diff --git "a/JupyterNotebooks/Cap\303\255tulo01/DSA-Python-Cap\303\255tulo1-Como utilizar o Jupyter Notebook.ipynb" "b/JupyterNotebooks/Cap\303\255tulo01/DSA-Python-Cap\303\255tulo1-Como utilizar o Jupyter Notebook.ipynb" index ca607ca8..8a43b28a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo01/DSA-Python-Cap\303\255tulo1-Como utilizar o Jupyter Notebook.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo01/DSA-Python-Cap\303\255tulo1-Como utilizar o Jupyter Notebook.ipynb" @@ -12,15 +12,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Como utilizar o Jupyer Notebook" + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Como utilizar o Jupyter Notebook" ] }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 1, + "metadata": {}, "outputs": [ { "data": { @@ -31,7 +36,7 @@ "" ] }, - "execution_count": 2, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -61,9 +66,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -75,9 +80,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Linux Ubuntu 16.04 LTS.pdf" "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Linux Ubuntu 16.04 LTS.pdf" index b10cc512..f471a7db 100644 Binary files "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Linux Ubuntu 16.04 LTS.pdf" and "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Linux Ubuntu 16.04 LTS.pdf" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Mac.pdf" "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Mac.pdf" index fd67cb32..b4b9666f 100644 Binary files "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Mac.pdf" and "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Mac.pdf" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Windows.pdf" "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Windows.pdf" index bf2d473a..7e85d248 100644 Binary files "a/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Windows.pdf" and "b/JupyterNotebooks/Cap\303\255tulo01/Instalando Anaconda Python no Windows.pdf" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Arquivos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Arquivos.ipynb" old mode 100644 new mode 100755 index af80c93e..ada0e947 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Arquivos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Arquivos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -45,9 +52,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -65,9 +70,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -85,9 +88,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -105,9 +106,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -144,9 +143,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "UnsupportedOperation", @@ -168,9 +165,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -214,9 +209,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -245,9 +238,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -289,9 +280,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -308,9 +297,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -331,9 +318,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -357,9 +342,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -398,9 +381,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -420,9 +401,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "arq3.close()" @@ -431,9 +410,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "arq3 = open(fileName, \"r\")" @@ -442,9 +419,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -521,9 +496,7 @@ { "cell_type": "code", "execution_count": 30, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -591,9 +564,7 @@ { "cell_type": "code", "execution_count": 35, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "for row in rows:\n", @@ -604,9 +575,7 @@ { "cell_type": "code", "execution_count": 36, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -700,9 +669,7 @@ { "cell_type": "code", "execution_count": 43, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -767,9 +734,7 @@ { "cell_type": "code", "execution_count": 47, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -793,9 +758,7 @@ { "cell_type": "code", "execution_count": 48, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -814,9 +777,7 @@ { "cell_type": "code", "execution_count": 49, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "arq4 = open(\"teste.txt\", 'r')" @@ -825,9 +786,7 @@ { "cell_type": "code", "execution_count": 50, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -847,9 +806,7 @@ { "cell_type": "code", "execution_count": 51, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -870,9 +827,7 @@ { "cell_type": "code", "execution_count": 52, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -893,9 +848,7 @@ { "cell_type": "code", "execution_count": 53, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -917,9 +870,7 @@ { "cell_type": "code", "execution_count": 54, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -963,15 +914,13 @@ }, "outputs": [], "source": [ - "file_name = \"http://www.ats.ucla.edu/stat/data/binary.csv\"" + "file_name = \"binary.csv\"" ] }, { "cell_type": "code", "execution_count": 57, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(file_name)" @@ -980,14 +929,25 @@ { "cell_type": "code", "execution_count": 58, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "\n", " \n", " \n", @@ -1016,7 +976,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1042,7 +1002,7 @@ " admit gre gpa rank\n", "0 0 380 3.61 3\n", "1 1 660 3.67 3\n", - "2 1 800 4.00 1\n", + "2 1 880 4.00 1\n", "3 1 640 3.19 4\n", "4 0 520 2.93 4" ] @@ -1059,9 +1019,7 @@ { "cell_type": "code", "execution_count": 59, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "file2 = \"salarios.csv\"" @@ -1081,14 +1039,25 @@ { "cell_type": "code", "execution_count": 61, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
218008804.001
\n", " \n", " \n", @@ -1181,9 +1150,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1195,9 +1164,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Dicion\303\241rios.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Dicion\303\241rios.ipynb" index 7107af78..5e760bad 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Dicion\303\241rios.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Dicion\303\241rios.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -31,9 +38,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -65,9 +70,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -87,9 +90,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -120,9 +121,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -142,9 +141,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -175,9 +172,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -208,9 +203,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "NameError", @@ -242,9 +235,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -264,9 +255,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -286,14 +275,12 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "dict_keys(['Cris', 'Pedro', 'Tania', 'Fernando'])" + "dict_keys(['Pedro', 'Fernando', 'Tania', 'Cris'])" ] }, "execution_count": 16, @@ -308,14 +295,12 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "dict_values([25, 24, 26, 22])" + "dict_values([24, 22, 26, 25])" ] }, "execution_count": 17, @@ -330,14 +315,12 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "dict_items([('Cris', 25), ('Pedro', 24), ('Tania', 26), ('Fernando', 22)])" + "dict_items([('Pedro', 24), ('Fernando', 22), ('Tania', 26), ('Cris', 25)])" ] }, "execution_count": 18, @@ -363,9 +346,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -396,9 +377,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -435,9 +414,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -468,9 +445,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -498,9 +473,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -531,14 +504,12 @@ { "cell_type": "code", "execution_count": 30, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'key_one': 2, 8.2: 'Olá', 10: 5}" + "{'key_one': 2, 10: 5, 8.2: 'Olá'}" ] }, "execution_count": 30, @@ -564,14 +535,12 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'key_one': 2, 8.2: 'Olá', 10: 5, 'teste': 5}" + "{'key_one': 2, 10: 5, 8.2: 'Olá', 'teste': 5}" ] }, "execution_count": 32, @@ -597,9 +566,7 @@ { "cell_type": "code", "execution_count": 34, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -641,9 +608,7 @@ { "cell_type": "code", "execution_count": 37, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -708,9 +673,7 @@ { "cell_type": "code", "execution_count": 42, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -763,9 +726,7 @@ { "cell_type": "code", "execution_count": 46, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -797,9 +758,7 @@ { "cell_type": "code", "execution_count": 48, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -819,9 +778,7 @@ { "cell_type": "code", "execution_count": 49, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -841,9 +798,7 @@ { "cell_type": "code", "execution_count": 50, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -876,9 +831,7 @@ { "cell_type": "code", "execution_count": 52, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -910,9 +863,7 @@ { "cell_type": "code", "execution_count": 54, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -951,9 +902,7 @@ { "cell_type": "code", "execution_count": 56, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -973,9 +922,7 @@ { "cell_type": "code", "execution_count": 57, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1010,9 +957,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1024,9 +971,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" index f208f5cc..8ebcd82d 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -40,9 +45,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -61,9 +64,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -84,9 +85,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -109,15 +108,13 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'k2': 'serrote', 'k1': 'martelo', 'k3': 'machado'}\n" + "{'k1': 'martelo', 'k2': 'serrote', 'k3': 'machado'}\n" ] } ], @@ -130,15 +127,13 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'k2': 'serrote', 'k1': 'martelo', 'k4': 'parafuso', 'k3': 'machado'}\n" + "{'k1': 'martelo', 'k2': 'serrote', 'k3': 'machado', 'k4': 'parafuso'}\n" ] } ], @@ -151,9 +146,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 7 - Crie um arquivo chamado nomes.txt no diretório onde está este notebook, grave 5 nomes no arquivo e \n", @@ -166,9 +159,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -190,9 +181,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -211,14 +200,25 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", + "\n", "
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395006204.0023803.613
39605603.04116603.673
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399406003.8935202.934
\n", "
" ], "text/plain": [ - " admit gre gpa rank\n", - "395 0 620 4.00 2\n", - "396 0 560 3.04 3\n", - "397 0 460 2.63 2\n", - "398 0 700 3.65 2\n", - "399 0 600 3.89 3" + " admit gre gpa rank\n", + "0 0 380 3.61 3\n", + "1 1 660 3.67 3\n", + "2 1 880 4.00 1\n", + "3 1 640 3.19 4\n", + "4 0 520 2.93 4" ] }, "execution_count": 10, @@ -287,7 +287,7 @@ "# Exercício 10 - Complelete o trecho de código abaixo criado com Pandas e use a função tail() para ler os últimos \n", "# elementos do dataset.\n", "import pandas as pd\n", - "file_name = \"http://www.ats.ucla.edu/stat/data/binary.csv\"\n", + "file_name = \"binary.csv\"\n", "df = pd.read_csv(file_name)\n", "df.tail()" ] @@ -323,9 +323,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios.ipynb" index f4f7e176..854db310 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Exerc\303\255cios.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 1 - Imprima na tela os números de 1 a 10\n" @@ -30,9 +35,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 2 - Crie uma lista de 5 objetos e imprima na tela\n" @@ -41,9 +44,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 3 - Crie duas strings e concatene as duas em uma terceira string\n" @@ -52,9 +53,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 4 - Crie uma tupla com os seguintes elementos: 1, 2, 2, 3, 4, 4, 4, 5 e depois utilize a função count do \n", @@ -64,9 +63,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 5 - Crie um dicionário com 3 chaves e 3 valores e imprima na tela\n" @@ -75,9 +72,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 6 - Adicione mais uma ferramenta ao dicionário criado no exercício anterior e imprima na tela\n" @@ -86,9 +81,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 7 - Crie um arquivo chamado nomes.txt no diretório onde está este notebook, grave 5 nomes no arquivo e \n", @@ -98,9 +91,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 8 - Abra o arquivo criado no item anterior e leia o arquivo na tela.\n" @@ -109,9 +100,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 9 - Crie um dicionário vazio e imrpima na tela\n" @@ -120,15 +109,13 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 10 - Complelete o trecho de código abaixo criado com Pandas e use a função tail() para ler os últimos \n", "# elementos do dataset.\n", "import pandas as pd\n", - "file_name = \"http://www.ats.ucla.edu/stat/data/binary.csv\"\n", + "file_name = \"binary.csv\"\n", "df = pd.read_csv(file_name)" ] }, @@ -163,9 +150,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Listas.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Listas.ipynb" index ce551c4b..79e7d69f 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Listas.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Listas.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -31,9 +38,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -63,9 +68,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -95,9 +98,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -115,9 +116,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "lista3 = [12, 100, \"Universidade\"]" @@ -140,9 +139,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -167,9 +164,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -202,9 +197,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -232,9 +225,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "IndexError", @@ -268,9 +259,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -311,9 +300,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -346,9 +333,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -379,9 +364,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -412,9 +395,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -445,9 +426,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -478,9 +457,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -511,9 +488,7 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -544,9 +519,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -585,9 +558,7 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -619,9 +590,7 @@ { "cell_type": "code", "execution_count": 35, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -652,9 +621,7 @@ { "cell_type": "code", "execution_count": 37, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -685,9 +652,7 @@ { "cell_type": "code", "execution_count": 39, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -718,9 +683,7 @@ { "cell_type": "code", "execution_count": 41, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -751,9 +714,7 @@ { "cell_type": "code", "execution_count": 43, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -791,9 +752,7 @@ { "cell_type": "code", "execution_count": 45, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -824,9 +783,7 @@ { "cell_type": "code", "execution_count": 47, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -858,9 +815,7 @@ { "cell_type": "code", "execution_count": 49, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -899,9 +854,7 @@ { "cell_type": "code", "execution_count": 51, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -919,9 +872,7 @@ { "cell_type": "code", "execution_count": 52, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -946,9 +897,7 @@ { "cell_type": "code", "execution_count": 53, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -969,9 +918,7 @@ { "cell_type": "code", "execution_count": 54, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -992,9 +939,7 @@ { "cell_type": "code", "execution_count": 55, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1039,9 +984,7 @@ { "cell_type": "code", "execution_count": 58, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1072,9 +1015,7 @@ { "cell_type": "code", "execution_count": 60, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1094,9 +1035,7 @@ { "cell_type": "code", "execution_count": 61, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1128,9 +1067,7 @@ { "cell_type": "code", "execution_count": 63, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1147,9 +1084,7 @@ { "cell_type": "code", "execution_count": 64, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1180,9 +1115,7 @@ { "cell_type": "code", "execution_count": 66, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1213,9 +1146,7 @@ { "cell_type": "code", "execution_count": 68, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1270,9 +1201,7 @@ { "cell_type": "code", "execution_count": 72, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1325,9 +1254,7 @@ { "cell_type": "code", "execution_count": 76, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1347,9 +1274,7 @@ { "cell_type": "code", "execution_count": 77, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1369,9 +1294,7 @@ { "cell_type": "code", "execution_count": 78, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1390,9 +1313,7 @@ { "cell_type": "code", "execution_count": 79, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1419,9 +1340,7 @@ { "cell_type": "code", "execution_count": 80, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "ValueError", @@ -1442,9 +1361,7 @@ { "cell_type": "code", "execution_count": 81, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1464,9 +1381,7 @@ { "cell_type": "code", "execution_count": 82, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "cidades.insert(2, 110)" @@ -1475,9 +1390,7 @@ { "cell_type": "code", "execution_count": 83, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1509,9 +1422,7 @@ { "cell_type": "code", "execution_count": 85, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1543,9 +1454,7 @@ { "cell_type": "code", "execution_count": 87, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1577,9 +1486,7 @@ { "cell_type": "code", "execution_count": 89, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1611,9 +1518,7 @@ { "cell_type": "code", "execution_count": 91, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1648,9 +1553,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1662,9 +1567,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-N\303\272meros.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-N\303\272meros.ipynb" index d94bfcf3..e6434900 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-N\303\272meros.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-N\303\272meros.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -33,9 +40,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -56,9 +61,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -79,9 +82,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -102,9 +103,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -125,9 +124,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -148,9 +145,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -178,9 +173,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -200,9 +193,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -222,9 +213,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -252,9 +241,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -274,9 +261,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -296,9 +281,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -318,9 +301,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -341,9 +322,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -364,9 +343,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -386,9 +363,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -415,9 +390,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -437,9 +410,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -459,9 +430,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -488,9 +457,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -510,9 +477,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -532,9 +497,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -554,9 +517,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -583,9 +544,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -606,9 +565,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -629,9 +586,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -652,9 +607,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -675,9 +628,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -713,9 +664,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -727,9 +678,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Strings.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Strings.ipynb" index 18a93489..897b9d34 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Strings.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Strings.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -27,9 +34,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -50,9 +55,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -73,9 +76,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -96,9 +97,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -126,9 +125,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -145,9 +142,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -167,9 +162,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -206,9 +199,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -225,9 +216,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -248,9 +237,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -270,9 +257,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -299,9 +284,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -323,9 +306,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -346,9 +327,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -369,9 +348,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -391,9 +368,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -414,9 +389,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -444,9 +417,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -466,9 +437,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -488,9 +457,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -517,9 +484,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -539,9 +504,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -563,9 +526,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -597,9 +558,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -628,9 +587,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -657,9 +614,7 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -679,9 +634,7 @@ { "cell_type": "code", "execution_count": 30, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -702,9 +655,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -725,9 +676,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -766,9 +715,7 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -808,9 +755,7 @@ { "cell_type": "code", "execution_count": 35, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -830,9 +775,7 @@ { "cell_type": "code", "execution_count": 36, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -852,9 +795,7 @@ { "cell_type": "code", "execution_count": 37, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -874,9 +815,7 @@ { "cell_type": "code", "execution_count": 38, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -896,9 +835,7 @@ { "cell_type": "code", "execution_count": 39, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -918,9 +855,7 @@ { "cell_type": "code", "execution_count": 40, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -940,9 +875,7 @@ { "cell_type": "code", "execution_count": 41, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -962,9 +895,7 @@ { "cell_type": "code", "execution_count": 42, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -984,9 +915,7 @@ { "cell_type": "code", "execution_count": 43, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1006,9 +935,7 @@ { "cell_type": "code", "execution_count": 44, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1035,9 +962,7 @@ { "cell_type": "code", "execution_count": 45, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1054,9 +979,7 @@ { "cell_type": "code", "execution_count": 46, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1088,9 +1011,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1102,9 +1025,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Tuplas.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Tuplas.ipynb" index 1e4d6ff0..3f6b7bc8 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Tuplas.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Tuplas.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -31,9 +38,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -54,9 +59,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "AttributeError", @@ -78,9 +81,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -114,9 +115,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -147,9 +146,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -169,9 +166,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -192,9 +187,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -215,9 +208,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -237,9 +228,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -273,9 +262,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "NameError", @@ -308,9 +295,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -330,9 +315,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -366,9 +349,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -411,9 +392,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -448,9 +427,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -462,9 +441,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Vari\303\241veis.ipynb" "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Vari\303\241veis.ipynb" index 9895358a..34ce0c0d 100644 --- "a/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Vari\303\241veis.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo02/DSA-Python-Cap\303\255tulo2-Vari\303\241veis.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -31,9 +38,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -54,9 +59,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -74,9 +77,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "NameError", @@ -109,9 +110,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -131,9 +130,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -164,9 +161,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -197,9 +192,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -237,9 +230,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -259,9 +250,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -281,9 +270,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -314,9 +301,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -336,9 +321,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -376,9 +359,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -398,9 +379,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "SyntaxError", @@ -460,9 +439,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "SyntaxError", @@ -521,9 +498,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -554,9 +529,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -576,9 +549,7 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# A ordem dos operadores é a mesma seguida na Matemática\n", @@ -588,9 +559,7 @@ { "cell_type": "code", "execution_count": 30, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -639,9 +608,7 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -661,9 +628,7 @@ { "cell_type": "code", "execution_count": 34, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -683,9 +648,7 @@ { "cell_type": "code", "execution_count": 35, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -705,9 +668,7 @@ { "cell_type": "code", "execution_count": 36, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -727,9 +688,7 @@ { "cell_type": "code", "execution_count": 37, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -789,9 +748,7 @@ { "cell_type": "code", "execution_count": 41, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -826,9 +783,9 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [Root]", + "display_name": "Python 3", "language": "python", - "name": "Python [Root]" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -840,9 +797,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo02/binary.csv" "b/JupyterNotebooks/Cap\303\255tulo02/binary.csv" new file mode 100755 index 00000000..b2488b11 --- /dev/null +++ "b/JupyterNotebooks/Cap\303\255tulo02/binary.csv" @@ -0,0 +1,6 @@ +admit,gre,gpa,rank +0,380,3.61,3 +1,660,3.67,3 +1,880,4.00,1 +1,640,3.19,4 +0,520,2.93,4 diff --git "a/JupyterNotebooks/Cap\303\255tulo02/teste.txt" "b/JupyterNotebooks/Cap\303\255tulo02/teste.txt" new file mode 100644 index 00000000..674e65e6 --- /dev/null +++ "b/JupyterNotebooks/Cap\303\255tulo02/teste.txt" @@ -0,0 +1,2 @@ +Olá este arquivo foi gerado pelo próprio Jupyter Notebook. +Podemos gerar quantas linhas quisermos e o Jupyter gera o arquivo final. \ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" index 4265233e..288ddf1a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,16 +26,14 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite o dia da semana: Sábado\n", - "Hoje é dia de descanso\n" + "Digite o dia da semana: Segunda\n", + "Você precisa trabalhar!\n" ] } ], @@ -45,9 +50,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -68,9 +71,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -94,9 +95,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -140,9 +139,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -168,9 +165,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -216,9 +211,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -242,9 +235,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -263,15 +254,13 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Qual a temperatura? 35\n", + "Qual a temperatura? 34\n", "Vista roupas leves.