hy6D/h1a+3vrrnmKeCbwNX8oeettZ+tWZCya2QzLpMT+drw0QwLqZIG\nPgHYH1/bzn520zMrWylB0Q4oUk80bku5pqamWFpaIhAIEAgEyOVyLCwsbHkHllwux9jYWGE2fGJi\nYt01Bw8e5OjRozz22GNEIhE18JG65mtSbq19CzgNYIwJAsPACxtc+j1r7UdqGZvsDgvJ1Xb2k+MZ\nciUVIY1NDm0dYdoSIeLtYaYn01y5tMK1d0eINFGTEhTtgCL1ROO2lCuXyxW2QwQK75fWdW/G4uJi\n0Wx4aQOfhoYGDh8+zNGjR+nu7i4sJlU7e9kO6ql85UeBK9baIb8DkZ0rl3WZnsx4ifhImuR8SU2K\nA60HgrR1hmnvDNGyb7WBz9oSlEgkxNJipmYlKNoBReqUxm15T7dnp0tnxjcza+26LhMTE4XZ8Js3\nb667Zv/+/YV9wzs7O9XAR7atekrKPwF8/Q7nnjTGvA7/f3v3HhzZWd55/Nvdp3WXPLqNRprRjMbO\nDKyxYyO8zmZhd4dK4mAX4N0UvDHLboVkk4lZ/EcWqK1AtkLKtdnK1m5CXGEXrwkEnIKQJwEMxSW2\nK8sUBNYubNlgDPYEM9KMRhpdZ0YaXfty9o/Taqu7JY1a6u7TLf0+VSpJfU53P3O6+9Ez73nP+zAG\nfNDMXqxcWFLrlpfSTGSmpExNJEglc7fX1Uc4mGng033Io65+4z8U66egRCIRPC+iKSiy3ylvy3V1\ndnZy+fJlVldXs+uU19XVbdrRc2VlhfPnz2dHxBcXF3O2e55Hf39/dn54W1tbJf4ZImVXFUW5c64O\neDvwoQ02DwHHzOyac+4e4DHgxCaPcxo4DWBmdHV1lSninfM8T3EVYSdxpdM+UxPLjI4sMjqywOz0\nauHjxiNEItB6Qx2Dd7bTP9By3cddWbpGfb2XPfXqeR6xmM/KUvq6MXZ1wQ1tC7zw3BWuzSVobYtz\n6+sPcORYadfp3UuvYyVUa1y1oBR5Wzl752oprlOnTvG1r32NxsZG4vE4iUSCVCrFqVOn6Orqyo6G\nnz17lrNnz3L+/PmCBj4dHR2cPHmSEydOMDAwUHQDn1o6XtVAcYUjUg2tbp1z9wLvM7O7trHvMHCH\nmV1vcpg/NjZWivBKqlrntdV6XCvLaSYvrWtnv5r7vvbi0H0oTkNjhEsXEkS9SM6I9S1vaLjuaPd3\nv3ktMwUlKMiTySTJpE9DY5R//ubrF/WVUOuvY6VVa1x9fX0AVb0+WxnytnJ2EWotrqeffprnn3+e\n1dVV6urquPXWW+nt7c1OS5mfn8/ZPxqNcvjw4ey0lM1G1XcbV9gUV3GqNa5S5extj5Q75z4KfMbM\nnt/tk27gXWxyCtQ5dwiYMDPfOXcnEAVmyhCD1BDf97l6OcXkeJKJscSG7exb26Ic7Ava2Xd0Be3s\nv/vNa0S9SAlWQfFJJn1NQZGqVeacDcrbsk3Dw8P84Ac/IJkM5g6urq7yzDPPFOzX0tKSXTe8v7+f\nujrlVtlfipm+EgMed85NAX8JfNbMRncbgHOuGfgl4LfX3XY/gJk9DLwDeK9zLgksAfeZWfjD+1Jx\nidWggc/IKyvMTKUK1g2PxaCrZ62BT5ym5sK54aVaBWVlKU1DY1SroEg1K0vOBuVt2Z5kMsnY2BhP\nPPFEwSopa9ba2Q8MDNDZ2akGPrKvFTV9JbP81d3Au4G3Ak8DjxKsQXutLBHunE6FFqEa4/J9Hy/a\nxss/mgra2U+nyH+7RiJBUX3Ta+u56bUN121nv34KypqdTEGpxuMFiqtY1RpXqU6FKmfvXrW+R6o1\nrng8znPPPce5c+cYHR0taOAD5CyN+MADD1Qkrmo9XoqrONUaV8WnrwCYWQr4KvBV59zrgM8Bnwb+\nt3Pu88BHzOziboOS/SuZ9JmeSGY6aSZYWrxasE80BnV1Ebx4hFgsWAFlejLFyddd//OgVVBkP1HO\nlnJLpVJcunQpOzd8Zmb7s5Q0Ki6Sq6ii3DnXBrwT+HfAzwJfAP4jcB74APCNzO0iW5oYX802w6mv\nj9LWHmVpwWdmMkneRfc0NEXoyUxJeWFogbq6aE4y3+70E1AjHtlflLOlHBYXF7PLFY6MjLC6mrvC\nVX19PUePHs3ODzcz5ubmstvXztCvNfYRkUAxF3r+LfDLwLeAh4HHzGxl3fb3A4XDmiJ5xi+u8ML3\nlkmlfdIpWFpI5VyoGYlAR1fQwOc1N3eTTM9li/CfnvV21YQH1IhH9gflbCkV3/ez7exHRkaYmJgo\n2Kerq4tjx45x++2309jYmNMYKB6PE4lEcpoHRSKRopc1FNnrihkpfwp4wMwK22kBZpZ2zvWUJizZ\naxYX0tkpKRNjyYLtkUjQxOeWwUa6ezzidUFCb++sZ3r61VFxTT8R2TblbNmx5eVlzp8/ny3El5aW\ncrbH43H6+/uzo+Gtra3AxnN+E4kEra2tLC0tZZsHNTY2bjjfXGQ/23ZRbmb/cxv7LF5vH9k71k9B\nyZ8Gkk77zE6ngkJ8LMH8XLrg/rFY0MTHi0eIRn2SSejr37q41vQTke1RzpZi+L7PzMwM586dY2Rk\nhPHxcfIXgmhvb88W4X19fXje9kqItrY2FhYWctYaTyQSmr4ikqcqOnpK7ZkYX+WHzy4TiUI8HmF5\nKc0L31tiqj/J8mKwdGEybxAkXhe0s796JUU65WdHwwGSSTZcwnAjmn4iIrJ7q6urXLhwIXuR5sLC\nQs72WCzGkSNHsoX4gQMHdvQ8g4ODnDlzBiDbeC2VSjE4OLjbf4LInqKiXHbklZdWIeIDEVaWfZIJ\nn1QKzp3NveCn7UCMnr5g7fADHUEDn7WCXlNQREQqx/d9rly5ki3CL168WNDOvrW1lYGBAY4fP87h\nw4dLMu97YGCAU6dOMTQ0xNzcHG1tbQwODjIwMLDrxxbZS1SU73NrU1BWlq5R38h1p4KsrgTt7K/M\nBKukbLTO/aHD8Wwh3tBYOPqtKSgiIpWRTCYZHR1lZGSEc+fO5ayCAkE7+/UNfNrb27VUoUhIVJTv\nY+unoNTXeywvJfnhs8vwBrIFsu/7zF1JMTGeZHIsweXZFOTV4dEomXnh0NQS5Z++6frzBDUFRUSk\nPObm5rKj4aOjo9n29muam5s5duwYAwMD9Pf3U19fX9Z4hoeHOXPmDLFYjPr6ehYWFjhz5gynTp3S\naLnIOirK97FXXlolEgXPixCJRPC8oBHPP/5ohXQKJsaCJj4ry7lVeDQGrTdEWbzm48WDOeVrU1B+\n5p+UN7mLiEiuVCrF2NhYdu3w2dnZnO2RSIRDhw5l54Z3d3dXdDR8aGiIVCqVs/pKXV0dQ0NDKspF\n1lFRXuO2WgHlehYXUsTjwdqxyWSaleU0iYTPwjw8M527KENTc5SDvR4H++J0dXvEvMiunltERHZu\nfn6eF198keHhYc6fP1+wvGBDQ0N2NPzo0aM0NjaGFCnMzMywsrJCJBIMAKXTaZaWlgrms4vsdyrK\na9hGK6DkTz/ZTDLp43kRFhfSmVHu3OQYiUJnt8fBQ0Eh3tIaLRhZ0RQUEZHKSKfT2QY+w8PDTE1N\nFezT3d3N8ePHOXbsGD09PTkNfMKUTqfxfT/7tfa3REW5SC4V5TVs/fQTAM8Liu1XXlrdsFheuJZi\ncjyYkjI9mSSd15k+Egmmphw/WceJ1zbixXWxj4hIWJaWlnIa+CwvL+dsr6ury2lnX63rfq8V4+t/\nX/9dRAJVUZQ754aBeSAFJM3sjrztEeAh4B5gEXiPmQ1VOs5qszb9ZL1YLLgdIJ3ymZlOMpmZG35t\nPm9UIgItrVHSKfD9CI3NwZxwjX6LyFaUs8vD932mpqayo+GXLhU2Y+3o6GBgYIDbbruNpqYmYrFY\nCJEWZ23aCpAzUq5VXkRyVUVRnvFmM5veZNvdwInM188BH89839eammMsL6VZ31QtkfCJRiN87x8W\nmJpIkMrraF9XH8lOSenu8airD05vbtQaWURkC8rZJbCyspLTwGdxMfd6Hs/zOHLkSHZaSltbG1Bb\nOTsajeYU5hAU59UyvUakWlRTUb6Ve4FHzcwHnnLOHXDO9ZrZeNiBhemm19bxwjNLrCR90mmfZAKC\nKXo+C+tGxW9oz23go9EJESkz5exN+L7P7OxstggfHx8vmFvd1tbG8ePHGRgY4PDhw9tuZ1+tOjs7\nuXz5Mqurqzmrr7S3t4cdmkhVqZZPug884Zzzgf9jZo/kbT8MXFj3+2jmtn2Z4FeWgwY+k2MJVlf9\ngtFwLw7dh+L09MY52OtR36DRCBEpKeXsIiQSCUZHR7OF+Pz8fM72aDTK4cOHsw18Dhw4sKcGTwYH\nBzlz5gwtLS14nkcymSSVSjE4OBh2aCJVpVqK8jeZ2UXn3EHgSefcS2b2rWIfxDl3GjgNYGZ0dXWV\nOs5d8zyv6Lh832d6coXRkUVGRxaYnlwp2Ke9s47DR5voH2jm4KEGotHiEvpO4qoExVUcxVWcao2r\nBihnX8fs7Cxnz57l7NmzDA8PFzTwaWtr48SJE5w8eZIbb7yx6AY+1fre3Siurq4u2tra+M53vsPl\ny5dpb2/njW98IydPngw1rmqguIpTrXGVSlUU5WZ2MfN90jn3JeBOYH2Cvwj0r/v9SOa2/Md5BFgb\nsfGrcb7dducBJlbTTF1KMjGeYHI8yepK7lXqMQ+6ejwOHorT0xensWltNHyB2dmFssVVaYqrOIqr\nONUaV19fX9ghbEk5u1AymWRsbCw7Gn7lypWc7ZFIhN7e3uxoeGdnZ3Y0fH5+vmD0vFRxVdpmcXV0\ndPC2t70t57ZKxl9rxytsiqs4pcrZoRflzrlmIGpm85mf7wIezNvtK8ADzrnPE1wsdHWvzU30fZ/5\nq2kmxxNMjCe4PJ0if7Wo5tZodkpKR7dHLLZ3Tm+KSG1Qzn7V/Px8tovmhQsXChr4NDY25jTwaWho\nCClSEakFoRflQA/wJeccBPF8zsz+zjl3P4CZPQx8nWBprZ8QLK/16yHFWlLJhM/0ZJKJsQST4wmW\nl/La2Ueh86CXLcSbW6t/6SsR2fP2bc5Op9OMj49n1w3faMSup6cnW4j39PTsqbnhIlJekT28eL8/\nNjYWdgw5fN+nLn4DL704yeR4ktmpJPkNzRqbIhzsDaakdB70so2Byq1aTwkpruIoruJUa1yZU6H7\nrZqrupwNQbv65557LtvOfmUl95qe+vr6nAY+TU1NFYmrWt+7iqs4iqs41RpXqXJ2NYyU72mplM/M\nZDIzLSXJ4rWrOdsjEejo9jjYG4yIt7QVtrMXEZHK8H0/285+ZGSEiYmJgn06Ozuzc8N7e3u13raI\nlISK8jJYXAjmhk+OJ5iaKGxnX98QjIYf7PXo7okTr1MRLiISluXl5Zx29ktLSznb4/E4/f392dHw\n1tbWkCIVkb1MRXkJpNM+s9NJJseD+eHX5tIF+7R3xjjYG+fkzV34zGs0XEQkJL7vMzMzk9PAJ38q\nZ3t7O8eOHeO2226jubm55hv4iEj1U5bZoeWltdHwJFMTCZK5F90Tr8u0s++N093rUZ9tZ9/A9PS1\nECIWEdm/VldXuXDhQna1lGvXcvNwLBbjyJEj2dHwAwcOANU7h1VE9h4V5dvkp30uz6aCueFjSeau\npAr2uaE9xsHeoBBv74gRKbKBj4iIlIbv+1y5ciU7Gn7x4sWCdvatra3ZueFHjhwhHo+HFK2IiIry\nLa2uvNrOfvJSksRq7ulNzwva2a8V4g2NuthHRCQsyWSS0dHR7Gj41au5F9ZHo1H6+vqySxZ2dHRo\nKqGIVA0V5ev4vs/Vyykmx4PVUi7PFI6Gt7Sta+DT5RFVAx8RkdDMzc1lR8NHR0cL2tk3NTVlp6Qc\nPXq06Hb2IiKVsu+L8sSqz9REIluIryznNfCJQXePl10tpalZDXxERMKSSqUYGxvLjobPzs7mbI9E\nIhw6dChbiHd3d2s0XERqwr4ryn3f59pcmonMRZqzU8mCdvZNzVF6+oJCvLPbI1ahBj4iIlJoYWEh\nOxp+/vz5gnb2DQ0NOe3sGxsbQ4pURGTn9kVRnkwGDXzW2tk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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -660,7 +814,7 @@ " - histogramas\n", " - densidade\n", " - boxplot\n", - " - dispersão" + " - dispersão " ] }, { @@ -678,9 +832,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { - "collapsed": true, "slideshow": { "slide_type": "fragment" } @@ -725,9 +878,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -736,18 +888,18 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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H59cdQs+wLgrrYZR1Ucz2euiV+AcH57NgwTq1Xr8XdLMeOk0ELgceAJ4JXFiVPRu4ZIxz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\nNZiJgCRJDWYiIElSg/1/UQJFzNGD3sYAAAAASUVORK5CYII=\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -761,9 +913,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 47, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -771,9 +922,9 @@ "outputs": [ { "data": { - "image/png": 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lr/GrX13D6aefCcDEiZOZMOE2xo4dr7MCIiISUn3GCJwDfAicDnhq6bcYuDdI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\ntTITWF7Su4H1mXt8cDQwvbSozMxsUPn4oLVyKXAd8BrwBHC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rr71Gw4YNadWqFatWrSpRbtu2baNXr140aNCATp06sWHDBtu2w4cP06dPH2JiYnjooYc4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\nTRBQF4gH+gEfKqUqu2nfPic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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -781,14 +932,13 @@ } ], "source": [ - "gdp.loc[BRICS,['1990','1995','2000','2005','2010','2014']].plot.bar();" + "gdp.loc[BRICS,['1990','1995','2000','2005','2010','2014']].T.plot.bar();" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 30, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -796,19 +946,36 @@ "outputs": [ { "data": { + "image/png": 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kSZKKUtMc5JTSLcAt/V47K/d1Bny6+pAkSZLGLG81LUmSJOXYIEuSJEk5NsiS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\nrud6PV4zeb0JxyDnY4rfB1wC/CHbpJsi4sSI2C9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vzmtKzmu56sprXrvvM+s9yCsbmcPv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\nZmZmZmYF3oNsZmZmZlbgDrKZmZmZWYE7yGZmZmZmBe4gm5mZmZkVuIN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"text/plain": [ - "" + "" ] }, - "execution_count": 10, "metadata": {}, - "output_type": "execute_result" - }, + "output_type": "display_data" + } + ], + "source": [ + "gdp.loc[BRICS,['1990','1995','2000','2005','2010','2014']].plot.bar(subplots=True,\n", + " layout=(2,3),\n", + " sharey=True,\n", + " figsize=(12,7));" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ { "data": { - "image/png": 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2Jr6k8+Z84EnAgYOAVYglkQ8EzgI2SS+0hl0AvJs4kdmHSPoHArslj308vdCa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\nFVL+n94OAAAAAElFTkSuQmCC\n", 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H/IZ0Q3KPiFheIp4mhxU+f0uStgdexbplbkuW6lgVEQ9Kaeh8blAVa6XmUXq7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\n8ZPC8dUtoUO6NF4FPLtpW5E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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -821,7 +988,7 @@ " 'Europe & Central Asia','Euro area',\n", " 'European Union','Latin America & Caribbean','Sub-Saharan Africa'\n", " ]\n", - "expvida.loc[regions].mean(axis=1).plot.bar(yerr=expvida.loc[regions].std(axis=1))" + "expvida.loc[regions].mean(axis=1).plot.bar(yerr=expvida.loc[regions].std(axis=1));" ] }, { @@ -839,7 +1006,6 @@ "cell_type": "code", "execution_count": 34, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -847,9 +1013,9 @@ "outputs": [ { "data": { - "image/png": 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yxC8AAMkoLfQAANDeZepqI+pqW10v6dI1sjt37PtaNpuX+YD3T/wCwN7U1caO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\nxzHHHGO/O5h169bFYYcd1uI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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -864,9 +1030,8 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 52, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -874,9 +1039,9 @@ "outputs": [ { "data": { - "image/png": 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ldruDXvdy0VhzR9gFAACmVl5ebkjdhIQElZWVGVIbwcMyBgAAAJgWYRcAAACm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\nYw6nyWlq7tx5unbtWpSVlWHZsmW4efOmwzbMeGo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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -885,7 +1050,7 @@ ], "source": [ "expvida[['1960','1980','2000','2014']].plot.hist(stacked=False,\n", - " bins=20, alpha=0.6);" + " bins=20, alpha=0.4);" ] }, { @@ -901,16 +1066,14 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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ShBCVpLvz4CqTtva6EecVRaFtlgcAf+8A8VhyRBshjhRTPqKSCT4+D3xQ07RNwCZVVX8A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\nG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mCUrKHHR2pCbMXQzkOVpbW8/rPAdAT08Pn/rUp/iXf/mXEbPShBC2tuDNJdXjUBTFlnBX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\nv9GKAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -918,14 +1081,13 @@ } ], "source": [ - "expvida[['1960','1980','2000','2014']].plot.density(alpha=.6);" + "expvida[['1960','1980','2000','2014']].plot.density(alpha=.8);" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 38, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -933,9 +1095,9 @@ "outputs": [ { "data": { - "image/png": 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otLRUWVlZstbGciroJV6vlykiCYqxSVyJNjatgQaFMzIvveMleDIylJZA59VVnxyfeH1+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\naGgoPXr04M477yQ6OrrSeW+++Sbp6emkpaWRn5/Pv/zLv3Drrbf+YC1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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -959,16 +1121,14 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 56, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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yj9/MTgD+ExgDUtHtD939rWa2BDhuwmPHufud1QtZREREylXOUP+BwO3AGYTk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\nJ0mqmCP+ZhtF0acPQGZ+BwwHjgCTLfqS1H4s/M3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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -976,7 +1136,7 @@ } ], "source": [ - "expvida.loc[BRICS].T.plot.box(rot=90,sym='*');" + "expvida.loc[BRICS].T.plot.box(rot=90,sym='*',showmeans=True,meanline=True);" ] }, { @@ -1014,9 +1174,8 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 15, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1041,9 +1200,8 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 16, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -1051,9 +1209,9 @@ "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1066,21 +1224,21 @@ }, { "cell_type": "code", - "execution_count": 49, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'v' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquantile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m.25\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m.5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m.75\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mNameError\u001b[0m: name 'v' is not defined" - ] + "data": { + "text/plain": [ + "0.25 4.75\n", + "0.50 7.50\n", + "0.75 15.00\n", + "dtype: float64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -1100,26 +1258,14 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "data": { + "image/png": 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"text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1128,15 +1274,14 @@ ], "source": [ "df = pd.melt(gdp.reset_index(),id_vars='Country Name'); df.set_index(['Country Name'], inplace=True); \n", - "df.variable = df.variable.astype(int)\n", - "df.loc['Brazil'].plot.scatter(x='variable',y='value')" + "df.variable = df.variable.astype('int64')\n", + "df.loc['Brazil'].plot.scatter(x='variable',y='value');" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -1144,9 +1289,9 @@ "outputs": [ { "data": { - "image/png": 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LB4wpLbIYUwK1be6PMX4lhPAx4P0hhOsp19zfWHk/38S5vil5i9l402GxxnnX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\nwHLgUGAP4BRgPLARuBM4zd3/kPZdAfwYeCfwIuC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bgf2atvct9kmSpDb5EBhp8MqSXF8FnBERl1OfyPjzzNyhJESSJM3OEhBp8Pq1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\nQPFn5jXLFCvUO8tDiz9dTaw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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1175,9 +1320,8 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1185,9 +1329,9 @@ "outputs": [ { "data": { - "image/png": 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6gKqezGh/znuuX7x4AU9PL2sQABAcHIKnpxcXL57H3d0DINPn7u4eGI3Z94sQ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\nTkSuQmCC\n", + "image/png": 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vtufsNyqry8BkqSE6cHSH7+2t8Wdkr2sZ2etaIsLbfqpRq9TMGfBXtwr4jZw9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\nae8wlkQf+/kgFv65QCk0z0f3fTTPi5Y+uuuOi7wWBOPRpab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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1200,9 +1344,8 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -1210,9 +1353,9 @@ "outputs": [ { "data": { - "image/png": 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XlZUvRefmZmlvd+jq6lgqIAbh9aml5QB797YQjd6f0Wd5cCmZFhGR++LKlUtL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Hnfl9wnk2lJkqRzlJbupq2tBYDCwrlDYp90F7u6HiynoI7cL32+uMDTgLMf1Mi9yuVoJMldnspN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HohGSlRVUVCZJVlaQrEySqEgQCoWwQhaWZQ3PLYtINExtXQWZrINphQhH/Fo3h+qzIVMo0JVO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\nZmZmZmZNcjBtZmZmZmZm1qT/B+N6AA46ByX5AAAAAElFTkSuQmCC\n", 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3M05lY4JCewwMCeLE/BnZK0R7vk6k5+tY4ycBcOt3ktv7LyivfxOV5v2gL384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AwM4HQ66enpIRAIUFBQwLx58zAYxreLEYCx2YN+IIj3xCwQXXQEILHuXvTuVgZOu08U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\n0BFCCCGEEEJIjKKAjhBCCCGEEEJi1P8Hsjr1CBQx1HAAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1220,7 +1363,7 @@ } ], "source": [ - "fig, ax = plt.subplots(1,2,figsize=(12,5))\n", + "fig, ax = plt.subplots(1,2,figsize=(15,5))\n", "gdp.loc[BRICS].T.plot.line(ax=ax[0],legend=False,colormap='Set1')\n", "expvida.loc[BRICS].T.plot.line(ax=ax[1],legend=False,colormap='Set1')\n", "handles, labels = ax[0].get_legend_handles_labels()\n", @@ -1229,9 +1372,8 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -1240,30 +1382,34 @@ { "data": { "text/plain": [ - "['seaborn-white',\n", - " 'ggplot',\n", - " 'seaborn-dark-palette',\n", - " 'seaborn-talk',\n", + "['seaborn-dark',\n", " 'seaborn-darkgrid',\n", - " 'seaborn-dark',\n", - " 'seaborn-pastel',\n", " 'seaborn-ticks',\n", + " 'fivethirtyeight',\n", " 'seaborn-whitegrid',\n", + " 'classic',\n", + " '_classic_test',\n", + " 'fast',\n", + " 'seaborn-talk',\n", + " 'seaborn-dark-palette',\n", + " 'seaborn-bright',\n", + " 'seaborn-pastel',\n", + " 'grayscale',\n", " 'seaborn-notebook',\n", + " 'ggplot',\n", + " 'seaborn-colorblind',\n", " 'seaborn-muted',\n", - " 'fivethirtyeight',\n", - " 'dark_background',\n", - " 'grayscale',\n", - " 'seaborn-bright',\n", + " 'seaborn',\n", + " 'Solarize_Light2',\n", + " 'seaborn-paper',\n", " 'bmh',\n", - " 'seaborn-colorblind',\n", - " 'seaborn-deep',\n", - " 'classic',\n", + " 'seaborn-white',\n", + " 'dark_background',\n", " 'seaborn-poster',\n", - " 'seaborn-paper']" + " 'seaborn-deep']" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1274,9 +1420,8 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 23, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "slide" } @@ -1288,9 +1433,8 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 24, "metadata": { - "collapsed": false, "slideshow": { "slide_type": "fragment" } @@ -1298,9 +1442,9 @@ "outputs": [ { "data": { - "image/png": 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Pn2f58uXo6Ojkuh95BF/KGBsbY2try7///put+umPo/Ny9FBqaqrW8sz+w00fMzsMDQ21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\nkqPK/wf/yzOxTQSvbQAAAABJRU5ErkJggg==\n", 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Ki4tT93y8qGLFiqhUKuLj4zWSjJzutz4fgRaiOIuKimLUqFF8//33lC9fXt/h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\nBzQslkSs1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JiidPe5YD3m++q3BWvzxlwwCQhifWMvNmn4zU0afnNzI0C0N/EyWDu+962p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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1314,9 +1458,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -1338,7 +1480,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula10-datavis-parte02.ipynb b/aula10-datavis-parte02.ipynb index 5593f79..72ba22f 100644 --- a/aula10-datavis-parte02.ipynb +++ b/aula10-datavis-parte02.ipynb @@ -33,44 +33,156 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING: param.Version now supports PEP440 and a new tag based workflow. See param/version.py for more details\n" + ] }, { "data": { "application/javascript": [ "\n", - "(function(global) {\n", + "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", - " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", - " window._bokeh_onload_callbacks = [];\n", - " window._bokeh_is_loading = undefined;\n", + " if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id !== undefined) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var element_id = msg.content.text.trim();\n", + " Bokeh.index[element_id].model.document.clear();\n", + " delete Bokeh.index[element_id];\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", " }\n", "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", "\n", " \n", - " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", - " window._bokeh_timeout = Date.now() + 5000;\n", - " window._bokeh_failed_load = false;\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", @@ -90,23 +202,33 @@ " \"\"}};\n", "\n", " function display_loaded() {\n", - " if (window.Bokeh !== undefined) {\n", - " var el = document.getElementById(\"d8e42bad-4230-4c11-b19f-916fdcf2ee6c\");\n", - " el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n", - " } else if (Date.now() < window._bokeh_timeout) {\n", + " var el = document.getElementById(null);\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", + "\n", " function run_callbacks() {\n", - " window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", - " delete window._bokeh_onload_callbacks\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", + " }\n", + " finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", " console.info(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(js_urls, callback) {\n", - " window._bokeh_onload_callbacks.push(callback);\n", - " if (window._bokeh_is_loading > 0) {\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", @@ -115,15 +237,15 @@ " return null;\n", " }\n", " console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " window._bokeh_is_loading = js_urls.length;\n", + " root._bokeh_is_loading = js_urls.length;\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", " var s = document.createElement('script');\n", " s.src = url;\n", " s.async = false;\n", " s.onreadystatechange = s.onload = function() {\n", - " window._bokeh_is_loading--;\n", - " if (window._bokeh_is_loading === 0) {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", " run_callbacks()\n", " }\n", @@ -134,55 +256,316 @@ " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", - " };var element = document.getElementById(\"d8e42bad-4230-4c11-b19f-916fdcf2ee6c\");\n", - " if (element == null) {\n", - " console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'd8e42bad-4230-4c11-b19f-916fdcf2ee6c' but no matching script tag was found. \")\n", - " return false;\n", - " }\n", + " };\n", "\n", - " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.js\"];\n", + " var js_urls = [];\n", "\n", " var inline_js = [\n", " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", + " /* BEGIN bokeh.min.js */\n", + " !function(t,e){t.Bokeh=function(t,e,i){var n={},r=function(i){var o=null!=e[i]?e[i]:i;if(!n[o]){if(!t[o]){var s=new Error(\"Cannot find module '\"+i+\"'\");throw s.code=\"MODULE_NOT_FOUND\",s}var a=n[o]={exports:{}};t[o].call(a.exports,r,a,a.exports)}return n[o].exports},o=r(52);return o.require=r,o.register_plugin=function(i,n,s){for(var a in i)t[a]=i[a];for(var a in n)e[a]=n[a];var l=r(s);for(var a in l)o[a]=l[a];return l},o}([function(t,e,i){var n=t(142),r=t(32);i.overrides={};var o=r.clone(n);i.Models=function(t){var e=i.overrides[t]||o[t];if(null==e)throw new Error(\"Model '\"+t+\"' does not exist. This could be due to a widget\\n or a custom model not being registered before first usage.\");return e},i.Models.register=function(t,e){i.overrides[t]=e},i.Models.unregister=function(t){delete i.overrides[t]},i.Models.register_models=function(t,e,i){if(void 0===e&&(e=!1),null!=t)for(var n in t){var r=t[n];e||!o.hasOwnProperty(n)?o[n]=r:null!=i?i(n):console.warn(\"Model '\"+n+\"' was already registered\")}},i.register_models=i.Models.register_models,i.Models.registered_names=function(){return Object.keys(o)},i.index={}},function(t,e,i){var n=t(317),r=t(14),o=t(50),s=t(260),a=t(261),l=t(2);i.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",i.DEFAULT_SESSION_ID=\"default\";var h=0,c=function(){function t(t,e,n,o,s){void 0===t&&(t=i.DEFAULT_SERVER_WEBSOCKET_URL),void 0===e&&(e=i.DEFAULT_SESSION_ID),void 0===n&&(n=null),void 0===o&&(o=null),void 0===s&&(s=null),this.url=t,this.id=e,this.args_string=n,this._on_have_session_hook=o,this._on_closed_permanently_hook=s,this._number=h++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_ack=null,this._pending_replies={},this._receiver=new a.Receiver,r.logger.debug(\"Creating websocket \"+this._number+\" to '\"+this.url+\"' session '\"+this.id+\"'\")}return t.prototype.connect=function(){var t=this;if(this.closed_permanently)return n.Promise.reject(new Error(\"Cannot connect() a closed ClientConnection\"));if(null!=this.socket)return n.Promise.reject(new Error(\"Already connected\"));this._pending_replies={},this._current_handler=null;try{var e=this.url+\"?bokeh-protocol-version=1.0&bokeh-session-id=\"+this.id;return null!=this.args_string&&this.args_string.length>0&&(e+=\"&\"+this.args_string),this.socket=new WebSocket(e),new n.Promise(function(e,i){t.socket.binaryType=\"arraybuffer\",t.socket.onopen=function(){return 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r(t){0===p.size&&a.defer(o),p.add(t)}function o(){p.forEach(function(t){l.removeBy(t,function(t){return null==t.signal})}),p.clear()}var s=t(379),a=t(25),l=t(21),h=function(){function t(t,e){this.sender=t,this.name=e}return t.prototype.connect=function(t,e){void 0===e&&(e=null),u.has(this.sender)||u.set(this.sender,[]);var i=u.get(this.sender);if(null!=n(i,this,t,e))return!1;var r=e||t;_.has(r)||_.set(r,[]);var o=_.get(r),s={signal:this,slot:t,context:e};return i.push(s),o.push(s),!0},t.prototype.disconnect=function(t,e){void 0===e&&(e=null);var i=u.get(this.sender);if(null==i||0===i.length)return!1;var o=n(i,this,t,e);if(null==o)return!1;var s=e||t,a=_.get(s);return o.signal=null,r(i),r(a),!0},t.prototype.emit=function(t){for(var e=u.get(this.sender)||[],i=0,n=e;i0;var p=function(){function t(t,e,i,n){this.plot_view=t,this.toolbar=e,this.hit_area=i,this.plot=n,this.pan_start=new o.Signal(this,\"pan:start\"),this.pan=new o.Signal(this,\"pan\"),this.pan_end=new o.Signal(this,\"pan:end\"),this.pinch_start=new o.Signal(this,\"pinch:start\"),this.pinch=new o.Signal(this,\"pinch\"),this.pinch_end=new o.Signal(this,\"pinch:end\"),this.rotate_start=new o.Signal(this,\"rotate:start\"),this.rotate=new o.Signal(this,\"rotate\"),this.rotate_end=new o.Signal(this,\"rotate:end\"),this.tap=new o.Signal(this,\"tap\"),this.doubletap=new o.Signal(this,\"doubletap\"),this.press=new o.Signal(this,\"press\"),this.move_enter=new o.Signal(this,\"move:enter\"),this.move=new o.Signal(this,\"move\"),this.move_exit=new o.Signal(this,\"move:exit\"),this.scroll=new o.Signal(this,\"scroll\"),this.keydown=new o.Signal(this,\"keydown\"),this.keyup=new o.Signal(this,\"keyup\"),this.hammer=new r(this.hit_area),this._configure_hammerjs()}return t.prototype._configure_hammerjs=function(){var t=this;this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",function(e){return t._doubletap(e)}),this.hammer.on(\"tap\",function(e){return t._tap(e)}),this.hammer.on(\"press\",function(e){return t._press(e)}),this.hammer.get(\"pan\").set({direction:r.DIRECTION_ALL}),this.hammer.on(\"panstart\",function(e){return t._pan_start(e)}),this.hammer.on(\"pan\",function(e){return t._pan(e)}),this.hammer.on(\"panend\",function(e){return t._pan_end(e)}),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",function(e){return t._pinch_start(e)}),this.hammer.on(\"pinch\",function(e){return t._pinch(e)}),this.hammer.on(\"pinchend\",function(e){return t._pinch_end(e)}),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",function(e){return t._rotate_start(e)}),this.hammer.on(\"rotate\",function(e){return t._rotate(e)}),this.hammer.on(\"rotateend\",function(e){return t._rotate_end(e)}),this.hit_area.addEventListener(\"mousemove\",function(e){return t._mouse_move(e)}),this.hit_area.addEventListener(\"mouseenter\",function(e){return t._mouse_enter(e)}),this.hit_area.addEventListener(\"mouseleave\",function(e){return t._mouse_exit(e)}),this.hit_area.addEventListener(\"wheel\",function(e){return t._mouse_wheel(e)}),document.addEventListener(\"keydown\",function(e){return t._key_down(e)}),document.addEventListener(\"keyup\",function(e){return t._key_up(e)})},t.prototype.register_tool=function(t){var e=this,i=t.model.event_type;null!=i&&(u.isString(i)?this._register_tool(t,i):i.forEach(function(i,n){return e._register_tool(t,i,n<1)}))},t.prototype._register_tool=function(t,e,n){void 0===n&&(n=!0);var r=t,o=r.model.id,a=function(t){return function(e){e.id==o&&t(e.e)}},l=function(t){return function(e){t(e.e)}};switch(e){case\"pan\":null!=r._pan_start&&r.connect(this.pan_start,a(r._pan_start.bind(r))),null!=r._pan&&r.connect(this.pan,a(r._pan.bind(r))),null!=r._pan_end&&r.connect(this.pan_end,a(r._pan_end.bind(r)));break;case\"pinch\":null!=r._pinch_start&&r.connect(this.pinch_start,a(r._pinch_start.bind(r))),null!=r._pinch&&r.connect(this.pinch,a(r._pinch.bind(r))),null!=r._pinch_end&&r.connect(this.pinch_end,a(r._pinch_end.bind(r)));break;case\"rotate\":null!=r._rotate_start&&r.connect(this.rotate_start,a(r._rotate_start.bind(r))),null!=r._rotate&&r.connect(this.rotate,a(r._rotate.bind(r))),null!=r._rotate_end&&r.connect(this.rotate_end,a(r._rotate_end.bind(r)));break;case\"move\":null!=r._move_enter&&r.connect(this.move_enter,a(r._move_enter.bind(r))),null!=r._move&&r.connect(this.move,a(r._move.bind(r))),null!=r._move_exit&&r.connect(this.move_exit,a(r._move_exit.bind(r)));break;case\"tap\":null!=r._tap&&r.connect(this.tap,a(r._tap.bind(r)));break;case\"press\":null!=r._press&&r.connect(this.press,a(r._press.bind(r)));break;case\"scroll\":null!=r._scroll&&r.connect(this.scroll,a(r._scroll.bind(r)));break;default:throw new Error(\"unsupported event_type: \"+e)}n&&(null!=r._doubletap&&r.connect(this.doubletap,l(r._doubletap.bind(r))),null!=r._keydown&&r.connect(this.keydown,l(r._keydown.bind(r))),null!=r._keyup&&r.connect(this.keyup,l(r._keyup.bind(r))),i.is_mobile&&null!