\n" ] } @@ -288,9 +277,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -346,9 +333,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios.ipynb" index bf185807..ae1f4a38 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Exerc\303\255cios.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 1 - Crie uma estrutura que pergunte ao usuário qual o dia da semana. Se o dia for igual a Domingo ou \n", @@ -31,9 +36,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 2 - Crie uma lista de 5 frutas e verifique se a fruta 'Morango' faz parte da lista\n" @@ -42,9 +45,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 3 - Crie uma tupla de 4 elementos, multiplique cada elemento da tupla por 2 e guarde os resultados em uma \n", @@ -54,9 +55,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 4 - Crie uma sequência de números pares entre 100 e 150 e imprima na tela\n" @@ -65,9 +64,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 5 - Crie uma variável chamada temperatura e atribua o valor 40. Enquanto temperatura for maior que 35, \n", @@ -77,9 +74,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 6 - Crie uma variável chamada contador = 0. Enquanto counter for menor que 100, imprima os valores na tela,\n", @@ -89,9 +84,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 7 - Crie uma lista vazia e uma variável com valor 4. Enquanto o valor da variável for menor ou igual a 20, \n", @@ -101,9 +94,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 8 - Transforme o resultado desta função range em uma lista: range(5, 45, 2)\n" @@ -112,9 +103,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 9 - Faça a correção dos erros no código abaixo e execute o programa. Dica: são 3 erros.\n", @@ -128,9 +117,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 10 - Faça um programa que conte quantas vezes a letra \"a\" aparece na frase abaixo. Use um placeholder na \n", @@ -172,9 +159,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-For.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-For.ipynb" index 5e410751..2742ffb2 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-For.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-For.ipynb" @@ -10,6 +10,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -20,9 +27,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -44,9 +49,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -68,9 +71,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -93,9 +94,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -120,9 +119,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -191,9 +188,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -266,9 +261,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -311,10 +304,8 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -338,9 +329,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -362,9 +351,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -387,9 +374,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -413,9 +398,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -438,9 +421,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -462,9 +443,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -513,9 +492,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-If-Elif-Else.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-If-Elif-Else.ipynb" index 76b5cd27..6197946a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-If-Elif-Else.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-If-Elif-Else.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -41,9 +46,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -64,9 +67,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -86,9 +87,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -108,9 +107,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -130,9 +127,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -152,9 +147,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -172,9 +165,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -192,9 +183,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "SyntaxError", @@ -221,9 +210,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -242,9 +229,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -266,9 +251,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -288,9 +271,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -317,9 +298,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -340,9 +319,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -371,9 +348,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -393,9 +368,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -414,9 +387,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -443,18 +414,16 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Digite o nome da disciplina: Matemática\n", - "Digite a nota final (entre 0 e 100): 90\n", + "Digite a nota final (entre 0 e 100): 70\n", "Digite o semestre (1 a 4): 3\n", - "Você foi aprovado em Matemática com média final '90'!\n" + "Você foi aprovado em Matemática com média final '70'!\n" ] } ], @@ -509,9 +478,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Range.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Range.ipynb" index b97fd3c9..6a839943 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Range.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-Range.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -65,9 +70,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -87,9 +90,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -116,9 +117,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -141,9 +140,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -192,9 +189,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-While.ipynb" "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-While.ipynb" index 5e1ae173..be0a323c 100644 --- "a/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-While.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo03/DSA-Python-Cap\303\255tulo3-While.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -51,9 +56,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -106,9 +109,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -135,9 +136,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -168,9 +167,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -237,9 +234,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" index a3bd4f49..1f2a6fca 100644 --- "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -53,9 +58,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -78,9 +81,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -107,9 +108,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -139,9 +138,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -161,9 +158,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -191,14 +186,25 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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count400.000000400.000000400.000000400.000005.0000005.0000005.0000005.000000
mean0.317500587.7000003.3899002.485000.600000616.0000003.4800003.000000
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min0.000000220.0000002.2600001.00000380.0000002.9300001.000000
25%0.000000520.0000003.1300002.000003.1900003.000000