=r._scroll&&\"pinch\"==e&&(s.logger.debug(\"Registering scroll on touch screen\"),r.connect(this.scroll,a(r._scroll.bind(r)))))},t.prototype._hit_test_renderers=function(t,e){for(var i=this.plot_view.get_renderer_views(),n=0,r=h.reversed(i);n0,\"'step' must be a positive number\"),null==e&&(e=t,t=0);for(var n=Math.max,r=Math.ceil,o=Math.abs,s=t<=e?i:-i,a=n(r(o(e-t)/i),0),l=Array(a),c=0;c0?0:n-1;r>=0&&r=0?e:t.length+e]},i.zip=function(t,e){for(var i=Math.min(t.length,e.length),n=new Array(i),r=0;rn||void 0===i)return 1;if(io&&(e=o),null==i||i>o-e?i=o-e:i<0&&(i=0);for(var s=o-i+n.length,a=new t.constructor(s),l=0;li&&(i=e);return i},i.maxBy=function(t,e){if(0==t.length)throw new Error(\"maxBy() called with an empty array\");for(var i=t[0],n=e(i),r=1,o=t.length;rn&&(i=s,n=a)}return i},i.sum=function(t){for(var e=0,i=0,n=t.length;i=0&&c>=0))throw new Error(\"invalid bbox {x: \"+a+\", y: \"+l+\", width: \"+h+\", height: \"+c+\"}\");this.x0=a,this.y0=l,this.x1=a+h,this.y1=l+c}}return Object.defineProperty(t.prototype,\"minX\",{get:function(){return this.x0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"minY\",{get:function(){return this.y0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"maxX\",{get:function(){return this.x1},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"maxY\",{get:function(){return this.y1},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"left\",{get:function(){return this.x0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"top\",{get:function(){return this.y0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"right\",{get:function(){return this.x1},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"bottom\",{get:function(){return this.y1},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"p0\",{get:function(){return[this.x0,this.y0]},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"p1\",{get:function(){return[this.x1,this.y1]},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"x\",{get:function(){return this.x0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"y\",{get:function(){return this.y0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"width\",{get:function(){return this.x1-this.x0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"height\",{get:function(){return this.y1-this.y0},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"rect\",{get:function(){return{x:this.x,y:this.y,width:this.width,height:this.height}},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"h_range\",{get:function(){return{start:this.x0,end:this.x1}},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"v_range\",{get:function(){return{start:this.y0,end:this.y1}},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"ranges\",{get:function(){return[this.h_range,this.v_range]},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,\"aspect\",{get:function(){return this.width/this.height},enumerable:!0,configurable:!0}),t.prototype.contains=function(t,e){return t>=this.x0&&t<=this.x1&&e>=this.y0&&e<=this.y1},t.prototype.clip=function(t,e){return tthis.x1&&(t=this.x1),ethis.y1&&(e=this.y1),[t,e]},t.prototype.union=function(e){return new t({x0:n(this.x0,e.x0),y0:n(this.y0,e.y0),x1:r(this.x1,e.x1),y1:r(this.y1,e.y1)})},t}();i.BBox=o},function(t,e,i){i.delay=function(t,e){return setTimeout(t,e)};var n=\"function\"==typeof requestAnimationFrame?requestAnimationFrame:setImmediate;i.defer=function(t){return n(t)},i.throttle=function(t,e,i){void 0===i&&(i={});var n,r,o,s=null,a=0,l=function(){a=!1===i.leading?0:Date.now(),s=null,o=t.apply(n,r),s||(n=r=null)};return function(){var h=Date.now();a||!1!==i.leading||(a=h);var c=e-(h-a);return n=this,r=arguments,c<=0||c>e?(s&&(clearTimeout(s),s=null),a=h,o=t.apply(n,r),s||(n=r=null)):s||!1===i.trailing||(s=setTimeout(l,c)),o}},i.once=function(t){var e,i=!1;return function(){return i||(i=!0,e=t()),e}}},function(t,e,i){i.fixup_ctx=function(t){(function(t){t.setLineDash||(t.setLineDash=function(e){t.mozDash=e,t.webkitLineDash=e});t.getLineDash||(t.getLineDash=function(){return t.mozDash})})(t),function(t){t.setLineDashOffset=function(e){t.lineDashOffset=e,t.mozDashOffset=e,t.webkitLineDashOffset=e},t.getLineDashOffset=function(){return t.mozDashOffset}}(t),function(t){t.setImageSmoothingEnabled=function(e){t.imageSmoothingEnabled=e,t.mozImageSmoothingEnabled=e,t.oImageSmoothingEnabled=e,t.webkitImageSmoothingEnabled=e,t.msImageSmoothingEnabled=e},t.getImageSmoothingEnabled=function(){var e=t.imageSmoothingEnabled;return null==e||e}}(t),function(t){t.measureText&&null==t.html5MeasureText&&(t.html5MeasureText=t.measureText,t.measureText=function(e){var i=t.html5MeasureText(e);return i.ascent=1.6*t.html5MeasureText(\"m\").width,i})}(t),function(t){t.ellipse||(t.ellipse=function(e,i,n,r,o,s,a,l){void 0===l&&(l=!1);t.translate(e,i),t.rotate(o);var 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u=\"height\"==i?[1,0]:[0,1],_=u[0],p=u[1],d=[t,c],f=[h,c];this._lower_sx=d[_],this._lower_sy=d[p],this._upper_sx=f[_],this._upper_sy=f[p]},e.prototype.render=function(){if(this.model.visible){this._map_data();var t=this.plot_view.canvas_view.ctx;if(this.visuals.line.doit)for(var e=0,i=this._lower_sx.length;eu&&(u=f)}return u>0&&(u+=n),u},e}(r.GuideRendererView);i.AxisView=_;var p=function(t){function e(e){return t.call(this,e)||this}return 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s.SidePanel({side:t}),this.panel.attach_document(this.document)},Object.defineProperty(e.prototype,\"normals\",{get:function(){return this.panel.normals},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"dimension\",{get:function(){return this.panel.dimension},enumerable:!0,configurable:!0}),e.prototype.compute_labels=function(t){for(var e=this.formatter.doFormat(t,this),i=0;ih(a-_)?(n=u(c(o,s),a),r=c(u(o,s),_)):(n=c(o,s),r=u(o,s)),[n,r]}throw new Error(\"user bounds '\"+e+\"' not understood\")},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"rule_coords\",{get:function(){var t=this.dimension,e=(t+1)%2,i=this.ranges[0],n=this.computed_bounds,r=n[0],o=n[1],s=new Array(2),a=new Array(2),l=[s,a];return l[t][0]=Math.max(r,i.min),l[t][1]=Math.min(o,i.max),l[t][0]>l[t][1]&&(l[t][0]=l[t][1]=NaN),l[e][0]=this.loc,l[e][1]=this.loc,l},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"tick_coords\",{get:function(){for(var t=this.dimension,e=(t+1)%2,i=this.ranges[0],n=this.computed_bounds,r=n[0],o=n[1],s=this.ticker.get_ticks(r,o,i,this.loc,{}),a=s.major,l=s.minor,h=[[],[]],c=[[],[]],u=[i.min,i.max],_=u[0],p=u[1],d=0;dp||(h[t].push(a[d]),h[e].push(this.loc));for(var d=0;dp||(c[t].push(l[d]),c[e].push(this.loc));return{major:h,minor:c}},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"loc\",{get:function(){var t=this.ranges,e=t[1];switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}},enumerable:!0,configurable:!0}),e}(r.GuideRenderer);i.Axis=p,p.initClass()},function(t,e,i){var n=t(379),r=t(72),o=t(192),s=t(97),a=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype._render=function(t,e,i){this._draw_group_separators(t,e,i)},e.prototype._draw_group_separators=function(t,e,i){var n=this.model.ranges[0],r=this.model.computed_bounds,o=r[0],s=r[1];if(n.tops&&!(n.tops.length<2)&&this.visuals.separator_line.doit){for(var a=this.model.dimension,l=(a+1)%2,h=[[],[]],c=0,u=0;uo&&f1&&(l.tops[e]=a.tops),l.tops[i]=a.tops.map(function(e){return t.loc}),l},enumerable:!0,configurable:!0}),e}(r.Axis);i.CategoricalAxis=l,l.initClass()},function(t,e,i){var n=t(379),r=t(72),o=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"ContinuousAxis\"},e}(r.Axis);i.ContinuousAxis=o,o.initClass()},function(t,e,i){var n=t(379),r=t(77),o=t(98),s=t(195),a=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e}(r.LinearAxisView);i.DatetimeAxisView=a;var l=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"DatetimeAxis\",this.prototype.default_view=a,this.override({ticker:function(){return new s.DatetimeTicker},formatter:function(){return new o.DatetimeTickFormatter}})},e}(r.LinearAxis);i.DatetimeAxis=l,l.initClass()},function(t,e,i){var n=t(72);i.Axis=n.Axis;var r=t(73);i.CategoricalAxis=r.CategoricalAxis;var o=t(74);i.ContinuousAxis=o.ContinuousAxis;var s=t(75);i.DatetimeAxis=s.DatetimeAxis;var a=t(77);i.LinearAxis=a.LinearAxis;var l=t(78);i.LogAxis=l.LogAxis;var h=t(79);i.MercatorAxis=h.MercatorAxis},function(t,e,i){var n=t(379),r=t(72),o=t(74),s=t(96),a=t(191),l=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e}(r.AxisView);i.LinearAxisView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"LinearAxis\",this.prototype.default_view=l,this.override({ticker:function(){return new a.BasicTicker},formatter:function(){return new s.BasicTickFormatter}})},e}(o.ContinuousAxis);i.LinearAxis=h,h.initClass()},function(t,e,i){var n=t(379),r=t(72),o=t(74),s=t(101),a=t(199),l=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e}(r.AxisView);i.LogAxisView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"LogAxis\",this.prototype.default_view=l,this.override({ticker:function(){return new a.LogTicker},formatter:function(){return new s.LogTickFormatter}})},e}(o.ContinuousAxis);i.LogAxis=h,h.initClass()},function(t,e,i){var n=t(379),r=t(72),o=t(77),s=t(102),a=t(200),l=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e}(r.AxisView);i.MercatorAxisView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"MercatorAxis\",this.prototype.default_view=l,this.override({ticker:function(){return new a.MercatorTicker},formatter:function(){return new s.MercatorTickFormatter}})},e}(o.LinearAxis);i.MercatorAxis=h,h.initClass()},function(t,e,i){var n=t(379),r=t(53),o=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Callback\"},e}(r.Model);i.Callback=o,o.initClass()},function(t,e,i){var n=t(379),r=t(80),o=t(15),s=t(32),a=function(e){function i(t){return e.call(this,t)||this}return n.__extends(i,e),i.initClass=function(){this.prototype.type=\"CustomJS\",this.define({args:[o.Any,{}],code:[o.String,\"\"]})},Object.defineProperty(i.prototype,\"names\",{get:function(){return s.keys(this.args)},enumerable:!0,configurable:!0}),Object.defineProperty(i.prototype,\"values\",{get:function(){return s.values(this.args)},enumerable:!0,configurable:!0}),Object.defineProperty(i.prototype,\"func\",{get:function(){return new(Function.bind.apply(Function,[void 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this.filter=this.func.apply(this,this.values.concat([i,t,{}])),e.prototype.compute_indices.call(this,i)},i}(r.Filter);i.CustomJSFilter=a,a.initClass()},function(t,e,i){var n=t(379),r=t(53),o=t(15),s=t(44),a=t(21),l=t(14),h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Filter\",this.define({filter:[o.Array,null]})},e.prototype.compute_indices=function(t){var e=this.filter;return null!=e&&e.length>=0?s.isArrayOf(e,s.isBoolean)?a.range(0,e.length).filter(function(t){return!0===e[t]}):s.isArrayOf(e,s.isInteger)?e:(l.logger.warn(\"Filter \"+this.id+\": filter should either be array of only booleans or only integers, defaulting to no filtering\"),null):(l.logger.warn(\"Filter \"+this.id+\": filter was not set to be an array, defaulting to no filtering\"),null)},e}(r.Model);i.Filter=h,h.initClass()},function(t,e,i){var n=t(379),r=t(92),o=t(15),s=t(14),a=t(21),l=function(t){function e(e){var i=t.call(this,e)||this;return i.indices=null,i}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"GroupFilter\",this.define({column_name:[o.String],group:[o.String]})},e.prototype.compute_indices=function(t){var e=this,i=t.get_column(this.column_name);return null==i?(s.logger.warn(\"group filter: groupby column not found in data source\"),null):(this.indices=a.range(0,t.get_length()||0).filter(function(t){return i[t]===e.group}),0===this.indices.length&&s.logger.warn(\"group filter: group '\"+this.group+\"' did not match any values in column '\"+this.column_name+\"'\"),this.indices)},e}(r.Filter);i.GroupFilter=l,l.initClass()},function(t,e,i){var n=t(90);i.BooleanFilter=n.BooleanFilter;var r=t(91);i.CustomJSFilter=r.CustomJSFilter;var o=t(92);i.Filter=o.Filter;var s=t(93);i.GroupFilter=s.GroupFilter;var a=t(95);i.IndexFilter=a.IndexFilter},function(t,e,i){var n=t(379),r=t(92),o=t(15),s=t(14),a=t(44),l=t(21),h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"IndexFilter\",this.define({indices:[o.Array,null]})},e.prototype.compute_indices=function(t){return null!=this.indices&&this.indices.length>=0?l.all(this.indices,a.isInteger)?this.indices:(s.logger.warn(\"IndexFilter \"+this.id+\": indices should be array of integers, defaulting to no filtering\"),null):(s.logger.warn(\"IndexFilter \"+this.id+\": indices was not set, defaulting to no filtering\"),null)},e}(r.Filter);i.IndexFilter=h,h.initClass()},function(t,e,i){var n=t(379),r=t(105),o=t(15),s=t(44),a=function(t){function e(e){var i=t.call(this,e)||this;return i.last_precision=3,i}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"BasicTickFormatter\",this.define({precision:[o.Any,\"auto\"],use_scientific:[o.Bool,!0],power_limit_high:[o.Number,5],power_limit_low:[o.Number,-3]})},Object.defineProperty(e.prototype,\"scientific_limit_low\",{get:function(){return Math.pow(10,this.power_limit_low)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"scientific_limit_high\",{get:function(){return Math.pow(10,this.power_limit_high)},enumerable:!0,configurable:!0}),e.prototype.doFormat=function(t,e){if(0==t.length)return[];var i=0;t.length>=2&&(i=Math.abs(t[1]-t[0])/1e4);var n=!1;if(this.use_scientific)for(var r=0,o=t;ri&&(l>=this.scientific_limit_high||l<=this.scientific_limit_low)){n=!0;break}}var h=new Array(t.length),c=this.precision;if(null==c||s.isNumber(c))if(n)for(var u=0,_=t.length;u<_;u++)h[u]=t[u].toExponential(c||void 0);else for(var u=0,_=t.length;u<_;u++)h[u]=t[u].toFixed(c||void 0).replace(/(\\.[0-9]*?)0+$/,\"$1\").replace(/\\.$/,\"\");else for(var p=this.last_precision,d=this.last_precision<=15;d?p<=15:p>=15;d?p++:p--){var f=!0;if(n){for(var u=0,_=t.length;u<_;u++)if(h[u]=t[u].toExponential(p),u>0&&h[u]===h[u-1]){f=!1;break}if(f)break}else{for(var u=0,_=t.length;u<_;u++)if(h[u]=t[u].toFixed(p).replace(/(\\.[0-9]*?)0+$/,\"$1\").replace(/\\.$/,\"\"),u>0&&h[u]==h[u-1]){f=!1;break}if(f)break}if(f){this.last_precision=p;break}}return h},e}(r.TickFormatter);i.BasicTickFormatter=a,a.initClass()},function(t,e,i){var n=t(379),r=t(105),o=t(21),s=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"CategoricalTickFormatter\"},e.prototype.doFormat=function(t,e){return o.copy(t)},e}(r.TickFormatter);i.CategoricalTickFormatter=s,s.initClass()},function(t,e,i){function n(t){return a(t,\"%Y %m %d %H %M %S\").split(/\\s+/).map(function(t){return parseInt(t,10)})}function r(t,e){if(_.isFunction(e))return e(t);var i=s.sprintf(\"$1%06d\",function(t){return Math.round(t/1e3%1*1e6)}(t));return-1==(e=e.replace(/((^|[^%])(%%)*)%f/,i)).indexOf(\"%\")?e:a(t,e)}var o=t(379),s=t(377),a=t(378),l=t(105),h=t(14),c=t(15),u=t(21),_=t(44),p=[\"microseconds\",\"milliseconds\",\"seconds\",\"minsec\",\"minutes\",\"hourmin\",\"hours\",\"days\",\"months\",\"years\"],d=function(t){function e(e){var i=t.call(this,e)||this;return i.strip_leading_zeros=!0,i}return o.__extends(e,t),e.initClass=function(){this.prototype.type=\"DatetimeTickFormatter\",this.define({microseconds:[c.Array,[\"%fus\"]],milliseconds:[c.Array,[\"%3Nms\",\"%S.%3Ns\"]],seconds:[c.Array,[\"%Ss\"]],minsec:[c.Array,[\":%M:%S\"]],minutes:[c.Array,[\":%M\",\"%Mm\"]],hourmin:[c.Array,[\"%H:%M\"]],hours:[c.Array,[\"%Hh\",\"%H:%M\"]],days:[c.Array,[\"%m/%d\",\"%a%d\"]],months:[c.Array,[\"%m/%Y\",\"%b%y\"]],years:[c.Array,[\"%Y\"]]})},e.prototype.initialize=function(){t.prototype.initialize.call(this),this._update_width_formats()},e.prototype._update_width_formats=function(){var t=+a(new Date),e=function(e){var i=e.map(function(e){return r(t,e).length}),n=u.sortBy(u.zip(i,e),function(t){var e=t[0];return e});return u.unzip(n)};this._width_formats={microseconds:e(this.microseconds),milliseconds:e(this.milliseconds),seconds:e(this.seconds),minsec:e(this.minsec),minutes:e(this.minutes),hourmin:e(this.hourmin),hours:e(this.hours),days:e(this.days),months:e(this.months),years:e(this.years)}},e.prototype._get_resolution_str=function(t,e){var i=1.1*t;switch(!1){case!(i<.001):return\"microseconds\";case!(i<1):return\"milliseconds\";case!(i<60):return e>=60?\"minsec\":\"seconds\";case!(i<3600):return e>=3600?\"hourmin\":\"minutes\";case!(i<86400):return\"hours\";case!(i<2678400):return\"days\";case!(i<31536e3):return\"months\";default:return\"years\"}},e.prototype.doFormat=function(t,e){if(0==t.length)return[];for(var i=Math.abs(t[t.length-1]-t[0])/1e3,o=i/(t.length-1),s=this._get_resolution_str(o,i),a=this._width_formats[s],l=a[1],c=l[0],u=[],_=p.indexOf(s),d={},f=0,v=p;f0&&r[o]==r[o-1]){n=!0;break}return n?this.basic_formatter.doFormat(t,e):r},e}(r.TickFormatter);i.LogTickFormatter=l,l.initClass()},function(t,e,i){var n=t(379),r=t(96),o=t(15),s=t(33),a=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"MercatorTickFormatter\",this.define({dimension:[o.LatLon]})},e.prototype.doFormat=function(e,i){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==e.length)return[];var n=e.length,r=new Array(n);if(\"lon\"==this.dimension)for(var o=0;o=x&&f.push([y,S])}for(var C=this.model.properties.direction.value(),T=[],A=0,E=f;A=v&&c.push([d,k])}return o.create_hit_test_result_from_hits(c)},e.prototype.draw_legend_for_index=function(t,e,i){var n=e.x0,r=e.y0,o=e.x1,s=e.y1,a=i+1,l=new Array(a);l[i]=(n+o)/2;var h=new Array(a);h[i]=(r+s)/2;var c=.5*Math.min(Math.abs(o-n),Math.abs(s-r)),u=new Array(a);u[i]=.4*c;var _=new Array(a);_[i]=.8*c,this._render(t,[i],{sx:l,sy:h,sinner_radius:u,souter_radius:_})},e}(r.XYGlyphView);i.AnnulusView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Annulus\",this.prototype.default_view=l,this.mixins([\"line\",\"fill\"]),this.define({inner_radius:[s.DistanceSpec],outer_radius:[s.DistanceSpec]})},e}(r.XYGlyph);i.Annulus=h,h.initClass()},function(t,e,i){var n=t(379),r=t(135),o=t(132),s=t(15),a=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype._map_data=function(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this._radius):this.sradius=this._radius},e.prototype._render=function(t,e,i){var n=i.sx,r=i.sy,o=i.sradius,s=i._start_angle,a=i._end_angle;if(this.visuals.line.doit)for(var l=this.model.properties.direction.value(),h=0,c=e;h1?(_[i]=u,p[i]=u/c):(_[i]=u*c,p[i]=u),this._render(t,[i],{sx:l,sy:h,sw:_,sh:p})},e.prototype._bounds=function(t){var e=t.minX,i=t.maxX,n=t.minY,r=t.maxY;return{minX:e-this.max_w2,maxX:i+this.max_w2,minY:n-this.max_h2,maxY:r+this.max_h2}},e}(r.XYGlyphView);i.EllipseView=s;var a=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Ellipse\",this.prototype.default_view=s,this.mixins([\"line\",\"fill\"]),this.define({angle:[o.AngleSpec,0],width:[o.DistanceSpec],height:[o.DistanceSpec]})},e}(r.XYGlyph);i.Ellipse=a,a.initClass()},function(t,e,i){var n=t(379),r=t(9),o=t(15),s=t(24),a=t(33),l=t(49),h=t(48),c=t(53),u=t(14),_=t(22),p=t(32),d=t(44),f=t(120),v=t(165),m=function(e){function i(){var t=null!==e&&e.apply(this,arguments)||this;return t._nohit_warned={},t}return n.__extends(i,e),i.prototype.initialize=function(i){e.prototype.initialize.call(this,i),this._nohit_warned={},this.renderer=i.renderer,this.visuals=new l.Visuals(this.model);var n=this.renderer.plot_view.gl;if(null!=n){var r=null;try{r=t(440)}catch(t){if(\"MODULE_NOT_FOUND\"!==t.code)throw t;u.logger.warn(\"WebGL was requested and is supported, but bokeh-gl(.min).js is not available, falling back to 2D rendering.\")}if(null!=r){var o=r[this.model.type+\"GLGlyph\"];null!=o&&(this.glglyph=new o(n.ctx,this))}}},i.prototype.set_visuals=function(t){this.visuals.warm_cache(t),null!=this.glglyph&&this.glglyph.set_visuals_changed()},i.prototype.render=function(t,e,i){t.beginPath(),null!=this.glglyph&&this.glglyph.render(t,e,i)||this._render(t,e,i)},i.prototype.has_finished=function(){return!0},i.prototype.notify_finished=function(){this.renderer.notify_finished()},i.prototype._bounds=function(t){return t},i.prototype.bounds=function(){return this._bounds(this.index.bbox)},i.prototype.log_bounds=function(){for(var t=s.empty(),e=this.index.search(s.positive_x()),i=0,n=e;it.maxX&&(t.maxX=r.maxX)}for(var o=this.index.search(s.positive_y()),a=0,l=o;at.maxY&&(t.maxY=h.maxY)}return this._bounds(t)},i.prototype.get_anchor_point=function(t,e,i){var n=i[0],r=i[1];switch(t){case\"center\":return{x:this.scenterx(e,n,r),y:this.scentery(e,n,r)};default:return null}},i.prototype.sdist=function(t,e,i,n,r){void 0===n&&(n=\"edge\"),void 0===r&&(r=!1);var o,s,a=e.length;if(\"center\"==n){var l=_.map(i,function(t){return t/2});o=new Float64Array(a);for(var h=0;h0){n=this._image[e];var r=this._image_shape[e];this._height[e]=r[0],this._width[e]=r[1]}else{var o=this._image[e];n=a.concat(o),this._height[e]=o.length,this._width[e]=o[0].length}var s=this.image_data[e],l=void 0;null!=s&&s.width==this._width[e]&&s.height==this._height[e]?l=s:((l=document.createElement(\"canvas\")).width=this._width[e],l.height=this._height[e]);var h=l.getContext(\"2d\"),c=h.getImageData(0,0,this._width[e],this._height[e]),u=t.v_compute(n);c.data.set(u),h.putImageData(c,0,0),this.image_data[e]=l,this.max_dw=0,\"data\"==this.model.properties.dw.units&&(this.max_dw=a.max(this._dw)),this.max_dh=0,\"data\"==this.model.properties.dh.units&&(this.max_dh=a.max(this._dh))}},e.prototype._map_data=function(){switch(this.model.properties.dw.units){case\"data\":this.sw=this.sdist(this.renderer.xscale,this._x,this._dw,\"edge\",this.model.dilate);break;case\"screen\":this.sw=this._dw}switch(this.model.properties.dh.units){case\"data\":this.sh=this.sdist(this.renderer.yscale,this._y,this._dh,\"edge\",this.model.dilate);break;case\"screen\":this.sh=this._dh}},e.prototype._render=function(t,e,i){var n=i.image_data,r=i.sx,o=i.sy,s=i.sw,a=i.sh,l=t.getImageSmoothingEnabled();t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.global_alpha;for(var h=0,c=e;h0){n=this._image[e].buffer;var r=this._image_shape[e];this._height[e]=r[0],this._width[e]=r[1]}else{var o=this._image[e],a=s.concat(o);n=new ArrayBuffer(4*a.length);for(var l=new Uint32Array(n),h=0,c=a.length;h0?(o.logger.trace(\"ImageURL failed to load \"+t._url[e]+\" image, retrying in \"+r+\" ms\"),setTimeout(function(){return a.src=t._url[e]},r)):o.logger.warn(\"ImageURL unable to load \"+t._url[e]+\" image after \"+n+\" retries\"),t.retries[e]-=1},a.onload=function(){t.image[e]=a,t.renderer.request_render()},a.src=l._url[e]},l=this,h=0,c=this._url.length;h1&&(t.stroke(),o=!1)}o?t.lineTo(n[h],r[h]):(t.beginPath(),t.moveTo(n[h],r[h]),o=!0),s=h}o&&t.stroke()},e.prototype._hit_point=function(t){for(var e=this,i=s.create_empty_hit_test_result(),n={x:t.sx,y:t.sy},r=9999,o=Math.max(2,this.visuals.line.line_width.value()/2),a=0,l=this.sx.length-1;a0&&(l[h]=u)}return a.indices=s.keys(l).map(function(t){return parseInt(t,10)}),a.multiline_indices=l,a},e.prototype.get_interpolation_hit=function(t,e,i){var n,r,s,a,l=i.sx,h=i.sy,c=this._xs[t][e],u=this._ys[t][e],_=this._xs[t][e+1],p=this._ys[t][e+1];\"point\"==i.type?(m=this.renderer.yscale.r_invert(h-1,h+1),s=m[0],a=m[1],g=this.renderer.xscale.r_invert(l-1,l+1),n=g[0],r=g[1]):\"v\"==i.direction?(y=this.renderer.yscale.r_invert(h,h),s=y[0],a=y[1],n=(b=[c,_])[0],r=b[1]):(x=this.renderer.xscale.r_invert(l,l),n=x[0],r=x[1],s=(w=[u,p])[0],a=w[1]);var d=o.check_2_segments_intersect(n,s,r,a,c,u,_,p),f=d.x,v=d.y;return[f,v];var m,g,y,b,x,w},e.prototype.draw_legend_for_index=function(t,e,i){c.generic_line_legend(this.visuals,t,e,i)},e.prototype.scenterx=function(){throw new Error(\"not implemented\")},e.prototype.scentery=function(){throw new Error(\"not implemented\")},e}(h.GlyphView);i.MultiLineView=u;var _=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"MultiLine\",this.prototype.default_view=u,this.coords([[\"xs\",\"ys\"]]),this.mixins([\"line\"])},e}(h.Glyph);i.MultiLine=_,_.initClass()},function(t,e,i){var n=t(379),r=t(135),o=t(15),s=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype._set_data=function(){this.max_w2=0,\"data\"==this.model.properties.width.units&&(this.max_w2=this.max_width/2),this.max_h2=0,\"data\"==this.model.properties.height.units&&(this.max_h2=this.max_height/2)},e.prototype._map_data=function(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this._width,\"center\"):this.sw=this._width,\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this._height,\"center\"):this.sh=this._height},e.prototype._render=function(t,e,i){for(var n=i.sx,r=i.sy,o=i.sw,s=i.sh,a=i._angle,l=0,h=e;l1?(_[i]=u,p[i]=u/c):(_[i]=u*c,p[i]=u),this._render(t,[i],{sx:l,sy:h,sw:_,sh:p})},e.prototype._bounds=function(t){var e=t.minX,i=t.maxX,n=t.minY,r=t.maxY;return{minX:e-this.max_w2,maxX:i+this.max_w2,minY:n-this.max_h2,maxY:r+this.max_h2}},e}(r.XYGlyphView);i.OvalView=s;var a=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Oval\",this.prototype.default_view=s,this.mixins([\"line\",\"fill\"]),this.define({angle:[o.AngleSpec,0],width:[o.DistanceSpec],height:[o.DistanceSpec]})},e}(r.XYGlyph);i.Oval=a,a.initClass()},function(t,e,i){var n=t(379),r=t(135),o=t(132),s=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype._render=function(t,e,i){var n=i.sx,r=i.sy;if(this.visuals.fill.doit){this.visuals.fill.set_value(t);for(var o=0,s=e;o0;){var o=a.findLastIndex(r,function(t){return h.isStrictNaN(t)}),s=void 0;o>=0?s=r.splice(o):(s=r,r=[]);var l=s.filter(function(t){return!h.isStrictNaN(t)});e[i].push(l)}}return e},e.prototype._index_data=function(){for(var t=this._build_discontinuous_object(this._xs),e=this._build_discontinuous_object(this._ys),i=[],n=0,o=this._xs.length;n=0,x=i-this.sy1[a]<=this.sh[a]&&i-this.sy1[a]>=0;x&&w&&m.push(a)}var A=s.create_empty_hit_test_result();return A.indices=m,A},e.prototype._map_dist_corner_for_data_side_length=function(t,e,i){for(var n=t.length,r=new Float64Array(n),o=new Float64Array(n),s=0;so[1]&&(e=o[1]);else{t=o[0],e=o[1];for(var s=0,l=this.plot.select(r.Axis);s1?y[1]:\"\",w=this._horizontal?\"row\":\"col\";g=b+\" \"+w+\"-\"+o+\"-\"+a+\"-\"+x}else g=v;s[g]=g in s?s[g].concat(m):m}a++}return s},e.prototype._align_inner_cell_edges_constraints=function(){var t=[];if(null!=this.document&&s.includes(this.document.roots(),this)){var e=this._flatten_cell_edge_variables(this._horizontal);for(var i in e){var n=e[i];if(n.length>1)for(var o=n[0],a=1;a0)if(this._horizontal==t){var r=i[0],o=i[i.length-1];r instanceof e?n[0]=n[0].concat(r._find_edge_leaves(t)[0]):n[0].push(r),o instanceof e?n[1]=n[1].concat(o._find_edge_leaves(t)[1]):n[1].push(o)}else for(var s=0,a=i;s1)for(var e=t[0],i=1;i0?this.model._width.value-20+\"px\":\"100%\",this.el.style.width=i}},e.prototype.get_height=function(){var t=0;for(var e in this.child_views){var i=this.child_views[e],n=i.el,r=getComputedStyle(n),o=parseInt(r.marginTop)||0,s=parseInt(r.marginBottom)||0;t+=n.offsetHeight+o+s}return t+20},e.prototype.get_width=function(){if(null!=this.model.width)return this.model.width;var t=this.el.scrollWidth+20;for(var e in this.child_views){var i=this.child_views[e],n=i.el.scrollWidth;n>t&&(t=n)}return t},e}(a.LayoutDOMView);i.WidgetBoxView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"WidgetBox\",this.prototype.default_view=l,this.define({children:[o.Array,[]]})},e.prototype.initialize=function(){t.prototype.initialize.call(this),\"fixed\"==this.sizing_mode&&null==this.width&&(this.width=300,r.logger.info(\"WidgetBox mode is fixed, but no width specified. Using default of 300.\"))},e.prototype.get_constrained_variables=function(){var e=s.extend({},t.prototype.get_constrained_variables.call(this),{on_edge_align_top:this._top,on_edge_align_bottom:this._height_minus_bottom,on_edge_align_left:this._left,on_edge_align_right:this._width_minus_right,box_cell_align_top:this._top,box_cell_align_bottom:this._height_minus_bottom,box_cell_align_left:this._left,box_cell_align_right:this._width_minus_right,box_equal_size_top:this._top,box_equal_size_bottom:this._height_minus_bottom});return\"fixed\"!=this.sizing_mode&&(e.box_equal_size_left=this._left,e.box_equal_size_right=this._width_minus_right),e},e.prototype.get_layoutable_children=function(){return this.children},e}(a.LayoutDOM);i.WidgetBox=h,h.initClass()},function(t,e,i){var n=t(379),r=t(151),o=t(15),s=t(21),a=t(44),l=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"CategoricalColorMapper\",this.define({factors:[o.Array],start:[o.Number,0],end:[o.Number]})},e.prototype._v_compute=function(t,e,i,n){for(var r=n.nan_color,o=function(n,o){var h=t[n],c=void 0;a.isString(h)?c=l.factors.indexOf(h):(null!=l.start?h=null!=l.end?h.slice(l.start,l.end):h.slice(l.start):null!=l.end&&(h=h.slice(0,l.end)),c=1==h.length?l.factors.indexOf(h[0]):s.findIndex(l.factors,function(t){return function(t,e){if(t.length!=e.length)return!1;for(var i=0,n=t.length;i=i.length?r:i[c],e[n]=u},l=this,h=0,c=t.length;hc?null!=a?a:i[c]:i[m]}else e[p]=i[c]}},e}(r.ContinuousColorMapper);i.LinearColorMapper=s,s.initClass()},function(t,e,i){var n=t(379),r=t(152),o=t(22),s=null!=Math.log1p?Math.log1p:function(t){return Math.log(1+t)},a=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"LogColorMapper\"},e.prototype._v_compute=function(t,e,i,n){for(var r=n.nan_color,a=n.low_color,l=n.high_color,h=i.length,c=null!=this.low?this.low:o.min(t),u=null!=this.high?this.high:o.max(t),_=h/(s(u)-s(c)),p=i.length-1,d=0,f=t.length;du)e[d]=null!=l?l:i[p];else if(v!=u)if(vp&&(g=p),e[d]=i[g]}else e[d]=i[p]}},e}(r.ContinuousColorMapper);i.LogColorMapper=a,a.initClass()},function(t,e,i){function n(t,e){t.moveTo(-e,e),t.lineTo(e,-e),t.moveTo(-e,-e),t.lineTo(e,e)}function r(t,e){t.moveTo(0,e),t.lineTo(0,-e),t.moveTo(-e,0),t.lineTo(e,0)}function o(t,e){t.moveTo(0,e),t.lineTo(e/1.5,0),t.lineTo(0,-e),t.lineTo(-e/1.5,0),t.closePath()}function s(t,e){var i=e*c,n=i/3;t.moveTo(-e,n),t.lineTo(e,n),t.lineTo(0,n-i),t.closePath()}function a(t,e){var i=function(t){function i(){return null!==t&&t.apply(this,arguments)||this}return l.__extends(i,t),i.initClass=function(){this.prototype._render_one=e},i}(h.MarkerView);i.initClass();var n=function(e){function n(){return null!==e&&e.apply(this,arguments)||this}return l.__extends(n,e),n.initClass=function(){this.prototype.default_view=i,this.prototype.type=t},n}(h.Marker);return n.initClass(),n}var l=t(379),h=t(157),c=Math.sqrt(3);i.Asterisk=a(\"Asterisk\",function(t,e,i,o,s){var a=.65*i;r(t,i),n(t,a),o.doit&&(o.set_vectorize(t,e),t.stroke())}),i.CircleCross=a(\"CircleCross\",function(t,e,i,n,o){t.arc(0,0,i,0,2*Math.PI,!1),o.doit&&(o.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),r(t,i),t.stroke())}),i.CircleX=a(\"CircleX\",function(t,e,i,r,o){t.arc(0,0,i,0,2*Math.PI,!1),o.doit&&(o.set_vectorize(t,e),t.fill());r.doit&&(r.set_vectorize(t,e),n(t,i),t.stroke())}),i.Cross=a(\"Cross\",function(t,e,i,n,o){r(t,i),n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.Diamond=a(\"Diamond\",function(t,e,i,n,r){o(t,i),r.doit&&(r.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.DiamondCross=a(\"DiamondCross\",function(t,e,i,n,s){o(t,i),s.doit&&(s.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),r(t,i),t.stroke())}),i.Hex=a(\"Hex\",function(t,e,i,n,r){(function(t,e){var i=e/2,n=c*i;t.moveTo(e,0),t.lineTo(i,-n),t.lineTo(-i,-n),t.lineTo(-e,0),t.lineTo(-i,n),t.lineTo(i,n),t.closePath()})(t,i),r.doit&&(r.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.InvertedTriangle=a(\"InvertedTriangle\",function(t,e,i,n,r){t.rotate(Math.PI),s(t,i),t.rotate(-Math.PI),r.doit&&(r.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.Square=a(\"Square\",function(t,e,i,n,r){var o=2*i;t.rect(-i,-i,o,o),r.doit&&(r.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.SquareCross=a(\"SquareCross\",function(t,e,i,n,o){var s=2*i;t.rect(-i,-i,s,s),o.doit&&(o.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),r(t,i),t.stroke())}),i.SquareX=a(\"SquareX\",function(t,e,i,r,o){var s=2*i;t.rect(-i,-i,s,s),o.doit&&(o.set_vectorize(t,e),t.fill());r.doit&&(r.set_vectorize(t,e),n(t,i),t.stroke())}),i.Triangle=a(\"Triangle\",function(t,e,i,n,r){s(t,i),r.doit&&(r.set_vectorize(t,e),t.fill());n.doit&&(n.set_vectorize(t,e),t.stroke())}),i.X=a(\"X\",function(t,e,i,r,o){n(t,i),r.doit&&(r.set_vectorize(t,e),t.stroke())})},function(t,e,i){var n=t(379),r=t(135),o=t(9),s=t(15),a=t(21),l=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype._render=function(t,e,i){for(var n=i.sx,r=i.sy,o=i._size,s=i._angle,a=0,l=e;a=2){this.map.setZoom(r);var o=this._get_projected_bounds(),s=o[0],a=o[1];a-s<0&&this.map.setZoom(n)}this.unpause()}this._set_bokeh_ranges()},e.prototype._build_map=function(){var t=this,e=google.maps;this.map_types={satellite:e.MapTypeId.SATELLITE,terrain:e.MapTypeId.TERRAIN,roadmap:e.MapTypeId.ROADMAP,hybrid:e.MapTypeId.HYBRID};var i=this.model.plot.map_options,n={center:new e.LatLng(i.lat,i.lng),zoom:i.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[i.map_type],scaleControl:i.scale_control};null!=i.styles&&(n.styles=JSON.parse(i.styles)),this.map=new e.Map(this.canvas_view.map_el,n),e.event.addListener(this.map,\"idle\",function(){return t._set_bokeh_ranges()}),e.event.addListener(this.map,\"bounds_changed\",function(){return t._set_bokeh_ranges()}),e.event.addListenerOnce(this.map,\"tilesloaded\",function(){return t._render_finished()}),this.connect(this.model.plot.properties.map_options.change,function(){return t._update_options()}),this.connect(this.model.plot.map_options.properties.styles.change,function(){return t._update_styles()}),this.connect(this.model.plot.map_options.properties.lat.change,function(){return t._update_center(\"lat\")}),this.connect(this.model.plot.map_options.properties.lng.change,function(){return t._update_center(\"lng\")}),this.connect(this.model.plot.map_options.properties.zoom.change,function(){return t._update_zoom()}),this.connect(this.model.plot.map_options.properties.map_type.change,function(){return t._update_map_type()}),this.connect(this.model.plot.map_options.properties.scale_control.change,function(){return t._update_scale_control()})},e.prototype._render_finished=function(){this._tiles_loaded=!0,this.notify_finished()},e.prototype.has_finished=function(){return t.prototype.has_finished.call(this)&&!0===this._tiles_loaded},e.prototype._get_latlon_bounds=function(){var t=this.map.getBounds(),e=t.getNorthEast(),i=t.getSouthWest(),n=i.lng(),r=e.lng(),o=i.lat(),s=e.lat();return[n,r,o,s]},e.prototype._get_projected_bounds=function(){var t=this._get_latlon_bounds(),e=t[0],i=t[1],n=t[2],r=t[3],s=o.wgs84_mercator.forward([e,n]),a=s[0],l=s[1],h=o.wgs84_mercator.forward([i,r]),c=h[0],u=h[1];return[a,c,l,u]},e.prototype._set_bokeh_ranges=function(){var t=this._get_projected_bounds(),e=t[0],i=t[1],n=t[2],r=t[3];this.frame.x_range.setv({start:e,end:i}),this.frame.y_range.setv({start:n,end:r})},e.prototype._update_center=function(t){var e=this.map.getCenter().toJSON();e[t]=this.model.plot.map_options[t],this.map.setCenter(e),this._set_bokeh_ranges()},e.prototype._update_map_type=function(){this.map.setOptions({mapTypeId:this.map_types[this.model.plot.map_options.map_type]})},e.prototype._update_scale_control=function(){this.map.setOptions({scaleControl:this.model.plot.map_options.scale_control})},e.prototype._update_options=function(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()},e.prototype._update_styles=function(){this.map.setOptions({styles:JSON.parse(this.model.plot.map_options.styles)})},e.prototype._update_zoom=function(){this.map.setOptions({zoom:this.model.plot.map_options.zoom}),this._set_bokeh_ranges()},e.prototype._map_hook=function(t,e){var i=e[0],n=e[1],r=e[2],o=e[3];this.canvas_view.map_el.style.top=n+\"px\",this.canvas_view.map_el.style.left=i+\"px\",this.canvas_view.map_el.style.width=r+\"px\",this.canvas_view.map_el.style.height=o+\"px\",null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map()},e.prototype._paint_empty=function(t,e){var i=this.canvas._width.value,n=this.canvas._height.value,r=e[0],o=e[1],s=e[2],a=e[3];t.clearRect(0,0,i,n),t.beginPath(),t.moveTo(0,0),t.lineTo(0,n),t.lineTo(i,n),t.lineTo(i,0),t.lineTo(0,0),t.moveTo(r,o),t.lineTo(r+s,o),t.lineTo(r+s,o+a),t.lineTo(r,o+a),t.lineTo(r,o),t.closePath(),t.fillStyle=this.model.plot.border_fill_color,t.fill()},e}(s.PlotCanvasView);i.GMapPlotCanvasView=l;var h=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"GMapPlotCanvas\",this.prototype.default_view=l},e.prototype.initialize=function(){this.use_map=!0,t.prototype.initialize.call(this)},e}(s.PlotCanvas);i.GMapPlotCanvas=h,h.initClass()},function(t,e,i){var n=t(158);i.MapOptions=n.MapOptions;var r=t(158);i.GMapOptions=r.GMapOptions;var o=t(158);i.GMapPlot=o.GMapPlot;var s=t(159);i.GMapPlotCanvas=s.GMapPlotCanvas;var a=t(161);i.Plot=a.Plot;var l=t(162);i.PlotCanvas=l.PlotCanvas},function(t,e,i){var n=t(379),r=t(13),o=t(14),s=t(15),a=t(21),l=t(32),h=t(44),c=t(146),u=t(68),_=t(176),p=t(247),d=t(69),f=t(162),v=t(184),m=t(169),g=t(3),y=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype.connect_signals=function(){t.prototype.connect_signals.call(this);this.connect(this.model.properties.title.change,function(){return o.logger.warn(\"Title object cannot be replaced. Try changing properties on title to update it after initialization.\")})},e.prototype.css_classes=function(){return t.prototype.css_classes.call(this).concat(\"bk-plot-layout\")},e.prototype.get_height=function(){return this.model._width.value/this.model.get_aspect_ratio()},e.prototype.get_width=function(){return this.model._height.value*this.model.get_aspect_ratio()},e.prototype.save=function(t){this.plot_canvas_view.save(t)},Object.defineProperty(e.prototype,\"plot_canvas_view\",{get:function(){return this.child_views[this.model.plot_canvas.id]},enumerable:!0,configurable:!0}),e}(c.LayoutDOMView);i.PlotView=y;var b=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Plot\",this.prototype.default_view=y,this.mixins([\"line:outline_\",\"fill:background_\",\"fill:border_\"]),this.define({toolbar:[s.Instance,function(){return new p.Toolbar}],toolbar_location:[s.Location,\"right\"],toolbar_sticky:[s.Boolean,!0],plot_width:[s.Number,600],plot_height:[s.Number,600],title:[s.Any,function(){return new u.Title({text:\"\"})}],title_location:[s.Location,\"above\"],h_symmetry:[s.Bool,!0],v_symmetry:[s.Bool,!1],above:[s.Array,[]],below:[s.Array,[]],left:[s.Array,[]],right:[s.Array,[]],renderers:[s.Array,[]],x_range:[s.Instance],extra_x_ranges:[s.Any,{}],y_range:[s.Instance],extra_y_ranges:[s.Any,{}],x_scale:[s.Instance,function(){return new _.LinearScale}],y_scale:[s.Instance,function(){return new _.LinearScale}],lod_factor:[s.Number,10],lod_interval:[s.Number,300],lod_threshold:[s.Number,2e3],lod_timeout:[s.Number,500],hidpi:[s.Bool,!0],output_backend:[s.OutputBackend,\"canvas\"],min_border:[s.Number,5],min_border_top:[s.Number,null],min_border_left:[s.Number,null],min_border_bottom:[s.Number,null],min_border_right:[s.Number,null],inner_width:[s.Number],inner_height:[s.Number],layout_width:[s.Number],layout_height:[s.Number],match_aspect:[s.Bool,!1],aspect_scale:[s.Number,1]}),this.override({outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"}),g.register_with_event(g.UIEvent,this)},e.prototype.initialize=function(){t.prototype.initialize.call(this);for(var e=0,i=l.values(this.extra_x_ranges).concat(this.x_range);el.end;if(!i){var u=this._get_weight_to_constrain_interval(l,h);u<1&&(h.start=u*h.start+(1-u)*l.start,h.end=u*h.end+(1-u)*l.end)}if(null!=l.bounds&&\"auto\"!=l.bounds){var _=l.bounds,p=_[0],d=_[1],f=Math.abs(h.end-h.start);c?(null!=p&&p>=h.end&&(r=!0,h.end=p,(e||i)&&(h.start=p+f)),null!=d&&d<=h.start&&(r=!0,h.start=d,(e||i)&&(h.end=d-f))):(null!=p&&p>=h.start&&(r=!0,h.start=p,(e||i)&&(h.end=p+f)),null!=d&&d<=h.end&&(r=!0,h.end=d,(e||i)&&(h.start=d-f)))}}if(!(i&&r&&n))for(var v=0,m=t;v0&&c0&&c>n&&(l=(n-h)/(c-h)),l=Math.max(0,Math.min(1,l))}return l},e.prototype.update_range=function(t,e,i,n){void 0===e&&(e=!1),void 0===i&&(i=!1),void 0===n&&(n=!0),this.pause();var r=this.frame,o=r.x_ranges,s=r.y_ranges;if(null==t){for(var a in o){var l=o[a];l.reset()}for(var h in s){var l=s[h];l.reset()}this.update_dataranges()}else{var c=[];for(var u in o){var l=o[u];c.push([l,t.xrs[u]])}for(var _ in s){var l=s[_];c.push([l,t.yrs[_]])}i&&this._update_ranges_together(c),this._update_ranges_individually(c,e,i,n)}this.unpause()},e.prototype.reset_range=function(){this.update_range(null)},e.prototype.build_levels=function(){for(var t=this.model.plot.all_renderers,e=k.keys(this.renderer_views),i=c.build_views(this.renderer_views,t,this.view_options()),n=w.difference(e,t.map(function(t){return t.id})),r=0,o=n;r=0&&in.lod_timeout&&e.interactive_stop(n),t.request_render()},n.lod_timeout):e.interactive_stop(n)}for(var r in this.renderer_views){var o=this.renderer_views[r];if(null==this.range_update_timestamp||o instanceof a.GlyphRendererView&&o.set_data_timestamp>this.range_update_timestamp){this.update_dataranges();break}}this.model.frame.update_scales();var s=this.canvas_view.ctx,l=this.canvas.pixel_ratio;s.save(),s.scale(l,l),s.translate(.5,.5);var h=[this.frame._left.value,this.frame._top.value,this.frame._width.value,this.frame._height.value];if(this._map_hook(s,h),this._paint_empty(s,h),this.prepare_webgl(l,h),s.save(),this.visuals.outline_line.doit){this.visuals.outline_line.set_value(s);var c=h[0],u=h[1],_=h[2],p=h[3];c+_==this.canvas._width.value&&(_-=1),u+p==this.canvas._height.value&&(p-=1),s.strokeRect(c,u,_,p)}s.restore(),this._paint_levels(s,[\"image\",\"underlay\",\"glyph\"],h),this.blit_webgl(l),this._paint_levels(s,[\"annotation\"],h),this._paint_levels(s,[\"overlay\"]),null==this._initial_state_info.range&&this.set_initial_range(),s.restore(),this._has_finished||(this._has_finished=!0,this.notify_finished())}},e.prototype._paint_levels=function(t,e,i){t.save(),null!=i&&(t.beginPath(),t.rect.apply(t,i),t.clip());for(var n={},r=0;r0&&(e=e.filter(function(e){return h.includes(t,e.name)})),s.logger.debug(\"computed \"+e.length+\" renderers for DataRange1d \"+this.id);for(var l=0,c=e;lu&&(\"start\"==this.follow?n=i+c*u:\"end\"==this.follow&&(i=n-c*u)),[i,n];var _},e.prototype.update=function(t,e,i,n){if(!this.have_updated_interactively){var r=this.computed_renderers(),o=this._compute_plot_bounds(r,t);null!=n&&(o=this.adjust_bounds_for_aspect(o,n)),this._plot_bounds[i]=o;var s=this._compute_min_max(this._plot_bounds,e),a=s[0],l=s[1],h=this._compute_range(a,l),c=h[0],u=h[1];null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(c=this._initial_start):c=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(u=this._initial_end):u=this._initial_end);var _=[this.start,this.end],p=_[0],d=_[1];if(c!=p||u!=d){var f={};c!=p&&(f.start=c),u!=d&&(f.end=u),this.setv(f)}\"auto\"==this.bounds&&this.setv({bounds:[c,u]},{silent:!0}),this.change.emit()}},e.prototype.reset=function(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()},e}(r.DataRange);i.DataRange1d=c,c.initClass()},function(t,e,i){function n(t,e,i){void 0===i&&(i=0);for(var n={},r=0;rthis.end},enumerable:!0,configurable:!0}),e.prototype.reset=function(){this._set_auto_bounds(),this.start!=this._initial_start||this.end!=this._initial_end?this.setv({start:this._initial_start,end:this._initial_end}):this.change.emit()},e}(r.Range);i.Range1d=s,s.initClass()},function(t,e,i){var n=t(379),r=t(173),o=t(120),s=t(189),a=t(183),l=t(14),h=t(15),c=t(22),u=t(21),_=t(32),p=t(165),d={fill:{},line:{}},f={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},v={fill:{fill_alpha:.2},line:{}},m=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype.initialize=function(e){function i(t){var e=_.clone(a);return r&&_.extend(e,t.fill),o&&_.extend(e,t.line),new n.constructor(e)}t.prototype.initialize.call(this,e);var n=this.model.glyph,r=u.includes(n.mixins,\"fill\"),o=u.includes(n.mixins,\"line\"),a=_.clone(n.attributes);delete a.id,this.glyph=this.build_glyph_view(n);var l=this.model.selection_glyph;null==l?l=i({fill:{},line:{}}):\"auto\"===l&&(l=i(d)),this.selection_glyph=this.build_glyph_view(l);var h=this.model.nonselection_glyph;null==h?h=i({fill:{},line:{}}):\"auto\"===h&&(h=i(v)),this.nonselection_glyph=this.build_glyph_view(h);var c=this.model.hover_glyph;null!=c&&(this.hover_glyph=this.build_glyph_view(c));var p=this.model.muted_glyph;null!=p&&(this.muted_glyph=this.build_glyph_view(p));var m=i(f);this.decimated_glyph=this.build_glyph_view(m),this.xscale=this.plot_view.frame.xscales[this.model.x_range_name],this.yscale=this.plot_view.frame.yscales[this.model.y_range_name],this.set_data(!1),this.model.data_source instanceof s.RemoteDataSource&&this.model.data_source.setup()},e.prototype.build_glyph_view=function(t){return new t.default_view({model:t,renderer:this,plot_view:this.plot_view,parent:this})},e.prototype.connect_signals=function(){var e=this;t.prototype.connect_signals.call(this),this.connect(this.model.change,function(){return e.request_render()}),this.connect(this.model.glyph.change,function(){return e.set_data()}),this.connect(this.model.data_source.change,function(){return e.set_data()}),this.connect(this.model.data_source.streaming,function(){return e.set_data()}),this.connect(this.model.data_source.patching,function(t){return e.set_data(!0,t)}),this.connect(this.model.data_source._select,function(){return e.request_render()}),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,function(){return e.request_render()}),this.connect(this.model.properties.view.change,function(){return e.set_data()}),this.connect(this.model.view.change,function(){return e.set_data()});var i=this.plot_model.frame,n=i.x_ranges,r=i.y_ranges;for(var o in n){var s=n[o];s instanceof p.FactorRange&&this.connect(s.change,function(){return e.set_data()})}for(var a in r){var s=r[a];s instanceof p.FactorRange&&this.connect(s.change,function(){return e.set_data()})}this.connect(this.model.glyph.transformchange,function(){return e.set_data()})},e.prototype.have_selection_glyphs=function(){return null!=this.selection_glyph&&null!=this.nonselection_glyph},e.prototype.set_data=function(t,e){void 0===t&&(t=!0),void 0===e&&(e=null);var i=Date.now(),n=this.model.data_source;this.all_indices=this.model.view.indices,this.glyph.model.setv({x_range_name:this.model.x_range_name,y_range_name:this.model.y_range_name},{silent:!0}),this.glyph.set_data(n,this.all_indices,e),this.glyph.set_visuals(n),this.decimated_glyph.set_visuals(n),this.have_selection_glyphs()&&(this.selection_glyph.set_visuals(n),this.nonselection_glyph.set_visuals(n)),null!=this.hover_glyph&&this.hover_glyph.set_visuals(n),null!=this.muted_glyph&&this.muted_glyph.set_visuals(n);var r=this.plot_model.plot.lod_factor;this.decimated=[];for(var o=0,s=Math.floor(this.all_indices.length/r);o0?d[\"1d\"].indices:function(){for(var t=[],e=0,i=Object.keys(d[\"2d\"].indices);e0&&!i&&null!=y&&this.all_indices.length>y?(s=this.decimated,f=this.decimated_glyph,v=this.decimated_glyph,m=this.selection_glyph):(f=this.model.muted&&null!=this.muted_glyph?this.muted_glyph:this.glyph,v=this.nonselection_glyph,m=this.selection_glyph),null!=this.hover_glyph&&g.length&&(s=u.difference(s,g));var b,x=null;if(c.length&&this.have_selection_glyphs()){for(var w=Date.now(),k={},S=0,C=c;S0){for(var a=i[0],l=0,h=i;l0){for(var a=i[0],l=0,h=i;l0?this.selected_glyphs[0]:null},enumerable:!0,configurable:!0}),e.prototype.add_to_selected_glyphs=function(t){this.selected_glyphs.push(t)},e.prototype.update=function(t,e,i){this.final=e,i?this.update_through_union(t):(this.indices=t.indices,this.line_indices=t.line_indices,this.selected_glyphs=t.selected_glyphs,this.get_view=t.get_view,this.multiline_indices=t.multiline_indices)},e.prototype.clear=function(){this.final=!0,this.indices=[],this.line_indices=[],this.multiline_indices={},this.get_view=function(){return null},this.selected_glyphs=[]},e.prototype.is_empty=function(){return 0==this.indices.length&&0==this.line_indices.length},e.prototype.update_through_union=function(t){this.indices=s.union(t.indices,this.indices),this.selected_glyphs=s.union(t.selected_glyphs,this.selected_glyphs),this.line_indices=s.union(t.line_indices,this.line_indices),this.get_view()||(this.get_view=t.get_view),this.multiline_indices=a.merge(t.multiline_indices,this.multiline_indices)},e.prototype.update_through_intersection=function(t){this.indices=s.intersection(t.indices,this.indices),this.selected_glyphs=s.union(t.selected_glyphs,this.selected_glyphs),this.line_indices=s.union(t.line_indices,this.line_indices),this.get_view()||(this.get_view=t.get_view),this.multiline_indices=a.merge(t.multiline_indices,this.multiline_indices)},e}(r.Model);i.Selection=l,l.initClass()},function(t,e,i){var n=t(379),r=t(189),o=t(14),s=t(15),a=function(t){function e(e){var i=t.call(this,e)||this;return i.initialized=!1,i}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"AjaxDataSource\",this.define({mode:[s.String,\"replace\"],content_type:[s.String,\"application/json\"],http_headers:[s.Any,{}],max_size:[s.Number],method:[s.String,\"POST\"],if_modified:[s.Bool,!1]})},e.prototype.destroy=function(){null!=this.interval&&clearInterval(this.interval),t.prototype.destroy.call(this)},e.prototype.setup=function(){var t=this;if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),this.polling_interval)){var e=function(){return t.get_data(t.mode,t.max_size,t.if_modified)};this.interval=setInterval(e,this.polling_interval)}},e.prototype.get_data=function(t,e,i){var n=this;void 0===e&&(e=0),void 0===i&&(i=!1);var r=this.prepare_request();r.addEventListener(\"load\",function(){return n.do_load(r,t,e)}),r.addEventListener(\"error\",function(){return n.do_error(r)}),r.send()},e.prototype.prepare_request=function(){var t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);var e=this.http_headers;for(var i in e){var n=e[i];t.setRequestHeader(i,n)}return t},e.prototype.do_load=function(t,e,i){if(200===t.status){var n=JSON.parse(t.responseText);switch(e){case\"replace\":this.data=n;break;case\"append\":for(var r=this.data,o=0,s=this.columns();o0?this.indices=a.intersection.apply(this,e):this.source instanceof l.ColumnarDataSource&&(this.indices=this.source.get_indices()),this.indices_map_to_subset()},e.prototype.indices_map_to_subset=function(){this.indices_map={};for(var t=0;ti?n.slice(-i):n}if(_.isTypedArray(t)){var r=t.length+e.length;if(null!=i&&r>i){var o=r-i,s=t.length,n=void 0;t.length1&&o.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");for(var p=t.coordinates[0],u=0;u1&&o.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),v.push(y[0])}for(var c=v.reduce(r),u=0;ui&&l0&&h.length>0){for(var _=r/c,p=s.range(0,c).map(function(t){return t*_}),d=0,f=p.slice(1);d1?this.interval=(e[1]-e[0])*o.ONE_DAY:this.interval=31*o.ONE_DAY},e.prototype.get_ticks_no_defaults=function(t,e,i,n){var r=function(t,e){var i=o.last_month_no_later_than(new Date(t)),n=o.last_month_no_later_than(new Date(e));n.setUTCMonth(n.getUTCMonth()+1);var r=[],s=i;for(;r.push(o.copy_date(s)),s.setUTCMonth(s.getUTCMonth()+1),!(s>n););return r}(t,e),s=this.days,l=this.interval,h=a.concat(r.map(function(t){return function(t,e){for(var i=[],n=0,r=s;n0&&o.length>0){for(var f=_/s,v=r.range(0,s).map(function(t){return t*f}),m=0,g=v.slice(1);m0&&o.length>0){for(var E=Math.pow(l,A)/s,v=r.range(1,s+1).map(function(t){return t*E}),M=0,O=v;M1?this.interval=(e[1]-e[0])*o.ONE_MONTH:this.interval=12*o.ONE_MONTH},e.prototype.get_ticks_no_defaults=function(t,e,i,n){var r=function(t,e){var i=o.last_year_no_later_than(new Date(t)),n=o.last_year_no_later_than(new Date(e));n.setUTCFullYear(n.getUTCFullYear()+1);var r=[],s=i;for(;r.push(o.copy_date(s)),s.setUTCFullYear(s.getUTCFullYear()+1),!(s>n););return r}(t,e),s=this.months,l=a.concat(r.map(function(t){return s.map(function(e){var i=o.copy_date(t);return i.setUTCMonth(e),i})})),h=l.map(function(t){return t.getTime()}),c=h.filter(function(i){return t<=i&&i<=e});return{major:c,minor:[]}},e}(r.SingleIntervalTicker);i.MonthsTicker=l,l.initClass()},function(t,e,i){var n=t(379),r=t(194),o=t(15),s=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"SingleIntervalTicker\",this.define({interval:[o.Number]})},e.prototype.get_interval=function(t,e,i){return this.interval},Object.defineProperty(e.prototype,\"min_interval\",{get:function(){return this.interval},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"max_interval\",{get:function(){return this.interval},enumerable:!0,configurable:!0}),e}(r.ContinuousTicker);i.SingleIntervalTicker=s,s.initClass()},function(t,e,i){var n=t(379),r=t(53),o=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"Ticker\"},e}(r.Model);i.Ticker=o,o.initClass()},function(t,e,i){function n(t){return new Date(t.getTime())}function r(t){var e=n(t);return e.setUTCDate(1),e.setUTCHours(0),e.setUTCMinutes(0),e.setUTCSeconds(0),e.setUTCMilliseconds(0),e}i.ONE_MILLI=1,i.ONE_SECOND=1e3,i.ONE_MINUTE=60*i.ONE_SECOND,i.ONE_HOUR=60*i.ONE_MINUTE,i.ONE_DAY=24*i.ONE_HOUR,i.ONE_MONTH=30*i.ONE_DAY,i.ONE_YEAR=365*i.ONE_DAY,i.copy_date=n,i.last_month_no_later_than=r,i.last_year_no_later_than=function(t){var e=r(t);return e.setUTCMonth(0),e}},function(t,e,i){var n=t(379),r=t(191),o=t(202),s=t(204),a=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"YearsTicker\"},e.prototype.initialize=function(){t.prototype.initialize.call(this),this.interval=s.ONE_YEAR,this.basic_ticker=new r.BasicTicker({num_minor_ticks:0})},e.prototype.get_ticks_no_defaults=function(t,e,i,n){var r=s.last_year_no_later_than(new Date(t)).getUTCFullYear(),o=s.last_year_no_later_than(new Date(e)).getUTCFullYear(),a=this.basic_ticker.get_ticks_no_defaults(r,o,i,n).major,l=a.map(function(t){return Date.UTC(t,0,1)}),h=l.filter(function(i){return t<=i&&i<=e});return{major:h,minor:[]}},e}(o.SingleIntervalTicker);i.YearsTicker=a,a.initClass()},function(t,e,i){var n=t(379),r=t(209),o=t(15),s=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"BBoxTileSource\",this.define({use_latlon:[o.Bool,!1]})},e.prototype.get_image_url=function(t,e,i){var n,r,o,s,a=this.string_lookup_replace(this.url,this.extra_url_vars);return this.use_latlon?(l=this.get_tile_geographic_bounds(t,e,i),r=l[0],s=l[1],n=l[2],o=l[3]):(h=this.get_tile_meter_bounds(t,e,i),r=h[0],s=h[1],n=h[2],o=h[3]),a.replace(\"{XMIN}\",r.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",n.toString()).replace(\"{YMAX}\",o.toString());var l,h},e}(r.MercatorTileSource);i.BBoxTileSource=s,s.initClass()},function(t,e,i){var n=t(44),r=function(){function t(){this.images=[]}return t.prototype.pop=function(){var t=this.images.pop();return null!=t?t:new Image},t.prototype.push=function(t){if(!(this.images.length>50)){n.isArray(t)?(e=this.images).push.apply(e,t):this.images.push(t);var e}},t}();i.ImagePool=r},function(t,e,i){var n=t(206);i.BBoxTileSource=n.BBoxTileSource;var r=t(209);i.MercatorTileSource=r.MercatorTileSource;var o=t(210);i.QUADKEYTileSource=o.QUADKEYTileSource;var s=t(211);i.TileRenderer=s.TileRenderer;var a=t(212);i.TileSource=a.TileSource;var l=t(214);i.TMSTileSource=l.TMSTileSource;var h=t(215);i.WMTSTileSource=h.WMTSTileSource},function(t,e,i){var n=t(379),r=t(212),o=t(15),s=t(21),a=t(213),l=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"MercatorTileSource\",this.define({snap_to_zoom:[o.Bool,!1],wrap_around:[o.Bool,!0]}),this.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})},e.prototype.initialize=function(){var e=this;t.prototype.initialize.call(this),this._resolutions=s.range(this.min_zoom,this.max_zoom+1).map(function(t){return e.get_resolution(t)})},e.prototype._computed_initial_resolution=function(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size},e.prototype.is_valid_tile=function(t,e,i){return!(!this.wrap_around&&(t<0||t>=Math.pow(2,i)))&&!(e<0||e>=Math.pow(2,i))},e.prototype.parent_by_tile_xyz=function(t,e,i){var n=this.tile_xyz_to_quadkey(t,e,i),r=n.substring(0,n.length-1);return this.quadkey_to_tile_xyz(r)},e.prototype.get_resolution=function(t){return this._computed_initial_resolution()/Math.pow(2,t)},e.prototype.get_resolution_by_extent=function(t,e,i){var n=(t[2]-t[0])/i,r=(t[3]-t[1])/e;return[n,r]},e.prototype.get_level_by_extent=function(t,e,i){for(var n=(t[2]-t[0])/i,r=(t[3]-t[1])/e,o=Math.max(n,r),s=0,a=0,l=this._resolutions;ah){if(0===s)return 0;if(s>0)return s-1}s+=1}throw new Error(\"unreachable code\")},e.prototype.get_closest_level_by_extent=function(t,e,i){var n=(t[2]-t[0])/i,r=(t[3]-t[1])/e,o=Math.max(n,r),s=this._resolutions.reduce(function(t,e){return Math.abs(e-o)_?(h=s-r,c*=u):(h*=_,c=a-o)}var p=(h-(s-r))/2,d=(c-(a-o))/2;return[r-p,o-d,s+p,a+d]},e.prototype.tms_to_wmts=function(t,e,i){\"Note this works both ways\";return[t,Math.pow(2,i)-1-e,i]},e.prototype.wmts_to_tms=function(t,e,i){\"Note this works both ways\";return[t,Math.pow(2,i)-1-e,i]},e.prototype.pixels_to_meters=function(t,e,i){var n=this.get_resolution(i),r=t*n-this.x_origin_offset,o=e*n-this.y_origin_offset;return[r,o]},e.prototype.meters_to_pixels=function(t,e,i){var n=this.get_resolution(i),r=(t+this.x_origin_offset)/n,o=(e+this.y_origin_offset)/n;return[r,o]},e.prototype.pixels_to_tile=function(t,e){var i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;var n=Math.max(Math.ceil(e/this.tile_size)-1,0);return[i,n]},e.prototype.pixels_to_raster=function(t,e,i){var n=this.tile_size<=h;d--)for(var f=l;f<=u;f++)this.is_valid_tile(f,d,e)&&p.push([f,d,e,this.get_tile_meter_bounds(f,d,e)]);return this.sort_tiles_from_center(p,[l,h,u,_]),p},e.prototype.quadkey_to_tile_xyz=function(t){for(var e=0,i=0,n=t.length,r=n;r>0;r--){var o=t.charAt(n-r),s=1<0;r--){var o=1<0;)if(r=r.substring(0,r.length-1),s=this.quadkey_to_tile_xyz(r),t=s[0],e=s[1],i=s[2],a=this.denormalize_xyz(t,e,i,n),t=a[0],e=a[1],i=a[2],this.tile_xyz_to_key(t,e,i)in this.tiles)return[t,e,i];return[0,0,0];var o,s,a},e.prototype.normalize_xyz=function(t,e,i){if(this.wrap_around){var n=Math.pow(2,i);return[(t%n+n)%n,e,i]}return[t,e,i]},e.prototype.denormalize_xyz=function(t,e,i,n){return[t+n*Math.pow(2,i),e,i]},e.prototype.denormalize_meters=function(t,e,i,n){return[t+2*n*Math.PI*6378137,e]},e.prototype.calculate_world_x_by_tile_xyz=function(t,e,i){return Math.floor(t/Math.pow(2,i))},e}(r.TileSource);i.MercatorTileSource=l,l.initClass()},function(t,e,i){var n=t(379),r=t(209),o=function(t){function e(e){return t.call(this,e)||this}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"QUADKEYTileSource\"},e.prototype.get_image_url=function(t,e,i){var n=this.string_lookup_replace(this.url,this.extra_url_vars),r=this.tms_to_wmts(t,e,i),o=r[0],s=r[1],a=r[2],l=this.tile_xyz_to_quadkey(o,s,a);return n.replace(\"{Q}\",l)},e}(r.MercatorTileSource);i.QUADKEYTileSource=o,o.initClass()},function(t,e,i){var n=t(379),r=t(207),o=t(215),s=t(173),a=t(5),l=t(15),h=t(21),c=t(44),u=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype.initialize=function(e){this.attributionEl=null,this._tiles=[],t.prototype.initialize.call(this,e)},e.prototype.connect_signals=function(){var e=this;t.prototype.connect_signals.call(this),this.connect(this.model.change,function(){return e.request_render()})},e.prototype.get_extent=function(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]},Object.defineProperty(e.prototype,\"map_plot\",{get:function(){return this.plot_model.plot},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"map_canvas\",{get:function(){return this.plot_view.canvas_view.ctx},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"map_frame\",{get:function(){return this.plot_model.frame},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"x_range\",{get:function(){return this.map_plot.x_range},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"y_range\",{get:function(){return this.map_plot.y_range},enumerable:!0,configurable:!0}),e.prototype._set_data=function(){this.pool=new r.ImagePool,this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0},e.prototype._add_attribution=function(){var t=this.model.tile_source.attribution;if(c.isString(t)&&t.length>0){if(null==this.attributionEl){var e=this.plot_model.canvas._right.value-this.plot_model.frame._right.value,i=this.plot_model.canvas._bottom.value-this.plot_model.frame._bottom.value,n=this.map_frame._width.value;this.attributionEl=a.div({class:\"bk-tile-attribution\",style:{position:\"absolute\",bottom:i+\"px\",right:e+\"px\",\"max-width\":n+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.8)\",\"font-size\":\"9pt\",\"font-family\":\"sans-serif\"}});var r=this.plot_view.canvas_view.events_el;r.appendChild(this.attributionEl)}this.attributionEl.innerHTML=t}},e.prototype._map_data=function(){this.initial_extent=this.get_extent();var t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame._height.value,this.map_frame._width.value),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame._height.value,this.map_frame._width.value,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this._add_attribution()},e.prototype._on_tile_load=function(t,e){t.img=e.target,t.loaded=!0,this.request_render()},e.prototype._on_tile_cache_load=function(t,e){t.img=e.target,t.loaded=!0,t.finished=!0,this.notify_finished()},e.prototype._on_tile_error=function(t){t.finished=!0},e.prototype._create_tile=function(t,e,i,n,r){void 0===r&&(r=!1);var o=this.model.tile_source.normalize_xyz(t,e,i),s=o[0],a=o[1],l=o[2],h=this.pool.pop(),c={img:h,tile_coords:[t,e,i],normalized_coords:[s,a,l],quadkey:this.model.tile_source.tile_xyz_to_quadkey(t,e,i),cache_key:this.model.tile_source.tile_xyz_to_key(t,e,i),bounds:n,loaded:!1,finished:!1,x_coord:n[0],y_coord:n[3]};h.onload=r?this._on_tile_cache_load.bind(this,c):this._on_tile_load.bind(this,c),h.onerror=this._on_tile_error.bind(this,c),h.alt=\"\",h.src=this.model.tile_source.get_image_url(s,a,l),this.model.tile_source.tiles[c.cache_key]=c,this._tiles.push(c)},e.prototype._enforce_aspect_ratio=function(){if(this._last_height!