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" ], "text/plain": [ - " admit gre gpa rank\n", - "count 400.000000 400.000000 400.000000 400.00000\n", - "mean 0.317500 587.700000 3.389900 2.48500\n", - "std 0.466087 115.516536 0.380567 0.94446\n", - "min 0.000000 220.000000 2.260000 1.00000\n", - "25% 0.000000 520.000000 3.130000 2.00000\n", - "50% 0.000000 580.000000 3.395000 2.00000\n", - "75% 1.000000 660.000000 3.670000 3.00000\n", - "max 1.000000 800.000000 4.000000 4.00000" + " admit gre gpa rank\n", + "count 5.000000 5.000000 5.000000 5.000000\n", + "mean 0.600000 616.000000 3.480000 3.000000\n", + "std 0.547723 185.148589 0.421307 1.224745\n", + "min 0.000000 380.000000 2.930000 1.000000\n", + "25% 0.000000 520.000000 3.190000 3.000000\n", + "50% 1.000000 640.000000 3.610000 3.000000\n", + "75% 1.000000 660.000000 3.670000 4.000000\n", + "max 1.000000 880.000000 4.000000 4.000000" ] }, "execution_count": 7, @@ -290,9 +296,9 @@ "source": [ "# Exercício 7 - Crie uma função que receba o arquivo abaixo como argumento e retorne um resumo estatístico descritivo \n", "# do arquivo. Dica, use Pandas e um de seus métodos, describe()\n", - "# Arquivo: \"http://www.ats.ucla.edu/stat/data/binary.csv\"\n", + "# Arquivo: \"binary.csv\"\n", "import pandas as pd\n", - "file_name = \"http://www.ats.ucla.edu/stat/data/binary.csv\"\n", + "file_name = \"binary.csv\"\n", "\n", "def retornaArq(file_name):\n", " df = pd.read_csv(file_name)\n", @@ -332,9 +338,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios.ipynb" "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios.ipynb" index 68a63dec..8351243b 100644 --- "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Exerc\303\255cios.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "binary.csv" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 1 - Crie uma função que imprima a sequência de números pares entre 1 e 20 (a função não recebe parâmetro) e \n", @@ -32,9 +37,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 2 - Crie uam função que receba uma string como argumento e retorne a mesma string em letras maiúsculas.\n", @@ -44,9 +47,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 3 - Crie uma função que receba como parâmetro uma lista de 4 elementos, adicione 2 elementos a lista e \n", @@ -56,9 +57,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 4 - Crie uma função que receba um argumento formal e uma possível lista de elementos. Faça duas chamadas \n", @@ -68,9 +67,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 5 - Crie uma função anônima e atribua seu retorno a uma variável chamada soma. A expressão vai receber 2 \n", @@ -80,9 +77,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 6 - Execute o código abaixo e certifique-se que compreende a diferença entre variável global e local\n" @@ -91,14 +86,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 7 - Crie uma função que receba o arquivo abaixo como argumento e retorne um resumo estatístico descritivo \n", "# do arquivo. Dica, use Pandas e um de seus métodos, describe()\n", - "# Arquivo: \"http://www.ats.ucla.edu/stat/data/binary.csv\"\n", + "# Arquivo: \"binary.csv\"\n", " " ] }, @@ -133,9 +126,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Fun\303\247\303\265es.ipynb" "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Fun\303\247\303\265es.ipynb" index b7b8cd38..3af027a9 100644 --- "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Fun\303\247\303\265es.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Fun\303\247\303\265es.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -32,9 +39,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -64,9 +69,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -96,9 +99,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -133,9 +134,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -161,9 +160,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Variável Global\n", @@ -176,9 +173,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -195,9 +190,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -214,9 +207,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Variável Local\n", @@ -229,9 +220,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -248,9 +237,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "NameError", @@ -278,9 +265,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -300,9 +285,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -322,9 +305,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -344,9 +325,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -378,9 +357,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -401,9 +378,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -423,6 +398,7 @@ " '__gt__',\n", " '__hash__',\n", " '__init__',\n", + " '__init_subclass__',\n", " '__iter__',\n", " '__le__',\n", " '__len__',\n", @@ -499,9 +475,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -525,9 +499,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -559,26 +531,24 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite sua idade: 14\n" + "Digite sua idade: 78\n" ] }, { "ename": "TypeError", - "evalue": "unorderable types: str() > int()", + "evalue": "'>' not supported between instances of 'str' and 'int'", "output_type": "error", "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# Erro ao executar por causa da conversão\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0midade\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Digite sua idade: \"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0midade\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m13\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Você pode acessar o Facebook\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mTypeError\u001b[0m: unorderable types: str() > int()" + "\u001b[0;31mTypeError\u001b[0m: '>' not supported between instances of 'str' and 'int'" ] } ], @@ -592,15 +562,13 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite sua idade: 14\n", + "Digite sua idade: 78\n", "Você pode acessar o Facebook\n" ] } @@ -615,9 +583,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -637,9 +603,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -659,9 +623,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -681,9 +643,7 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -714,9 +674,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -736,9 +694,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -769,9 +725,7 @@ { "cell_type": "code", "execution_count": 34, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -791,9 +745,7 @@ { "cell_type": "code", "execution_count": 35, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -813,9 +765,7 @@ { "cell_type": "code", "execution_count": 36, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -846,9 +796,7 @@ { "cell_type": "code", "execution_count": 38, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -898,9 +846,7 @@ { "cell_type": "code", "execution_count": 40, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -951,9 +897,7 @@ { "cell_type": "code", "execution_count": 43, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -983,9 +927,7 @@ { "cell_type": "code", "execution_count": 45, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1049,9 +991,7 @@ { "cell_type": "code", "execution_count": 49, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1090,9 +1030,7 @@ { "cell_type": "code", "execution_count": 51, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1110,9 +1048,7 @@ { "cell_type": "code", "execution_count": 52, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1159,9 +1095,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Lambda.ipynb" "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Lambda.ipynb" index 42703f5a..e4ee37b6 100644 --- "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Lambda.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-Lambda.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -33,9 +40,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -68,9 +73,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -90,9 +93,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Definindo uma função - 1 linha de código\n", @@ -102,9 +103,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -124,9 +123,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -159,9 +156,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -181,9 +176,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -214,9 +207,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -247,9 +238,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -280,9 +269,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -330,9 +317,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-M\303\251todos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-M\303\251todos.ipynb" index 25628b2f..57eafe4a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-M\303\251todos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo04/DSA-Python-Cap\303\255tulo4-M\303\251todos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -43,9 +50,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -66,9 +71,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -89,9 +92,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -113,9 +114,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -137,6 +136,7 @@ " '__iadd__',\n", " '__imul__',\n", " '__init__',\n", + " '__init_subclass__',\n", " '__iter__',\n", " '__le__',\n", " '__len__',\n", @@ -191,9 +191,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -239,9 +237,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo04/binary.csv" "b/JupyterNotebooks/Cap\303\255tulo04/binary.csv" new file mode 100755 index 00000000..b2488b11 --- /dev/null +++ "b/JupyterNotebooks/Cap\303\255tulo04/binary.csv" @@ -0,0 +1,6 @@ +admit,gre,gpa,rank +0,380,3.61,3 +1,660,3.67,3 +1,880,4.00,1 +1,640,3.19,4 +0,520,2.93,4 diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Classes.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Classes.ipynb" index aeff6fb5..7097d3b0 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Classes.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Classes.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -57,9 +64,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -77,9 +82,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -100,9 +103,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -123,9 +124,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -143,9 +142,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando a classe Livro com parâmetros no método construtor\n", @@ -162,9 +159,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -182,9 +177,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -204,9 +197,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -239,9 +230,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -259,9 +248,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -279,9 +266,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -302,9 +287,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -353,9 +336,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" index 71b52067..ce498903 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios-Solu\303\247\303\243o.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -62,9 +67,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -107,9 +110,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -170,9 +171,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios.ipynb" index 7a4d31af..760afff4 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Exerc\303\255cios.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 1 - Crie um objeto a partir da classe abaixo, chamado roc1, passando 2 parâmetros e depois faça uma chamada\n", @@ -46,9 +51,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 2 - Crie uma classe chamada Pessoa() com os atributos: nome, cidade, telefone e e-mail. Use pelo menos 2\n", @@ -59,9 +62,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Exercício 3 - Crie a classe Smartphone com 2 atributos, tamanho e interface e crie a classe MP3Player com os \n", @@ -99,9 +100,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Heran\303\247a.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Heran\303\247a.ipynb" index e6ca7f84..49835fea 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Heran\303\247a.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Heran\303\247a.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -60,9 +67,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -81,9 +86,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -101,9 +104,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -121,9 +122,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -169,9 +168,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-MetodosEspeciais.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-MetodosEspeciais.ipynb" index 0e21be9c..770190ca 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-MetodosEspeciais.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-MetodosEspeciais.ipynb" @@ -7,6 +7,13 @@ "# Data Science Academy - Python Fundamentos - Capítulo 5" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -41,9 +48,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -60,9 +65,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -80,9 +83,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -102,9 +103,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -124,9 +123,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Ao executar a função del para remover um atributo, o Python executa:\n", @@ -137,9 +134,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -187,9 +182,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-M\303\251todos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-M\303\251todos.ipynb" index 8bae504c..9d06d01d 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-M\303\251todos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-M\303\251todos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -64,9 +71,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -87,9 +92,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -107,9 +110,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -127,9 +128,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Gerando um novo valor para o raio do círculo\n", @@ -139,9 +138,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -187,9 +184,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Objetos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Objetos.ipynb" index 66de4119..892cca02 100644 --- "a/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Objetos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo05/DSA-Python-Cap\303\255tulo5-Objetos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -26,9 +33,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma lista\n", @@ -38,9 +43,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -61,9 +64,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -89,9 +90,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -115,9 +114,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma classe\n", @@ -143,9 +140,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -166,9 +161,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -189,9 +182,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -212,9 +203,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma classe\n", @@ -242,9 +231,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -262,9 +249,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -281,9 +266,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -303,9 +286,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -336,9 +317,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -358,9 +337,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -391,9 +368,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -441,9 +416,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte1 - Criando um Banco de Dados SQLite.