==this.map_frame._height.value||this._last_width!==this.map_frame._width.value){var t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame._height.value,this.map_frame._width.value),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame._height.value,this.map_frame._width.value,e);return this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame._height.value,this._last_width=this.map_frame._width.value,!0}return!1},e.prototype.has_finished=function(){if(!t.prototype.has_finished.call(this))return!1;if(0===this._tiles.length)return!1;for(var e=0,i=this._tiles;en&&(r=this.extent,l=n,c=!0),c&&(this.x_range.setv({x_range:{start:r[0],end:r[2]}}),this.y_range.setv({start:r[1],end:r[3]}),this.extent=r),this.extent=r;for(var u=e.get_tiles_by_extent(r,l),_=[],p=[],d=[],f=[],v=0,m=u;v=o?[1,_/o]:[o/_,1])[0];t[0]<=e[0]?(n=t[0],(r=t[0]+c*p)>s&&(r=s)):(r=t[0],(n=t[0]-c*p)l&&(d=l)):(d=t[1],(f=t[1]-c/o)r.end)&&(this.v_axis_only=!0),(io.end)&&(this.h_axis_only=!0)}null!=this.model.document&&this.model.document.interactive_start(this.plot_model.plot)},e.prototype._pan=function(t){this._update(t.deltaX,t.deltaY),null!=this.model.document&&this.model.document.interactive_start(this.plot_model.plot)},e.prototype._pan_end=function(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.push_state(\"pan\",{range:this.pan_info})},e.prototype._update=function(t,e){var i,n,r,o=this.plot_model.frame,s=t-this.last_dx,a=e-this.last_dy,l=o.bbox.h_range,h=l.start-s,c=l.end-s,u=o.bbox.v_range,_=u.start-a,p=u.end-a,d=this.model.dimensions;\"width\"!=d&&\"both\"!=d||this.v_axis_only?(i=l.start,n=l.end,r=0):(i=h,n=c,r=-s);var f,v,m;\"height\"!=d&&\"both\"!=d||this.h_axis_only?(f=u.start,v=u.end,m=0):(f=_,v=p,m=-a),this.last_dx=t,this.last_dy=e;var g=o.xscales,y=o.yscales,b={};for(var x in g){var w=g[x],k=w.r_invert(i,n),S=k[0],C=k[1];b[x]={start:S,end:C}}var T={};for(var A in y){var w=y[A],E=w.r_invert(f,v),S=E[0],C=E[1];T[A]={start:S,end:C}}this.pan_info={xrs:b,yrs:T,sdx:r,sdy:m},this.plot_view.update_range(this.pan_info,!0)},e}(r.GestureToolView);i.PanToolView=s;var a=function(t){function e(e){var i=t.call(this,e)||this;return i.tool_name=\"Pan\",i.event_type=\"pan\",i.default_order=10,i}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"PanTool\",this.prototype.default_view=s,this.define({dimensions:[o.Dimensions,\"both\"]})},Object.defineProperty(e.prototype,\"tooltip\",{get:function(){return this._get_dim_tooltip(\"Pan\",this.dimensions)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,\"icon\",{get:function(){switch(this.dimensions){case\"both\":return\"bk-tool-icon-pan\";case\"width\":return\"bk-tool-icon-xpan\";case\"height\":return\"bk-tool-icon-ypan\"}},enumerable:!0,configurable:!0}),e}(r.GestureTool);i.PanTool=a,a.initClass()},function(t,e,i){var n=t(379),r=t(236),o=t(65),s=t(5),a=t(15),l=t(21),h=t(32),c=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),e.prototype.initialize=function(e){t.prototype.initialize.call(this,e),this.data={sx:[],sy:[]}},e.prototype.connect_signals=function(){var e=this;t.prototype.connect_signals.call(this),this.connect(this.model.properties.active.change,function(){return e._active_change()})},e.prototype._active_change=function(){this.model.active||this._clear_data()},e.prototype._keyup=function(t){t.keyCode==s.Keys.Enter&&this._clear_data()},e.prototype._doubletap=function(t){var e=t.shiftKey;this._do_select(this.data.sx,this.data.sy,!0,e),this.plot_view.push_state(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()},e.prototype._clear_data=function(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})},e.prototype._tap=function(t){var e=t.sx,i=t.sy,n=this.plot_model.frame;n.bbox.contains(e,i)&&(this.data.sx.push(e),this.data.sy.push(i),this.model.overlay.update({xs:l.copy(this.data.sx),ys:l.copy(this.data.sy)}))},e.prototype._do_select=function(t,e,i,n){var r={type:\"poly\",sx:t,sy:e};this._select(r,i,n)},e.prototype._emit_callback=function(t){var e=this.computed_renderers[0],i=this.plot_model.frame,n=i.xscales[e.x_range_name],r=i.yscales[e.y_range_name],o=n.v_invert(t.sx),s=r.v_invert(t.sy),a=h.extend({x:o,y:s},t);this.model.callback.execute(this.model,{geometry:a})},e}(r.SelectToolView);i.PolySelectToolView=c;var u=function(){return new o.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:{value:\"lightgrey\"},fill_alpha:{value:.5},line_color:{value:\"black\"},line_alpha:{value:1},line_width:{value:2},line_dash:{value:[4,4]}})},_=function(t){function e(e){var i=t.call(this,e)||this;return i.tool_name=\"Poly Select\",i.icon=\"bk-tool-icon-polygon-select\",i.event_type=\"tap\",i.default_order=11,i}return n.__extends(e,t),e.initClass=function(){this.prototype.type=\"PolySelectTool\",this.prototype.default_view=c,this.define({callback:[a.Instance],overlay:[a.Instance,u]})},e}(r.SelectTool);i.PolySelectTool=_,_.initClass()},function(t,e,i){var n=t(379),r=t(232),o=t(169),s=t(170),a=t(15),l=t(32),h=t(21),c=t(5),u=t(3),_=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n.__extends(e,t),Object.defineProperty(e.prototype,\"computed_renderers\",{get:function(){var t=this.model.renderers,e=this.model.names;if(0==t.length){var i=this.plot_model.plot.renderers;t=i.filter(function(t){return t instanceof o.GlyphRenderer||t instanceof s.GraphRenderer})}return e.length>0&&(t=t.filter(function(t){return h.includes(e,t.name)})),t},enumerable:!0,configurable:!0}),e.prototype._computed_renderers_by_data_source=function(){for(var t={},e=0,i=this.computed_renderers;e.9?e=.9:e<-.9&&(e=-.9),this._update_ranges(e)},e.prototype._update_ranges=function(t){var e,i,n,r,o=this.plot_model.frame,s=o.bbox.h_range,a=o.bbox.v_range,l=[s.start,s.end],h=l[0],c=l[1],u=[a.start,a.end],_=u[0],p=u[1];switch(this.model.dimension){case\"height\":var d=Math.abs(p-_);e=h,i=c,n=_-d*t,r=p-d*t;break;case\"width\":var 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+ " Copyright (c) 2012, Anaconda, Inc.\n", + " All rights reserved.\n", + "\n", + " Redistribution and use in source and binary forms, with or without modification,\n", + " are permitted provided that the following conditions are met:\n", + "\n", + " Redistributions of source code must retain the above copyright notice,\n", + " this list of conditions and the following disclaimer.\n", + "\n", + " Redistributions in binary form must reproduce the above copyright notice,\n", + " this list of conditions and the following disclaimer in the documentation\n", + " and/or other materials provided with the distribution.\n", + "\n", + " Neither the name of Anaconda nor the names of any contributors\n", + " may be used to endorse or promote products derived from this software\n", + " without specific prior written permission.\n", + "\n", + " THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", + " AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", + " IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", + " ARE DISCLAIMED. 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" + ], + "text/plain": [ + ":Bars [Country Name] (2010)" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "bar = charts.Bar(gdp.loc[BRICS], values='2010', \n", - " plot_height=400, legend=None, color='#0067A9')\n", - "show(bar)" + "%%opts Bars [width=600, height=400, tools=['hover']] (color='#0067A9')\n", + "bar = hv.Bars(gdp.loc[BRICS,'2010'].reset_index(), 'Country Name','2010')\n", + "bar" ] }, { @@ -447,342 +1295,136 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 370, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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Application\",\"version\":\"0.12.15\"}};\n", + " var render_items = [{\"docid\":\"5acf1b1f-c815-4915-9261-2122d65071a1\",\"elementid\":\"f7653b02-9a80-43d2-b028-dd29c65aeb21\",\"modelid\":\"f3127248-423b-4378-acaa-96beaf8dbfdf\"}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " clearInterval(timer);\n", + " }\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n", + " clearInterval(timer);\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);\n", + "\n", + "
" + ], + "text/plain": [ + ":Bars [variable,Country Name] (value)" ] }, + "execution_count": 370, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ + "%%opts Bars [height=500, width=700, xrotation=90, show_legend=False] (color=Cycle(Set1_7))\n", "dados = gdplong[(gdplong['Country Name'].isin(BRICS)) & \\\n", - " (gdplong['variable'].isin(['1990','1995','2000','2005','2010','2014']))]\n", - "bar = charts.Bar(dados, values='value', group='Country Name', label='variable',\n", - " color=Set1_7,plot_height=400,plot_width=800)\n", - "show(bar)" + " (gdplong['variable'].isin(['1990','1995','2000','2005','2010','2014']))].copy()\n", + "from pandas.api.types import CategoricalDtype\n", + "dados['Country Name'] = dados.loc[:,'Country Name'].astype(CategoricalDtype(BRICS,ordered=True))\n", + "bar = hv.Bars(dados,kdims=['variable','Country Name'],vdims='value')\n", + "#bar = hv.Bars(dados,kdims=['Country Name','variable'],vdims='value')\n", + "bar.sort(by='Country Name')\n", + "#bar.sort(by=['Country Name','variable'])\n", + "#bar.sort(by='Country Name').groupby('variable')\n", + "#bar.groupby('Country Name')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Uma funcionalidade interessante dos gráficos básicos de Bokeh é a computação de funções de agregação dos dados. Assim, ao contrário dos gráficos com Matplotlib em Pandas, podemos passar a tabela de dados para a função normalmente e especificar a forma como os dados devem ser sumarizados. De fato, esse parâmetro é obrigatório e possui como valor padrão a soma dos dados em cada séries. As possíveis funções de agregação são: sum, mean, count, nunique, median, min, max. Elas devem ser passadas como strings.\n", + "Uma funcionalidade interessante de HoloViews é a computação de funções de agregação dos dados. Assim, ao contrário dos gráficos com Matplotlib em Pandas, podemos passar a tabela de dados para a função normalmente e especificar a forma como os dados devem ser sumarizados. A função `aggregate` espera como parâmetro a coluna em que os dados serão agrupados e a função que será aplicada aos valores. Essa coluna deve ser uma das colunas definidas como `kdims`.\n", "\n", "A seguir construimos um gráfico em que mostramos a expectativa de vida média dos países dos BRICS." ] }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "collapsed": false - }, + "execution_count": 376, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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Application\",\"version\":\"0.12.15\"}};\n", + " var render_items = [{\"docid\":\"f99c71ab-bb71-4a1a-98c5-5861a6aae80d\",\"elementid\":\"f7b833e9-eb17-4b39-8772-aee773177019\",\"modelid\":\"5b82c080-9072-4ac9-8ee2-b98ebb7915ca\"}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " clearInterval(timer);\n", + " }\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n", + " clearInterval(timer);\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);\n", + "\n", + "
" + ], + "text/plain": [ + ":Bars [Country Name] (value)" ] }, + "execution_count": 376, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "bar = charts.Bar(evidalong[evidalong['Country Name'].isin(BRICS)], \n", - " values='value', label='Country Name', agg='median',\n", - " plot_height=400, legend=None)\n", - "show(bar)" + "%%opts Bars [height=500, width=700, xrotation=90, show_legend=False] (color=Cycle(Set1_7)) \n", + "dados = evidalong[evidalong['Country Name'].isin(BRICS)].copy()\n", + "from pandas.api.types import CategoricalDtype\n", + "dados['Country Name'] = dados.loc[:,'Country Name'].astype(CategoricalDtype(BRICS,ordered=True))\n", + "bar = hv.Bars(dados,kdims=['Country Name','variable'],vdims='value')\n", + "bar.aggregate('Country Name',function=np.median)" ] }, { @@ -796,166 +1438,61 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 381, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":Histogram [x] (Frequency)" ] }, + "execution_count": 381, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "hist = charts.Histogram(expvida['1960'].dropna(), bins=20, plot_height=400)\n", - "hist.x_range=Range1d(0,100)\n", - "show(hist)" + "%%output size=130\n", + "%%opts Histogram (color=Cycle(Set1_7), alpha=0.6) \n", + "hist = hv.Histogram(np.histogram(expvida['1960'].dropna(),bins=20,range=(0,100)))\n", + "hist\n", + "#hv.Dataset(expvida['1960'].dropna().reset_index()).hist(dimension='1960',adjoin=False)" ] }, { @@ -969,176 +1506,71 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 385, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":NdOverlay [variable]\n", + " :Histogram [value] (value_frequency)" ] }, + "execution_count": 385, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "dados = evidalong[evidalong.variable.isin(['1960','1980','2000','2014'])].dropna()\n", - "hist = charts.Histogram(dados, values='value',label='variable', color='variable',\n", - " fill_alpha=0.3, density=True,\n", - " bins=20, plot_height=400)\n", - "hist.x_range=Range1d(0,100)\n", - "show(hist)" + "%%output size=120\n", + "%%opts Histogram [show_legend=True] (color=Cycle(Set1_7), fill_alpha=0.6) \n", + "ds = hv.Dataset(evidalong.dropna())\n", + "ds.select(variable=['1960','2014']).hist(dimension='value',groupby='variable',adjoin=False)\n", + "#ds.select(variable=('1960','1963')).hist(dimension='value',groupby='variable',adjoin=False)\n", + "#hv.HoloMap({ano:ds.select(variable=ano).hist(dimension='value',groupby='variable',adjoin=False)\\\n", + "# for ano in ['1960','1980','2014']},kdims='ano')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Infelizmente Bokeh não conta com uma função para desenhar gráficos de densidade nem compô-los com o histograma, tal como fizemos com Seaborn. É possível fazê-lo, porém com a interface intermediária. Quando apresentarmos a interface intermediária, voltaremos a esse exemplo." + "~~Infelizmente Bokeh não conta com uma função para desenhar gráficos de densidade nem compô-los com o histograma, tal como fizemos com Seaborn. É possível fazê-lo, porém com a interface intermediária. Quando apresentarmos a interface intermediária, voltaremos a esse exemplo.~~" ] }, { @@ -1152,1246 +1584,293 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "
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\n", - "
\n", - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dados = evidalong[evidalong['Country Name'].isin(BRICS)]\n", - "box = charts.BoxPlot(dados,values='value',label='Country Name', \n", - " legend=None, plot_height=500, \n", - " color='Country Name')\n", - " #color='#dddddd')\n", - "show(box)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "Bokeh também possui uma interface bem amigável para combinar vários gráficos em um painel. As diversas funções para especificar a diagramação da exibição estão no submódulo `bokeh.layouts`." - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from bokeh.layouts import row" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "
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\n", - "
\n", - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dados = evidalong[evidalong['Country Name'].isin(BRICS)]\n", - "box = charts.BoxPlot(dados,values='value',label='Country Name', \n", - " legend=None, plot_height=400, plot_width=450, \n", - " color='#dddddd', tools='')\n", - "dados = gdplong[gdplong['Country Name'].isin(BRICS)]\n", - "box1 = charts.BoxPlot(dados,values='value',label='Country Name', \n", - " legend=None, plot_height=400, plot_width=450, \n", - " color='#dddddd', tools='')\n", - "show(row([box,box1]))" - ] - }, - { - "cell_type": "markdown", + "execution_count": 212, "metadata": {}, - "source": [ - "#### Gráficos de dispersão\n", - "\n", - "Para os gráficos de dispersão, devemos especificar as colunas que representam os eixos x e y nos dados. Ambas as colunas devem ser numéricas, naturalmente. \n", - "\n", - "Em nosso exemplo, vamos criar um novo conjunto de dados formado pela expectativa de vida dos países em 1960 e o eixo x será simplesmente o índice da linha." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "
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\n", - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dados = pd.DataFrame({'x':np.arange(1,expvida['1960'].shape[0]+1), 'y':expvida['1960']})\n", - "scatter = charts.Scatter(dados,x='x',y='y',plot_height=400)\n", - "show(scatter)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Vamos criar um outro exemplo para explorar os dados do PIB dos BRICS ao longo dos anos." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":BoxWhisker [Country Name] (value)" ] }, + "execution_count": 212, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "dados = gdplong.loc[gdplong['Country Name'].isin(BRICS[:-2])].dropna()\n", - "dados[['variable','value']].astype(np.number,inplace=True)\n", - "scatter = charts.Scatter(dados,x='variable',y='value',\n", - " plot_height=400, plot_width=900,\n", - " color='Country Name')\n", - "show(scatter)" + "%%opts BoxWhisker [height=500, width=700, xrotation=90, show_legend=False] (box_color='#0067A9',box_fill_alpha=0.4)\n", + "boxplot = hv.BoxWhisker(evidalong,kdims=['Country Name'],vdims='value')\n", + "boxplot[BRICS]" ] }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "collapsed": true + }, "source": [ - "#### Gráfico de linha\n", - "\n", - "O gráfico de linha segue a mesma lógica do gráfico de dispersão. Devemos informar o conjunto de dados e as colunas representando os eixos x e y do gráfico. Para exemplificar, vamos recriar o exemplo da aula passada, exibindo a variação do PIB e expectativa de vida dos BRICS." + "HoloViews também possui uma interface bem amigável para combinar vários gráficos em um. Basicamente, para sobrepor ou justapor dois gráficos, são usados os operadores `*` e `+`." ] }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 390, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":Layout\n", + " .BoxWhisker.I :BoxWhisker [Country Name] (anos)\n", + " .BoxWhisker.II :BoxWhisker [Country Name] (dólares)" ] }, + "execution_count": 390, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "dados = gdplong.loc[gdplong['Country Name'].isin(BRICS[:-2])].dropna()\n", - "dados.variable = dados.variable.astype(int)\n", - "dados.value = dados.value.astype(np.number)\n", - "line = charts.Line(dados,x='variable',y='value',\n", - " plot_height=400, plot_width=450,\n", - " color='Country Name')\n", - "\n", - "dados = evidalong.loc[evidalong['Country Name'].isin(BRICS[:-2])].dropna()\n", - "dados.variable = dados.variable.astype(int)\n", - "dados.value = dados.value.astype(np.number)\n", - "line1 = charts.Line(dados,x='variable',y='value',\n", - " plot_height=400, plot_width=450, legend='bottom_right',\n", - " color='Country Name')\n", - "show(row([line,line1]))" + "%%output size=150\n", + "%%opts BoxWhisker [xrotation=90, show_legend=False] (box_color='#0067A9',box_fill_alpha=0.4)\n", + "boxplot_ev = hv.BoxWhisker(evidalong.rename(columns={'value': 'anos'}, inplace=False),kdims=['Country Name'],vdims='anos')\n", + "boxplot_pib = hv.BoxWhisker(gdplong.rename(columns={'value': 'dólares'}, inplace=False),kdims=['Country Name'],vdims='dólares')\n", + "layout = boxplot_ev[BRICS] + boxplot_pib[BRICS]\n", + "layout\n", + "#(boxplot_ev[BRICS] + boxplot_pib[BRICS]).cols(1)" ] }, { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, - "outputs": [], + "cell_type": "markdown", + "metadata": {}, "source": [ - "line.legend.background_fill_alpha = 0\n", - "line1.legend.background_fill_alpha = 0\n", - "line.yaxis[0].formatter = NumeralTickFormatter(format=\"$0,0a\")" + "#### Gráficos de dispersão\n", + "\n", + "Para os gráficos de dispersão, devemos especificar as colunas que representam os eixos x e y nos dados. Ambas as colunas devem ser numéricas, naturalmente. \n", + "\n", + "Em nosso exemplo, vamos criar um gráfico para explorar os dados do PIB dos BRICS ao longo dos anos." ] }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 395, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":NdOverlay [Country Name]\n", + " :Scatter [variable] (value,Country Name)" ] }, + "execution_count": 395, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "show(row([line,line1]))" + "%%opts Scatter [width=800,xrotation=90,legend_position='right' tools=['hover']]\n", + "%%opts NdOverlay [width=800,xrotation=90,legend_position='right']\n", + "dados = gdplong.loc[gdplong['Country Name'].isin(BRICS[:-2])]\n", + "dados[['variable','value']].astype(np.number,inplace=True)\n", + "hv.Scatter(dados,kdims=['variable'],vdims=['value','Country Name']).groupby('Country Name').overlay()\n", + "#hv.Dataset(dados).to(hv.Points,['variable','value'],groupby='Country Name').overlay()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Gráficos de escada\n", + "#### Gráfico de linha\n", "\n", - "O gráfico de linha nos exemplos acima pode ser um tanto enganoso, uma vez que os dados foram coletados anualmente. O gráfico de linha passa a impressão de uma variação contínua. Isso não acontece de fato. Podemos usar um gráfico de escada para representar melhor as alterações ocorridas. Bokeh possui uma função para isso. A sintaxe é exatamente igual à dos gráficos de linha." + "O gráfico de linha segue a mesma lógica do gráfico de dispersão. Devemos informar o conjunto de dados e as colunas representando os eixos x e y do gráfico. Para exemplificar, vamos recriar o exemplo da aula passada, exibindo a variação do PIB e expectativa de vida dos BRICS." ] }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 397, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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" + ], + "text/plain": [ + ":Layout\n", + " .NdOverlay.I :NdOverlay [Country Name]\n", + " :Curve [variable] (PIB,Country Name)\n", + " .NdOverlay.II :NdOverlay [Country Name]\n", + " :Curve [variable] (Idade,Country Name)" ] }, + "execution_count": 397, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "dados = evidalong.loc[(evidalong['Country Name'].isin(BRICS[:-2])) & \n", - " (evidalong['variable'].isin([str(a) for a in range(1960,2015,5)]))].dropna()\n", - "dados.variable = dados.variable.astype(int)\n", - "dados.value = dados.value.astype(np.number)\n", - "escada = charts.Step(dados,x='variable',y='value',\n", - " plot_height=400, plot_width=450, legend='bottom_right',\n", - " color='Country Name')\n", - "escada.legend.background_fill_alpha = 0\n", - "show(escada)" + "%%output size=120\n", + "%%opts Curve [xrotation=90]\n", + "dados = gdplong.loc[gdplong['Country Name'].isin(BRICS[:-2])]\n", + "dados[['variable','value']].astype(np.number,inplace=True)\n", + "gdpLine = hv.Curve(dados.rename(columns={'value':'PIB'},inplace=False),\n", + " 'variable',['PIB','Country Name']).groupby('Country Name')\n", + "\n", + "dados = evidalong.loc[evidalong['Country Name'].isin(BRICS[:-2])]\n", + "dados[['variable','value']].astype(np.number,inplace=True)\n", + "evLine = hv.Curve(dados.rename(columns={'value':'Idade'},inplace=False),\n", + " 'variable',['Idade','Country Name']).groupby('Country Name')\n", + "\n", + "#gdpLine + evLine\n", + "gdpLine.overlay('Country Name') + evLine.overlay('Country Name')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "~~#### Gráficos de escada~~\n", + "\n", + "~~O gráfico de linha nos exemplos acima pode ser um tanto enganoso, uma vez que os dados foram coletados anualmente. O gráfico de linha passa a impressão de uma variação contínua. Isso não acontece de fato. Podemos usar um gráfico de escada para representar melhor as alterações ocorridas. HoloViews possui uma função para isso. A sintaxe é exatamente igual à dos gráficos de linha.~~" ] }, { @@ -2400,15 +1879,13 @@ "source": [ "#### Heatmap\n", "\n", - "Outro tipo de gráfico que é bastante útil para visualização de dados tabulares é o heatmap. Por exemplo, se quisermos ver " + "Outro tipo de gráfico que é bastante útil para visualização de dados tabulares é o heatmap. Por exemplo, se quisermos ver a relação entre as características químicas dos vinhos e a qualidade, podemos usar o heatmap para isso." ] }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": true - }, + "execution_count": 316, + "metadata": {}, "outputs": [], "source": [ "wine = pd.read_csv(\"http://mlr.cs.umass.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv\",\n", @@ -2417,10 +1894,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 317, + "metadata": {}, "outputs": [], "source": [ "wine = wine.groupby('quality').mean().apply(lambda x: (x-x.mean())/x.std())\n", @@ -2429,15 +1904,26 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 318, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -2559,7 +2045,7 @@ "4 1.671893 0.575544 " ] }, - "execution_count": 20, + "execution_count": 318, "metadata": {}, "output_type": "execute_result" } @@ -2570,180 +2056,78 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, + "execution_count": 400, + "metadata": {}, + "outputs": [], + "source": [ + "dados = pd.melt(wine,id_vars='quality')\n", + "dados.quality = dados.quality.astype('category')" + ] + }, + { + "cell_type": "code", + "execution_count": 402, + "metadata": {}, "outputs": [ { "data": { "text/html": [ + "
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Application\",\"version\":\"0.12.15\"}};\n", + " var render_items = [{\"docid\":\"0ae3ae2a-cb2c-4c11-8430-743931cf2ece\",\"elementid\":\"3e814d62-cfdc-4610-9b09-9f95624918ff\",\"modelid\":\"a65e4b09-a126-4843-85bc-c84f08e02cdb\"}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " clearInterval(timer);\n", + " }\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n", + " clearInterval(timer);\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);\n", + "\n", + "
" + ], + "text/plain": [ + ":Layout\n", + " .HeatMap.I :HeatMap [quality,variable] (value)\n", + " .HeatMap.II :HeatMap [quality,variable] (value)" ] }, + "execution_count": 402, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "dados = pd.melt(wine,id_vars='quality')\n", - "dados.quality = dados.quality.astype(str)\n", - "heatmap = charts.HeatMap(dados,x='quality',y='variable',values='value',\n", - " stat='mean',legend=False, plot_height=400,plot_width=400,\n", - " hover_tool=True, color=RdBu11)\n", - "#l = heatmap.legend\n", - "#l.location = (100,-30)\n", - "#heatmap.add_layout(Legend(items=l[0].items,location=(100,-30)))\n", - "show(heatmap)" + "%%output size=120\n", + "%%opts HeatMap [colorbar=True width=400 height=300 tools=['hover'] toolbar='above']\n", + "heatmap = hv.HeatMap(dados.groupby(['quality','variable'],as_index=False).mean())\n", + "heatmap + hv.HeatMap(dados)" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -2764,7 +2148,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula11-datavis-parte03.ipynb b/aula11-datavis-parte03.ipynb index 565bcb2..2c95aa2 100644 --- a/aula11-datavis-parte03.ipynb +++ b/aula11-datavis-parte03.ipynb @@ -10,7 +10,7 @@ "\n", "rv2 {em} cin.ufpe.br\n", "\n", - "setembro 2017" + "abril 2018" ] }, { @@ -27,17 +27,15 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", - " \n", - " Loading BokehJS ...\n", + " \n", + " Loading BokehJS ...\n", "
" ] }, @@ -48,23 +46,143 @@ "data": { "application/javascript": [ "\n", - "(function(global) {\n", + "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", - " if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", - " window._bokeh_onload_callbacks = [];\n", - " window._bokeh_is_loading = undefined;\n", + " if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id !== undefined) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var element_id = msg.content.text.trim();\n", + " Bokeh.index[element_id].model.document.clear();\n", + " delete Bokeh.index[element_id];\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", " }\n", "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", "\n", " \n", - " if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n", - " window._bokeh_timeout = Date.now() + 5000;\n", - " window._bokeh_failed_load = false;\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", @@ -84,23 +202,33 @@ " \"\"}};\n", "\n", " function display_loaded() {\n", - " if (window.Bokeh !== undefined) {\n", - " var el = document.getElementById(\"460a31b5-7f62-49a0-9eae-0bfcc4ed50f8\");\n", - " el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n", - " } else if (Date.now() < window._bokeh_timeout) {\n", + " var el = document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", + "\n", " function run_callbacks() {\n", - " window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", - " delete window._bokeh_onload_callbacks\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", + " }\n", + " finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", " console.info(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(js_urls, callback) {\n", - " window._bokeh_onload_callbacks.push(callback);\n", - " if (window._bokeh_is_loading > 0) {\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", @@ -109,15 +237,15 @@ " return null;\n", " }\n", " console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " window._bokeh_is_loading = js_urls.length;\n", + " root._bokeh_is_loading = js_urls.length;\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", " var s = document.createElement('script');\n", " s.src = url;\n", " s.async = false;\n", " s.onreadystatechange = s.onload = function() {\n", - " window._bokeh_is_loading--;\n", - " if (window._bokeh_is_loading === 0) {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", " run_callbacks()\n", " }\n", @@ -128,13 +256,13 @@ " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", - " };var element = document.getElementById(\"460a31b5-7f62-49a0-9eae-0bfcc4ed50f8\");\n", + " };var element = document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\");\n", " if (element == null) {\n", - " console.log(\"Bokeh: ERROR: autoload.js configured with elementid '460a31b5-7f62-49a0-9eae-0bfcc4ed50f8' but no matching script tag was found. \")\n", + " console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c9d7ef6f-10ee-4b23-899c-e57ed761e243' but no matching script tag was found. \")\n", " return false;\n", " }\n", "\n", - " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.js\"];\n", + " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.15.min.js\"];\n", "\n", " var inline_js = [\n", " function(Bokeh) {\n", @@ -144,39 +272,36 @@ " function(Bokeh) {\n", " \n", " },\n", - " \n", - " function(Bokeh) {\n", - " \n", - " document.getElementById(\"460a31b5-7f62-49a0-9eae-0bfcc4ed50f8\").textContent = \"BokehJS is loading...\";\n", - " },\n", " function(Bokeh) {\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " \n", - " if ((window.Bokeh !== undefined) || (force === true)) {\n", + " if ((root.Bokeh !== undefined) || (force === true)) {\n", " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i](window.Bokeh);\n", + " inline_js[i].call(root, root.Bokeh);\n", " }if (force === true) {\n", " display_loaded();\n", - " }} else if (Date.now() < window._bokeh_timeout) {\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", - " } else if (!window._bokeh_failed_load) {\n", + " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " window._bokeh_failed_load = true;\n", + " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"460a31b5-7f62-49a0-9eae-0bfcc4ed50f8\")).parents('.cell').data().cell;\n", + " var cell = $(document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", "\n", " }\n", "\n", - " if (window._bokeh_is_loading === 0) {\n", + " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", @@ -185,8 +310,9 @@ " run_inline_js();\n", " });\n", " }\n", - "}(this));" - ] + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n }\n finally {\n delete root._bokeh_onload_callbacks\n }\n console.info(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(js_urls, callback) {\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = js_urls.length;\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var s = document.createElement('script');\n s.src = url;\n s.async = false;\n s.onreadystatechange = s.onload = function() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: all BokehJS libraries loaded\");\n run_callbacks()\n }\n };\n s.onerror = function() {\n console.warn(\"failed to load library \" + url);\n };\n console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.getElementsByTagName(\"head\")[0].appendChild(s);\n }\n };var element = document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\");\n if (element == null) {\n console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c9d7ef6f-10ee-4b23-899c-e57ed761e243' but no matching script tag was found. \")\n return false;\n }\n\n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.15.min.js\"];\n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n \n function(Bokeh) {\n \n },\n function(Bokeh) {\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n }\n ];\n\n function run_inline_js() {\n \n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"c9d7ef6f-10ee-4b23-899c-e57ed761e243\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(js_urls, function() {\n console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" @@ -196,7 +322,6 @@ "import pandas as pd\n", "import numpy as np\n", "\n", - "import bokeh.charts as charts\n", "from bokeh.plotting import figure, show\n", "from bokeh.io import output_notebook, push_notebook\n", "from bokeh.models import (Range1d, NumeralTickFormatter, \n", @@ -223,9 +348,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -243,9 +366,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -275,14 +396,25 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -402,9 +534,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -425,14 +555,25 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -515,9 +656,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "from bokeh.models import ColumnDataSource" @@ -533,9 +672,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "source = ColumnDataSource(ipcalong[ipcalong.OPCAO == 'Indice geral'])" @@ -555,9 +692,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "p = figure(plot_height=400,plot_width=800,toolbar_location='above',\n", @@ -574,158 +709,56 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "71b30938-3943-4e8d-8397-9567eabc2791" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -747,158 +780,56 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "71b30938-3943-4e8d-8397-9567eabc2791" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -918,166 +849,64 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "GlyphRenderer(id='6b60c63f-a11b-4138-80e3-c8396ff2e17a', ...)\n" + "GlyphRenderer(id='8e954e3a-7236-4d13-93f4-ad17583a4094', ...)\n" ] }, { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "05603f09-a8e2-46e2-88e1-fa18eabcfd4a" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -1114,159 +943,57 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", + "
\n", + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = 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aHOZkIAAADK8eFmQgAAAMrx4WZCAAAAyvHhZkIAAADK8eFmQgAAAMrx4WZCAAAAyvHhZkIAAADK8eFmQgAAAMrx4WZCAAAAyvHhZkIAAADK8eFmQgAAgG7m9WZCAACAbub1ZkIAAIBu5vVmQgAAgG7m9WZCAACAbub1ZkIAAIBu5vVmQgAAgG7m9WZCAACAbub1ZkIAAIBu5vVmQgAAgG7m9WZCAAAAE9sJZ0IAAAAT2wlnQgAAABPbCWdCAAAAE9sJZ0IAAAAT2wlnQgAAABPbCWdCAAAAE9sJZ0IAAAAT2wlnQgAAABPbCWdCAAAAE9sJZ0IAAABV4RtnQgAAAFXhG2dCAAAAVeEbZ0IAAABV4RtnQgAAAFXhG2dCAAAAVeEbZ0IAAABV4RtnQgAAAFXhG2dCAAAAVeEbZ0IAAABV4RtnQgAAgPnVL2dCAACA+dUvZ0IAAID51S9nQgAAgPnVL2dCAACA+dUvZ0IAAID51S9nQgAAgPnVL2dCAACA+dUvZ0IAAID51S9nQgAAgPnVL2dCAACA0iVDZ0IAAIDSJUNnQgAAgNIlQ2dCAACA0iVDZ0IAAIDSJUNnQgAAgNIlQ2dCAACA0iVDZ0IAAIDSJUNnQgAAgNIlQ2dCAACA0iVDZ0IAAAB3GldnQgAAAHcaV2dCAAAAdxpXZ0IAAAB3GldnQgAAAHcaV2dCAAAAdxpXZ0IAAAB3GldnQgAAAHcaV2dCAAAAdxpXZ0IAAAB3GldnQgAAAFBqamdCAAAAUGpqZ0IAAABQampnQgAAAFBqamdCAAAAUGpqZ0IAAABQampnQgAAAFBqamdCAAAAUGpqZ0IAAABQampnQgAAAFBqamdCAACA9F5+Z0IAAID0Xn5nQgAAgPRefmdCAACA9F5+Z0IAAID0Xn5nQgAAgPRefmdCAACA9F5+Z0IAAID0Xn5nQgAAgPRefmdCAACA9F5+Z0IAAACZU5JnQgAAAJlTkmdCAAAAmVOSZ0IAAACZU5JnQgAAAJlTkmdCAAAAmVOSZ0IAAACZU5JnQgAAAJlTkmdCAAAAmVOSZ0IAAACZU5JnQgAAAHKjpWdCAAAAcqOlZ0IAAAByo6VnQgAAAHKjpWdCAAAAcqOlZ0IAAAByo6VnQgAAAHKjpWdCAAAAcqOlZ0IAAAByo6VnQgAAAHKjpWdCAACAFpi5Z0IAAIAWmLlnQgAAgBaYuWdCAACAFpi5Z0IAAIAWmLlnQgAAgBaYuWdCAACAFpi5Z0IAAIAWmLlnQgAAgBaYuWdCAACAFpi5Z0IAAIDv58xnQgAAgO/nzGdCAACA7+fMZ0IAAIDv58xnQgAAgO/nzGdCAACA7+fMZ0IAAIDv58xnQgAAgO/nzGdCAACA7+fMZ0IAAIDv58xnQgAAAJTc4GdCAAAAlNzgZ0IAAACU3OBnQgAAAJTc4GdCAAAAlNzgZ0IAAACU3OBnQgAAAJTc4GdCAAAAlNzgZ0IAAACU3OBnQgAAAJTc4GdCAACAONH0Z0IAAIA40fRnQgAAgDjR9GdCAACAONH0Z0IAAIA40fRnQgAAgDjR9GdCAACAONH0Z0IAAIA40fRnQgAAgDjR9GdCAACAONH0Z0IAAABGfAdoQgAAAEZ8B2hCAAAARnwHaEIAAABGfAdoQgAAAEZ8B2hCAAAARnwHaEIAAABGfAdoQgAAAEZ8B2hCAAAARnwHaEIAAABGfAdoQgAAgOpwG2hCAACA6nAbaEIAAIDqcBtoQgAAgOpwG2hCAACA6nAbaEIAAIDqcBtoQgAAgOpwG2hCAACA6nAbaEIAAIDqcBtoQgAAgOpwG2hCAACAw8AuaEIAAIDDwC5oQgAAgMPALmhCAACAw8AuaEIAAIDDwC5oQgAAgMPALmhCAACAw8AuaEIAAIDDwC5oQgAAgMPALmhCAACAw8AuaEIAAABotUJoQgAAAGi1QmhCAAAAaLVCaEIAAABotUJoQgAAAGi1QmhCAAAAaLVCaEIAAABotUJoQgAAAGi1QmhCAAAAaLVCaEIAAABotUJoQgAAAEEFVmhCAAAAQQVWaEIAAABBBVZoQgAAAEEFVmhCAAAAQQVWaEIAAABBBVZoQgAAAEEFVmhCAAAAQQVWaEIAAABBBVZoQgAAAEEFVmhCAACA5flpaEIAAIDl+WloQgAAgOX5aWhCAACA5flpaEIAAIDl+WloQgAAgOX5aWhCAACA5flpaEIAAIDl+WloQgAAgOX5aWhCAACA5flpaEIAAACK7n1oQgAAAIrufWhCAAAAiu59aEIAAACK7n1oQgAAAIrufWhCAAAAiu59aEIAAACK7n1oQgAAAIrufWhCAAAAiu59aEIAAACK7n1oQgAAAGM+kWhCAAAAYz6RaEIAAABjPpFoQgAAAGM+kWhCAAAAYz6RaEIAAABjPpFoQgAAAGM+kWhCAAAAYz6RaEIAAABjPpFoQgAAAGM+kWhCAACABzOlaEIAAIAHM6VoQgAAgAczpWhCAACABzOlaEIAAIAHM6VoQgAAgAczpWhCAACABzOlaEIAAIAHM6VoQgAAgAczpWhCAACABzOlaEIAAIDggrhoQgAAgOCCuGhCAACA4IK4aEIAAIDggrhoQgAAgOCCuGhCAACA4IK4aEIAAIDggrhoQgAAgOCCuGhCAACA4IK4aEIAAIDggrhoQgAAAIV3zGhCAAAAhXfMaEIAAACFd8xoQgAAAIV3zGhCAAAAhXfMaEIAAACFd8xoQgAAAIV3zGhCAAAAhXfMaEIAAACFd8xoQgAAAIV3zGhCAACAKWzgaEIAAIApbOBoQgAAgCls4GhCAACAKWzgaEIAAIApbOBoQgAAgCls4GhCAACAKWzgaEIAAIApbOBoQgAAgCls4GhCAACAKWzgaEIAAIBrcvJoQgAAgGty8mhCAACAa3LyaEIAAIBrcvJoQgAAgGty8mhCAACAa3LyaEIAAIBrcvJoQgAAgGty8mhCAACAa3LyaEIAAIBrcvJoQgAAABBnBmlCAAAAEGcGaUIAAAAQZwZpQgAAABBnBmlCAAAAEGcGaUIAAAAQZwZpQgAAABBnBmlCAAAAEGcGaUIAAAAQZwZpQgAAABBnBmlCAAAA6bYZaUIAAADpthlpQgAAAOm2GWlCAAAA6bYZaUIAAADpthlpQgAAAOm2GWlCAAAA6bYZaUIAAADpthlpQgAAAOm2GWlCAAAA6bYZaUIAAICNqy1pQgAAgI2rLWlCAACAjastaUIAAICNqy1pQgAAgI2rLWlCAACAjastaUIAAICNqy1pQgAAgI2rLWlCAACAjastaUIAAICNqy1pQgAAgGb7QGlCAACAZvtAaUIAAIBm+0BpQgAAgGb7QGlCAACAZvtAaUIAAIBm+0BpQgAAgGb7QGlCAACAZvtAaUIAAIBm+0BpQgAAgGb7QGlCAAAAC/BUaUIAAAAL8FRpQgAAAAvwVGlCAAAAC/BUaUIAAAAL8FRpQgAAAAvwVGlCAAAAC/BUaUIAAAAL8FRpQgAAAAvwVGlCAAAAC/BUaUIAAICv5GhpQgAAgK/kaGlCAACAr+RoaUIAAICv5GhpQgAAgK/kaGlCAACAr+RoaUIAAICv5GhpQgAAgK/kaGlCAACAr+RoaUIAAICv5GhpQgAAgIg0fGlCAACAiDR8aUIAAICINHxpQgAAgIg0fGlCAACAiDR8aUIAAICINHxpQgAAgIg0fGlCAACAiDR8aUIAAICINHxpQgAAgIg0fGlCAAAALSmQaUIAAAAtKZBpQgAAAC0pkGlCAAAALSmQaUIAAAAtKZBpQgAAAC0pkGlCAAAALSmQaUIAAAAtKZBpQgAAAC0pkGlCAAAALSmQaUIAAAAGeaNpQgAAAAZ5o2lCAAAABnmjaUIAAAAGeaNpQgAAAAZ5o2lCAAAABnmjaUIAAAAGeaNpQgAAAAZ5o2lCAAAABnmjaUIAAAAGeaNpQgAAgKptt2lCAACAqm23aUIAAICqbbdpQgAAgKptt2lCAACAqm23aUIAAICqbbdpQgAAgKptt2lCAACAqm23aUIAAICqbbdpQgAAgKptt2lCAAAAT2LLaUIAAABPYstpQgAAAE9iy2lCAAAAT2LLaUIAAABPYstpQgAAAE9iy2lCAAAAT2LLaUIAAABPYstpQgAAAE9iy2lCAAAAT2LLaUIAAACRaN1pQgAAAJFo3WlCAAAAkWjdaUIAAACRaN1pQgAAAJFo3WlCAAAAkWjdaUIAAACRaN1pQgAAAJFo3WlCAAAAkWjdaUIAAACRaN1pQgAAgDVd8WlCAACANV3xaUIAAIA1XfFpQgAAgDVd8WlCAACANV3xaUIAAIA1XfFpQgAAgDVd8WlCAACANV3xaUIAAIA1XfFpQgAAgDVd8WlCAACADq0EakIAAIAOrQRqQgAAgA6tBGpCAACADq0EakIAAIAOrQRqQgAAgA6tBGpCAACADq0EakIAAIAOrQRqQgAAgA6tBGpCAACADq0EakIAAACzoRhqQgAAALOhGGpCAAAAs6EYakIAAACzoRhqQgAAALOhGGpCAAAAs6EYakIAAACzoRhqQgAAALOhGGpCAAAAs6EYakIAAACzoRhqQgAAAIzxK2pCAAAAjPErakIAAACM8StqQgAAAIzxK2pCAAAAjPErakIAAACM8StqQgAAAIzxK2pCAAAAjPErakIAAACM8StqQgAAAIzxK2pCAACAMOY/akIAAIAw5j9qQgAAgDDmP2pCAACAMOY/akIAAIAw5j9qQgAAgDDmP2pCAACAMOY/akIAAIAw5j9qQgAAgDDmP2pCAACAMOY/akIAAADV2lNqQgAAANXaU2pCAAAA1dpTakIAAADV2lNqQgAAANXaU2pCAAAA1dpTakIAAADV2lNqQgAAANXaU2pCAAAA1dpTakIAAADV2lNqQgAAAK4qZ2pCAAAAripnakIAAACuKmdqQgAAAK4qZ2pCAAAAripnakIAAACuKmdqQgAAAK4qZ2pCAAAAripnakIAAACuKmdqQgAAAK4qZ2pCAACAUh97akIAAIBSH3tqQgAAgFIfe2pCAACAUh97akIAAIBSH3tqQgAAgFIfe2pCAACAUh97akIAAIBSH3tqQgAAgFIfe2pCAACAUh97akIAAIArb45qQgAAgCtvjmpCAACAK2+OakIAAIArb45qQgAAgCtvjmpCAACAK2+OakIAAIArb45qQgAAgCtvjmpCAACAK2+OakIAAIArb45qQgAAANBjompCAAAA0GOiakIAAADQY6JqQgAAANBjompCAAAA0GOiakIAAADQY6JqQgAAANBjompCAAAA0GOiakIAAADQY6JqQgAAANBjompCAACAdFi2akIAAIB0WLZqQgAAgHRYtmpCAACAdFi2akIAAIB0WLZqQgAAgHRYtmpCAACAdFi2akIAAIB0WLZqQgAAgHRYtmpCAACAdFi2akIAAIC2XshqQgAAgLZeyGpCAACAtl7IakIAAIC2XshqQgAAgLZeyGpCAACAtl7IakIAAIC2XshqQgAAgLZeyGpCAACAtl7IakIAAIC2XshqQgAAAFtT3GpCAAAAW1PcakIAAABbU9xqQgAAAFtT3GpCAAAAW1PcakIAAABbU9xqQgAAAFtT3GpCAAAAW1PcakIAAABbU9xqQgAAAFtT3GpCAAAANKPvakIAAAA0o+9qQgAAADSj72pCAAAANKPvakIAAAA0o+9qQgAAADSj72pCAAAANKPvakIAAAA0o+9qQgAAADSj72pCAAAANKPvakIAAIDYlwNrQgAAgNiXA2tCAACA2JcDa0IAAIDYlwNrQgAAgNiXA2tCAACA2JcDa0IAAIDYlwNrQgAAgNiXA2tCAACA2JcDa0IAAIDYlwNrQgAAgLHnFmtCAACAsecWa0IAAICx5xZrQgAAgLHnFmtCAACAsecWa0IAAICx5xZrQgAAgLHnFmtCAACAsecWa0IAAICx5xZrQgAAgLHnFmtCAAAADWlJc0IAAAANaUlzQgAAAA1pSXNCAAAADWlJc0IAAAANaUlzQgAAAA1pSXNCAAAADWlJc0IAAAANaUlzQgAAAA1pSXNCAAAADWlJc0IAAEBfY1NzQgAAQF9jU3NCAABAX2NTc0IAAEBfY1NzQgAAQF9jU3NCAABAX2NTc0IAAEBfY1NzQgAAQF9jU3NCAABAX2NTc0IAAEBfY1NzQgAAAOa4XHNCAAAA5rhcc0IAAADmuFxzQgAAAOa4XHNCAAAA5rhcc0IAAADmuFxzQgAAAOa4XHNCAAAA5rhcc0IAAADmuFxzQgAAAOa4XHNCAABAOLNmc0IAAEA4s2ZzQgAAQDizZnNCAABAOLNmc0IAAEA4s2ZzQgAAQDizZnNCAABAOLNmc0IAAEA4s2ZzQgAAQDizZnNCAABAOLNmc0IAAMAkW3BzQgAAwCRbcHNCAADAJFtwc0IAAMAkW3BzQgAAwCRbcHNCAADAJFtwc0IAAMAkW3BzQgAAwCRbcHNCAADAJFtwc0IAAMAkW3BzQgAAAHdVenNCAAAAd1V6c0IAAAB3VXpzQgAAAHdVenNCAAAAd1V6c0IAAAB3VXpzQgAAAHdVenNCAAAAd1V6c0IAAAB3VXpzQgAAAHdVenNCAACAY/2Dc0IAAIBj/YNzQgAAgGP9g3NCAACAY/2Dc0IAAIBj/YNzQgAAgGP9g3NCAACAY/2Dc0IAAIBj/YNzQgAAgGP9g3NCAACAY/2Dc0IAAMC1941zQgAAwLX3jXNCAADAtfeNc0IAAMC1941zQgAAwLX3jXNCAADAtfeNc0IAAMC1941zQgAAwLX3jXNCAADAtfeNc0IAAMC1941zQgAAAAjyl3NCAAAACPKXc0IAAAAI8pdzQgAAAAjyl3NCAAAACPKXc0IAAAAI8pdzQgAAAAjyl3NCAAAACPKXc0IAAAAI8pdzQgAAAAjyl3NCAACA9Jmhc0IAAID0maFzQgAAgPSZoXNCAACA9Jmhc0IAAID0maFzQgAAgPSZoXNCAACA9Jmhc0IAAID0maFzQgAAgPSZoXNCAACA9Jmhc0IAAMBGlKtzQgAAwEaUq3NCAADARpSrc0IAAMBGlKtzQgAAwEaUq3NCAADARpSrc0IAAMBGlKtzQgAAwEaUq3NCAADARpSrc0IAAMBGlKtzQgAAQDM8tXNCAABAMzy1c0IAAEAzPLVzQgAAQDM8tXNCAABAMzy1c0IAAEAzPLVzQgAAQDM8tXNCAABAMzy1c0IAAEAzPLVzQgAAQDM8tXNCAACAhTa/c0IAAICFNr9zQgAAgIU2v3NCAACAhTa/c0IAAICFNr9zQgAAgIU2v3NCAACAhTa/c0IAAICFNr9zQgAAgIU2v3NCAACAhTa/c0IAAMDXMMlzQgAAwNcwyXNCAADA1zDJc0IAAMDXMMlzQgAAwNcwyXNCAADA1zDJc0IAAMDXMMlzQgAAwNcwyXNCAADA1zDJc0IAAMDXMMlzQgAAwPgz0nNCAADA+DPSc0IAAMD4M9JzQgAAwPgz0nNCAADA+DPSc0IAAMD4M9JzQgAAwPgz0nNCAADA+DPSc0IAAMD4M9JzQgAAwPgz0nNCAAAASy7cc0IAAABLLtxzQgAAAEsu3HNCAAAASy7cc0IAAABLLtxzQgAAAEsu3HNCAAAASy7cc0IAAABLLtxzQgAAAEsu3HNCAAAASy7cc0IAAIA31uVzQgAAgDfW5XNCAACAN9blc0IAAIA31uVzQgAAgDfW5XNCAACAN9blc0IAAIA31uVzQgAAgDfW5XNCAACAN9blc0IAAIA31uVzQgAAwInQ73NCAADAidDvc0IAAMCJ0O9zQgAAwInQ73NCAADAidDvc0IAAMCJ0O9zQgAAwInQ73NCAADAidDvc0IAAMCJ0O9zQgAAwInQ73NCAABAdnj5c0IAAEB2ePlzQgAAQHZ4+XNCAABAdnj5c0IAAEB2ePlzQgAAQHZ4+XNCAABAdnj5c0IAAEB2ePlzQgAAQHZ4+XNCAABAdnj5c0IAAIDIcgN0QgAAgMhyA3RCAACAyHIDdEIAAIDIcgN0QgAAgMhyA3RCAACAyHIDdEIAAIDIcgN0QgAAgMhyA3RCAACAyHIDdEIAAIDIcgN0QgAAwBptDXRCAADAGm0NdEIAAMAabQ10QgAAwBptDXRCAADAGm0NdEIAAMAabQ10QgAAwBptDXRCAADAGm0NdEIAAMAabQ10QgAAwBptDXRCAABABxUXdEIAAEAHFRd0QgAAQAcVF3RCAABABxUXdEIAAEAHFRd0QgAAQAcVF3RCAABABxUXdEIAAEAHFRd0QgAAQAcVF3RCAABABxUXdEIAAIBZDyF0QgAAgFkPIXRCAACAWQ8hdEIAAIBZDyF0QgAAgFkPIXRCAACAWQ8hdEIAAIBZDyF0QgAAgFkPIXRCAACAWQ8hdEIAAIBZDyF0QgAAAEa3KnRCAAAARrcqdEIAAABGtyp0QgAAAEa3KnRCAAAARrcqdEIAAABGtyp0QgAAAEa3KnRCAAAARrcqdEIAAABGtyp0QgAAAEa3KnRCAABAmLE0dEIAAECYsTR0QgAAQJixNHRCAABAmLE0dEIAAECYsTR0QgAAQJixNHRCAABAmLE0dEIAAECYsTR0QgAAQJixNHRCAABAmLE0dEIAAIDqqz50QgAAgOqrPnRCAACA6qs+dEIAAIDqqz50QgAAgOqrPnRCAACA6qs+dEIAAIDqqz50QgAAgOqrPnRCAACA6qs+dEIAAIDqqz50QgAAgAuvR3RCAACAC69HdEIAAIALr0d0QgAAgAuvR3RCAACAC69HdEIAAIALr0d0QgAAgAuvR3RCAACAC69HdEIAAIALr0d0QgAAgAuvR3RCAADAXalRdEIAAMBdqVF0QgAAwF2pUXRCAADAXalRdEIAAMBdqVF0QgAAwF2pUXRCAADAXalRdEIAAMBdqVF0QgAAwF2pUXRCAADAXalRdEIAAEBKUVt0QgAAQEpRW3RCAABASlFbdEIAAEBKUVt0QgAAQEpRW3RCAABASlFbdEIAAEBKUVt0QgAAQEpRW3RCAABASlFbdEIAAEBKUVt0QgAAgJxLZXRCAACAnEtldEIAAICcS2V0QgAAgJxLZXRCAACAnEtldEIAAICcS2V0QgAAgJxLZXRCAACAnEtldEIAAICcS2V0QgAAgJxLZXRCAAAAifNudEIAAACJ8250QgAAAInzbnRCAAAAifNudEIAAACJ8250QgAAAInzbnRCAAAAifNudEIAAACJ8250QgAAAInzbnRCAAAAifNudEIAAEDb7Xh0QgAAQNvteHRCAABA2+14dEIAAEDb7Xh0QgAAQNvteHRCAABA2+14dEIAAEDb7Xh0QgAAQNvteHRCAABA2+14dEIAAEDb7Xh0QgAAgC3ognRCAACALeiCdEIAAIAt6IJ0QgAAgC3ognRCAACALeiCdEIAAIAt6IJ0QgAAgC3ognRCAACALeiCdEIAAIAt6IJ0QgAAgC3ognRCAAAAGpCMdEIAAAAakIx0QgAAABqQjHRCAAAAGpCMdEIAAAAakIx0QgAAABqQjHRCAAAAGpCMdEIAAAAakIx0QgAAABqQjHRCAAAAGpCMdEIAAEBsipZ0QgAAQGyKlnRCAABAbIqWdEIAAEBsipZ0QgAAQGyKlnRCAABAbIqWdEIAAEBsipZ0QgAAQGyKlnRCAABAbIqWdEIAAEBsipZ0QgAAwFgyoHRCAADAWDKgdEIAAMBYMqB0QgAAwFgyoHRCAADAWDKgdEIAAMBYMqB0QgAAwFgyoHRCAADAWDKgdEIAAMBYMqB0QgAAwFgyoHRCAAAAqyyqdEIAAACrLKp0QgAAAKssqnRCAAAAqyyqdEIAAACrLKp0QgAAAKssqnRCAAAAqyyqdEIAAACrLKp0QgAAAKssqnRCAAAAqyyqdEIAAED9JrR0QgAAQP0mtHRCAABA/Sa0dEIAAED9JrR0QgAAQP0mtHRCAABA/Sa0dEIAAED9JrR0QgAAQP0mtHRCAABA/Sa0dEIAAED9JrR0QgAAQB4qvXRCAABAHiq9dEIAAEAeKr10QgAAQB4qvXRCAABAHiq9dEIAAEAeKr10QgAAQB4qvXRCAABAHiq9dEIAAEAeKr10QgAAQB4qvXRCAACAcCTHdEIAAIBwJMd0QgAAgHAkx3RCAACAcCTHdEIAAIBwJMd0QgAAgHAkx3RCAACAcCTHdEIAAIBwJMd0QgAAgHAkx3RCAACAcCTHdEIAAABdzNB0QgAAAF3M0HRCAAAAXczQdEIAAABdzNB0QgAAAF3M0HRCAAAAXczQdEIAAABdzNB0QgAAAF3M0HRCAAAAXczQdEIAAABdzNB0QgAAQK/G2nRCAABAr8badEIAAECvxtp0QgAAQK/G2nRCAABAr8badEIAAECvxtp0QgAAQK/G2nRCAABAr8badEIAAECvxtp0QgAAQK/G2nRCAADAm27kdEIAAMCbbuR0QgAAwJtu5HRCAADAm27kdEIAAMCbbuR0QgAAwJtu5HRCAADAm27kdEIAAMCbbuR0QgAAwJtu5HRCAADAm27kdEIAAADuaO50QgAAAO5o7nRCAAAA7mjudEIAAADuaO50QgAAAO5o7nRCAAAA7mjudEIAAADuaO50QgAAAO5o7nRCAAAA7mjudEIAAADuaO50QgAAQEBj+HRCAABAQGP4dEIAAEBAY/h0QgAAQEBj+HRCAABAQGP4dEIAAEBAY/h0QgAAQEBj+HRCAABAQGP4dEIAAEBAY/h0QgAAQEBj+HRCAADALAsCdUIAAMAsCwJ1QgAAwCwLAnVCAADALAsCdUIAAMAsCwJ1QgAAwCwLAnVCAADALAsCdUIAAMAsCwJ1QgAAwCwLAnVCAADALAsCdUIAAAB/BQx1QgAAAH8FDHVCAAAAfwUMdUIAAAB/BQx1QgAAAH8FDHVCAAAAfwUMdUIAAAB/BQx1QgAAAH8FDHVCAAAAfwUMdUIAAAB/BQx1QgAAgGutFXVCAACAa60VdUIAAIBrrRV1QgAAgGutFXVCAACAa60VdUIAAIBrrRV1QgAAgGutFXVCAACAa60VdUIAAIBrrRV1QgAAgGutFXVCAADAvacfdUIAAMC9px91QgAAwL2nH3VCAADAvacfdUIAAMC9px91QgAAwL2nH3VCAADAvacfdUIAAMC9px91QgAAwL2nH3VCAADAvacfdUIAAAAQoil1QgAAABCiKXVCAAAAEKIpdUIAAAAQoil1QgAAABCiKXVCAAAAEKIpdUIAAAAQoil1QgAAABCiKXVCAAAAEKIpdUIAAAAQoil1QgAAwJb3MnVCAADAlvcydUIAAMCW9zJ1QgAAwJb3MnVCAADAlvcydUIAAMCW9zJ1QgAAwJb3MnVCAADAlvcydUIAAMCW9zJ1QgAAwJb3MnVCAAAA6fE8dUIAAADp8Tx1QgAAAOnxPHVCAAAA6fE8dUIAAADp8Tx1QgAAAOnxPHVCAAAA6fE8dUIAAADp8Tx1QgAAAOnxPHVCAAAA6fE8dUIAAIDVmUZ1QgAAgNWZRnVCAACA1ZlGdUIAAIDVmUZ1QgAAgNWZRnVCAACA1ZlGdUIAAIDVmUZ1QgAAgNWZRnVCAACA1ZlGdUIAAIDVmUZ1QgAAwCeUUHVCAADAJ5RQdUIAAMAnlFB1QgAAwCeUUHVCAADAJ5RQdUIAAMAnlFB1QgAAwCeUUHVCAADAJ5RQdUIAAMAnlFB1QgAAwCeUUHVCAABAFDxadUIAAEAUPFp1QgAAQBQ8WnVCAABAFDxadUIAAEAUPFp1QgAAQBQ8WnVCAABAFDxadUIAAEAUPFp1QgAAQBQ8WnVCAABAFDxadUIAAIAndsJwQgAAgCd2wnBCAACAJ3bCcEIAAIAndsJwQgAAgCd2wnBCAACAJ3bCcEIAAIAndsJwQgAAgCd2wnBCAACAJ3bCcEIAAIAndsJwQgAAwHlwzHBCAADAeXDMcEIAAMB5cMxwQgAAwHlwzHBCAADAeXDMcEIAAMB5cMxwQgAAwHlwzHBCAADAeXDMcEIAAMB5cMxwQgAAwHlwzHBCAAAAzGrWcEIAAADMatZwQgAAAMxq1nBCAAAAzGrWcEIAAADMatZwQgAAAMxq1nBCAAAAzGrWcEIAAADMatZwQgAAAMxq1nBCAAAAzGrWcEIAAIC4EuBwQgAAgLgS4HBCAACAuBLgcEIAAIC4EuBwQgAAgLgS4HBCAACAuBLgcEIAAIC4EuBwQgAAgLgS4HBCAACAuBLgcEIAAIC4EuBwQgAAwAoN6nBCAADACg3qcEIAAMAKDepwQgAAwAoN6nBCAADACg3qcEIAAMAKDepwQgAAwAoN6nBCAADACg3qcEIAAMAKDepwQgAAwAoN6nBCAABA97TzcEIAAED3tPNwQgAAQPe083BCAABA97TzcEIAAED3tPNwQgAAQPe083BCAABA97TzcEIAAED3tPNwQgAAQPe083BCAABA97TzcEIAAIBJr/1wQgAAgEmv/XBCAACASa/9cEIAAIBJr/1wQgAAgEmv/XBCAACASa/9cEIAAIBJr/1wQgAAgEmv/XBCAACASa/9cEIAAIBJr/1wQgAAwJupB3FCAADAm6kHcUIAAMCbqQdxQgAAwJupB3FCAADAm6kHcUIAAMCbqQdxQgAAwJupB3FCAADAm6kHcUIAAMCbqQdxQgAAwJupB3FCAADAvKwQcUIAAMC8rBBxQgAAwLysEHFCAADAvKwQcUIAAMC8rBBxQgAAwLysEHFCAADAvKwQcUIAAMC8rBBxQgAAwLysEHFCAADAvKwQcUIAAAAPpxpxQgAAAA+nGnFCAAAAD6cacUIAAAAPpxpxQgAAAA+nGnFCAAAAD6cacUIAAAAPpxpxQgAAAA+nGnFCAAAAD6cacUIAAAAPpxpxQgAAgPtOJHFCAACA+04kcUIAAID7TiRxQgAAgPtOJHFCAACA+04kcUIAAID7TiRxQgAAgPtOJHFCAACA+04kcUIAAID7TiRxQgAAgPtOJHFCAADATUkucUIAAMBNSS5xQgAAwE1JLnFCAADATUkucUIAAMBNSS5xQgAAwE1JLnFCAADATUkucUIAAMBNSS5xQgAAwE1JLnFCAADATUkucUIAAEA68TdxQgAAQDrxN3FCAABAOvE3cUIAAEA68TdxQgAAQDrxN3FCAABAOvE3cUIAAEA68TdxQgAAQDrxN3FCAABAOvE3cUIAAEA68TdxQgAAgIzrQXFCAACAjOtBcUIAAICM60FxQgAAgIzrQXFCAACAjOtBcUIAAICM60FxQgAAgIzrQXFCAACAjOtBcUIAAICM60FxQgAAgIzrQXFCAADA3uVLcUIAAMDe5UtxQgAAwN7lS3FCAADA3uVLcUIAAMDe5UtxQgAAwN7lS3FCAADA3uVLcUIAAMDe5UtxQgAAwN7lS3FCAADA3uVLcUIAAEDLjVVxQgAAQMuNVXFCAABAy41VcUIAAEDLjVVxQgAAQMuNVXFCAABAy41VcUIAAEDLjVVxQgAAQMuNVXFCAABAy41VcUIAAEDLjVVxQgAAgB2IX3FCAACAHYhfcUIAAIAdiF9xQgAAgB2IX3FCAACAHYhfcUIAAIAdiF9xQgAAgB2IX3FCAACAHYhfcUIAAIAdiF9xQgAAgB2IX3FCAAAACjBpcUIAAAAKMGlxQgAAAAowaXFCAAAACjBpcUIAAAAKMGlxQgAAAAowaXFCAAAACjBpcUIAAAAKMGlxQgAAAAowaXFCAAAACjBpcUIAAEBcKnNxQgAAQFwqc3FCAABAXCpzcUIAAEBcKnNxQgAAQFwqc3FCAABAXCpzcUIAAEBcKnNxQgAAQFwqc3FCAABAXCpzcUIAAEBcKnNxQgAAgK4kfXFCAACAriR9cUIAAICuJH1xQgAAgK4kfXFCAACAriR9cUIAAICuJH1xQgAAgK4kfXFCAACAriR9cUIAAICuJH1xQgAAgK4kfXFCAABANXqGcUIAAEA1eoZxQgAAQDV6hnFCAABANXqGcUIAAEA1eoZxQgAAQDV6hnFCAABANXqGcUIAAEA1eoZxQgAAQDV6hnFCAABANXqGcUIAAICHdJBxQgAAgId0kHFCAACAh3SQcUIAAICHdJBxQgAAgId0kHFCAACAh3SQcUIAAICHdJBxQgAAgId0kHFCAACAh3SQcUIAAICHdJBxQgAAAHQcmnFCAAAAdByacUIAAAB0HJpxQgAAAHQcmnFCAAAAdByacUIAAAB0HJpxQgAAAHQcmnFCAAAAdByacUIAAAB0HJpxQgAAAHQcmnFCAABAxhakcUIAAEDGFqRxQgAAQMYWpHFCAABAxhakcUIAAEDGFqRxQgAAQMYWpHFCAABAxhakcUIAAEDGFqRxQgAAQMYWpHFCAABAxhakcUIAAMCyvq1xQgAAwLK+rXFCAADAsr6tcUIAAMCyvq1xQgAAwLK+rXFCAADAsr6tcUIAAMCyvq1xQgAAwLK+rXFCAADAsr6tcUIAAMCyvq1xQgAAAAW5t3FCAAAABbm3cUIAAAAFubdxQgAAAAW5t3FCAAAABbm3cUIAAAAFubdxQgAAAAW5t3FCAAAABbm3cUIAAAAFubdxQgAAAAW5t3FCAABAV7PBcUIAAEBXs8FxQgAAQFezwXFCAABAV7PBcUIAAEBXs8FxQgAAQFezwXFCAABAV7PBcUIAAEBXs8FxQgAAQFezwXFCAABAV7PBcUIAAMBDW8txQgAAwENby3FCAADAQ1vLcUIAAMBDW8txQgAAwENby3FCAADAQ1vLcUIAAMBDW8txQgAAwENby3FCAADAQ1vLcUIAAMBDW8txQgAAAJZV1XFCAAAAllXVcUIAAACWVdVxQgAAAJZV1XFCAAAAllXVcUIAAACWVdVxQgAAAJZV1XFCAAAAllXVcUIAAACWVdVxQgAAAJZV1XFCAACAgv3ecUIAAICC/d5xQgAAgIL93nFCAACAgv3ecUIAAICC/d5xQgAAgIL93nFCAACAgv3ecUIAAICC/d5xQgAAgIL93nFCAACAgv3ecUIAAMDU9+hxQgAAwNT36HFCAADA1PfocUIAAMDU9+hxQgAAwNT36HFCAADA1PfocUIAAMDU9+hxQgAAwNT36HFCAADA1PfocUIAAMDU9+hxQgAAACfy8nFCAAAAJ/LycUIAAAAn8vJxQgAAACfy8nFCAAAAJ/LycUIAAAAn8vJxQgAAACfy8nFCAAAAJ/LycUIAAAAn8vJxQgAAACfy8nFCAAAASPX7cUIAAABI9ftxQgAAAEj1+3FCAAAASPX7cUIAAABI9ftxQgAAAEj1+3FCAAAASPX7cUIAAABI9ftxQgAAAEj1+3FCAAAASPX7cUIAAECa7wVyQgAAQJrvBXJCAABAmu8FckIAAECa7wVyQgAAQJrvBXJCAABAmu8FckIAAECa7wVyQgAAQJrvBXJCAABAmu8FckIAAECa7wVyQgAAwIaXD3JCAADAhpcPckIAAMCGlw9yQgAAwIaXD3JCAADAhpcPckIAAMCGlw9yQgAAwIaXD3JCAADAhpcPckIAAMCGlw9yQgAAwIaXD3JCAAAA2ZEZckIAAADZkRlyQgAAANmRGXJCAAAA2ZEZckIAAADZkRlyQgAAANmRGXJCAAAA2ZEZckIAAADZkRlyQgAAANmRGXJCAAAA2ZEZckIAAIDFOSNyQgAAgMU5I3JCAACAxTkjckIAAIDFOSNyQgAAgMU5I3JCAACAxTkjckIAAIDFOSNyQgAAgMU5I3JCAACAxTkjckIAAIDFOSNyQgAAwBc0LXJCAADAFzQtckIAAMAXNC1yQgAAwBc0LXJCAADAFzQtckIAAMAXNC1yQgAAwBc0LXJCAADAFzQtckIAAMAXNC1yQgAAwBc0LXJCAAAAai43ckIAAABqLjdyQgAAAGouN3JCAAAAai43ckIAAABqLjdyQgAAAGouN3JCAAAAai43ckIAAABqLjdyQgAAAGouN3JCAAAAai43ckIAAIBW1kByQgAAgFbWQHJCAACAVtZAckIAAIBW1kByQgAAgFbWQHJCAACAVtZAckIAAIBW1kByQgAAgFbWQHJCAACAVtZAckIAAIBW1kByQgAAwKjQSnJCAADAqNBKckIAAMCo0EpyQgAAwKjQSnJCAADAqNBKckIAAMCo0EpyQgAAwKjQSnJCAADAqNBKckIAAMCo0EpyQgAAwKjQSnJCAABAlXhUckIAAECVeFRyQgAAQJV4VHJCAABAlXhUckIAAECVeFRyQgAAQJV4VHJCAABAlXhUckIAAECVeFRyQgAAQJV4VHJCAABAlXhUckIAAIDncl5yQgAAgOdyXnJCAACA53JeckIAAIDncl5yQgAAgOdyXnJCAACA53JeckIAAIDncl5yQgAAgOdyXnJCAACA53JeckIAAIDncl5yQgAAwDltaHJCAADAOW1ockIAAMA5bWhyQgAAwDltaHJCAADAOW1ockIAAMA5bWhyQgAAwDltaHJCAADAOW1ockIAAMA5bWhyQgAAwDltaHJCAADAWnBxckIAAMBacHFyQgAAwFpwcXJCAADAWnBxckIAAMBacHFyQgAAwFpwcXJCAADAWnBxckIAAMBacHFyQgAAwFpwcXJCAADAWnBxckIAAACtantyQgAAAK1qe3JCAAAArWp7ckIAAACtantyQgAAAK1qe3JCAAAArWp7ckIAAACtantyQgAAAK1qe3JCAAAArWp7ckIAAACtantyQgAAgJkShXJCAACAmRKFckIAAICZEoVyQgAAgJkShXJCAACAmRKFckIAAICZEoVyQgAAgJkShXJCAACAmRKFckIAAICZEoVyQgAAgJkShXJCAADA6wyPckIAAMDrDI9yQgAAwOsMj3JCAADA6wyPckIAAMDrDI9yQgAAwOsMj3JCAADA6wyPckIAAMDrDI9yQgAAwOsMj3JCAADA6wyPckIAAEDYtJhyQgAAQNi0mHJCAABA2LSYckIAAEDYtJhyQgAAQNi0mHJCAABA2LSYckIAAEDYtJhyQgAAQNi0mHJCAABA2LSYckIAAEDYtJhyQgAAgCqvonJCAACAKq+ickIAAIAqr6JyQgAAgCqvonJCAACAKq+ickIAAIAqr6JyQgAAgCqvonJCAACAKq+ickIAAIAqr6JyQgAAgCqvonJCAADAfKmsckIAAMB8qaxyQgAAwHyprHJCAADAfKmsckIAAMB8qaxyQgAAwHyprHJCAADAfKmsckIAAMB8qaxyQgAAwHyprHJCAADAfKmsckIAAEBpUbZyQgAAQGlRtnJCAABAaVG2ckIAAEBpUbZyQgAAQGlRtnJCAABAaVG2ckIAAEBpUbZyQgAAQGlRtnJCAABAaVG2ckIAAEBpUbZyQgAAgLtLwHJCAACAu0vAckIAAIC7S8ByQgAAgLtLwHJCAACAu0vAckIAAIC7S8ByQgAAgLtLwHJCAACAu0vAckIAAIC7S8ByQgAAgLtLwHJCAAAAqPPJckIAAACo88lyQgAAAKjzyXJCAAAAqPPJckIAAACo88lyQgAAAKjzyXJCAAAAqPPJckIAAACo88lyQgAAAKjzyXJCAAAAqPPJckIAAED67dNyQgAAQPrt03JCAABA+u3TckIAAED67dNyQgAAQPrt03JCAABA+u3TckIAAED67dNyQgAAQPrt03JCAABA+u3TckIAAED67dNyQgAAgEzo3XJCAACATOjdckIAAIBM6N1yQgAAgEzo3XJCAACATOjdckIAAIBM6N1yQgAAgEzo3XJCAACATOjdckIAAIBM6N1yQgAAgEzo3XJCAACAbevmckIAAIBt6+ZyQgAAgG3r5nJCAACAbevmckIAAIBt6+ZyQgAAgG3r5nJCAACAbevmckIAAIBt6+ZyQgAAgG3r5nJCAACAbevmckIAAMC/5fByQgAAwL/l8HJCAADAv+XwckIAAMC/5fByQgAAwL/l8HJCAADAv+XwckIAAMC/5fByQgAAwL/l8HJCAADAv+XwckIAAMC/5fByQgAAQKyN+nJCAABArI36ckIAAECsjfpyQgAAQKyN+nJCAABArI36ckIAAECsjfpyQgAAQKyN+nJCAABArI36ckIAAECsjfpyQgAAQKyN+nJCAACA/ocEc0IAAID+hwRzQgAAgP6HBHNCAACA/ocEc0IAAID+hwRzQgAAgP6HBHNCAACA/ocEc0IAAID+hwRzQgAAgP6HBHNCAACA/ocEc0IAAADrLw5zQgAAAOsvDnNCAAAA6y8Oc0IAAADrLw5zQgAAAOsvDnNCAAAA6y8Oc0IAAADrLw5zQgAAAOsvDnNCAAAA6y8Oc0IAAADrLw5zQgAAQD0qGHNCAABAPSoYc0IAAEA9KhhzQgAAQD0qGHNCAABAPSoYc0IAAEA9KhhzQgAAQD0qGHNCAABAPSoYc0IAAEA9KhhzQgAAQD0qGHNCAACAjyQic0IAAICPJCJzQgAAgI8kInNCAACAjyQic0IAAICPJCJzQgAAgI8kInNCAACAjyQic0IAAICPJCJzQgAAgI8kInNCAACAjyQic0IAAAB8zCtzQgAAAHzMK3NCAAAAfMwrc0IAAAB8zCtzQgAAAHzMK3NCAAAAfMwrc0IAAAB8zCtzQgAAAHzMK3NCAAAAfMwrc0IAAAB8zCtzQgAAQM7GNXNCAABAzsY1c0IAAEDOxjVzQgAAQM7GNXNCAABAzsY1c0IAAEDOxjVzQgAAQM7GNXNCAABAzsY1c0IAAEDOxjVzQgAAQM7GNXNCAADAum4/c0IAAMC6bj9zQgAAwLpuP3NCAADAum4/c0IAAMC6bj9zQgAAwLpuP3NCAADAum4/c0IAAMC6bj9zQgAAwLpuP3NCAADAum4/c0IAAABW3CprQgAAAFbcKmtCAAAAVtwqa0IAAABW3CprQgAAAFbcKmtCAAAAVtwqa0IAAABW3CprQgAAAFbcKmtCAAAAVtwqa0IAAABW3CprQgAAgPrQPmtCAACA+tA+a0IAAID60D5rQgAAgPrQPmtCAACA+tA+a0IAAID60D5rQgAAgPrQPmtCAACA+tA+a0IAAID60D5rQgAAgPrQPmtCAACA0yBSa0IAAIDTIFJrQgAAgNMgUmtCAACA0yBSa0IAAIDTIFJrQgAAgNMgUmtCAACA0yBSa0IAAIDTIFJrQgAAgNMgUmtCAACA0yBSa0IAAAB4FWZrQgAAAHgVZmtCAAAAeBVma0IAAAB4FWZrQgAAAHgVZmtCAAAAeBVma0IAAAB4FWZrQgAAAHgVZmtCAAAAeBVma0IAAAB4FWZrQgAAAFFleWtCAAAAUWV5a0IAAABRZXlrQgAAAFFleWtCAAAAUWV5a0IAAABRZXlrQgAAAFFleWtCAAAAUWV5a0IAAABRZXlrQgAAAFFleWtCAACA9VmNa0IAAID1WY1rQgAAgPVZjWtCAACA9VmNa0IAAID1WY1rQgAAgPVZjWtCAACA9VmNa0IAAID1WY1rQgAAgPVZjWtCAACA9VmNa0IAAACaTqFrQgAAAJpOoWtCAAAAmk6ha0IAAACaTqFrQgAAAJpOoWtCAAAAmk6ha0IAAACaTqFrQgAAAJpOoWtCAAAAmk6ha0IAAACaTqFrQgAAgKf5s2tCAACAp/mza0IAAICn+bNrQgAAgKf5s2tCAACAp/mza0IAAICn+bNrQgAAgKf5s2tCAACAp/mza0IAAICn+bNrQgAAgKf5s2tCAAAATO7Ha0IAAABM7sdrQgAAAEzux2tCAAAATO7Ha0IAAABM7sdrQgAAAEzux2tCAAAATO7Ha0IAAABM7sdrQgAAAEzux2tCAAAATO7Ha0IAAAAlPttrQgAAACU+22tCAAAAJT7ba0IAAAAlPttrQgAAACU+22tCAAAAJT7ba0IAAAAlPttrQgAAACU+22tCAAAAJT7ba0IAAAAlPttrQgAAgMky72tCAACAyTLva0IAAIDJMu9rQgAAgMky72tCAACAyTLva0IAAIDJMu9rQgAAgMky72tCAACAyTLva0IAAIDJMu9rQgAAgMky72tCAACAooICbEIAAICiggJsQgAAgKKCAmxCAACAooICbEIAAICiggJsQgAAgKKCAmxCAACAooICbEIAAICiggJsQgAAgKKCAmxCAACAooICbEIAAABHdxZsQgAAAEd3FmxCAAAAR3cWbEIAAABHdxZsQgAAAEd3FmxCAAAAR3cWbEIAAABHdxZsQgAAAEd3FmxCAAAAR3cWbEIAAABHdxZsQgAAgOtrKmxCAACA62sqbEIAAIDraypsQgAAgOtrKmxCAACA62sqbEIAAIDraypsQgAAgOtrKmxCAACA62sqbEIAAIDraypsQgAAgOtrKmxCAACAxLs9bEIAAIDEuz1sQgAAgMS7PWxCAACAxLs9bEIAAIDEuz1sQgAAgMS7PWxCAACAxLs9bEIAAIDEuz1sQgAAgMS7PWxCAACAxLs9bEIAAABpsFFsQgAAAGmwUWxCAAAAabBRbEIAAABpsFFsQgAAAGmwUWxCAAAAabBRbEIAAABpsFFsQgAAAGmwUWxCAAAAabBRbEIAAABpsFFsQgAAAEIAZWxCAAAAQgBlbEIAAABCAGVsQgAAAEIAZWxCAAAAQgBlbEIAAABCAGVsQgAAAEIAZWxCAAAAQgBlbEIAAABCAGVsQgAAAEIAZWxCAACA5vR4bEIAAIDm9HhsQgAAgOb0eGxCAACA5vR4bEIAAIDm9HhsQgAAgOb0eGxCAACA5vR4bEIAAIDm9HhsQgAAgOb0eGxCAACA5vR4bEIAAACL6YxsQgAAAIvpjGxCAAAAi+mMbEIAAACL6YxsQgAAAIvpjGxCAAAAi+mMbEIAAACL6YxsQgAAAIvpjGxCAAAAi+mMbEIAAACL6YxsQgAAAM3vnmxCAAAAze+ebEIAAADN755sQgAAAM3vnmxCAAAAze+ebEIAAADN755sQgAAAM3vnmxCAAAAze+ebEIAAADN755sQgAAAM3vnmxCAACAceSybEIAAIBx5LJsQgAAgHHksmxCAACAceSybEIAAIBx5LJsQgAAgHHksmxCAACAceSybEIAAIBx5LJsQgAAgHHksmxCAACAceSybEIAAIBKNMZsQgAAgEo0xmxCAACASjTGbEIAAIBKNMZsQgAAgEo0xmxCAACASjTGbEIAAIBKNMZsQgAAgEo0xmxCAACASjTGbEIAAIBKNMZsQgAAAO8o2mxCAAAA7yjabEIAAADvKNpsQgAAAO8o2mxCAAAA7yjabEIAAADvKNpsQgAAAO8o2mxCAAAA7yjabEIAAADvKNpsQgAAAO8o2mxCAAAAyHjtbEIAAADIeO1sQgAAAMh47WxCAAAAyHjtbEIAAADIeO1sQgAAAMh47WxCAAAAyHjtbEIAAADIeO1sQgAAAMh47WxCAAAAyHjtbEIAAIBsbQFtQgAAgGxtAW1CAACAbG0BbUIAAIBsbQFtQgAAgGxtAW1CAACAbG0BbUIAAIBsbQFtQgAAgGxtAW1CAACAbG0BbUIAAIBsbQFtQgAAABFiFW1CAAAAEWIVbUIAAAARYhVtQgAAABFiFW1CAAAAEWIVbUIAAAARYhVtQgAAABFiFW1CAAAAEWIVbUIAAAARYhVtQgAAABFiFW1CAAAA6rEobUIAAADqsShtQgAAAOqxKG1CAAAA6rEobUIAAADqsShtQgAAAOqxKG1CAAAA6rEobUIAAADqsShtQgAAAOqxKG1CAAAA6rEobUIAAICOpjxtQgAAgI6mPG1CAACAjqY8bUIAAICOpjxtQgAAgI6mPG1CAACAjqY8bUIAAICOpjxtQgAAgI6mPG1CAACAjqY8bUIAAICOpjxtQgAAgGf2T21CAACAZ/ZPbUIAAIBn9k9tQgAAgGf2T21CAACAZ/ZPbUIAAIBn9k9tQgAAgGf2T21CAACAZ/ZPbUIAAIBn9k9tQgAAgGf2T21CAAAADOtjbUIAAAAM62NtQgAAAAzrY21CAAAADOtjbUIAAAAM62NtQgAAAAzrY21CAAAADOtjbUIAAAAM62NtQgAAAAzrY21CAAAADOtjbUIAAICw33dtQgAAgLDfd21CAACAsN93bUIAAICw33dtQgAAgLDfd21CAACAsN93bUIAAICw33dtQgAAgLDfd21CAACAsN93bUIAAICw33dtQgAAgPLliW1CAACA8uWJbUIAAIDy5YltQgAAgPLliW1CAACA8uWJbUIAAIDy5YltQgAAgPLliW1CAACA8uWJbUIAAIDy5YltQgAAgPLliW1CAAAAl9qdbUIAAACX2p1tQgAAAJfanW1CAAAAl9qdbUIAAACX2p1tQgAAAJfanW1CAAAAl9qdbUIAAACX2p1tQgAAAJfanW1CAAAAl9qdbUIAAABwKrFtQgAAAHAqsW1CAAAAcCqxbUIAAABwKrFtQgAAAHAqsW1CAAAAcCqxbUIAAABwKrFtQgAAAHAqsW1CAAAAcCqxbUIAAABwKrFtQgAAgBQfxW1CAACAFB/FbUIAAIAUH8VtQgAAgBQfxW1CAACAFB/FbUIAAIAUH8VtQgAAgBQfxW1CAACAFB/FbUIAAIAUH8VtQgAAgBQfxW1CAACA7W7YbUIAAIDtbthtQgAAgO1u2G1CAACA7W7YbUIAAIDtbthtQgAAgO1u2G1CAACA7W7YbUIAAIDtbthtQgAAgO1u2G1CAACA7W7YbUIAAACSY+xtQgAAAJJj7G1CAAAAkmPsbUIAAACSY+xtQgAAAJJj7G1CAAAAkmPsbUIAAACSY+xtQgAAAJJj7G1CAAAAkmPsbUIAAACSY+xtQgAAgDZYAG5CAACANlgAbkIAAIA2WABuQgAAgDZYAG5CAACANlgAbkIAAIA2WABuQgAAgDZYAG5CAACANlgAbkIAAIA2WABuQgAAgDZYAG5CAACAD6gTbkIAAIAPqBNuQgAAgA+oE25CAACAD6gTbkIAAIAPqBNuQgAAgA+oE25CAACAD6gTbkIAAIAPqBNuQgAAgA+oE25CAACAD6gTbkIAAAC0nCduQgAAALScJ25CAAAAtJwnbkIAAAC0nCduQgAAALScJ25CAAAAtJwnbkIAAAC0nCduQgAAALScJ25CAAAAtJwnbkIAAAC0nCduQgAAAI3sOm5CAAAAjew6bkIAAACN7DpuQgAAAI3sOm5CAAAAjew6bkIAAACN7DpuQgAAAI3sOm5CAAAAjew6bkIAAACN7DpuQgAAAI3sOm5CAACAMeFObkIAAIAx4U5uQgAAgDHhTm5CAACAMeFObkIAAIAx4U5uQgAAgDHhTm5CAACAMeFObkIAAIAx4U5uQgAAgDHhTm5CAACAMeFObkIAAADW1WJuQgAAANbVYm5CAAAA1tVibkIAAADW1WJuQgAAANbVYm5CAAAA1tVibkIAAADW1WJuQgAAANbVYm5CAAAA1tVibkIAAADW1WJuQgAAABjcdG5CAAAAGNx0bkIAAAAY3HRuQgAAABjcdG5CAAAAGNx0bkIAAAAY3HRuQgAAABjcdG5CAAAAGNx0bkIAAAAY3HRuQgAAABjcdG5CAACAvNCIbkIAAIC80IhuQgAAgLzQiG5CAACAvNCIbkIAAIC80IhuQgAAgLzQiG5CAACAvNCIbkIAAIC80IhuQgAAgLzQiG5CAACAvNCIbkIAAICVIJxuQgAAgJUgnG5CAACAlSCcbkIAAICVIJxuQgAAgJUgnG5CAACAlSCcbkIAAICVIJxuQgAAgJUgnG5CAACAlSCcbkIAAICVIJxuQgAAADoVsG5CAAAAOhWwbkIAAAA6FbBuQgAAADoVsG5CAAAAOhWwbkIAAAA6FbBuQgAAADoVsG5CAAAAOhWwbkIAAAA6FbBuQgAAADoVsG5CAAAAE2XDbkIAAAATZcNuQgAAABNlw25CAAAAE2XDbkIAAAATZcNuQgAAABNlw25CAAAAE2XDbkIAAAATZcNuQgAAABNlw25CAAAAE2XDbkIAAIC3WdduQgAAgLdZ125CAACAt1nXbkIAAIC3WdduQgAAgLdZ125CAACAt1nXbkIAAIC3WdduQgAAgLdZ125CAACAt1nXbkIAAIC3WdduQgAAAFxO625CAAAAXE7rbkIAAABcTutuQgAAAFxO625CAAAAXE7rbkIAAABcTutuQgAAAFxO625CAAAAXE7rbkIAAABcTutuQgAAAFxO625CAAAANZ7+bkIAAAA1nv5uQgAAADWe/m5CAAAANZ7+bkIAAAA1nv5uQgAAADWe/m5CAAAANZ7+bkIAAAA1nv5uQgAAADWe/m5CAAAANZ7+bkIAAIDZkhJvQgAAgNmSEm9CAACA2ZISb0IAAIDZkhJvQgAAgNmSEm9CAACA2ZISb0IAAIDZkhJvQgAAgNmSEm9CAACA2ZISb0IAAIDZkhJvQgAAgLLiJW9CAACAsuIlb0IAAICy4iVvQgAAgLLiJW9CAACAsuIlb0IAAICy4iVvQgAAgLLiJW9CAACAsuIlb0IAAICy4iVvQgAAgLLiJW9CAAAAV9c5b0IAAABX1zlvQgAAAFfXOW9CAAAAV9c5b0IAAABX1zlvQgAAAFfXOW9CAAAAV9c5b0IAAABX1zlvQgAAAFfXOW9CAAAAV9c5b0IAAID7y01vQgAAgPvLTW9CAACA+8tNb0IAAID7y01vQgAAgPvLTW9CAACA+8tNb0IAAID7y01vQgAAgPvLTW9CAACA+8tNb0IAAID7y01vQgAAAAl3YG9CAAAACXdgb0IAAAAJd2BvQgAAAAl3YG9CAAAACXdgb0IAAAAJd2BvQgAAAAl3YG9CAAAACXdgb0IAAAAJd2BvQgAAAAl3YG9CAACArWt0b0IAAICta3RvQgAAgK1rdG9CAACArWt0b0IAAICta3RvQgAAgK1rdG9CAACArWt0b0IAAICta3RvQgAAgK1rdG9CAACArWt0b0IAAICGu4dvQgAAgIa7h29CAACAhruHb0IAA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\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "05603f09-a8e2-46e2-88e1-fa18eabcfd4a" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -1289,13 +1016,12 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 33, + "metadata": {}, "outputs": [], "source": [ "df = pd.pivot_table(ipcalong,columns='Regiao',values='ipca',index=['mes','OPCAO']).reset_index()\n", + "#df.head()\n", "source = ColumnDataSource(df[df.OPCAO=='Indice geral'].drop('OPCAO',axis=1))" ] }, @@ -1308,10 +1034,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { @@ -1328,7 +1052,7 @@ " 'Sao Paulo - SP': '#4daf4a'}" ] }, - "execution_count": 11, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1342,159 +1066,57 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "34972d89-44f2-4daf-bc05-269d89b761fc" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -1525,16 +1147,14 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[ -2.04202954e-10 2.65492788e-01]\n" + "[-2.04202954e-10 2.65492788e-01]\n" ] } ], @@ -1547,165 +1167,152 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "662688000.0\n" + ] + }, + { + "data": { + "text/plain": [ + "10 6.626880e+08\n", + "21 6.626880e+08\n", + "32 6.626880e+08\n", + "43 6.626880e+08\n", + "64 6.626880e+08\n", + "75 6.626880e+08\n", + "86 6.626880e+08\n", + "97 6.626880e+08\n", + "108 6.626880e+08\n", + "119 6.653664e+08\n", + "130 6.653664e+08\n", + "141 6.653664e+08\n", + "152 6.653664e+08\n", + "173 6.653664e+08\n", + "184 6.653664e+08\n", + "195 6.653664e+08\n", + "206 6.653664e+08\n", + "217 6.653664e+08\n", + "228 6.677856e+08\n", + "239 6.677856e+08\n", + "250 6.677856e+08\n", + "261 6.677856e+08\n", + "282 6.677856e+08\n", + "293 6.677856e+08\n", + "304 6.677856e+08\n", + "315 6.677856e+08\n", + "326 6.677856e+08\n", + "337 6.704640e+08\n", + "348 6.704640e+08\n", + "359 6.704640e+08\n", + " ... \n", + "33004 1.141171e+09\n", + "33015 1.141171e+09\n", + "33026 1.141171e+09\n", + "33037 1.143850e+09\n", + "33048 1.143850e+09\n", + "33059 1.143850e+09\n", + "33070 1.143850e+09\n", + "33091 1.143850e+09\n", + "33102 1.143850e+09\n", + "33113 1.143850e+09\n", + "33124 1.143850e+09\n", + "33135 1.143850e+09\n", + "33146 1.146442e+09\n", + "33157 1.146442e+09\n", + "33168 1.146442e+09\n", + "33179 1.146442e+09\n", + "33200 1.146442e+09\n", + "33211 1.146442e+09\n", + "33222 1.146442e+09\n", + "33233 1.146442e+09\n", + "33244 1.146442e+09\n", + "33255 1.149120e+09\n", + "33266 1.149120e+09\n", + "33277 1.149120e+09\n", + "33288 1.149120e+09\n", + "33309 1.149120e+09\n", + "33320 1.149120e+09\n", + "33331 1.149120e+09\n", + "33342 1.149120e+09\n", + "33353 1.149120e+09\n", + "Name: mes, Length: 2785, dtype: float64" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(float(source.data['mes'][0] - np.datetime64('1970-01-01'))*1E-9)\n", + "(d['mes'] - pd.datetime(1970,1,1)).dt.total_seconds()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "34972d89-44f2-4daf-bc05-269d89b761fc" + } }, - "metadata": {}, "output_type": "display_data" } ], "source": [ "p.line(x=source.data['mes'],\n", - " y=func_ipca((source.data['mes'] - pd.datetime(1970,1,1)).dt.total_seconds()),\n", + " y=func_ipca((source.data['mes'] - np.datetime64('1970-01-01')).astype('float')*1E-9),\n", " color='black')\n", "show(p)" ] @@ -1719,15 +1326,26 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1803,7 +1421,7 @@ "5 PMDB " ] }, - "execution_count": 13, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1822,15 +1440,26 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -1881,7 +1510,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1895,10 +1524,10 @@ "2 Fernando Henrique Cardoso 1995-01-01 2003-01-01 PSDB\n", "3 Luiz Inácio Lula da Silva 2003-01-01 2011-01-01 PT\n", "4 Dilma Rousseff 2011-01-01 2016-08-31 PT\n", - "5 Michel Temer 2016-08-31 2016-07-01 PMDB" + "5 Michel Temer 2016-08-31 2018-12-31 PMDB" ] }, - "execution_count": 14, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1906,7 +1535,7 @@ "source": [ "presidentes.inicio = pd.to_datetime(presidentes.inicio,format='%d de %B de %Y')\n", "presidentes.fim = pd.to_datetime(presidentes.fim,format='%d de %B de %Y')\n", - "presidentes.fim.fillna(ipcalong.mes.max(), inplace=True)\n", + "presidentes.fim.fillna(pd.datetime(2018,12,31), inplace=True)\n", "presidentes" ] }, @@ -1919,18 +1548,16 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'PMDB': 'orange', 'PRN': 'teal', 'PSDB': 'blue', 'PT': 'red'}" + "{'PRN': 'teal', 'PMDB': 'orange', 'PSDB': 'blue', 'PT': 'red'}" ] }, - "execution_count": 15, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1949,10 +1576,8 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [], "source": [ "boxes = presidentes.apply(lambda x: BoxAnnotation(left=x['inicio'].timestamp()*1000,\\\n", @@ -1971,159 +1596,57 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "34972d89-44f2-4daf-bc05-269d89b761fc" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -2143,15 +1666,13 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false - }, + "execution_count": 25, + "metadata": {}, "outputs": [], "source": [ "from bokeh.models import LabelSet\n", "labelSource = ColumnDataSource(dict(x=presidentes['inicio'].map(lambda x: x.timestamp()*1000),\n", - " y=np.repeat(0.55,presidentes.shape[0]),\n", + " y=np.repeat(0.5,presidentes.shape[0]),\n", " text=presidentes['partido']))\n", "labels = LabelSet(x='x', y='y', text='text',\n", " x_offset=5, y_offset=5, source=labelSource, text_font_size='8pt')\n", @@ -2160,159 +1681,57 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "34972d89-44f2-4daf-bc05-269d89b761fc" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -2333,10 +1752,8 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": { - "collapsed": false - }, + "execution_count": 27, + "metadata": {}, "outputs": [], "source": [ "from bokeh.models import CustomJS, CheckboxGroup\n", @@ -2373,159 +1790,57 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": { - "collapsed": false - }, + "execution_count": 28, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "4488659e-d269-4464-a1d4-cc3afaeb4b30" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -2563,10 +1878,8 @@ }, { "cell_type": "code", - "execution_count": 44, - "metadata": { - "collapsed": true - }, + "execution_count": 29, + "metadata": {}, "outputs": [], "source": [ "d2 = ipcalong[(ipcalong.Regiao=='Recife - PE')]\n", @@ -2575,159 +1888,57 @@ }, { "cell_type": "code", - "execution_count": 45, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "\n", - "
\n", - "
\n", - "
\n", - "" - ] + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "d4fe743e-d3a2-433a-968a-b23bcf9836d9" + } }, - "metadata": {}, "output_type": "display_data" } ], @@ -2767,9 +1978,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -2790,7 +1999,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula12-datavis-parte04.ipynb b/aula12-datavis-parte04.ipynb index 57d7afd..a77cce8 100644 --- a/aula12-datavis-parte04.ipynb +++ b/aula12-datavis-parte04.ipynb @@ -15,10 +15,8 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "from IPython.display import YouTubeVideo, HTML, Image\n", @@ -65,19 +63,17 @@ "source": [ "## Contando uma estória com os dados\n", "\n", - "Existem vários bons exemplos de como contar uma estória com os dados. Um autor que se ~~destaca~~ destacava (eu não sabia que ele tinha morrido em 7 de fevereiro de 2017, segundo a Wikipedia, até o momento que terminei essa aula 02/05/17) com frequência foi o estatístico Hans Rosling. Existem vários vídeos na internet com palestras em que ele narra uma estória, usando visualizações. Para ilustrar como uma boa estória afeta a qualidade da visualização, vamos assistir uma de suas palestras, essa gravada para a BBC." + "Existem vários bons exemplos de como contar uma estória com os dados. Um autor que se destacava com frequência foi o estatístico Hans Rosling. Existem vários vídeos na internet com palestras em que ele narra uma estória, usando visualizações. Para ilustrar como uma boa estória afeta a qualidade da visualização, vamos assistir uma de suas palestras, essa gravada para a BBC." ] }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 3, + "metadata": {}, "outputs": [ { "data": { - "image/jpeg": 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R+DAq1DJh1xouIDsTIAVtzTD5w+4cYScEz2ATKBliYe0TDjY32Xm3ultrv6aOFPH89EZE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\n2ss7IOjXXP8AYp8CA/2uAks5DMeqS1B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\n", "text/html": [ "\n", " " + "" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -106,7 +102,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Observem que a visualização serve de suporte para reduzir a carga cognitiva e facilitar a comunicação da estória. Ele contextualiza as visualizações, o que nos permite rapidamente processar a mensagem que ele tenta passar. Em outras palavras, o gráfico é um 'mero' recurso de comunicação da estória dos países focada em dois aspectos: renda e expectativa de vida. A visualização, além de ser esteticamente bonita, é também muito efetiva para transmitir a mensagem que ele queria passar." + "Observem que a visualização serve de suporte para reduzir a carga cognitiva e facilitar a comunicação da estória. Ele contextualiza as visualizações, o que nos permite rapidamente processar a mensagem que ele tenta passar. Em outras palavras, o gráfico é um 'mero' recurso de comunicação da história dos países focada em dois aspectos: renda e expectativa de vida. A visualização, além de ser esteticamente bonita, é também muito efetiva para transmitir a mensagem que ele queria passar." ] }, { @@ -130,13 +126,11 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/jpeg": 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rYShZFPV2ikd6uPYjqbScrHevg7pj1DYqrSO4ZvO9x1pM3XyZMu2Nl+ly4ij8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\nuocIsRfNFubkuXL9FnpA1BqGGuFf/GpASkREIkC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\n", "text/plain": [ "" ] @@ -160,9 +154,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -184,16 +176,14 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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/NKh/NM/Yx54y8QekXPzB4P/wzw+X4buyY6fvG63DVnwrYz3++nBKNL4t/mCxCX8t+j38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\n", 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hw4ZRXl7OkiVLeOutt+jevTtpaWk8++yzbNu27YBjRo4cSf/+/at/fuihh4iJiaF3796MHDmSJk2a7Ld/aWkp27dvp3nz5jzyyCOUlpZyxhln8M1vfrN6mWX9+vUUFBSQm5sLQEFBAX369GH69Ok888wzpKWlkZ6ezttvv80999xzpEMqoZ17yoiNMf65dCNd2yVz/7BuvLN8M7vLgqDNXru9et+N20vp1DqJ/24qJiEuhlgzkhJiAdhWUsbL89fy8vy1XNy9DcvydnBNv/a8kb2eq89sz4AuaXyYUxiVPorUpkEf6p133nlMnjyZ8vJybr/9dt5++20APvvsMwCys7PJzs7GOUdRURG7du0iJycHM+Paa68lLi6OrKys6ll1TQUFBcybN4+ysrLqbZs3byYtLY1rrrmGvXv3HnBMx44dAcjIyOC6666jefPmLFq0iKVLl5Kenl695l2lvLwcCD58vO6669i4cSNz587lgw8+YNiwYVx44YXMnj2bJ598koSEBADi4+Np1aoVDz74IFu2bCE9PZ0pU6Zw4YUXkpOTw9SpU4mLi6teb66N/tuiumXlbqfSOfZWVFJWUUllJTRLiKVpkxgKd5Vx6+BMstduIyUxnvTUBNZsLSErN3hzvrx3O/pmNCdv227ytu0GwIBRAzpw99+W8ejVPcho0ZTUpHiaxOlLRj47GV8jDQrkfv36MWXKFFJTU+natesB5bfddhvNmzcHoLKyksTExHrXnZ+fz6xZszjllFMYNmwYy5cvZ9GiRdUBOnny5DpnyK1ataJXr17V29LS0lixYgWbNwdrkRUVFVRWVhIXF0ezZs1ISEigSZMmDBgwgPz8fObOnUtBQQEAw4cPZ/DgwezatYuVK1cybdo02rVrB0BSUhKZmZnk5eWxbt06rrvuOh5//HGuvPJKCgoKmDp1KnfddVe9+yyB3IISnp2+irsuPo3yCsfjU1fy/YtPo2f7FG54cRFJTWJ5dmRf4mNjmP5pPm9mb2BvRSVPT/uCH1xyOsWl5fx0yqdULUZc0SedeasKKC4t57VFeTz5jV6sK9zNAs2OxTMNCuTExERGjhxJQkLCfmu0PXr0YNmyZcyaNYuzzjqLrVu38sUXX3D33Xdz+umns2HDBt566y2Sk5PrnB1XKSsrY/v27Xz++ef7bb/pppv2mzlXqVq/nThxIunp6aSlpVUvi1TNnv/xj3+QlZXF3XffTYcOHTj33HOZN28eM2fOrA7tqpntzJkzadasGcXFxcyePZuMjAxOO+20/R5zypQpDB8+nJiYGCorK1m5ciXFxcVUVFQcznBKhEkL1zFp4brqn6cu21R9f9ysLxk368sDjnl1UR6vLso7YPvU5fuOXbRmG197em4jt7bxnIyzQtmnwd9D7tev3wHb+vfvz86dO1mwYAFvvvkmqamp1ftdcskl5Ofns3TpUrp3707r1q3ZunXrAXW0bduWIUOGsGDBAubNm0f37t1ZsGBBdXnnzp0POKbm8VlZWRQVFZGcnMzFF1/MBRdcUOu+w4YNo7i4mOnTp5OYmMhFF13EwIEDgeBrfjNmzKCyspLTTz+dESNGYGbVx3788cckJSXRrVs3AK688kr++c9/Eh8fzw033HCI0RMR2cdq+6bCQegj6UaimdA+Got9NBb7nGBjYYfe5TADedy4cQrkRvJR7vZD73QMnJPZItpN0FhE0FjscyKNxZgxY+oVyPqYWUTEE1qyiJIT7HSsQTQW+2gs9jnBxkIzZBGR44kCWUTEEwpkERFPKJBFRDxx1C9QL/XTPjWRqf8zuPrn1z9azxMRF2Xv2rYZP7umF22bJ/Bm9gZ+MzOHuBjjz6PPoXt6CkvWbueOV5YA6KLsckI6GV4jCmTP3DI+i81FpdWXkKzywLAz2LRjDy/OWc3Y6/uw8MtCPsrdzvRP86mM+KZMSmKcLsouJ7QT+TWiJQvP/PrGM3nuxr5ktmq63/bu7VNYsm4Hcz4P/sz8vM5pVDjHxPlr2b5r3zU9KiqdLsp+Ammfmkj2wxdX3358xRn7lZ+Zkcob3xvAhw9cyJ9vPYc2KfsuL3tl33SyH76Y+y8P/qz/2+dnMudHQ3gg/Ll9aiLP39j32HWmkZzIrxEFsid2lZbzwBsrGDMpOKX68RXd9ysvLN5Lp1ZJdGqdBATv8rUp2VtxwEXZ564qYNyofjx6VQ9irV5fhxTP3DI+i8ufm8fzM3L2237r+R1pEhvDbROy6XlKCt84O/gvygz49gWZ7C3f9x9A3DI4k/tfX8HVZ7UnJTGO717YmT/MWXMMe9EwJ8NrRIHsiaI95Uz7NJ+Vm4qZuXJL9ZOqyu9mfcmwPu14efS5lJZXkL/zwGtBV3l5/lpGvZTFnrLK/S7KnpYUz4AuaUe7K3IU1DUrzC3YTUlZBbmFJZRXuuqL+A/t3Y712/awtXjfrK+sopI1BSWUllXSsWVTkhNiWbGh6Jj2oyFOhteIAtkTAzqn8fW+6XRp04whXVuzZmsJKYlxtGwWD8B/N+3k5j9l8ct/f06MGTM+ywegU6skEpvEkhgfS6dWScTFBO/uVRdln/DhWuLjYnRR9uPUoWaFMz/Lp31qIrPvG0Jh8V7e+Cj4r65uuyCTP/5n9X77Pvv+KsZe35s/zV3DzYM6MnnJRn59Y19+dV1vksP/ZcVnJ8NrRK9OT+wuq+A7F3Ri0nfOJT7W+Nm/VvLDy7rywjfPAuDSnm2ZMPocbg8/fFhTUALAm2MG0r9TGr1Pbc6bYwbSJiX4X01qXpT9W4M74hy6KPtx5lCzwnuHdmNtQQm3T8wmMT6W2y7I5MJurSksLuOT9TuBfX+zO3XZJka9lMXiNdsor3CcndmCrDXbKNi1l8t7+///QJ4MrxFdyyJKTrC/028QjcU+NcdiQOc0Wqck8NnGnTwyvAexMcadf1lCfKxRuKuMl0efgwOeevdznruxLwtXF7Jy407uHdptv3qeeve/vJa1HoDnRvbl6WlfMLJ/BmbQrnkC2bnb+WvExf19HIto0bUsRAQ49KzwNzNzaN40jvGjz6Zg115e/nAt767YzKiXFjPqpcVs2VnKtE82896nwen7WR1S2Vpcyrptu3lryQYuOqMNnVo1Y1pYLtGl7yGLeGxZXhHXjluw37ZH3v6s+n5W7nZGjFt4wHHbSoKveQ19bt5+25es28GSdcF/m5azZRdXPP9hYzdZGkAzZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBMKZBERTyiQRUQ8oUAWEfGEAllExBNxx/LBzn585rF8uDplP3xxtJsgInIAzZBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEE14E8iPDe5D98MV8rUeb/bZ/d0hnZt/3FebeP4RffKMXcTFGXIzxym3nsvihi/jDzWdV7/vgsG7850dDuHVwJgBnZqTy8JXdj2k/REQaIuqBfEqLRC7p2abWso9yt3Hrnz/iufdzuKxnO87JbIFzMP3TfD7dWFS9X0piHMPPbM/9b6xg9PkdAbhjSCf+OGf1MemDiEhjiHogf/v8TKYu21RrWVbudlZvLWHD9t2UllewYcceKpxj4vy1bN9VVr1fRaWjrKKS1VtLKC2vZFCXlqzeWsKmotJj1Q0RkQaLaiC3a57AV7q25u9Z6+vc5/U7B/Dbm/qxPK+ILTtrD9iSvRWMn5vL2Ot789z7qxh9fiZzVxUwblQ/Hr2qB7FmR6sLIiKNJqqB/M0BHXgjez2l5ZVBY2oJzrteXcq9/1jO2ZktGN63fZ11vTx/LaNeymJPWSXL8nZwTb/2vJG9nrSkeAZ0STtqfRARaSxRDeRT0ppy54VdePv7gwB46hu9OatDKi2bxQNwWc+2xMcae8oqANhbEQR3p1ZJJDaJJTE+lk6tkoiLCYLcgFEDOjDhw7XEx8WQ0aIpqUnxNImL+sqMiMghRTWpnp2+ilEvLeYHf1sKwK/fX8UN/TN44ZvBtyeu6JPOq3ecxxPX9mLqsk28szxYa35zzED6d0qj96nNeXPMQNqkJFTvP29VAcWl5by2KI9vDe6Ic7AgpzA6HRQROQzH9PKbNeVt2w3AZ9R+ac4fvLas1uPquozn1OX7PhxctGYbX3t6bsMbKSJyjOhcXkTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPmHMu2m0QERE0QxYR8YYCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEEwpkERFPRD2QzayDmX1gZp+a2Sdmdne4vaWZTTezL8J/08LtZmbPm9kqM1tmZmdH1PWUma0IbyOj1acjdQRj0d3M5ptZqZndW6Ouy83sv+E4PRCN/jREI4/FeDPLN7MV0ehLQzXWWNRVz/GkEcci0cwWmdnSsJ5Ho9Wn/TjnonoD2gNnh/dTgM+BnsAvgQfC7Q8AT4X3rwDeBQwYCCwMt38dmA7EAc2AxUDzaPfvKI9FW6A/8HPg3oh6YoEcoAvQBFgK9Ix2/6IxFmHZEOBsYEW0+xXl50Wt9US7f1EaCwOSw/vxwEJgYLT7F/UZsnNuo3MuO7y/E/gMOBW4Gng53O1l4Jrw/tXARBdYALQws/YEv5Q5zrly59wuYBlw+THsSoMd7lg45/Kdc4uBshpVnQescs596ZzbC/wtrOO40YhjgXNuDlB4LNp9NDTWWByknuNGI46Fc84Vhz/Gh7eo/9ly1AM5kpl1As4ieLdq55zbGBZtAtqF908F1kUclhduWwpcbmZJZtYauAjocAyafVTUcyzqUtcYHZcaOBYnlMYaixr1HJcaOhZmFmtmHwP5wHTnXNTHwptANrNk4A3gB865osgyF5xXHPTdyzk3DXgH+BB4FZgPVByd1h5dDR2LE4nGYp/GGouD1XO8aIyxcM5VOOf6ARnAeWbW+6g09jB4EchmFk8wuJOcc2+GmzeHSxGE/+aH29ez/8w3I9yGc+7nzrl+zrlLCdaIPj8W7W9MhzkWdalzjI4njTQWJ4TGGos66jmuNPbzwjm3HfgAD5Y4ox7IZmbAn4DPnHPPRBS9DdwS3r8FmBKx/Vvhty0GAjuccxvD049WYZ19gb7AtGPSiUZyBGNRl8VAVzPrbGZNgBvDOo4bjTgWx73GGouD1HPcaMSxaGNmLcL7TYFLgZWN3+LDFO1PFYELCE4vlgEfh7dKX+aWAAAAlUlEQVQrgFbADOAL4H2gpdv36ejvCL5FsBw4N9yeCHwa3hYA/aLdt2MwFukE68NFwPbwfvOw7AqCM4Qc4KFo9y3KY/EqsJHgg5084LZo9y8aY1FXPdHuX5TGoi+wJKxnBfC/0e6bc07XQxYR8UXUlyxERCSgQBYR8YQCWUTEEwpkERFPKJBFRDyhQBYR8YQCWUTEE/8He1Iih+iblG8AAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -247,9 +237,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -269,6 +257,154 @@ "Image(url=\"https://abrilveja.files.wordpress.com/2016/12/paises-mais-inovadores-do-mundo.gif?w=600&h=400\")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Exemplo 4 -- Fox News (EUA)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Image(url=\"https://www.mediamatters.org/static/images/countyfair/fnc-an-20120220-gasprices.jpg\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Exemplo 5 -- Oversight Committee (Câmara dos Deputados -- EUA)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Image(url=\"http://stimms.files.wordpress.com/2013/02/bad-visualization.png\",height=800,width=400)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Exemplo 6 -- Desemprego no Brasil em 2014 (Globo News)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Image(url=\"https://jornalggn.com.br/sites/default/files/u16/10417500_594207114017852_1658933027615569882_n.jpg\",width=600)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "d = pd.read_csv(StringIO('''pais;desemprego\n", + "Reino Unido;6\n", + "EUA;5,8\n", + "Alemanha;5\n", + "Coreia do Sul;3,5\n", + "Chile;6,7\n", + "Peru;5,7\n", + "Mexico;4,8\n", + "Brasil;4,7\n", + "PNAD;6,8\n", + "'''),decimal=',',sep=';')\n", + "ax = d.set_index('pais').plot.bar(legend=False,color='#3182bd',edgecolor='none', figsize=(13,8))\n", + "plt.xlabel('')\n", + "ax.set_xticklabels(ax.get_xticklabels(),rotation=0)\n", + "fmt = '%.0f%%' # Format you want the ticks, e.g. '40%'\n", + "ax.yaxis.set_major_formatter(mtick.FormatStrFormatter(fmt))\n", + "#plt.axhline(y=5.694,color='#737373')\n", + "#ax.annotate('Média={:.2f}%'.format(5.694), \n", + "# (-0.5, 5.8),\n", + "# color='#737373',fontsize=10,fontweight='bold')\n", + "for p in ax.patches:\n", + " ax.annotate('{:.2f}%'.format((p.get_height())), \n", + " (p.get_x()+0.05, p.get_height() * 0.899),\n", + " color='white',fontsize=10,fontweight='bold') \n", + "\n", + "ax.set_title(\"Comparativo do desemprego nos países em 2014\") \n", + "ax.get_yaxis().set_ticks([])\n", + "ax.patch.set_facecolor('white')\n", + "ax.spines['top'].set_visible(False)\n", + "ax.spines['right'].set_visible(False)\n", + "ax.spines['bottom'].set_visible(False)\n", + "ax.spines['left'].set_visible(False)\n", + "plt.tick_params(\n", + " axis='both', # changes apply to the x-axis\n", + " which='both', # both major and minor ticks are affected\n", + " bottom='off', # ticks along the bottom edge are off\n", + " top='off', # ticks along the top edge are off\n", + " left='off',\n", + " right='off')\n" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -289,7 +425,6 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "collapsed": false, "scrolled": true }, "outputs": [ @@ -314,9 +449,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "dados = '''Country;Bottles Per Person Per Week\n", @@ -339,9 +472,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -380,15 +511,26 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
5Michel Temer2016-08-312016-07-012018-12-31PMDB
\n", " \n", " \n", @@ -442,7 +584,7 @@ "Excited 0.19 0.38" ] }, - "execution_count": 9, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -459,16 +601,14 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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AE9Ghr2yebnzgtBQEY6xtpmmm/QiC3uy/v10Xa8tQy8ykuQv4EZa0ln8OaA+M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NPUarU01GlFixcvhiAIeOGFF6Q0Ozs7o0/IdCMkpaSkSGlEhI8//tjoINvf3x+enp5YtGgRHjx4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\nYII=\n", 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XEDKuPNdDwANW1xGrJjQ3f5FXXDoz1O3sVr1WneZ54rgmEts7bWgxcMr2x86N3h/+KON2OPsDWzAG10SM8u6sujU7zswpdJ12QrPni1eL94b8/QqwTR+w7DTvH7oSuvs7a/tj534YhOOYJmqveF15rmMw7u0KC2hKlc/fWxbys+d1+ogvTvY8M7EDoQvGTkY3haomERKPEmGhC9CrlkmDytUOq+tok1LqgfLKIWY0tU3vvzyIoQvGwMmIWjEsaoMXeApMWSFJHMZN1bUF6boK6ZKcbwemf36R95GZnXwDP545b2GoNmoQQeR2OI8Hrre6js7QQLv5/cB2q+toS99A4KtjW6b7VTcrLvlXI47n6nEuqGf5Lj+//riZ4/9Uz7VvN+17zavrvTy9omMDt7fr/Zaf7v3DpCCGLhirEEbU+gxRGbyuPNdZwAVW1xGrUnV940+ra6aH6vhK4XvCd+mSX/iyZ3fhMOnAY0EqSYTWH4ngzypHESemNqkaq+s4mrsqq/cF4c8/aOaskXEU/DSNb+amMrCbjbUlAdbfkkaCHfL3BmjyKf76tY/sSe2/0Nyh911xqveJSQHsoRi8dV/mvIWWrLTVGRH7w3wkrjxXAsZOJaZTuuK7B75jx1NGz5K3zMvWh7ey+a7N7Hx+J7rfGGVY8XEFW+7dwvY/bt/3WMPmBopfL7ai7OBSSs3fW6ZCtZWYUtTf5rtt/XOBi4IxPewqmdsb3twO57kY6/RGLA1Sr/68Y4OszJSo69+d2dA4AaCmWfHFDj83jjfGoybYNXoma/gCoJSi0aeIt8MTy7zcNjmBeHv73uY79b4rsrxPnhii0AXjNsQTITp20EVd8AI/x6INECo+qiBx4PfLtZX8q4ReZ/Ti2MePxZ5ip+qLKgCql1cz8pGRpIxMoT6/HqUUZe+UBWXVGas5vb6llz1WPtb1p3rG5dZz4ov1AEHpqgoorfSH3pyi9/STgrUYhw34bZCOJYLM7XDGYaytHvFOWa9G2HQVsLqOw5lTU7fvjL+wWqdPisb1/2tm/Av1/PidJmwanDMqjvEvNDAgzUZ6osbK3QEudLRvssguvffKLO8TE0MYuq2uzJy30JTBYV0VVcHrynOlAb+2om1fpY+6b+rImJkBGGeHDe4G0icZtzkzZmRQt7Zu3/NV4Ps1VquXVZPmSiMuLcJ3vVKq5k8lpQ6Az+ak8PXcNL66OY2aZtXlriqPituW5X3Su1Yd6why1edlzlsoi6uEp58ATquLCAa7zuAz1nZ9QY1g05SquLmmZt+CGX4d1hbr3HJiPOt+kkZqvMZjSzzcNT2Rr+em8eSZSdz/mYeHT0nk5bVeLnuzkUe/OPLJc5HqvfIU7x8n+Ikza0rnH01qp0uiKniBbMD0hfgBil8vpv/l/fd1sAbqA9hT7GgtXTFxGXH4qozVZnqe2pNtj2zDV+EjZVTKvlVnIt1VtfXf9NL1QxY3sGl0qauqRqWsn+JZkLFD9R8cksLlXm/YcTuc6UCO1XUE0+Vf6JbtbXskpzQ25e+/Tefg7hqDu2tMGWxcBFwyJo61Jd8vxLGuOIBSMLqXjTc3+vjXpSlsrdLZUnHoxfxu1WvVbI+poQswMXPewjNNbK9ToiZ4XXmuVCxalaj261riuseRnNm+tSIypmcw8uGRDPnJECo+qqDXab2oy69j53M7KX69GKVH3vTSRF3fcldl1XQwNvM645VGJr5Yz4trvHRL1DrdVbVT77Nisuf5Y6vplhHC8qdnzlt4XgiPLzruHiJkhar2SvXgGrsjeJsndJlS3nsqqg7oUeifZmNIuo1N5UaQflroZ0zv72Pi/s88PJKViE+HQEse24BGHwfYo3qumu15apzJodvqbgva7JCoCV7gVix6ozZuaaR2XS2bfrmJoj8VUe+up/i1YgKNAVTACFF/lZ/4jAN/Bn1VPpq2NdF9YnfKPyhnyK1DsKfYadjYYMVfo0ueLC1vtIMdYMn1qaz9SRrvX53CgtVevtjh71RX1Sp99OJZ3qcme0gwY1pYRC+6Hk3cDmcP4KdW1xEKP/5QD5vRzSN9vtX9AoFDNu999uwkrn6rieP/VM/XJTr3nGyMW/lvgY8TB9oY2M1GjySNcf3tuP5UT3NAcUL/72cHFaueq2d5nh7nI86qubWzMuctNGWZ2s6KiuB15blSsHAN3v6X9sfxlIPRT45m8C2DSXOmMWTuEFIdqdSsNt5nVUuq6Db+wC0u9761d9+uI8rbcpXbyTVWrZTp9S2b1dS8b7GMQd2NH6u+qTYucsSxavf33VDt6apSCvWGf9bnl3kfnNWJNVw76/jMeQtPM6ktcXTXAx1ZECViDKxgcq8aFRbTF+4vr+x5uMfH9bfz1c1prL8ljf9ekUJGsnE76EJHPDmzvz8HfuKMJPJvSeO1i7//X1WiMlbP8jx1vIWh2+oei9s/qqgIXuBmoMsLkgdb/8v6U/FhBZvv2kygPrBv4BVA0w5jdG9r93T61HS+u+87Grc0kuaKoAV6lGp4saR03z67DV5FnUft+/1HWwMc1/f7s+G2uqqUwvs7/1XLfu3/yWyz/gr7+ZkFbYr9uB1ODaP3KippEPfjj/TNVteRHgisn+DxBnXgWonK+Gqm5+njvcQntv3skDs3c97C460u4kgifBgtuPJcGsagqrCQ5kwjzWkEZ0LfBEY8OOKwz0selszgG78fK9T7zN70PjPybmldUN/w1YBAYFbrn/c2KC56oxEwRkhedVw8Z400fsz276oC9nVVHd/Pxgn97ShF7Vzf7Vs/1CeHbPGNNpybOW/h8O2PnbvNovYFnAWMtLqIUJrwnTo+wacavfGaZVf1P6uqaQzm8UpVj69mep52hUnotrobuNLqIg4n4jdJcOW5TgM+trqOWBSvVOGK7bsGJUCXu5UCylZ8sTen7hs10pI52Pt5avtj595hcQ0xy+1wLgTOsbqOUPvfVO3L106xn2xF23FK7VqzfdcgW5B6PEtV+pqTPc+MNWksRkcEgFHbHzu30OpCDhYNXc1zrS4gVj1SVlERjNBtVvHfzfI+pcIgdAFuyJy3MOymfcQCt8M5HOOKN+qds1oNwqKrnkvq6rcFK3TLwjd0wRjseaPVRRxORAevK8/VH1mT2RID/P5V5zY0ntjV41SptK8nexb0KVJ9wmWd1XRgjtVFxKhbifDPpPaKDzB8xrdqjekNK1X3s8rqCcE4VLnqvvZkz9NjwjR0W12XOW9hMDdkCIpI/yG/kSi4Tx1xlGp+qbh0QFcPs03vv3yKZ4GzlrSQ7mLUCbdYXUCscTucycANVtdhpmsW6SFZz/xoJjV71nVTqlvbzzy6ctV97QzPM85mEtu3eIF1BgFht6BGxAavK89lQ/ZUtcRpjU0rh/n9Xdq7c2lg7OIs75NTw2wwRqvjMuctDPlewuIAVwOhXCQl7GQ0MDGzRG01rUGl9AfKKzO7epgK1W1dhIRuq7DbUjJigxeYDgyzuohYY1eq6HdlFZM7+3qlUK/4T1t8te/eWcYaV2HrKqsLiDExdbXb6uYPAnvMamugP7A60+8f2pVjGKE7f3QEhS4Y67F3t7qI/UVy8F5sdQGx6O6KqqIkpTr1plMKT47/2hX3+2+Y1fazLXdF5ryF4XxiEDXcDmcfYIrVdVhhRDEndmtUlWa0dU9FZZfuxVaptK9neOaPbiIx0hY3SSLM8iKSg/ciqwuINb38gTWX19VP7cxrlaLmRt+dBXmBs04Kdl0hMpQYDQMLnENkfxZ1mgbJcz7R80PdTrKuu/dfXa6jqlTaN9M980dFYOi2utrqAvYXkT/srjzXRKSb2VxK+V4oKe3UPTi/su051/vb8kX6hEi7bxpWZ8lRLKY3qJi+UY22B5Sv7Wd23k3VtZ2+qq5Wqd9M98wf2UhSJE+zOyVz3sKwGUMQkcGLfCCa7qSm5mWjfb7hHX1dk0rYfLLnGdtGlXn4JbzCm/SqhJjb4YwHzrC6DivZFf3PWxW6vXptSu2dU1M7qe1nHqpapa6f7pk/IsJDF4w5vVlWF9FKgle0yabU3j+Wlnd47l+56r52kuf5/sX06h+KukwwMnPewrFWFxHlTgbCauCLFS5eqofsauzMhsaCzix0U6NS1k/3zB/eQHIELR5/VKdbXUCriAteV55rFOCwuo5Y8rOqmu/SOjj3b7M+aOlUz3OuelIi/UP1FKsLiHIx3c3cKtmHc9xWfX3QD6xU868rqjp88lijUvKneZ49JopCF8KoZyXigpcw6i6IBd0DgfU31tR2aNOCRYFxn5/hfXyaRZtgB1skjMCOZBK8LW78SA/qxgUAY7zer3rpeod2X6k1QjezgeR2nWyX/9/T7Hr2avb8+ftNpao++wu7X5rLnr/8lNK3HkVvrgeguWgje/7yU4rzbsdXuRsAvbmevW/cj1Ih3w71mMx5C8PillckBq9cgZhFKf35vWXtXuBCKfSX/ed8cYPvrtlhPke3I2ZaXUC0cjuco4BRVtcRLvpWM6lfpSoK5jEfKK86ZKP7o6lVyRumeeYPa2/oAqS5TqPvpQ8d8FhS5jgG3riAgTc8R3zPQdSseNM4/uq36XtJDhmn3kTd1+8DULPsDdJPuhRNMyWOwuKqNxKDd7bVBcSKEzzeJSd4vKPb81ylaL7Xf8OqR/0/andQHe5MuaFgCXtevpUdvz8fT/GWfY9beKbcN3PewjGhbCCGydXufjSw3/yBHrSVrHoFAmvHer3tPrGpU8nfTvM8O7Sjt4eShhyH/aCcTj5mAprNWCI5ceBo/HXlAGi2OJTfg/J50Gxx+KqK8deVkzTUtK1zw+I+b0QFryvPNRLo0Bmc6BxNqYoFe8va9W7QFVXX+uZteT1wWofm+B7uTDmh9zD6XHQPiUMOvC1l8ZmydDeHhvy7HuS4HWp8skfVBeNYd1RWB9r7XCN05w8OxZiM+vUfkzzc2E8lfeqllL/3R2pWvEm3CedR/cXf6XHyj4Ld5NFkhcOmCREVvMA0qwuIFTfW1G5M1/UebT3Pp+xFZ3sfq/5SP97V0TYOd6Yc33sI8b0GH/Jci8+UJSBCY6LVBYQbDbpfsVhf29XjxCtVeH59Q7t2D6tXSRuneeYPriM16JuV1Cx7A2x2UsfMBiCh33AGXPsk/a/8Hf6aEuxpPQEo+9/vKX/3CQINVcEu4WDpgOUzFSR4xSFSdN19W1VNmwOqGlSie4bnmYRNaugxoa7J4jNlCd4ga1km8tAzLMHp61Sm1sX7J1fV1u3SoM1xFi2hOygUoVuf/wmNW1fR+/w70Q4a8qGUMnqspl1B9dLXyZh9PWknnEntmneDXcbhdPgiIdgiLXjHW11A1FNKPbO3LNDWRtmlqsdXkz3PD9lLz75mlGXxmXL/zHkLTfl7xhC52j2COJ1hp3zT+QU1NKWqb62qafPft0Eluad55g8KxbacTdvWULvyP/T94QPY4g9dIrphwyKSh5+IPbkbyucxxmJqmvH70DPthvKRRFrwyiCXEDvW61s2tdlz3NGe49aHLjnJ8+w4K+b4WXim7Ax1AzEmKJuxR6urPtc7vaHB9Kbmb1KUOupKUw0q0T3NM39AMEK37J3HKXnlTnyVuylaMIe6bz6i8uNcdG8Te9+4jz1/vY2KD5/b93zd10z9hk/oNuFcALpPupDSN3Oo+vQluo07u6vltIflV7wRs4m8K881BIimydzhR6ma3L2lxx7tKR8GTvz8J747ZptU0SEsPFMeAywOdSMxxPKrjnDWvYkTRu1Wm7YM0to1q2Afpfz3V1Qe9T3cqBILpnvmD6ghrc0xHO3R5wd3HfJYtxOOPGvHFp9E/yt/t+/PSUOOY+CNC4JRSntZ/rMXSVe8crUbYlfU1X/dJ6D3Odz3lCKwwP+DL4MZuoc7U27cvIyiBXPw7Cmg9N8PsfeN+/c93+IzZfn5Cy7pQWjDze8Hyjv6mkyff/VAf2DAkb7fqBI3TfPM71dNt6CEboQaZPWGCe2+4tU0bRgwSin1iaZpyUCcUsEZ9t5O8sEXQom6/t2vK6oOO6BKKRp/5f/Jhn8HZp0czDYPd6YMkHLs4cfQWXymLEERJG6H0wYc9aqsszy6zrW7duJVCr9SnNGtG7f17kOR18snIZUcAAAgAElEQVQvi/dQHQgwNimJxwYMJEHTeLWqkn9VVzMgPp5nBw0mQdNY09jIx/V1zOtr7czFoWVM6lGvyqrTtMOeDB/OvRWVR5wO1KgSNk33PNOnmm5hs0uPhY7Hwh6sdl3xapp2E/Bv4IWWhwYD/w1VUUcgH3wh9Puyirq4w5yI6Uorv9J3b+G/A7MmW1FXGJETv+DJxNicPOgSNI2/DBnK25nH8FbmMSxpaOCbpiaeLC9jTkZPPhw+gu42O29VVwPwXm0t/808hvHJySxtqEcpRW5FBXN7dWiVxZDQIOGGj/Rv2/v8NF3fMLXZc9ipMk0qYfN0z/w+VXTvGbwKI5ql93nb29WcDUwHagGUUlsAs0d5SvCGyFCfb/mpjU2HjBj3KfuO072PN6zQx1o+7y0MDMictzCWu+eCKWTvZU3TSLUZH2v+lqtegJWNjZzRzZgzfmF6Op/WG2sHq5bnNemKOE3j3dpaTk5NpYfd8jUWAJi8SR0X51ftGsBwa1XNYXsgm1TClumeZ3pJ6B5gpJWNtzd4PUopb+sfNE2Lw/iZNdMQk9uLDUo1vFhSOuzgh+tV0saTPM+mbFWDDvleDAv5fOUYMTSUBw8oxUXbC5nx3RampaYyND6ebjYbcS1zSfvFxbHXb+w7f3WPDK7YuYNin48Jycm8XVvDlRnh0xNrg94XLddXtfU8u1J7rqytO2TP3WYVv2WG55mMStJ7habCiGXpfYT2Bu9iTdPuAZI1TTsdeBMwZabzfmQeZQic19C4epA/MHD/x4pVz9WTPH/KLKdHu+8txQjr+x+7QNM0u6ZpT1hdBxDSKy+7pvF25jF8NmIk+U3NbPN6j/jcH6Sn81bmMTw+cCB5lVVc3SODLxvquX33bh4r3YuuzL6+OEyNK1Sb+1n/oL5hy8G3ippV/HfTPfMzKkiP6J/bELE0T9obvPOAMiAf+Anwf8B9oSrqYK48Vzcg2az2YkWcUjseKqs4af/HvtGHfzndM39CE4kpVtUVxiL6REQpFQBmWF0HYEqXfXe7nckpKXzd3ESdru/rdt7r99PvoB0rS/0+8pubOK1bN/5WWcmTAwfSzWZnRWPQd+rrsEQ/o6YU6OuO+ASlGn5ZWX3C/g81q/itMzzPpEvoHlF4X/FqmmYHXlFKvaSUulQpdUnL7808FZSNEUIgp7yyNAH2bfv3bmDq5xd4Hz1ZxxYeN7jCT0QHb4t1mqa9o2naNZqmXdz6ZXINIevLrfT7qQ0YewM06zrLGhsYkZDI5OQUPqozboH+t6aGrLQDlwSYX17Obb2N/70epdAwPhyb9JDvEdsucz7RfUf63jiPd83+66p7VPzWmZ6nu0uP1VFZmiltTidSSgU0TRumaVrC/vd5TSbdzEHWz+9ffUF9wyQApfA/7f/himcCP5xtcVnhLho+yJKACiBrv8cU8JaJNYQseMv8fu4uKUZXoKM4q1t3ZqelMSIhgTuL9/BMeRnOxCR+mP79gk0bm5sBGJNkDLQ+t1t3LtheyIC4eG7sGR7jkXrVMWlwmdpe1EfLPOAbSqkHyyv3jX/xqLhtMz1PdSslIxp+VkOpZ+a8hfbtj53b7h2cgqm983i3AUs1TXsHaGh9UCn1x5BUdSi54g0mpTwvlZT2NX5L/e2+7IL/6dPDoQsy3EV8t51S6nqrayCEwTs6KYm3Mg8dAzckIYE3hmUe9jVjkpJ4tP/3a05c27Mn14ZJ4LbSQLv5g8DOB66Jy9z/8X6BwFcjfb5JAB4VVzjT83SaWeunRzgbxol0iVWNt8dW4L2W53fb78ssEf+BF05OaWxafozPPyygtLLLvA/s+p8+vV3bh4nIv+LVNO1YTdM+1TRtQ8ufj9c0zbTxGi3CZ9hwBBldxMTUJlWz/2N3VVTFAXhVXOEsz9MpErodYtkFXbuueJVSDwFompbW8uf6UBZ1GCGZbB+L7Ert+X1ZxWSviis8w/v7uO1qgMyPbr9omJLxEvArWhbDUUqt1zTtdeBRE2uQ4O0EDVJ/9Jm++IVz7LMAEnV9yxmNTeON0H0quYSe0jPYMZb9HLZ35arjNE1bB3wLfKtp2hpN08xcVEEG+wTJryqrdvj05K1TPM+lb1cDZG50xyRYXUAQpCilDp4X6je5BlmIpJNmr1cjbboKAFxXU1fiVXHbZ3meSi6mV5tTjsQhLNskqL1dzS8CdyilhimlhgG/xDhzNkvE7KIUzjICgXUzq5Nskz0LRsoqNp0SDT+H5ZqmjaBlARxN0y4Bis1qvGWd5iOuJyyOzq4YdOYatUpTqvya6ob+sz1/TJTQ7TTL3s/tbThVKfVZ6x+UUp9rmnbU/R6DLBo+8KyllP/i4oElM70/P1Nhi6RdqcJJNPS8ZGOcSDs0TdsNFAJXm9h+MqCZ2F7UuexLPa14TNyac5qfPH4PvY+4E5Fok2Xv53aPatY07X7glZY//whjpLNZouEDzzIjitWW874aVlDS9xe9b4SVVtcTqXywy+oagkAppU5rOXG2KaXqNE0zcynMJhPbikqarW+6K/+u6tFa4nZgu7XVRK4qmzL7Fss+7Q3eG4CHMOb6KeDLlsfMIle8HWTTlf/0deqry77Uk7o1MU5ROPyzWZSj2WQARucltv2UsPcfYIJSqmG/x/4NTDSjcWeBW3c7nM3IgMlOaUzus2vlpPvsqcp+cqr1q1lGtAw9TK94NU17RSl1DXCtUupnJtUkuiC9QZVf86m+YfpGNdqumNr6uIay96zaVFDZ0ynB23mWTLYPBk3THMBYIP2glaq6Y34I1lvQZsQzQvd+m7LZB1ldS5Sw7P3c1pXkRE3TBgI3aJr2dw66N6OUqgxZZQeqNamdiOXcqTbe8FGgcmgZkzSYfbjnDC98Z2BlT5k91AWWdU0FwWjgPIwRxefv93gdcJPJtTQgc/M7pDG5d9HKSfdrErpBFbZdzbnAp8BwYO1B31Mtj5uhpu2nxJ64gPKes1qtvnip3iPFS5vTu7rX7RxlC3gKdHuiw4z6olAk/xxOU0pdr2naA0qphy2upaHtp4hWTUm9i1ZOegBlsw+2upYoY9n7+aijW5VS85VSTuAvSqljDvoyK3Qhsj/wgq5XrSr55X8Cn7/6h0DNjz7Tp7cndFsNKFlRGsraopxZPTyhcI6maRpwodWFIMHbbk1JvXavmPyAktANCcvez+1dueoWTdNmAKOUUn/VNK030E0pVRja8vaR4AXGbdXXX/eJ3jCgkhOP1J3clszt7zt3D5zpR9NkwFrHRXLwfgBUAWmaptVy4G0jXSmVfviXhYTZK99FpKaknntWTH4goGz2oVbXEqWqrGq4XR++mqY9CJyIcZ/orxgr+LwKTA9daQeI2eBN8KmmC5frX523SvVN8nF8V4+X6Kvrk+ipWu1J6jkpGPXFmIgNXqXUr4BfaZr2P6XUBa2Pa5p2MnClyeXIFW8bmhJ7Fq+Y/KBf2eIkdENDB6qtary9Vz0XAeNpuc+rlNqjaZqZmyTEXPD2q1RFN3ysbx23TR2vwcnBPPawXR/7N4+6PJiHjBURG7ytlFIXaJo2HiNsL8NYQOM/JpchwXsUTYk9i1dMedCrbHHDrK4lilVn52ZZNiGrvcHrVUopTdNal5kzc9UqgDKT27PM1AJ93TWf6t7etUzSICT3dQbuWTZh88jLqtE0WTO3YyI2eDVNOxYjbK8EyoE3AE0pdYoF5cTciXR7NSdmSOiaw9L3cnuD91+apr0A9NA07SaMxTNMW6s5f05+lSvPVU2ULq6e5FX1l36prz1zjRqUEGB8qNuzKX9i99rtK2vTj5kZ6raijGlrGodAAcbCN+cppb4D0DTtFxbVstWidsNac2KPkuVTcjzKduCeuyIkLH0vt3dw1ROapp2OMZ92NPCAUurjkFZ2qEIIfSiZaXCZKrzxw8DOMbsYr4GpITi88N2eX4+TNVE66DurC+iCi4ErgM80TfsA+CfWrZlcYFG7YcsI3YealC3OzOU7Y5ml7+V2j2xtCdqPW0Y0V4SupCPaRhQEr6aUPnODWnPVZ7rWo4GJGljyRutZvek4TfcXyhu93bzATquL6Cyl1H+B/7bcJroAuB3oq2nan4C3lVIfmVjOJhPbCnvNCT32Lp+SI6FrLkuD96jzeDVNm6pp2ueapr2ladp4TdM2ABuAvZqmnWVOifuYuSlD0KU2qZoffxBY/NrjgV3Z7+mTMho4UbN4l5a+ZWt3WNl+hCnMzs3SrS6iq5RSDUqp15VS52OMIVgH/NrkMrYCPpPbDEuehPTS5VNzGpQtXkLXXGF9xfsccA+QDiwCzlZKrWhZ9/UfGHMDzRKRwTu8WG358YeBkhHFTNRgltX17G944Xuj9vadpDAWVhBHF8ndzIellKrC2CLwRTPbdRa4/W6HcysQ0yuoeRK6ly2f+lCdssWPsLqWGBTWwRvX2gWladrDSqkVAEqpAgs+qyNmQIZNV4HT1qnVl32pJ3dv4gRglNU1HU5yc8WgeF/9Ol9Ct4jvwjdB1AWvxTYRw8Hrie9Wtnzqw7W6hK5Vwjp49+9aO3gfTbPnQOWb3F6HpTeo8h8t0r+d8a0atf/OQOFs8O7PGwqPOb/tJwq5LxlcBRj3mmOOEbqPSOhapyQ7N8vSjXfaCt4T9lteLrnl97T82dRtvfLn5Je48lxFhGhua1e07AxUNbSME8OtO7ktQ4o+G1eYeV4D5s/NjjRfWV1AlInJkc3e+G7ly6c+XKPb40daXUsMs/y9fNTgVUpZtlHwEawmTIK3ZWegry5apndP9XCc1fV0VlzAk5baULy0IW2gWct/RiIP8I3VRUSZmAteb3xaxbKpD1fp9oSwvPUUQ1ZaXUCkLZS/GmP5Ssv0qlUl132ib5q0WTltimlW1hIsx+z4v5QNY39sdRnh7Ovs3Cyv1UVEmQKM21UxMbDPCN1HKiV0w8IqqwuIxOC1xLitev51n+h1AyqZFGndyW3pU/b1CahAMZp9gNW1hCnL36jRxlngrnY7nBuh/VtaRipvfGrlsqmPVOj2hGOtrkWgCIP3cyQGr2lnyS07A605b5XqneTDZUabVtBQtl4VGzdX9HZJ8B6e5V1TUepzojx4W0K3TLcnjLa6FgHAluzcLMt2JWp11AU0wk3+nPwaTBhd2q9KFd39RuDzvz8RaL5kqZqR5Iv+aQ8jCt8ZYnUNYUyCNzQ+s7qAUPLFpVYZoZsooRs+wuK9HGlXvAAfEaL5f1MK9LXXfqr7QrkzULhKa9gz3O5v+jYQlxzVVyCdsDM7N0vm8IbGYqL0Pq8vLqV66UmP7NXtiVF/0h5hPrG6AIjM4H0fCNrq/gftDDQhWMeNRAOLl1XsGnKq1WWEm/etLiBaOQvc5W6HMx843upagskXl1K97KRHi3V7otPqWsQBFOautnhEkRi8n2Ms5pHclYMMLlPbb/wwsMOKnYHCVeaOD127Bmd50bSEYB731c//wIYdK+iW3IN7L/szAEUVW/nnF0/h8TfTK60fc069h+SEVLaWbOCNL5/Gbovn+tPupW/6YBo99fzlk4e59ZzHsGmm3x2R4A2tD4ii4PXFJdcsm/pIcUBCNxytzc7NKrW6CIiwe7wA+XPymzHCt+OUUrPy9dUvzPevefLlwLCxu5ilQfegFhjB4v0NGUnNFeuCfdypx55J9jm/O+Cx1xc/yQVTbuLeS1/mhGNm8Ok3/wJg0TdvcsvZv+OSabeyZOO7AHyw9lXOGH+VFaHrBT41u9EY839WFxAsRug+ujsQlyShG57C5mct4oK3RYf+AVt3Bnr98cDOlp2BJlq9M1C4ytz5YdCPOXLg8aQkHXh+U1pTxMgBxoWOY/BEvt72BQB2WxxefzNevwe7LY6ymj1U15dx7MBxQa+rHb7Mzs2qt6LhGLIUsHyUaVf57PtCd4zVtYgjCpveq0gN3nb9Aw4vVlt+8zf/l395OhB3xjo1K05nWKgLi3T9S1ZMQOkh3295QMYw1m9fCsDabYupaigD4IzxV/LKZ7/no69fZ+bYC3l39Z85b/L1oS7nSMLmDDlaOQvcfuBjq+voCr89qXbZSY8USeiGtQrCZEQzROY9XvLn5G915bk2wKFLNe63M1BS9ybGEaY7A4Urm9Lje9Rs3VDdY1RIFwm5etav+Pey5/hg7au4hk3DbjN+FAf3HsmdFz0HwHd71pOe0gulFH/5+BHsNjsXnTSX7ik9Q1laKwX8x4yGBO8Al1pdRGf47Um1S096dJfMBgh7b4fTftoRGbwtXgP23Tjs3qAqrlmk58/4Vh0bKTsDhavhhe/2XTv+jpC20T9jKD8993EA9lbv4tudKw74vlKKD9a9yvWn3sebS5/jwqk3U1FXwucb3uYHk28MaW0tvszOzdphRkOCtzD2/k63upCO8NsT65ae9OjOQFxyxK7VHkNesbqA/UVqVzPA64By7FLuP/zZv+Sl+YG0WRvUbLtioNWFRboeNVudtoA3pHNX65qqANCVzodrX2PGmAO3Jly5+SPGDplCalJ3vP5mNE1D0zR8fk8oy9pfWL1Ro5mzwN2IcSIdMfz2xLplUx/dLqEbEbYDX1pdxP4i9oo3f07+ziWTnP/sVceVVtcSjfqVflVUPGBaULYu++snj7Kl+Bvqm2u479XLOefEOXh8TXzx7f8AGHfMyUwdfda+53t9zazc/CE/Pce4Is46/hKef/8e4mxxXHfqvcEoqS3NwJtmNCT2eRG41eoi2sNvT6xfNvXRQn98StRMg4pyr2bnZpm9f/xRaUqFVT0d4nY4rwXyrK4jGjUn9ihZNvXRvmjmz+EJA//Kzs263OoiYo3b4VwFTLK6jqMxQveRbf74VAndyDE6Ozdrs9VF7C/SP1TfBGqsLiIaJXmq+yd4a4M+pzdC/N3qAmLUS1YXcDQtobtVQjeirAy30IUID15ngbsJ+IfVdUSrIUWLTLuhGkZ2ECbLysWgfwBhOW86YEtoaAndE6yuRXTIC1YXcDgRHbwtcq0uIFoN3v3FOJSqs7oOkz2TnZsVsLqIWOQscNcThifSAVtC47KTHtkioRtxSgjTQXsRH7zOAvc3yEIHIWHXvSlp9UVfW12HiWqAl60uIsaFVXdzwJbQuGzqI5t98WmWLJ0muuS57Nwsr9VFHE7EB2+L31hdQLQavn1hLK1l/XJ2blasXeGHFWeBezUQFid7AVt807KpD2/yJUjoRqBGwrg3NCqC11ngXkZnN04QR9WrIv94TQ8UWV2HCfzAM1YXIQB4zOoCjNB9pMCX0G281bWITsnLzs0K+dK3nRUVwdtCrnpDQAOtd8X6rVbXYYI3s3OzdlldhADgX8BaqxpvCV23hG7E0oGnrC7iaKImeJ0F7k8Io0Wwo8nwwnczra4hxALAw1YXIQzOArcC7rai7YAtrnn51Ic3+hK6TbCifREUr2XnZm2xuoijiZrgbSFXvSGQ2rh3WJyvMd/qOkLob9m5WQVWFyG+5yxwfwQsMrPNgC2uefmUh7/1JnSfaGa7Iqi8wANWF9GWaAve94D1VhfRlmKfj+t27uS8wm2cX7iNV6oqAXiuvIzZW7/jou2FXLS9kMX1xpTGtY2NXFhYyKXbt7PdawzSqw0E+PGunegmrTw2aM+XEb9n6hE0AQ9aXYQ4LNOuenUtzrN8ysMbvInpErqR7U/ZuVnbrS6iLRG9ZOThuB3OM4Dg7+YeRGV+P2V+P2OSkmjQA1yyfTvPDhrMB3W1pNhs3NCz1wHP/9nuIu7p24/dPh+f1Nfx6779eLy0lNlpqUxOSTWlZp89uebLGX9IRNOSTGnQPI9n52b92uoixOG5Hc63gItC2YauxXmWTX0o35vY48RQtmMmn9/L0+/cjj/gI6ACjD9mJudOuo5NRWt5e+ULKKVIjE/mmtl30Sd9EJ9veJulG98jI60vN5/5MHH2eLYW5/N14Zf8cFpELKENUAuMyM7NKre6kLZE2xVvaxfVv62u42j6xMUxJsnIr1SbneGJiZT6/Ud8fpym0awUzUoRr2ns9Hop8ftMC12A+EBTenJTabQtIVlFGIygFUd1D8Y9+JDQtTjP8qkPrY+m0AWIs8fzs/Of5O5LX+LuH77IxqLVFO7dyD+XPM11Wfdw9yUvcuLILD5Y+yoAX235lLsvfYnh/cfi3rUapRTvr32Vsyb8yOK/SYc8EQmhC1EYvC1+ATRYXUR77PZ5cTc3c3xLEL9eVcWFhYXcW1xMTcD4vLmpZy/mFe/hpYoKruqRwTPlZfysdx/Ta83c8UHE7mZ1BL/Nzs2qsroIcWTOAncBIdoIRdfs3uVTctZ7EnuE9cYMnaFpGonxyQAEdD8B3Y/W8l+ztxGAJm8D6SlG75pCEdD9eH3N2G1xrN7yCWOHTCY1KWKm8RcDf7S6iPaKyuB1FriLiIBRqg26zs937+buvv1Is9u5okcGHw4fwVuZmfSJi+Px0lIAnElJ/HNYJn8bOpQin48+cUb+3bFnN3ft2UP5Ua6Wg6n/3tUTUHqZKY2F3gZk3m6keBBjq8agMUL3oa89SRlRF7qtdD3A7/59M/P+/kMcgyaS2c/JVbN+yfPv3819r17O6s0fc/p4Y1fVWWMv5Mm3b6OqvpTh/Y9jxaYPmDn2Aov/Bh1ye3ZuVkRcbEEU3uNt5XY444FvAKfVtRyOTyluLSpiemoq1/Xsecj3d/u83FJUxDvHDN/3mFKKm4p28cTAQfxm715u79OHPT4fSxsauL2POVfA646/bXFVT8csUxoLHQXMzM7NWmJ1IaJ93A7nLwjSFU3Lle7XnqSek4NxvHDX6KnnpY8e4NLpt7Fw9d84fdwVZPZz8snXb7C3ZhdXz7rzgOe/v+bvDOw5HE2zsWrzR2Sk9eWik+ZiC98dQj/Izs062+oiOiJs/yW7ylng9gHZVtdxOEop7i8pZnhiwgGhW7bflesndfWMSkw84HX/q61lZmoaPex2mpWODdCAZqWbVDkML3x3gGmNhc7LEroR52mCsDqdrtl8K6Y8uC5WQhcgJTGNYweOY+POVeyu3EpmP+NaZMKI2RSWfHvAc6sbytleWsAJx8xg0fo3ueG0+0lOSGPTbsvWM2lLI2H6OX80URu8AM4C92fAP62u42Brm5p4p7aWlQ2NB0wdeqKslAsKC7mwsJBVjY3M69tv32uadJ3/1tRwZUYGAHMyejK3qIjHSvdyeY8eptWeXrf9WFvAs8m0BoNvN3Bnm88SYaVlUY3rMEaudoqu2XwrJuesbU7qNSVohYWpuqZqGj3GdESv30NB0Rr6ZQylydvA3mpjgbaC3WvolzHsgNctXP1XzjvxOgB8fg9oGpqmGb8PT/dl52Zts7qIjoraruZWboezL0aXc3+ra4kWm0Zdvnj3oJmR2t18fnZu1ntWFyE6x+1wXgf8taOv0zWbf8XkB79qTu49NfhVhZ/dFVt55bPH0VUApRQTRszi7InX8k3hEt776m/Y0EhO7MaPZt9J7+4DAdhVvoUvNvyXq2f/CoDP1v+HpQULyUjty81nPUy8PcHKv9LhrACmZ+dmmdflFyRRH7wAbofzVOAjovwK3yyehO5lS0/6bQaaFmmjnF/Izs2aa3URomvcDufbwIXtfX6shW6MqAUmZOdmReQ68jERRM4C96fIcpJBk+it7ZPoqY60Ob3rgdutLkIExU+Ado2u1zWbf+XkB1ZL6EadmyM1dCFGgrfFQ8Biq4uIFkN3fWLOHKbgaAAuy87NCuqUFGENZ4G7FLiprefpms2/ctL9q5uS+5xkQlnCPC9m52a9YXURXREzwesscAeAq4CIWNkk3A3as2QCStVYXUc73ZKdmxXJA8LEQZwF7v8BfzvS9xVaYOWk+1c3pfSV0I0u+cDPrS6iq2ImeAGcBe49wLUY8zhFF9iUP7F73Y6w35ACY0PsV6wuQoTEbRgDJw+g0AIrJ9+3UkI36kRNz1VMBS+As8D9PvC41XVEg2MK3zNvHlPnrARusboIERrOAnc9cD5Q0vqYcaV738rGlP7TrKtMhIAOXBMt23fGXPC2uAd40+oiIl2vKrdL0/3bra7jCAqBH2TnZjVZXYgIHWeBexdwAdBshO69KxpTJXSj0K+yc7PetrqIYInJ4HUWuHXgGuAzq2uJdH3L1u2wuobDqAbOzc7NKrW6EBF6zgL3KuC6VSfes7wxdcB0q+sRQfd8dm5WxGyA0B4xGbwAzgK3B2Mu4NdW1xLJhhe+N4LwmgzuAy7Ozs1yW12IMI+zwP1GQ9rAd62uQwTdQuBnVhcRbDEbvADOAnctcDZGt6TohOTm8sHx/oZwGWSlgB9n52ZJT0YMys7NehxjTWcRHdYBV2TnZoVsP2arxHTwAjgL3CXAmbRzQr441OCixXVW14ARurdm52b93epChKXuoBNLSoqw8w1wenZuVr3VhYRCzAcvgLPAvQU4B4jK/8mhNqTo0xNQqtHCEhTGXN1cC2sQYSA7N0sBNwIvWV2L6LSvgVOzc7MqrC4kVCR4WzgL3F8BWcgCGx0WF/B0S20ssepeuQLmZudmvWBR+yLMtITvT4Dnra5FdFjUhy7EyCYJHeF2OI/F2FBhWFvPFd/b22fCmm/H3jjR5GZbQ/dFk9sVEWLB3EXPEIWDc6JUa+hWWl1IqMkV70GcBe7NwDSMpclEO/UtWzcepReb2KQXuFZCVxxNdm7Wz5EFcyLBYiArFkIXJHgPq2VpyZnAEqtriRQaytarcqNZ6yFXYgy8eNWk9kQEy87N+jXGCmaRtLFHLHkFOCM7N6vK6kLMIl3NR+F2OJOAN4AfWF1LJKhLG7x19Yl3jwhxM99hLI6xOcTtiCizYO6i0zBWrAv3pU5jSU52btZDVhdhNrniPQpngbsZuBh4xupaIkG3+qIRdn/zxhA2sQSYKqErOiM7N+sT4CQgYvdxjSJe4EexGLogwdsmZ4E74Cxw346xylXMdIV01sDiZaGaDzlmXycAABUMSURBVP0n4LRoH+0oQqtlkf0pyHKxVtoJzM7OzXrN6kKsIl3NHeB2OIcC/8Q4axaH4Y1PrVwy7ffd0LT4IB2yGrgxOzfrrSAdTwgWzF1kA+4GcoA4a6uJKW9jvJ9j+iJGgreD3A5nHPAb4FeAZnE5YWnZlIdXNif3mhKMQwFXZedmheNGDCIKLJi76CTgNeAYq2uJcs3AL7Nzs2RuNdLV3GHOArffWeD+NcZKV7LM5GEM2/lRVw+hA78DZknoilDKzs1aDowD/mF1LVGsAGNshoRuC7ni7QK3wzkA+CNwhdW1hBNds3s/n/lMPZrWsxMvXwf8JDs3a3Ww6xLiaBbMXXQF8BTQ3+paooQXeAz4bXZulsfqYsKJBG8QuB3O2cBzwFiLSwkba8b94ouaHiNnduAl9cADwPxo3I1ERIYFcxelA48CtyI9gl3xOcaqcmbN7Y8oErxB0nLv96fAQ0B3i8uxXFX6qI3rxt8+pp1P/x9wW3Zu1q5Q1iREey2Yu2gCkAtMsrqWCFMO3Jmdm5VndSHhTII3yNwOZ3+MJep+RIwPvvp85tNbdVv80RbUWAPcm52b9aFZNQnRXi0jn38MPAgMtLiccNeI0ev3+1hZ9rErJHhDxO1wTgceAU6xuharbBx9zeKSAVNnHe5bwP0yRUhEggVzFyVh7HZ0N9DP4nLCjRdjC8ZHs3OzSqwuJlJI8IaY2+GcBtwHnG11LWZrTswoXjb1kX5oWuu9sm0Y8yZfy87N0q2rTIiOWzB3UQrGvd+7gD4Wl2O1AMYayzky86DjJHhN4nY4xwN3AJcDwVpcIuwtmfa7Nd6E7l7gaeCt7NwsWaheRLQFcxelAjdgbLzgtLgcs9UCLwPPZudmbbe4loglwWsyt8M5EMgGbiK6z5obgTcqMpzPzVj+1lqrixEiFBbMXZSFcRV8AdG9AlY+xmCzV7Jzs+qsLibSSfBaxO1w2oEsjDnAFwEZ1lYUNGuBvwF/dxa4ayyuRQhTLJi7aBDGyfQVwGiLywmWUuAt4NXs3KylVhcTTSR4w4Db4UwAzsB40/4A6GZtRR3ixZiz9z/gXWeBW6YEiZi2YO6iscAlwA8Bl8XldFQZRtj+C1gsc+pDQ4I3zLTsAXwOcCowHeONG24T+auAhcA7wAfOArd0PQlxGAvmLhqF0aN1KjADSLG2okN4gdXAYuAT4AsJ29CT4A1zboezOzAVmIYRxFOBNBNLaAC+wehCXtfy6wZngVsGSQnRAQvmLorHWJBjWsvXFMyfH1yJcb/2S4yequXZuVmNJtcQ8yR4I0zLveGxwAhgWMtX5n6/7+j6yArjCrYU2Nvy606+D9lNzgK3TP0RIgRalqh0YNwXdrR8jcIYeNmLjg/Y0jHCtRQoATZhzJv/FtiYnZu1NziVi66Q4I0yboczDRgEJGK8aeNbfo3b7886xr2cUqDUWeD2WVOtEOJoWoK5V8tXBsZqeKrlS2/5NQBUYLyfK6SrOPxJ8AohhBAmCrdBO0IIIURUk+AVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEiSR4hRBCCBNJ8AohhBAmkuAVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEiSR4hRBCCBNJ8AohhBAmkuAVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEiSR4hRBCCBNJ8AohhBAmkuAVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEiSR4hRBCCBNJ8AohhBAmkuAVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEiSR4hRBCCBNJ8AohhBAmkuAVQgghTCTBK4QQQphIglcIIYQwkQSvEEIIYSIJXiGEEMJEErxCCCGEieJCdeA1a9b0jYuLexk4Dgl4IYQQ0UkHNvj9/h9PnDixtD0vCFnwxsXFvdy/f39nnz59qmw2mwpVO0IIIYRVdF3XysrKxpSUlLwM/KA9rwnllehxffr0qZXQFUIIEa1sNpvq06dPDUbvbvteE9p6JHSFEEJEt5asa3eeRvW9V7vdPtHhcIwZPXr0mDFjxjg//vjj1FC0M3/+/F7XXnvt0FAc22yapk286aabBrf++YEHHuh3xx13DDzaa1555ZUea9asSQp9dQd6+OGH+9bV1UXVz/DWrVvjTz311BHDhg07bsiQIcddf/31Q5qbm7X33nuv2ymnnDKy9Xk/+9nPBp588smjmpqaNCvrDZaUlJTxrb9/44030jMzM4/bvHlzwuOPP97nueee69WRY02ePHn0F198kdLe53/wwQdpI0eOHOtwOMbU19cf8O85fvx4R1uvN+PncNmyZclvvPFGekdf19F/i3DW+nne+nXPPff07+gxXnvttfTW13X2c2v/n9XOCtk93oNlzls4MZjH2/7YuWvaek5iYqJeUFCwEeA///lP93vuuWfw6aefvqk9x/f9f3v3HtTE1TYA/EkIJIEAEsCUixiQbDabhCihXKx4oergjDClTiwjrZcWhw9KZbxAdWCsl1aZFtFixQAdSrHq0FKrYgURHWrVFgumKSIYgc9XXi5yJ4AmsEm+Pyh8vAiCGqDynt9/Zvfsnn32zHN2zzmL/f1gamr6stV8OXusjRoz2NM1bszMzMwMFy9etGlsbGxycHAgJ3LYs2fPziJJsksqlWpepFovGuu0tDTO5s2b2y0tLfUvct7xiL8VGzX+5RvKnxl/vV4Pb731lnt4eHhzTExMDUmSsG7durkxMTFOQUFBXYP7xcXFOZSUlLCuXLlyn8lkGn1UqRIXGPW6BVWV47a7QefOnbOMjY2dk5+ffx/DsL64uLgWY9ZlNNnZ2ext27Y1RkVFtY/cplAoqsYr/yLtkCRJoNEmnn5LS0vNS0tLLd55552u8feefMf+56pR28iH8oDnyucvKiwsrAsAugBePm+9jBn1tvAsXV1dJtbW1iTAQIKLiIhw5vF4QgzDiIyMDBsAgAsXLlhKpVJ+QECAO4/HEwEApKamssVisQDHcWLdunVzSXKgL/ryyy9tuVyuSCwWC27evMmatgszMhMTE8P69etbDhw4wBm57d69e2a+vr4YhmGEn58fdv/+fbPLly9bFBUVzUpISHDGcZyoqKigDy9TUVFBl0gkOIZhxJYtWxwHnxafJ9ZhYWEuIpFI4O7uLty6dasjAMCnn346u7m52XTJkiWYj48PNumBmQJ5eXmWdDpdHxMT0wYAQKPRQC6X1+Xk5Nj19vZSAQA++eQTTlFRkXVhYWE1i8WaUVM5+fn5rA8//JB77ty5aqFQqAUA2LZtm+Pu3bs5AANvb5GRkU5isVjA5XJFBQUFLACAnp4eyurVq93c3NyEK1asmKfRaEYdBTh37pylQCAgMAwjZDIZ98mTJ5Tk5GS7n3/+mf3ZZ585BQcHu44sM7y9ent78wMDA91cXV2FwcHBrnq9ftR2eObMGav58+fjBEEIVq1a5dbV1UUFAHBychJHRkY6EQQhyMzMtKmoqKD7+/vzhEKhQCqV8hUKBQMAIDMz04bH4wn5fD7h5eXF12g0lIMHDzrm5eXZ4DhOZGRk2KjVaqpMJuOKxWKBQCAgvvvuu1nPE4uZoq2tzYTL5YqUSiUdACAoKMj10KFDdgAAubm5VgRBCPh8PuHn54cB/P/o5Gh5a6z7UVVVZTZ//vyhHGaMek/ZG+900Gq1VBzHCa1WS2ltbTW9ePGiCgAgOzt7Vnl5ObOysrKisbGR5u3tLVi5cmUPAMDdu3fNFQpFBY7jfbdv32bk5uayS0tLq+h0uuHdd991kcvltkFBQerExETHsrKySjabrVu4cCFfJBI9nt6rNZ7Y2NhmsVgs3LNnT9Pw3yMjI13CwsLaPvroo7YjR47YRkZGzikqKqpZvnx55+rVq7s2bdrUMfJY0dHRc6KiopojIiLaP//8c/vh2yYS6+jo6Lbk5OR6DoejI0kSFi5cyC8pKWEmJCQ0Hz9+nPPLL7+oJvpm/k9XXl7OlEgk/9GO2Gy23sHBoe/+/fv0srIyVm1tLUOhUNy1traelLf86dLX10cJDQ11LywsvLdgwYIx30BIkqSUl5dX5uTkWO/bt88xMDBQlZSUNJvJZOpra2srSkpKmG+88QYxstzjx48pERERroWFhfc8PDy0ISEh3C+++MJ+9+7dzTdu3GCN1X6Hq6ysZP7555+1XC63XyqV4pcvX2aNbIeNjY20AwcOOFy7dk1lZWWlj4+Pf23//v2cpKSkRgAAW1tb8u7du5UAAH5+flh6evq/xGKx9urVqxaRkZEuv//+uyoxMdGhsLBQ5erq2t/a2mrCYDAMu3btaigtLbXIzs5+CAAQHR3ttGzZMvUPP/zwoLW11cTLy0sQHBysTk5Oth8vFq+qwXw++O/t27c3bt68uePw4cMPN2zY4BoVFfWos7OTtn379taGhgZadHQ0t7i4uArH8b5Hjx6ZDD/WihUrekfmrbHuR1RUlEt4eHhLdHR028GDB+1H1utFzOiOd/jQRFFRkcWmTZtcVSpVxa+//mq5du3adhqNBnPmzCF9fHx6rl+/bm5tba338PDoxXG8DwCgoKDA8s6dO+YSiUQAAKDRaKizZ88mr127ZuHr69vt6OhIAgC8/fbb7SqVasrnOCcLm83Wy2SytsTExNlMJnMowSsUCov8/PwaAIDIyMj2vXv3Oo99lKEyrMLCwmoAgPDw8LY9e/YMlZlIrAEAvv32W3ZWVpYdSZKUlpYWU6VSyfDx8Xli3Kv+53NxcdGq1WqT8+fPW23cuLFzuutjTKampgZPT88euVxu5+PjUzfWfjKZrAMAYOHChb2xsbFmAADXr19nbdmypRkAwMfH5wmGYU89BCuVSoazs7PWw8NDCwCwcePGtmPHjs0GgAl9dwkAIBaLe+fNm9cPACAUCh/X1NSYjdynuLjYoqamhuHt7Y0DAPT391OkUmnP4Pb169d3AAB0dXVRFQoFSyaTzRvc1tfXRwEA8PLy6gkLC+OuWbOmIywsbNSHgeLiYqtLly7NSklJeQ0AQKvVUqqrq80mEotX1VhDzSEhIervv//eJi4ubm5ZWVkFwMB98Pb27h7MLxwOR/esYz/rfty+fZs1mPciIiLa9u/fP27eG8+M7niHW758eW9HRwetsbHxmddsbm4+1NEYDAaKTCZrO3bsWP3wfU6cODFrsur5T7Fr165Hnp6eRGhoaOtknWMisa6qqjL76quvOGVlZZX29va6NWvWcDUazYycIhGJRE/Onj1rM/y39vZ2amNjoxmPx9Pa29v3nzp1qnblypV8W1tbXVBQUPd01dXYKBQKnD9/vtbf3x/buXPna4mJiU2j7cdgMAwAA8PwOp1uSodR6XT60NC+iYkJkCT51PkNBgMsWrRInZeX97+jHWNwHlin04GlpSU5Wkdy6tSph1evXrU4f/68tVQqJcrKyp7ax2AwQG5ubrVEItG+3FW9+nQ6HahUKgaDwdC3tbXRBh+OnvcYY90PgKFVy0YzIxPYaBQKBUOv1wOHwyEXL17cnZubyyZJEhoaGmi3bt1i+fv7944sExgYqL5w4YJNfX09DQDg0aNHJiqVymzx4sW9JSUllk1NTSZarZby008/2Tx9xlcbh8PRBQUFdZw6dcpu8LcFCxb0fv311zYAAGlpaWwvL68eAAAWi6VTq9WjtqX58+f3ZGVl2QAAZGZmssc631ix7ujoMGEymXo2m62rq6ujFRcXD63stLCw0A3On80EwcHB3RqNhjq4ipckSYiKipojk8laLSws9AAAHh4e2pycnOoPPvjA9ebNm8zprbFxWVpa6i9dunQ/NzfX9vDhw3bjlxiwaNGinpMnT7IBAP744w+GSqV6ahWvRCLR1NfXm925c4cOAJCdnW3r7+9vlAeX4e1w6dKlvaWlpazB86jVaupff/1FH1mGzWbrnZ2d+zIzM20ABtad/Pbbb0yAgXURAQEBvUeOHGmwsbEha2trzaysrHQ9PT1DbX3ZsmXqQ4cOcfT6gWfXGzduMCcai5lm3759HAzDNFlZWbXvv/8+V6vVUpYuXdp769Yty6qqKjOAgXwystzwvPWs++Hp6dmTkZHBBgDIyMh4rhX2Y5kxSWs0g3MCOI4ToaGhbsePH39Ao9Hgvffe6xQKhU8EAoFw6dKl2N69e//t4uLy1DyhVCrVJCQk1L/55psYhmFEQEAAVldXZzp37tz+jz/+uMHX11fg5eWFYxg25avipkJ8fHxTZ2fn0AiBXC5/eOLECTsMw4jTp0/bpqam1gEAhIWFtaekpLwmEAieWlx19OjRuqNHj3IwDCOqq6sZLBZr1CGfsWLt5+f3RCQSPZ43b55o7dq1bsOH7TZs2NAaGBg4YxZXUalUOHv2bPWZM2ds5s6dK3J1dRXR6XR9SkrKf4wCLFmy5LFcLn+wZs0a95HxftVxOBxdQUGBKikpyeHkyZMT+nxmx44dzb29vSZubm7C+Ph4J4IgnnqINjc3N8jl8gcymWwehmEElUqFHTt2GGXF9PB26OjoSKalpT0IDQ11wzCM8PLywsvLy0edhjp9+nTtN998Y8fn8wkejyf88ccfZwEAbN261RnDMILH4wlff/31Hl9f3yerVq3qVqlUzMHFVYmJiQ0kSVJwHCfc3d2FCQkJThONxatqeD7HcZyIiopyUiqV9BMnTtilpqbWBQYG9vj6+nbv3LnTwdHRkUxJSXkQEhLizufziZCQELeRxxuZt8a6H6mpqQ/T09NnYxhG1NfXG+VTF4rBMDkLI5VK5QOJRDJpw5TIq6G7u5tqYWGhp1KpkJ6ebpOTk8O+cuVKzXTXC0EQxJiUSqWdRCLhTmTf/5o5XmR63LhxwzwmJsbFYDCAlZWVLisr68F01wlBEGQ6oY4XmVSBgYE99+7de6mP3hEEQWaSGT3HiyAIgiD/NJPZ8er1ev2M/qspCIIgCPJ3XzfhP2ozmR3vnZaWFmvU+SIIgiAz1d//H681ANyZaJlJm+MlSTK8qanp66amJhGgIW0EQRBkZtIDwB2SJMMnWmDSPidCEARBEORp6E0UQRAEQaYQ6ngRBEEQZAqhjhdBEARBphDqeBEEQRBkCqGOF0EQBEGm0P8BjLwRXzqaWGsAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -484,16 +624,14 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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GvLy8ij3Z+LTg4GAkJiZi06ZNOHHiBFxcXDBv3jzs3bu32JN3JW33Z537LxLX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\nyP8DDkiaIGvcmJ4AAAAASUVORK5CYII=\n", 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -502,10 +640,12 @@ ], "source": [ "import seaborn as sns\n", + "import matplotlib\n", + "matplotlib.style.use('ggplot')\n", "\n", - "df = df*100\n", + "#df = df*100\n", "\n", - "fig,ax = plt.subplots(1,1,figsize=(7,4))\n", + "fig,ax = plt.subplots(1,1,figsize=(8,4))\n", "\n", "bars= df.plot.bar(ax=ax, color=['#bdbdbd','#a6bddb'],width=.8)\n", "ax.set_xticklabels(['Bored', 'Not great', 'OK', 'Kind of\\ninterested',\n", @@ -542,9 +682,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -591,9 +729,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -614,9 +750,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -637,9 +771,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -660,9 +792,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -683,9 +813,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -713,9 +841,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -745,9 +871,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -768,9 +892,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -823,9 +945,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -848,9 +968,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -883,9 +1001,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -934,7 +1050,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula13-regressao-linear.ipynb b/aula13-regressao-linear.ipynb index db006a8..74f1a37 100644 --- a/aula13-regressao-linear.ipynb +++ b/aula13-regressao-linear.ipynb @@ -15,10 +15,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": true - }, + "execution_count": 4, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -26,6 +24,8 @@ "\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", + "import matplotlib\n", + "matplotlib.style.use('ggplot')\n", "\n", "from sklearn.linear_model import LinearRegression\n", "\n", @@ -47,10 +47,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -63,6 +61,19 @@ "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -122,7 +133,7 @@ "4 180.8 10.8 58.4 12.9" ] }, - "execution_count": 13, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -136,35 +147,21 @@ }, { "cell_type": "markdown", - "metadata": { - "collapsed": false - }, + "metadata": {}, "source": [ "Antes de iniciarmos qualquer análise, devemos plotar os dados para avaliar se existe alguma relação entre o investimento em publicidade e o total de vendas." ] }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { + "image/png": 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\n", "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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lFsXfmb1txuoDRPYltLRzKyllSLzLVRKJwNFh87IsfyrL8quB/5YkyQVgGYDX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\n7V9C6TYM976FzOY3gvsGAMx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c0ijV+EP3Ngz3voXM5jdQ7N2nODHHwvmz4W3cGxwaFQi0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\nsby5+2F+0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yZJ0qCZBEwEJmbmI8BcYEsqs2gH6qbx1IgYDxARHwDmALOBMcCVwNR+6qW5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\npA73XzOhOpsxp3/PAAAAAElFTkSuQmCC\n", - "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -172,10 +169,10 @@ } ], "source": [ - "figs, axes = plt.subplots(1,3,figsize=(12,4))\n", + "figs, axes = plt.subplots(1,3,figsize=(15,4))\n", "ads[['TV','sales']].plot.scatter(x='TV',y='sales',ax=axes[0])\n", "ads[['radio','sales']].plot.scatter(x='radio',y='sales',ax=axes[1])\n", - "ads[['newspaper','sales']].plot.scatter(x='newspaper',y='sales',ax=axes[2])" + "ads[['newspaper','sales']].plot.scatter(x='newspaper',y='sales',ax=axes[2]);" ] }, { @@ -206,26 +203,14 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { + "image/png": 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\n", "text/plain": [ - "[]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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5s85ksnXSuGOCBYTfvu5STjv1JKqn1/LIky9IoJhkstmcvhkCkwFNRFGUw8An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\njBoPERERSYwaDxEREUmMGg8RERFJzP8D81kdFfcPP8gAAAAASUVORK5CYII=\n", - "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -233,11 +218,11 @@ } ], "source": [ - "figs, ax = plt.subplots(1,1,figsize=(6,4))\n", + "figs, ax = plt.subplots(1,1,figsize=(6,5))\n", "ads[['TV','sales']].plot.scatter(x='TV',y='sales',ax=ax)\n", - "ax.plot(ads.TV,np.repeat(ads.sales.mean(),ads.shape[0]))\n", - "ax.plot(ads.TV.sort_values(inplace=False),ads.TV.map(lambda x: 0.06*x+5).iloc[ads.TV.argsort()])\n", - "ax.plot(ads.TV.sort_values(inplace=False),ads.TV.map(lambda x: 0.02*x+10).iloc[ads.TV.argsort()])" + "ax.plot(ads.TV,np.repeat(ads.sales.mean(),ads.shape[0]),color='green')\n", + "ax.plot(ads.TV.sort_values(inplace=False),ads.TV.map(lambda x: 0.05*x+7).iloc[ads.TV.argsort()],color='red')\n", + "ax.plot(ads.TV.sort_values(inplace=False),ads.TV.map(lambda x: 0.03*x+10).iloc[ads.TV.argsort()],color='black');" ] }, { @@ -261,9 +246,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -284,9 +267,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -328,10 +309,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 39, + "metadata": {}, "outputs": [], "source": [ "f = lambda x: 5*x+3\n", @@ -349,16 +328,14 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 40, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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v2hRg167Y6nsqY7vj3UTYtCnAyc/9B2dEhe6Z7GfhHVew6e0PwenIY+rqAlRW2jHBe84c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\nK4ypMgv6VJFqrBBCCMuOHS7c7vDtVqW4o0Ph6NHo7xZCK93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2TGfnTvvQXV2tU5y5bymE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Jw44a92X3qpB4DpLz7Pxd/xj+X+Py7gIOaSZL133EPg7Gfr10fufQ8M3roOLS3m9wsXBq/zvWSJ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\nJEmSpJr9G7wjb6j1a795AAAAAElFTkSuQmCC\n", + "image/png": 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -367,7 +344,7 @@ ], "source": [ "fig, axes = plt.subplots(1,2,figsize=(12,4))\n", - "axes[0].plot(x,y,'o')\n", + "axes[0].plot(x,y,'o',color='blue')\n", "axes[0].plot(x,yv,color='red')\n", "axes[0].plot(x,yreg,color='black')\n", "\n", @@ -392,7 +369,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Observamos que, dadas as premissas de que os erros seguem uma distribuição normal com média zero e desvio padrão $\\sigma$, o valor médio entre as diversas predições para $Y$ se aproxima do valor real (dado pela equação da reta). Dessa forma, percebemos que não há um erro sistemático (viés) nas estimativas. Portanto, ainda que os coeficientes para um conjunto de dados específico não forneça a real relação entre as variáveis, se tivéssemos uma grande amostra de conjuntos de dados, a média dos coeficientes seria o valor exato deles. Isso é a base do **teorema de Gauss-Markov**." + "Observamos que, dadas as premissas de que os erros seguem uma distribuição normal com média zero e desvio padrão $\\sigma$, o valor médio entre as diversas predições para $Y$ se aproxima do valor real (dado pela equação da reta). Dessa forma, percebemos que não há um erro sistemático (viés) nas estimativas. Portanto, ainda que os coeficientes para um conjunto de dados específico não forneça a real relação entre as variáveis, se tivéssemos uma grande amostra de conjuntos de dados, a média dos coeficientes seria o valor exato deles." ] }, { @@ -419,9 +396,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -477,9 +452,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -532,9 +505,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -567,9 +538,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -610,9 +579,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -646,9 +613,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -674,9 +639,7 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -918,7 +881,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula14-regressao-linear-parte02.ipynb b/aula14-regressao-linear-parte02.ipynb index df56694..10d1fde 100644 --- a/aula14-regressao-linear-parte02.ipynb +++ b/aula14-regressao-linear-parte02.ipynb @@ -98,9 +98,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import statsmodels.api as sm\n", @@ -112,9 +110,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -193,9 +189,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -260,9 +254,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -354,9 +346,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -479,9 +469,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -624,9 +612,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -749,9 +735,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -891,9 +875,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1038,7 +1020,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula15-regressao-logistica.ipynb b/aula15-regressao-logistica.ipynb index 9eae4b5..99ff420 100644 --- a/aula15-regressao-logistica.ipynb +++ b/aula15-regressao-logistica.ipynb @@ -44,15 +44,16 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import seaborn as sns\n", + "from seaborn import color_palette\n", "import matplotlib.pyplot as plt\n", + "import matplotlib\n", + "matplotlib.style.use('ggplot')\n", "\n", "import statsmodels.formula.api as smf\n", "import statsmodels.api as sm\n", @@ -66,14 +67,25 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
\n", " \n", " \n", @@ -182,7 +194,7 @@ } ], "source": [ - "prostate = pd.read_csv(\"http://statweb.stanford.edu/~tibs/ElemStatLearn/datasets/prostate.data\",\n", + "prostate = pd.read_csv(\"https://web.stanford.edu/~hastie/ElemStatLearn/datasets/prostate.data\",\n", " header=0,index_col=0,sep='\\t')\n", "prostate.head()" ] @@ -197,9 +209,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -222,15 +232,13 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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TFZckTTYmPSSNq9n778a0nWe0XH+wfwCAWvfYphh6/LGNrL3toTF9RpKkKoiIRcAVLdSb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\n7NlFlyFJktS0DD0k1dXTT20bV/+hylazpc7xzbYb730kSZIktR9DD0l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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -239,11 +247,11 @@ ], "source": [ "fig, axes = plt.subplots(2,3,figsize=(13,6))\n", - "sns.boxplot(x='prognostico',y='lcavol',data=prostate,ax=axes[0][0],width=.2)\n", - "sns.boxplot(x='prognostico',y='lweight',data=prostate,ax=axes[0][1],width=.2)\n", - "sns.boxplot(x='prognostico',y='lbph',data=prostate,ax=axes[0][2],width=.2)\n", - "sns.boxplot(x='prognostico',y='lcp',data=prostate,ax=axes[1][0],width=.2)\n", - "sns.boxplot(x='prognostico',y='lpsa',data=prostate,ax=axes[1][1],width=.2)\n", + "sns.boxplot(x='prognostico',y='lcavol',data=prostate,ax=axes[0][0],width=.2,palette=color_palette(['#67a9cf','#ef8a62']))\n", + "sns.boxplot(x='prognostico',y='lweight',data=prostate,ax=axes[0][1],width=.2,palette=color_palette(['#67a9cf','#ef8a62']))\n", + "sns.boxplot(x='prognostico',y='lbph',data=prostate,ax=axes[0][2],width=.2,palette=color_palette(['#67a9cf','#ef8a62']))\n", + "sns.boxplot(x='prognostico',y='lcp',data=prostate,ax=axes[1][0],width=.2,palette=color_palette(['#67a9cf','#ef8a62']))\n", + "sns.boxplot(x='prognostico',y='lpsa',data=prostate,ax=axes[1][1],width=.2,palette=color_palette(['#67a9cf','#ef8a62']))\n", "#sns.boxplot(x='prognostico',y=prostate.prognostico.value_counts(),data=prostate,ax=axes[1][2])\n", "axes[0][0].xaxis.label.set_visible(False)\n", "axes[0][1].xaxis.label.set_visible(False)\n", @@ -267,9 +275,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -327,9 +333,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -346,10 +350,10 @@ " \n", "\n", "\n", - " \n", + " \n", "\n", "\n", - " \n", + " \n", "\n", "\n", " \n", @@ -394,7 +398,7 @@ "\n", " \n", "\n", - "
Method: Least Squares F-statistic: 9.858
Date: Mon, 15 May 2017 Prob (F-statistic): 2.03e-05Date: Thu, 03 May 2018 Prob (F-statistic): 2.03e-05
Time: 18:49:35 Log-Likelihood: -33.505Time: 10:32:04 Log-Likelihood: -33.505
No. Observations: 67 AIC: 75.01
Kurtosis: 2.384 Cond. No. 40.0
" + "

Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified." ], "text/plain": [ "\n", @@ -404,8 +408,8 @@ "Dep. Variable: Ip R-squared: 0.319\n", "Model: OLS Adj. R-squared: 0.287\n", "Method: Least Squares F-statistic: 9.858\n", - "Date: Mon, 15 May 2017 Prob (F-statistic): 2.03e-05\n", - "Time: 18:49:35 Log-Likelihood: -33.505\n", + "Date: Thu, 03 May 2018 Prob (F-statistic): 2.03e-05\n", + "Time: 10:32:04 Log-Likelihood: -33.505\n", "No. Observations: 67 AIC: 75.01\n", "Df Residuals: 63 BIC: 83.83\n", "Df Model: 3 \n", @@ -444,14 +448,12 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -460,9 +462,9 @@ }, { "data": { - "image/png": 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3pc++q7tW3K6WJiLSJc1mk4vTOZzkoCZkEREBKgsVSvUiR48fol6q4ffgSV25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\nsUTd4SPY4+PEj44Tnzi2vER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bj51evnmz0pGRJH/ugZvXTaz3/fNlcqX6qu/82nI3svoz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du3HOYnt+/MqXBnPG2DN7BeqKm46yOZ0e1LGV1//5EIQ92hnNH1AwEfnZ0tjI+H563k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\n/n9l63m89y5FQAAAAABJRU5ErkJggg==\n", 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -482,7 +484,7 @@ "source": [ "Vemos que, apesar do modelo com todas as variáveis indique relação entre elas e o prognóstico, os modelos individuais acima deixam bem claro que essa relação não foi exatamente modelada. O modelo linear não consegue se ajustar aos dados. É percepível que o domínio do modelo não é restrito ao domínio da variável prognóstico ${0,1}$. Outra questão a ser levada em conta é que o modelo também não pode ser generalizado para mais de duas categorias. Assim, usamos como alternativo a regressão logística.\n", "\n", - "No modelo logístico, ao de modelarmos o valor da variável dependente em função das variáveis independentes, modelamos a probabilidade condicional da variável dependente em função das variáveis independentes, $P(Y=1|x_1,x_2,\\dots,x_p)$. Por exemplo, poderíamos modelar $P(prognóstico=mau|lpsa)$. Nesse caso, poderíamos dizer que o prognóstico do paciente é mau se $P(prognóstico=mau|lpsa) > 0.5$, ou se quisermos ser menos alarmantes, $P(prognóstico=mau|lpsa) > 0.8$. Por conveniência, expressamos $P(Y=1|X) = p(X)$.\n", + "No modelo logístico, ao invés de modelarmos o valor da variável dependente em função das variáveis independentes, modelamos a probabilidade condicional da variável dependente em função das variáveis independentes, $P(Y=1|x_1,x_2,\\dots,x_p)$. Por exemplo, poderíamos modelar $P(prognóstico=mau|lpsa)$. Nesse caso, poderíamos dizer que o prognóstico do paciente é mau se $P(prognóstico=mau|lpsa) > 0.5$, ou se quisermos ser menos alarmantes, $P(prognóstico=mau|lpsa) > 0.8$. Por conveniência, expressamos $P(Y=1|X) = p(X)$.\n", "\n", "Como discutimos, modelar $p(X) = \\beta_0 + \\beta_1X$ fornece um péssimo modelo. Na regressão logística, usamos a função logística como modelo:\n", "\n", @@ -515,10 +517,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -544,10 +544,10 @@ " Method: MLE Df Model: 1 \n", "\n", "\n", - " Date: Mon, 15 May 2017 Pseudo R-squ.: 0.2013 \n", + " Date: Thu, 03 May 2018 Pseudo R-squ.: 0.2013 \n", "\n", "\n", - " Time: 18:49:36 Log-Likelihood: -35.353 \n", + " Time: 10:32:26 Log-Likelihood: -35.353 \n", "\n", "\n", " converged: True LL-Null: -44.260 \n", @@ -576,8 +576,8 @@ "Dep. Variable: Ip No. Observations: 67\n", "Model: Logit Df Residuals: 65\n", "Method: MLE Df Model: 1\n", - "Date: Mon, 15 May 2017 Pseudo R-squ.: 0.2013\n", - "Time: 18:49:36 Log-Likelihood: -35.353\n", + "Date: Thu, 03 May 2018 Pseudo R-squ.: 0.2013\n", + "Time: 10:32:26 Log-Likelihood: -35.353\n", "converged: True LL-Null: -44.260\n", " LLR p-value: 2.434e-05\n", "==============================================================================\n", @@ -589,7 +589,7 @@ "\"\"\"" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -603,26 +603,14 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { + "image/png": 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16qdq844hmk0K8dpLCvkkQQjhAZvJuCahAWulZD9cj33o7lw/hnAYjvsE6pPnjw6DUTOiUVfHEq+XZrpZkiCEKDObyUDXDhgOznAZtnsn9uF73KiqIw49BnXOpbXTKkkp1ychFqvJ4qNiSIIQooxsJp1NDsEYqdQOD8Gzj2OfeTgX06J9Uedfhtpnf3+D80Io5O4SYnGoi1V8M9RykwQhRJnYdBq6OgMzZ4Nd9zr29792MQE0taDOWw5HHF/dF8q8lkeqrvjJcoQkCCHKwg4Pw64dgRgyw3bvxD54N7zxZ7cgHIaTz0adcQEqFvc3uHJQKtvqKF6yeRFqlWcJQmt9PnAjEAZuNsZ8f8zzewO3A23Zdf4vY8yDXsUnRKnYwWS2j4O/zVhtJgN/ehr72G9zleNLDkRdfCVqznxfYyuLujqIN7hK5mq+I/KQJ2dRax0GbgIuAJYBV2qtl41Z7f8FjDHmaOAK4EdexCZEKdmBhGut5Hdy2LoZe/P/xD7wa5ccGptRl12Luva71ZUconXQ3Apz5qNmzUE1NEpyKCGv7iBOANYbY94D0FrfBVwKvJG3jgVG+u63Aps9ik2IkrCJfjdMt58xpNPw9CPYPz6YK9469hTUectR9ZUxRemkpI+CZ7xKEAuBDXmPNwInjlnnBuBRrfW3gEbgU96EJsTMBSI5bNmEvfd22Jz9qs2ag7r0KtR+B/saV0nU1UHM1SvIxEPeCdKZvhK4zRjzP7XWJwM/11ofZozZbbAarfX1wPUAxhg6Ojp8CHVikUgkkHFNRzUdC5TneDL9vWQGE9DeXtLtTiYcCdPe3o5Npxl4/H4GHrzb3TUoRfyMC2i4+PKKabUzciz5VCyOqm9AVeCdQrV8b7xKEJuAxXmPF2WX5bsOOB/AGPOC1joOdADb8lcyxqwEVmYf2s7OzrIEPBMdHR0EMa7pqKZjgdIfj+3vdeMq+aC9vZ2d767D/uY2+Og9t3DWHNTyLzK0zwEM9SegP1jDeoynvb2drq6uvIrmOIoQDCTdT4UJ+vdmwYIFRa3nVYJ4GViqtV6CSwxXAFeNWecj4GzgNq31IUAc2O5RfEJMme3rgb5ef/ZtLcnnn8TefXuuhdKJZ6DO/Syqrs6XmKYtGiXU0gaRyptQp9p5kiCMMSmt9TeBR3BNWG8xxqzVWn8PeMUYcz/w98BPtdZ/h6uwvsYYE6zhLoXIsr090O9Tchjox953J/1rX3ULmltRn/0iaunYhoEBFg5DfcPouEeh5hbUYHCGIhGOsgEbcniK7ObNwWvsFPTby6mopmOB0hyP7e+D3u4SRTTFfX/4LnbVLblRV5cd7SqiG5p8iWfKwmFobIb6ht3mUpDPmbeyRUyTTmYRpEpqIQLPDg666UG93m8m45qvPvk7N49ENErjimtJHHxUZUxaUxeDhsbanVOiQkmCEKJINpVyf7l7fNdt+3uxd98K6990C+YvQq34MvGDljHQ1eVpLFMSCrn+Cg2NMnx2hZIEIUQRbCbjyxSh9oN3sOZnuSKtE053I69GA3rBVWp0TgVi8cq4uxHjkgQhxCSstW74DA+H7LbWwvNPYB+91yWlWBx16edRhx/nWQxTopSrdG5slpZIVUQShBATsNa6+Rw8nAnODiaxv/1FbjKfeQtRV14fzIl8QiGob4TGRhk1tQpJghBiHG6a0B0w5F3zS9u5FXvnj2H7FrfgyBNRl1wVvL4N4TA0NkG8QQbHq2KSIIQowJfksO5114Q1OQDhMOqCFa7OIUjl+OM0UxXVSRKEEGO4OgfvkoO1Fp55FPv4fa6FVFOLK1LaO0BTgIZC7o6hoUkSQw2RBCFEnlydg0fJYXgIe+/PYc0rbsGifVFXfhXV0ubJ/icVCuXuGKQoqeZIghAiy+sKadvb7eobNn7gFhx9Euriq4LRhHUkMTQ0yh1DDZMEIcSI7i7vksPmDdhf/jv0dIFSqPOWwyln+38xVgoaGqGxSVolCUkQQkB28L3kgDf7evM1Vxk9PAR1MZS+DnXQ4Z7se1wh5YbZll7PIo8kCFHzbKLfs5FZ7QtPYh+621VGt81CfeHrqHkLPdl3QZGIK0qK1/t/9yICRxKEqGl2cNCTkVltJoN9aBW8+Ae3YNG+qM9/DdXUMuHryqq+AVraJDGIcUmCEDXLDibdEBplHnzPDg25IqW3XnMLlh2N+tw1/nV+U8rNIdHQ6M/+RcWQBCFqkk0moHtX+ZNDfx/2lz+CDe+7Bad+ys365leT0bo6aG4LRkspEXiSIETNsYl+6NlV/v3s3I6944ewY5trqfRpjTrpjLLvt6BwGJpbUPEGf/YvKpIkCFFTMj27vEkOmzdgf/5DN7lQJIq67FrUoUeXfb8FNTZDU7PUNYgpkwQhaoLNpKF7F5mG8s9oZt9723WAG0y6Hsif/zpqHx+GzYhGXSV0NGAD/YmKIQlCVD2bGnY9pNNpKHOCsGtfxa66FdIpaGlHfelbqLl7lXWfe1DKjZvUKHcNYmYkQYiqZoeHXHLwYCY4+8qz2PvvdBXfHfNR13wL1Tqr7PvdTTwOTa2oiHy1xczJp0hULTs06EZlzZR/Dmn7zKNu9jdwfRyu/gaqoans+x0VDrvipFjcu32KqicJQlQlz/o4WIt97D545hG3YP9D3FDdXl6o62LQ1i5jJ4mSkwQhqo4dSLiWSuVODpkM9vd3wcvPuAXLjkatuNbbsYyaW1CNzd7tT9QUSRCiqti+Hugr/7hKNp128zi89pJbcMwpbmrQsEd/xYfDhDvmoXq9GUNK1CZJEKIqWGvdXcNAovz7Sg27oTPe+ItbcPKZqAtWeNdiaKRIKRYDSRCijCRBiIpnhwZdckilyr+v4SHsr1bCO2vdgk9egDr7Yu+SQ2MzqtnHAf5ETZEEISqWzaSht8eTuwZwicj+8t/hvbcBUOd8BnX6eZ7sG6VcK6V6GSpDeEcShKhIu3V+82J/yQHsL26CD98FQF2oUSed6cm+CYXc3BF1MW/2J0SWJAhRcbzs/AauVZS943+5uaOVQl18Jer4T3iyb6JRaJ0lHd+EL+RTJyqKV/0bRvc30I+9/X/Bpg9dcvjM1ahjTvZk38TjbrgOv4YGFzXPswShtT4fuBEIAzcbY75fYB0N3ABY4DVjzFVexSeCz/b3eTL72+j+Ev3Y22+EzRtccvjcNagjT/Bm59K/QQSAJ3+aaK3DwE3ABcAy4Eqt9bIx6ywF/gk41RhzKPBdL2ITwWetxfZ0eZwc+rC3/qtLDqEQasWXvUkOSrn6BkkOIgC8unc9AVhvjHnPGDME3AVcOmadrwA3GWO6AIwx2zyKTQSYzaRdfUPCm5ZKkJ0F7tYbYcvGbHK4DnX4ceXfcSgE7bNR8fIPSS5EMbwqYloIbMh7vBE4ccw6BwJorZ/DFUPdYIx5eOyGtNbXA9cDGGPo6OgoS8AzEYlEAhnXdPh5LHZokPTOTmhscD8lEI6EaW9vH/f5TF8PPT//IektGyEUpunL3yF2lAd3DuEw4dlzpzQVqHzOgqtajidIldQRYClwBrAIeFprfbgxZrfpv4wxK4GV2Ye2s7PT0yCL0dHRQRDjmg6/jsX297nZ2EpcGd3e3k5XV9e4+7S35d05XP43JPZZSmKc9UsmHnfzRHdPrQhNPmfBFfTjWbBgQVHreZUgNgGL8x4vyi7LtxF4yRgzDLyvtV6HSxgvexOiCAKbSbte0cmkt/tNjE0OX0EtO6q8Ow2FoLlVOr+JwPIqQbwMLNVaL8ElhiuAsS2UfgtcCdyqte7AFTm951F8IgDsYBK6uzzr3zC630T/7nUOXiSHujrXv8Grwf2EmAZPKqmNMSngm8AjwJtukVmrtf6e1vqS7GqPADu01m8ATwH/hzFmhxfxCX/ZTMa1UvKw89vovgf6sbf/Wy456L/xIDnEoG22JAcReMp61OGoTOzmzZv9jmEPQS9/nIpyH4tNDrjmqx4NmZFfB2GTA65YadOHuaashx1b3gBicdeMtQSD+8nnLLiCfjzZOohJP4RBqqQWNcSm09DrfV3D6P6TA274jJEe0p+7pvzJIR53xUpejfwqxAxJghCes4l+6Ov2ZK7ogvsfTLqB9za875LD8i+hjji+vDsdGVNJkoOoIJIghGdsati1UBoa8i+GkSG7R0Zl/czVqKPGdskpsVDI1TlIchAVRhKE8ITt73VTgfpY52WHh+ld+T/g/XUAborQcg+8NzJ0hlRIiwokCUKUlU0NQ/cuGPbvrsHFkcLetZLhda8DoC663Jshu5tbZR4HUbEkQYiyKVdv6CnHkU5jzc0wkhwuuAx14hnl33FjE6qhsfz7EaJMJEGIkrOpFPR0+VrXMBpLOo29+1Z48zUAGi65kuTxp5d/x7E4qrm1/PsRooxkJhJRUnYgATu3BSM5ZDLYe38Or692C868kPpzxw4iXAaRCLSOPyCgEJVC7iBESQShhVI+ay32d7+C115yCz5xLurMC8u/45EWSzILnKgCkiDEjFhrXeukRJ/vdQ0jrLXYB1fBK8+6BSefiTrnM+VvZjrSYknmjxZVQj7JYtrs8LCraxge9juUUdZa7GO/hRefcguO/wTqghXe9EFobZMWS6KqSIIQ0xKEfg0FPfUAPPOo+//RJ6EuusKb5NDciorLsN2iukwpQWit24ALgQXAZuDBkSlCRW2w6TR07wxMXUM++8yj2KcecA8OO9b1kvaiLqCxCdXYVP79COGxor89WuuzgA+AbwPHA9/CTexzdnlCE0FjB5OwIxgtlMayLz6FffRe9+DgI1GXXetNcqhvkOasompN5Q7ih8D1xhgzskBrvQK4CTi41IGJ4HAV0T3Q3+d3KAXZV57FPpD9WB6wDHX5dd4MbRGLQ0tb+fcjhE+m8ifWAuA3Y5bdC8wvXTgiaGxyADq3Bjc5/OUl7P13ugdLDkRd+VVUJFr+HdfVlWxeByGCaioJ4ufAN8Ys+xpwR+nCEUFh02nsrp2kd2z3bDKfqbKvr8bec7urKN97P9Tnv4aqqyv/jqN1MjqrqAlTKWI6GvhbrfU/4uaVXgjMBV7SWj89spIxxoNxDES52EzG3S2M9Guoj/sdUkH2rb9iV93iYly4D+rqb6JiHsQarYN26QgnasNUEsRPsz+iStlkAnp7AnvHMMK+8wb2rp+6+avnLUR98VuoeH35d1xXJ72kRU2ZNEFkWy8BbBhvHWPMkyWLSHjOZjJumIzkgN+hTMq+vw57548hnYKO+ahrvu3NiKmSHEQNKuYO4meTPG+B/UoQi/CBHRqE7q7A3zUA2I/exf7iR5AahllzUNd+B9XUUv4dRyU5iNo0aYIwxizxIhDhLZvJuKariX6/QymK3fgB9o4fwtCgaz107XdRXjQxjUalzkHULBlqowZVSl3DCLt5A/b2f4PBJLS0ueTQNqv8O5bkIGqcJIgaYjPpbF1D0u9Qima3bMLefqOrH2lqcclh1pzy73h02G6ZS1rULkkQNaKS6hpG2O1bsLfd6IrBGptccuiY583OW1q96Y0tRIBJgqhy1loYGXm1gtjOrdhb/sXFXt+IuuY7qLl7ebPz+gYZmVUIJEFUtSDO11AMu3M79tZ/dZXo8XrXlHX+Im92Hg6DDL4nBCAJoipZa11P6CDO1zAJ29Xp7hx6dkEsjvrSt1EL9vYugJZ2qZQWIksSRJWxqWHo3gXDwRuSezJ21w6XHLq7ssnhW6hF+3oXQGMzKiYzwgkxQhJEFbH9fa5YpsLuGgDsrp3Yn/0L7NoJdTHU1d9ALfaw/2Usjmr2oNOdEBXEswShtT4fuBEIAzcbY74/znqfA+4GjjfGvOJVfJXMDg9D765ATuRTDNu909057NoB0TqXHPY5wLsAwmFolXkdhBjLk8JWrXUYN7HQBcAy4Eqt9bIC6zUD3wFe8iKuSmczaWxPV2BneSuG7e7C3vKv0NUJ0ahLDvsu9S4ApaS/gxDj8Ko27gRgvTHmPWPMEHAXcGmB9f4/4J+ByunJ5QNrLba/103kk0j4Hc60jd457NwOkSjqC19HLTnQ2yBa21BRDyYYEqICeZUgFrL7aLAbs8tGaa2PARYbYx7wKKaKZAcSLjH09kCm8uoaRozWOezcnr1z+DpqP49nrm0HJeGAAAAYRklEQVRqlv4OQkwgEJXUWusQ8APgmiLWvR64HsAYQ0dHR3mDm4ZIJFLSuKy12EQ/tq8HGwJavKtMDUfCtLe3l3Sb6Z2d9Nx+I7arE6J1tPztPxI96LCS7mM8I8ejGhoJt8/2ZJ/lUurPmZ+q6Vigeo7HqwSxCVic93hRdtmIZuAw4A9aa3DzXN+vtb5kbEW1MWYlsDL70HZ2dpYt6Onq6OigFHG5/gz9rk+DT0NktLe309XVVbLt2a4deRXSrlipb+5CKOE+JtLe3k5Xfz/U1aMC+NmZilJ9zoKgmo4Fgn88CxYsKGo9rxLEy8BSrfUSXGK4Arhq5EljTDcwmm611n8A/qGWWzHZoUHo7a64XtATsTu35/o51MV8qXNQkYgbLlzmkxZiUp7UQRhjUsA3gUeAN90is1Zr/T2t9SVexFApRlsm7eysruSwYxv2Zz/IJYcvftP7CmmlCLVLiyUhiqVsBXaqymM3b97sdwx7mO7tpU30u45umUwZopqeUhQx2W0f58ZWisXdHNJ7+zAJYUsrc/beN9C3/lMR9GKMqaimY4HgH0+2iGnS2+hAVFLXOjeoXmUOjzEZ+/EG7G3/5upR4vVubCUvh88YEa9HNTR5v18hKpgkCB/ZTDo77Wfl9mWYiN34gZsJLjkADY2oL30HtWDx5C8stXAYvJieVIgqIwnCBzaTcRfNgBUnlZL94B3sL37kpgltanHzOcwrruVEyckIrUJMiyQID9nBQUgmYHCgoju5Tca+sxb7q5+4SvaWdtS13/FuJrixGhpkhFYhpkkShAfsYNLdLVRRq6Tx2LWvYlfd4vptzJrj7hz86pAWCkGTjNAqxHRJgigjOzToEkOFDqQ3VfbPL2Dv/bkbbnzuXi45+Dk7W0urNGkVYgYkQZSBHUxid26vmcQAYJ97HPvwb9yDhfu4fg5+thqKxWWcJSFmSBJECdlkAvr7SQ8maiY5WGuxj98PTz/sFiw5EHXV36Li9f4FFQpJqyUhSkASxAzZTAYGEmPGS2r0NSav2EwG+/u74OVn3IJDjkStuM7/4bNbWlFhKVoSYqYkQUyTG0ivD/r7qrap6kTs8BB21a3w5l/cgmNORl3yef8vzPF6KVoSokQkQUyRtRYG+l1i8GmEVb/ZgX7sL38MH653C047B3XuZ/0fAE86xAlRUpIgihSEobeDwHZ3Ye/4IWxzY2CpCy5DnXK2z1FlSYc4IUpKEsQkCtcx1Cb78UbsL25y40aFw6jlX0IdcbzfYTkNjdIhTogSkwQxDptOuzuGgb6q7vVcLLv+TexdK93QGbE46sqvovb3eIrQ8YTD0iFOiDKQBJHHplLuApgcqMqRVafLvvoC9r5fuMr4ljbU1d9EzV84+Qu90twqRUtClIEkCLLFSP297o6hsufHKCmbyZC4/y7so791C+YtRF39DVRraeeonpF4vb99LoSoYjWfIGwyAb09NV+/MJYdHsL+5nYG1r7qFhxwCOryrwTrYhwKQYuPQ3kIUeVqNkG4AfR6pSipANvbjb3zx7DxA7fghNNRn9b+93EYq6VNxloSooxqLkFIYpiY3fShSw49u0ApGpZfzcCRJ/nfx2GslrZg3c0IUYVqIkG4zm3ZpqqplN/hBJZdsxp77+1uWPK6GEpfR/1Jp5Oc4ZzUJdfcgmqojeFMhPBTVScIm8k2VU301+RwGMWymQz2yd/BH7MD7rV3oD7/Nf9mgJtIYxOqsdnvKISoCVWZIGxq2N0tDAxIq6RJ2IEE9u5bYd3rbsGSA1FXfMXfobrHUxfzd34JIWpMVSUIO5h0YyQNDfodSkWwWze7+oad292Ck85Enf+54FVGg+sM1xag5rVC1ICKTxCjQ2EM9Ev9whTY1/6Eve+XrrI+EnEjsR59kt9hFaYUtM2SFktCeKziEwSdW2QojCmwqZSb+e2lP7gFre1u2IyF+/ga14SaWlDROr+jEKLmVH6CkORQNLtrB/bXN+f6NxywDHXZtajGANY3jIjXBzs+IapY5ScIURT7xl+w997hxplSCnXGp+GMTwd7DKNoHQRpWA8haowkiCpnU8PYR++FF55yCxqb3F3DAcv8DWwy4bCrdwhaBz0haogkiCpmt2/BrroFPt7gFiw50CWHoM+6NlIpHcTWVELUEEkQVchaC688i31olesVrZQrTgp6kRK4WFvbpVJaiACQBFFlbH+va7765mtuQess1GXXoPZd6mtcRQmF3J1DncwMJ0QQeJYgtNbnAzcCYeBmY8z3xzz/H4C/AVLAduDLxpgPvYqvGtg3X3MT+/T3uQWHH4e6+EpUfYO/gRUjHIb22ahI1O9IhBBZnpQ3aK3DwE3ABcAy4Eqt9dha0j8DxxljjgDuBv5/L2KrBnYgQeaeO1yv6P4+1zT0c9egVny5MpJDJAKz50hyECJgvLqDOAFYb4x5D0BrfRdwKfDGyArGmKfy1n8R+IJHsVU0+/YaV6TU2+0W7HcQavkXUa2z/A2sWOGwGxxQekkLETheJYiFwIa8xxuBEydY/zrgoUJPaK2vB64HMMbQ3h68dvLhSLjscWX6++i/+zaGXn7WLaiL0XDJlcRPP7ekFdFlPZZQiHDHXE8rpCORCB0dHZ7tr5zkWIKrWo4ncJXUWusvAMcBnyz0vDFmJbAy+9B2BW2uAqC9vZ1yxWWthb++7FoojdQ1LDkQ9ZkvkJw1h2R3d0n3V7ZjUcrVOXT3lH7bE+jo6KCzs9PTfZaLHEtwBf14Fiwobih/rxLEJmBx3uNF2WW70Vp/Cvh/gE8aY2RI1jFsVyf2/l/B+mzJXCyOOvezcNxpwW++OlZrm7RWEiLgvEoQLwNLtdZLcInhCuCq/BW01kcDPwHON8Zs8yiuimBTw/Ds49inH3L9GgAOOQp1oUZV4lAULa2oeAVUngtR4zxJEMaYlNb6m8AjuGautxhj1mqtvwe8Yoy5H/jvQBOwSmsN8JEx5hIv4gsy+85a7O9/nZuzoaUNdeHlqGVH+RvYdDU2BXMyIiHEHpSt7BnX7KZXX/Y7hj2Uotze7tjmhuV+669uQSgEJ5+FOvNCVCxegiiLU9I6iHg9qs3f1lVBLxueCjmW4Ar68WTrICYd6CxwldS1ziYHsH94EF58CtJpt3DfpaiLrgjmHNHFisdlZFYhKowkiICw6TS8/Az2qQfcfNrghp04bzkcekxlj2oai7shPyr5GISoQZIgfGathTf+jH3sPtiRrZuvi6E+cR6cenblD1pXF5Nhu4WoUJIgfGKthfVvYp+4HzZlh5xSCo49FXXWRajmVn8DLIV4vRuZVZKDEBVJEoQP7PvrsE/8Dj5cn1t40OGocz+LmruXf4GVilLQ3CKtlYSocJIgPGKthffXuTqGD97JPbHkQNSnLkXtvZ9/wZVSJOLqG6Iy8J4QlU4SRJlZa+GdtdinH4YP3809sXgJ6uyLYb+Dq6cIZqS+odJ6dQshCpIEUSY2nYbXV2OfeRS25o0qsvf+qDMvhP2rKDEANDRAc1t1HZMQNU4SRInZ5AADTzyHffJB6N6Ze2L/Q1CnnwtLDqqui6hS0NSCapT6BiGqjSSIErGdW7F/+iO8+gKJwaRbqJQbM+n081AL9/E3wHKIRqGlXeobhKhSkiBmwGYysO517Et/zI2wCq4s/piTUSefhZo1x78Ay0UpaGyCxubquhsSQuxGEsQ02O6dsPp57OrnoSdvnKK22agTT6ft7AvpHhz2L8BykrsGIWqGJIgi2eFheOuv2D+/4O4W8gc5POAQ1IlnwIGHoUIhQg1NMBi8iYxmRO4ahKg5kiAmYK2Fj97D/vVPsOYVGEjknmxshmNOQR13anUWI+WL1rlhxuWuQYiaIgliDGstbN2Mff0V+OvL0LUj92QoBEsPRR19suv5HKny0xdShNraUTGZ3EeIWlTlV7jijCaFN/4Ma1ZD55bdV5i/CHXUiXDE8dUxRlIx6hugqYVQYzMMyOyvQtSimk0QNpOBje9j33wN3vhLbsa2Ee2z4fDjUEecUNnzMExVXR00t1b+KLJCiBmrqQRhBxLw7lvYdWtg3evQ37f7Cm2z4bBjUIcdCwv2rq3K2HDYJYZ4vd+RCCECoqoThM1kYPNHbljt9Wthw/uQyey+0twFsOwoN8fz/EW1lRTA1as0NUN9Y+0duxBiQlWVIKy1sH2LGzX1vbfgvbchObD7SuEILFmKOugIOOgwVHuHP8H6LRRyzVbrG2VwPSFEQRWfIOzmDfDReuwH690w2v29e640aw4sXYZaeqgbXrsu5n2gQREOQ0MTNMgdgxBiYpWfIP79v+65sKnFJYL9D3bDabfP9j6woIlEXN+NeL0kBiFEUSo+QQDQ0uaG0V5yICw5EDrmyUVwRCzu7hZicb8jEUJUmIpPEOrv/4ubwUwSQk4o5Pox1DdWf2c+IUTZVPzVQ7VJ8RHgxkqKxSDeALG4JEwhxIxVfIKoaUq5ocXj9RCLoUJhvyMSQlQRSRCVJhRy9QqxGNTFpYmqEKJsJEEEXTjsRlOtq4NoTEZUFUJ4RhJEkEQiEIm6hBCJQjQixUZCCN9IgvBDKJRLBpGom6UtEpWKZSFEoHiWILTW5wM3AmHgZmPM98c8HwPuAI4FdgCXG2M+8Cq+kgqF3EU/HIZQePffEbkrEEJUBk8ShNY6DNwEnANsBF7WWt9vjHkjb7XrgC5jzAFa6yuAfwYuL3UsmXVr4dlHoasT2jvgtHMJHXjo5K976gF47gkYSrpK4tPPJ3T+cnfhD4WyCcD9jsydi4p2zizONauxj9wDnVtdx7/zlhM6/NiSbg8o6T4A0r+7Cx67DwYHIFYP51xK+OIrCsey6SNIp1wy3WsxHHQ4vL0mtxwLKPd8c6trtTWQmDDWyba9dctGGBoaXV7sMZfq/RhvO7stj9cXPNaxr02uuAb2WTrlGEqpVOclufoF0qtuK+lnUcycsvlzK5eJ1vpk4AZjzHnZx/8EYIz5b3nrPJJd5wWtdQTYAswxxkwUoN306st7LlUq9zP6OETm7TXw21+64p26OnehSKfhsmsIHXoUqBAo3O9QKPe6Bww8YNxzoTBk0u7addHle1z8ADo6OujsnH6CyKxZjb3zJ9k4YzA0CKkU6qqvTv+iNHZ7/X3u+BoaJ9zHVI4l/bu74Pe/nvA8jcaSGobebtwKuIviwADU10MymX2tde+Dtbn3c9YcN+BigViL2vbgINjsiL4tbRCOTnpeS/V+jLcdTjkLnn/SLU+loCs7N0nese62Tva1YZshc/lXfLuQlvK8hH79U9IqVJLPexDM9BpQbgsWLAD3TZ2QV20kFwIb8h5vzC4ruI4xJgV0A5P3gps7H+buBfMWoOYvdD/zFqDm7oWaM9/9dMxDzZ4Dzz/hmoc2NLqy/4ZGlyj++BCqoQlV34CKN6BicVS0DhWJosJhePx+dyrDEXeRCkfc48fuK8W52YN95B73pYvFsx3g4hCJuOWl2t7ggPsLtUT7ANz5mOQ8jcYykMhbJwSJhFs3kcgldnDJAdww7SoEPd3jxlr0tvOXF3HMpXo/xtsOj92XW97bnf1DZfdj3W2d0ddGZ/Z+zVBpz0u0tJ9FURIVV0mttb4euB7AGMOcufOKfu32rk5UU8tulcE23Ijt6qSjY/xhv7cOJl39Qf6FKxSGwWTB10UikQm3V644p7K9VPav+0jeUByF9jGVYynmPI3Eku7cmrtLC4XcX/2hOkgPQSgKqWxisKP/uPXSKSKRSMFYi9r2yJ1IdlvhhsnPa6nej/G2k972MeHs6LqpdMrFBrsda/46oyJhQtP8TJRCSc9LcwsRSvN5D4KZXgOCwqsEsQlYnPd4UXZZoXU2ZouYWnGV1bsxxqwEVmYf2qncxmXaO6C7y/2FMmIwCe2T3A7G4q7uIf/LmUlDLF7wdTMuYppunFPZXigMFlKp1IT7mNKxFHGeRmMJR1wdQSiUuzvIpLO/M24b1mZvgrP/z2QgHHExF4i1qG3n35GEI6QT/ZOe11K9H+NuJxZ3ccTiudhh92PNXycrnBomM83PRCmU8ryovh7Skbw+PjP4vAdBhRQxTcqrIqaXgaVa6yVa6zrgCuD+MevcD3wp+//LgCcnqX+YMnXecleeO5h0F4rBpCvrzFbYjuucS90fsemUe1065R6fc2kpw5t5nFPZXqzeDehXon0ARZ2n0VjqG/LWyUBDg1u3oSF3EYdcsgmF3HotrePGWvS285cXccylej/G2w7nXJpb3tzqYhtzrLutM/ra4Zm9XzNU2vMyXNrPoiiJ8A033FD2naxYsSKzatWqd4BfAt8CfmGM+Y3W+nurVq1qXrFixdurVq1aA3x+1apV/w04CvjbFStWdE2y6Rt6ewtMEDQONW8BzFsAGz+A7p0wqwP12asnrQgLHXSYK+T48F0YHnIX1ws+V7CCGqChoYFEIlF0XKWKc0rbu+xa1FEnTrqPqRxLMedpNJYtG13FcSjkKpEX7uMqYoeH3PJweLR/CPUNMHuuu3gOD40ba1HbHkoCyi2fv6io81qq92O87YQ/cW5ueaLPzY0+5lh3Wyf72parv87wgYdNKYZSKuV5adr/IAbffbskn/cgmOk1oNyam5sB/vNk63nSiqmM7ObNm/2OYQ9Bv72cimo6Fqiu45FjCa6gH0/QWjEJIYSoMJIghBBCFCQJQgghREGSIIQQQhQkCUIIIURBFd+Kye8AhBCiQlV9KyYVxB+t9Wq/Y5Bjqf7jkWMJ7k+FHM+kKj1BCCGEKBNJEEIIIQqSBFEeKydfpWJU07FAdR2PHEtwVcXxVHoltRBCiDKROwghhBAFVdyEQUGmtT4fuBEIAzcbY77vc0jTprW+BbgI2GaM8W/I0BLQWi8G7gDm4ZpGrzTG3OhvVNOntY4DTwMx3Hf4bmPMf/I3qpnJzlv/CrDJGHOR3/HMhNb6A6AXSAMpY8xx/kY0fXIHUSLZD/hNwAXAMuBKrfUyf6OakduA8/0OokRSwN8bY5YBJwHfqPD3ZhA4yxhzJG5o/PO11if5HNNMfQd40+8gSuhMY8xRlZwcQBJEKZ0ArDfGvGeMGQLuAsozo5AHjDFPAzv9jqMUjDEfG2Nezf6/F3chGjsnesUwxlhjTF/2YTT7U7GViVrrRcCFwM1+xyJ2J0VMpbMQ2JD3eCNwok+xiHForfcFjgZe8jmUGcnesa4GDgBuMsZU8vH8K/CPQLPfgZSIBR7VWlvgJ9lpkiuS3EGImqG1bgJ+A3zXGNPjdzwzYYxJG2OOws3vfoLWuiLribTWI/Vcq/2OpYROM8Ycgytu/obW+nS/A5ouSRClswlYnPd4UXaZCACtdRSXHH5pjLnH73hKxRizC3iKyq0vOhW4JFuxexdwltb6F/6GNDPGmE3Z39uAe3HFzxVJiphK52VgqdZ6CS4xXAFc5W9IAkBrrYCfAW8aY37gdzwzpbWeAwwbY3ZpreuBc4B/9jmsaTHG/BPwTwBa6zOAfzDGfMHXoGZAa90IhIwxvdn/nwt8z+ewpk3uIErEGJMCvgk8gqsENcaYtf5GNX1a618BLwAHaa03aq2v8zumGTgVuBr31+lfsj+f9juoGdgLeEpr/VfcHyaPGWN+73NMwpkHPKu1fg34E/CAMeZhn2OaNulJLYQQoiC5gxBCCFGQJAghhBAFSYIQQghRkCQIIYQQBUmCEEIIUZAkCCGKpLX+QGv9Kb/jEMIrkiCEEEIUJAlCCCFEQTLUhhBTpLW+ATgMNyHMp4F3gGuNMa9ln/8/gW8DLcBm4OvGmCe01ifgJpQ6BBjAjQ31H7LDwwsROHIHIcT0XAqsAmYBdwK/1VpHtdYH4YZcOd4Y0wycB3yQfU0a+DugAzgZOBv4usdxC1E0uYMQYnpWG2PuBtBa/wD4e9xsdR/jpgJdprXeboz5YOQFY4a0/kBr/RPgk7j5EIQIHEkQQkzP6ORQxpiM1nojsMAY84zW+rvADcChWutHcMVIm7XWBwI/AI4DGnDfv2qaB0FUGSliEmJ6Ruf+0FqHcPN/bAYwxtxpjDkN2Ac3u9jIUNz/DrwFLDXGtAD/N6C8DFqIqZA7CCGm51it9XLgflyF9CDwYrYOYiHwHJDEVUaHs69pBnqAPq31wcDXgO1eBy5EseQOQojpuQ+4HOjCzTWx3BgzjKt/+D7QCWwB5pKdEAf4B9wkUr3AT4FfexyzEFMi80EIMUXZZq4HVPLMZ0IUQ+4ghBBCFCQJQgghREFSxCSEEKIguYMQQghRkCQIIYQQBUmCEEIIUZAkCCGEEAVJghBCCFGQJAghhBAF/W9Q8MOJfO2w7QAAAABJRU5ErkJggg==\n", "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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69Z4hPnjTVrri7ZX507VtfK9CKhFl0+Cw9HiIDSGBiBAicJlslnTObopEZa7n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\naWjFp3KvR0MqQXNjig0DXer1EBFZ5/QuPstd776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- "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -630,22 +618,20 @@ } ], "source": [ - "sns.regplot(x='lpsa',y='Ip',logistic=True,data=treinoCP)" + "sns.regplot(x='lpsa',y='Ip',logistic=True,data=treinoCP);" ] }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Optimization terminated successfully.\n", - " Current function value: 0.455978\n", + " Current function value: 0.423807\n", " Iterations 7\n" ] }, @@ -658,22 +644,22 @@ " Dep. Variable: Ip No. Observations: 67 \n", "\n", "\n", - " Model: Logit Df Residuals: 64 \n", + " Model: Logit Df Residuals: 61 \n", "\n", "\n", - " Method: MLE Df Model: 2 \n", + " Method: MLE Df Model: 5 \n", "\n", "\n", - " Date: Mon, 15 May 2017 Pseudo R-squ.: 0.3098 \n", + " Date: Thu, 03 May 2018 Pseudo R-squ.: 0.3585 \n", "\n", "\n", - " Time: 20:12:03 Log-Likelihood: -30.551 \n", + " Time: 10:32:59 Log-Likelihood: -28.395 \n", "\n", "\n", " converged: True LL-Null: -44.260 \n", "\n", "\n", - " LLR p-value: 1.111e-06\n", + " LLR p-value: 6.717e-06\n", "\n", "\n", "\n", @@ -681,13 +667,22 @@ " \n", "\n", "\n", - " \n", + " \n", "\n", "\n", - " \n", + " \n", "\n", "\n", - " \n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", "\n", "
coef std err z P>|z| [0.025 0.975]
Intercept -0.7279 0.918 -0.793 0.428 -2.527 1.071Intercept 4.5834 2.935 1.562 0.118 -1.169 10.336
lpsa 0.7853 0.337 2.333 0.020 0.126 1.445lpsa 1.0838 0.539 2.011 0.044 0.027 2.140
lcp 0.9491 0.377 2.519 0.012 0.211 1.687lcavol 0.0818 0.433 0.189 0.850 -0.767 0.930
lweight -1.6921 0.890 -1.901 0.057 -3.437 0.053
lcp 0.9065 0.412 2.198 0.028 0.098 1.715
lbph 0.2431 0.265 0.917 0.359 -0.276 0.762
" ], @@ -697,23 +692,26 @@ " Logit Regression Results \n", "==============================================================================\n", "Dep. Variable: Ip No. Observations: 67\n", - "Model: Logit Df Residuals: 64\n", - "Method: MLE Df Model: 2\n", - "Date: Mon, 15 May 2017 Pseudo R-squ.: 0.3098\n", - "Time: 20:12:03 Log-Likelihood: -30.551\n", + "Model: Logit Df Residuals: 61\n", + "Method: MLE Df Model: 5\n", + "Date: Thu, 03 May 2018 Pseudo R-squ.: 0.3585\n", + "Time: 10:32:59 Log-Likelihood: -28.395\n", "converged: True LL-Null: -44.260\n", - " LLR p-value: 1.111e-06\n", + " LLR p-value: 6.717e-06\n", "==============================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", - "Intercept -0.7279 0.918 -0.793 0.428 -2.527 1.071\n", - "lpsa 0.7853 0.337 2.333 0.020 0.126 1.445\n", - "lcp 0.9491 0.377 2.519 0.012 0.211 1.687\n", + "Intercept 4.5834 2.935 1.562 0.118 -1.169 10.336\n", + "lpsa 1.0838 0.539 2.011 0.044 0.027 2.140\n", + "lcavol 0.0818 0.433 0.189 0.850 -0.767 0.930\n", + "lweight -1.6921 0.890 -1.901 0.057 -3.437 0.053\n", + "lcp 0.9065 0.412 2.198 0.028 0.098 1.715\n", + "lbph 0.2431 0.265 0.917 0.359 -0.276 0.762\n", "==============================================================================\n", "\"\"\"" ] }, - "execution_count": 17, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -741,48 +739,46 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "7 0.191164\n", - "9 0.227738\n", - "10 0.227738\n", - "15 0.490424\n", - "22 0.864571\n", - "25 0.335430\n", - "26 0.341547\n", - "28 0.350433\n", - "32 0.385434\n", - "34 0.387917\n", - "36 0.399939\n", - "42 0.442391\n", - "44 0.870658\n", - "48 0.706934\n", - "49 0.497879\n", - "50 0.633992\n", - "53 0.806359\n", - "54 0.940410\n", - "55 0.520091\n", - "57 0.874011\n", - "62 0.965289\n", - "64 0.971754\n", - "65 0.554688\n", - "66 0.756003\n", - "73 0.868077\n", - "74 0.942976\n", - "80 0.915565\n", - "84 0.976718\n", - "95 0.996493\n", - "97 0.998362\n", + "7 0.180741\n", + "9 0.126993\n", + "10 0.206372\n", + "15 0.412494\n", + "22 0.900738\n", + "25 0.358521\n", + "26 0.536305\n", + "28 0.302081\n", + "32 0.376385\n", + "34 0.413963\n", + "36 0.321005\n", + "42 0.349197\n", + "44 0.751478\n", + "48 0.659462\n", + "49 0.505584\n", + "50 0.743541\n", + "53 0.857350\n", + "54 0.919921\n", + "55 0.557184\n", + "57 0.950451\n", + "62 0.975161\n", + "64 0.974580\n", + "65 0.538045\n", + "66 0.781062\n", + "73 0.800235\n", + "74 0.977351\n", + "80 0.895569\n", + "84 0.982613\n", + "95 0.998565\n", + "97 0.999024\n", "dtype: float64" ] }, - "execution_count": 18, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -800,10 +796,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { @@ -814,7 +808,7 @@ "15 bom\n", "22 mau\n", "25 bom\n", - "26 bom\n", + "26 mau\n", "28 bom\n", "32 bom\n", "34 bom\n", @@ -822,7 +816,7 @@ "42 bom\n", "44 mau\n", "48 mau\n", - "49 bom\n", + "49 mau\n", "50 mau\n", "53 mau\n", "54 mau\n", @@ -841,7 +835,7 @@ "dtype: object" ] }, - "execution_count": 19, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -860,9 +854,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "df = pd.DataFrame(dict(prob=model.predict(teste),\n", @@ -872,15 +864,26 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -888,6 +891,7 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", @@ -896,225 +900,256 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", " \n", " \n", "
predprobrealgleason
bom0.180741bom6
9bom0.126993bom6
10bom0.206372bom6
15bom0.412494mau7
22mau0.900738mau7
25bom0.358521bom6
26mau0.536305bom6
28bom0.302081mau7
32bom0.376385bom6
34bom0.413963bom6
36bom0.321005mau7
42bom0.349197mau7
44mau0.751478mau7
48mau0.659462mau7
49mau0.505584bom6
50mau0.743541bom6
53mau0.857350mau7
54mau0.919921mau7
55mau0.557184mau7
57mau0.950451mau7
62mau0.975161mau7
64mau0.974580mau7
65mau0.538045bom6
66mau0.781062mau7
73mau0.800235mau7
74mau0.977351mau9
80mau0.895569mau7
84mau0.982613mau9
95mau0.998565mau7
97mau0.999024mau7
\n", "
" ], "text/plain": [ - " pred prob real\n", - "7 bom 0.180741 bom\n", - "9 bom 0.126993 bom\n", - "10 bom 0.206372 bom\n", - "15 bom 0.412494 mau\n", - "22 mau 0.900738 mau\n", - "25 bom 0.358521 bom\n", - "26 mau 0.536305 bom\n", - "28 bom 0.302081 mau\n", - "32 bom 0.376385 bom\n", - "34 bom 0.413963 bom\n", - "36 bom 0.321005 mau\n", - "42 bom 0.349197 mau\n", - "44 mau 0.751478 mau\n", - "48 mau 0.659462 mau\n", - "49 mau 0.505584 bom\n", - "50 mau 0.743541 bom\n", - "53 mau 0.857350 mau\n", - "54 mau 0.919921 mau\n", - "55 mau 0.557184 mau\n", - "57 mau 0.950451 mau\n", - "62 mau 0.975161 mau\n", - "64 mau 0.974580 mau\n", - "65 mau 0.538045 bom\n", - "66 mau 0.781062 mau\n", - "73 mau 0.800235 mau\n", - "74 mau 0.977351 mau\n", - "80 mau 0.895569 mau\n", - "84 mau 0.982613 mau\n", - "95 mau 0.998565 mau\n", - "97 mau 0.999024 mau" + " pred prob real gleason\n", + "7 bom 0.180741 bom 6\n", + "9 bom 0.126993 bom 6\n", + "10 bom 0.206372 bom 6\n", + "15 bom 0.412494 mau 7\n", + "22 mau 0.900738 mau 7\n", + "25 bom 0.358521 bom 6\n", + "26 mau 0.536305 bom 6\n", + "28 bom 0.302081 mau 7\n", + "32 bom 0.376385 bom 6\n", + "34 bom 0.413963 bom 6\n", + "36 bom 0.321005 mau 7\n", + "42 bom 0.349197 mau 7\n", + "44 mau 0.751478 mau 7\n", + "48 mau 0.659462 mau 7\n", + "49 mau 0.505584 bom 6\n", + "50 mau 0.743541 bom 6\n", + "53 mau 0.857350 mau 7\n", + "54 mau 0.919921 mau 7\n", + "55 mau 0.557184 mau 7\n", + "57 mau 0.950451 mau 7\n", + "62 mau 0.975161 mau 7\n", + "64 mau 0.974580 mau 7\n", + "65 mau 0.538045 bom 6\n", + "66 mau 0.781062 mau 7\n", + "73 mau 0.800235 mau 7\n", + "74 mau 0.977351 mau 9\n", + "80 mau 0.895569 mau 7\n", + "84 mau 0.982613 mau 9\n", + "95 mau 0.998565 mau 7\n", + "97 mau 0.999024 mau 7" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "df['gleason'] = teste.gleason\n", "df" ] }, @@ -1127,15 +1162,26 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -1171,7 +1217,7 @@ "mau 4 16" ] }, - "execution_count": 15, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1200,9 +1246,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1245,7 +1289,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula16-LDA-naiveBayes.ipynb b/aula16-LDA-naiveBayes.ipynb index 14c17a0..4b986f2 100644 --- a/aula16-LDA-naiveBayes.ipynb +++ b/aula16-LDA-naiveBayes.ipynb @@ -70,9 +70,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", @@ -86,10 +84,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "prostate = pd.read_csv(\"https://web.stanford.edu/~hastie/ElemStatLearn/datasets/prostate.data\",\n", @@ -101,41 +97,36 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "lpk = np.log(treino.prognostico.value_counts()/treino.shape[0])\n", "avgPSA = treino.groupby('prognostico').lpsa.mean()\n", - "varPSA = (np.sum((treino[treino.prognostico=='bom'].lpsa-avgPSA['bom'])**2)+\n", - " np.sum((treino[treino.prognostico=='mau'].lpsa-avgPSA['mau'])**2))*(1/(treino.shape[0]-2))\n", + "varPSA = treino.lpsa.var()\n", "deltaK = [treino.lpsa*(avgPSA[i]/varPSA)-((avgPSA[i]**2)/(2*varPSA))+lpk[i] for i in ['bom','mau']]" ] }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 5, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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FdgoVIppJ0iDECmkyV06sL0jD5YzNH61Kc4iipnkA3xU+AKe905wyixrtzt+O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\nsarvkbOmoTEAAAAASUVORK5CYII=\n", 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\n", 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"execution_count": 18, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -808,9 +865,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -845,9 +900,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -879,9 +932,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -938,7 +989,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula17-arvores-decisao.ipynb b/aula17-arvores-decisao.ipynb index b88e15e..404c93c 100644 --- a/aula17-arvores-decisao.ipynb +++ b/aula17-arvores-decisao.ipynb @@ -61,9 +61,7 @@ { "cell_type": "code", "execution_count": 76, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -90,9 +88,7 @@ { "cell_type": "code", "execution_count": 77, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -134,9 +130,7 @@ { "cell_type": "code", "execution_count": 61, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -185,9 +179,7 @@ { "cell_type": "code", "execution_count": 69, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -255,9 +247,7 @@ { "cell_type": "code", "execution_count": 70, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -314,9 +304,7 @@ { "cell_type": "code", "execution_count": 74, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -343,9 +331,7 @@ { "cell_type": "code", "execution_count": 73, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -379,9 +365,7 @@ { "cell_type": "code", "execution_count": 75, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -406,9 +390,7 @@ { "cell_type": "code", "execution_count": 79, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -443,9 +425,7 @@ { "cell_type": "code", "execution_count": 80, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -480,9 +460,7 @@ { "cell_type": "code", "execution_count": 81, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -540,9 +518,7 @@ { "cell_type": "code", "execution_count": 84, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -568,9 +544,7 @@ { "cell_type": "code", "execution_count": 85, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -604,9 +578,7 @@ { "cell_type": "code", "execution_count": 86, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -631,9 +603,7 @@ { "cell_type": "code", "execution_count": 87, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -684,9 +654,7 @@ { "cell_type": "code", "execution_count": 90, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -721,9 +689,7 @@ { "cell_type": "code", "execution_count": 91, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -776,9 +742,7 @@ { "cell_type": "code", "execution_count": 92, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -846,9 +810,7 @@ { "cell_type": "code", "execution_count": 119, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -878,9 +840,7 @@ { "cell_type": "code", "execution_count": 120, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -933,9 +893,7 @@ { "cell_type": "code", "execution_count": 121, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -988,9 +946,7 @@ { "cell_type": "code", "execution_count": 123, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1032,7 +988,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula18-knn-avaliacao.ipynb b/aula18-knn-avaliacao.ipynb index 9c7369e..ba89920 100644 --- a/aula18-knn-avaliacao.ipynb +++ b/aula18-knn-avaliacao.ipynb @@ -78,9 +78,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -105,9 +103,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -160,9 +156,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -238,9 +232,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -289,9 +281,7 @@ { "cell_type": "code", "execution_count": 46, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -327,9 +317,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -376,9 +364,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -405,9 +391,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -429,9 +413,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -452,9 +434,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -476,9 +456,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -556,9 +534,7 @@ { "cell_type": "code", "execution_count": 47, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -748,9 +724,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -780,9 +754,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -944,9 +916,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1174,7 +1144,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4, diff --git a/aula19-clustering.ipynb b/aula19-clustering.ipynb index 5ab56cb..feb8cb9 100644 --- a/aula19-clustering.ipynb +++ b/aula19-clustering.ipynb @@ -98,9 +98,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -139,9 +137,7 @@ { "cell_type": "code", "execution_count": 85, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -166,9 +162,7 @@ { "cell_type": "code", "execution_count": 86, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -201,9 +195,7 @@ { "cell_type": "code", "execution_count": 87, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -662,9 +654,7 @@ { "cell_type": "code", "execution_count": 88, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -690,9 +680,7 @@ { "cell_type": "code", "execution_count": 89, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -727,9 +715,7 @@ { "cell_type": "code", "execution_count": 90, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "c = df.groupby(clusters)[['x','y']].mean()\n", @@ -741,9 +727,7 @@ { "cell_type": "code", "execution_count": 91, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -776,9 +760,7 @@ { "cell_type": "code", "execution_count": 92, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -823,9 +805,7 @@ { "cell_type": "code", "execution_count": 94, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -849,9 +829,7 @@ { "cell_type": "code", "execution_count": 102, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -901,9 +879,7 @@ { "cell_type": "code", "execution_count": 122, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -952,9 +928,7 @@ { "cell_type": "code", "execution_count": 125, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1012,9 +986,7 @@ { "cell_type": "code", "execution_count": 128, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1035,9 +1007,7 @@ { "cell_type": "code", "execution_count": 129, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1074,9 +1044,7 @@ { "cell_type": "code", "execution_count": 132, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1137,7 +1105,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.3" } }, "nbformat": 4,