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte1 - Criando um Banco de Dados SQLite.ipynb" index 4c20b35c..7fff359e 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte1 - Criando um Banco de Dados SQLite.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte1 - Criando um Banco de Dados SQLite.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo de acesso ao SQLite\n", @@ -31,9 +36,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Cria uma conexão com o banco de dados. \n", @@ -44,9 +47,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -79,9 +80,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -101,9 +100,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Cria uma instrução sql\n", @@ -116,14 +113,12 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -151,9 +146,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Dados\n", @@ -165,9 +158,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Inserindo os registros\n", @@ -202,14 +193,12 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -225,9 +214,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Recupera os resultados\n", @@ -237,9 +224,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -263,9 +248,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Gerando outros registros\n", @@ -283,9 +266,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -359,9 +340,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte2 - Instru\303\247\303\243o Insert no SQLite.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte2 - Instru\303\247\303\243o Insert no SQLite.ipynb" index 3b0d8c6b..9198931b 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte2 - Instru\303\247\303\243o Insert no SQLite.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte2 - Instru\303\247\303\243o Insert no SQLite.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import sqlite3\n", @@ -60,9 +65,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Inserir dados\n", @@ -100,9 +103,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte3 - Instru\303\247\303\243o Insert no SQLite usando Vari\303\241veis.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte3 - Instru\303\247\303\243o Insert no SQLite usando Vari\303\241veis.ipynb" index 5f3380ee..4e205f05 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte3 - Instru\303\247\303\243o Insert no SQLite usando Vari\303\241veis.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte3 - Instru\303\247\303\243o Insert no SQLite usando Vari\303\241veis.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -60,9 +67,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Gerando valores e inserindo na tabela\n", @@ -115,9 +120,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte4 - Instru\303\247\303\243o Select no SQLite.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte4 - Instru\303\247\303\243o Select no SQLite.ipynb" index 904be036..cd848e8e 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte4 - Instru\303\247\303\243o Select no SQLite.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte4 - Instru\303\247\303\243o Select no SQLite.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -78,25 +85,23 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(10, '2016-05-02 14:32:11', 'Teclado', 90.0)\n", - "(11, '2016-05-23 14:13:21.779164', 'Monitor', 70.0)\n", - "(12, '2016-05-23 14:13:22.785889', 'Monitor', 60.0)\n", - "(13, '2016-05-23 14:13:23.791211', 'Monitor', 50.0)\n", - "(14, '2016-05-23 14:13:24.796350', 'Monitor', 92.0)\n", - "(15, '2016-05-23 14:13:25.802804', 'Monitor', 91.0)\n", - "(16, '2016-05-23 14:13:26.805365', 'Monitor', 62.0)\n", - "(17, '2016-05-23 14:13:27.810955', 'Monitor', 83.0)\n", - "(18, '2016-05-23 14:13:28.813340', 'Monitor', 82.0)\n", - "(19, '2016-05-23 14:13:29.819722', 'Monitor', 98.0)\n", - "(20, '2016-05-23 14:13:30.825445', 'Monitor', 71.0)\n" + "(11, '2017-06-06 13:53:13.750298', 'Monitor', 94.0)\n", + "(12, '2017-06-06 13:53:14.754985', 'Monitor', 64.0)\n", + "(13, '2017-06-06 13:53:15.763645', 'Monitor', 77.0)\n", + "(14, '2017-06-06 13:53:16.771173', 'Monitor', 94.0)\n", + "(15, '2017-06-06 13:53:17.778486', 'Monitor', 70.0)\n", + "(16, '2017-06-06 13:53:18.782498', 'Monitor', 65.0)\n", + "(17, '2017-06-06 13:53:19.794125', 'Monitor', 61.0)\n", + "(18, '2017-06-06 13:53:20.805552', 'Monitor', 61.0)\n", + "(19, '2017-06-06 13:53:21.817571', 'Monitor', 89.0)\n", + "(20, '2017-06-06 13:53:22.829989', 'Monitor', 73.0)\n" ] } ], @@ -108,23 +113,23 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(10, '2016-05-02 14:32:11', 'Teclado', 90.0)\n", - "(11, '2016-05-23 14:13:21.779164', 'Monitor', 70.0)\n", - "(14, '2016-05-23 14:13:24.796350', 'Monitor', 92.0)\n", - "(15, '2016-05-23 14:13:25.802804', 'Monitor', 91.0)\n", - "(16, '2016-05-23 14:13:26.805365', 'Monitor', 62.0)\n", - "(17, '2016-05-23 14:13:27.810955', 'Monitor', 83.0)\n", - "(18, '2016-05-23 14:13:28.813340', 'Monitor', 82.0)\n", - "(19, '2016-05-23 14:13:29.819722', 'Monitor', 98.0)\n", - "(20, '2016-05-23 14:13:30.825445', 'Monitor', 71.0)\n" + "(11, '2017-06-06 13:53:13.750298', 'Monitor', 94.0)\n", + "(12, '2017-06-06 13:53:14.754985', 'Monitor', 64.0)\n", + "(13, '2017-06-06 13:53:15.763645', 'Monitor', 77.0)\n", + "(14, '2017-06-06 13:53:16.771173', 'Monitor', 94.0)\n", + "(15, '2017-06-06 13:53:17.778486', 'Monitor', 70.0)\n", + "(16, '2017-06-06 13:53:18.782498', 'Monitor', 65.0)\n", + "(17, '2017-06-06 13:53:19.794125', 'Monitor', 61.0)\n", + "(18, '2017-06-06 13:53:20.805552', 'Monitor', 61.0)\n", + "(19, '2017-06-06 13:53:21.817571', 'Monitor', 89.0)\n", + "(20, '2017-06-06 13:53:22.829989', 'Monitor', 73.0)\n" ] } ], @@ -136,25 +141,23 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "90.0\n", + "94.0\n", + "64.0\n", + "77.0\n", + "94.0\n", "70.0\n", - "60.0\n", - "50.0\n", - "92.0\n", - "91.0\n", - "62.0\n", - "83.0\n", - "82.0\n", - "98.0\n", - "71.0\n" + "65.0\n", + "61.0\n", + "61.0\n", + "89.0\n", + "73.0\n" ] } ], @@ -207,9 +210,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte5 - Instru\303\247\303\265es Update e Delete no SQLite.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte5 - Instru\303\247\303\265es Update e Delete no SQLite.ipynb" index 63607ff5..014d615f 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte5 - Instru\303\247\303\265es Update e Delete no SQLite.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte5 - Instru\303\247\303\265es Update e Delete no SQLite.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -18,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": { "collapsed": true }, @@ -88,9 +95,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "atualiza_dados()" @@ -99,25 +104,23 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(10, '2016-05-02 14:32:11', 'Teclado', 90.0)\n", - "(11, '2016-05-23 14:13:21.779164', 'Monitor', 70.0)\n", - "(12, '2016-05-23 14:13:22.785889', 'Monitor', 60.0)\n", - "(13, '2016-05-23 14:13:23.791211', 'Monitor', 50.0)\n", - "(14, '2016-05-23 14:13:24.796350', 'Monitor', 92.0)\n", - "(15, '2016-05-23 14:13:25.802804', 'Monitor', 91.0)\n", - "(16, '2016-05-23 14:13:26.805365', 'Monitor', 62.0)\n", - "(17, '2016-05-23 14:13:27.810955', 'Monitor', 83.0)\n", - "(18, '2016-05-23 14:13:28.813340', 'Monitor', 82.0)\n", - "(19, '2016-05-23 14:13:29.819722', 'Monitor', 98.0)\n", - "(20, '2016-05-23 14:13:30.825445', 'Monitor', 71.0)\n" + "(11, '2017-06-06 13:53:13.750298', 'Monitor', 94.0)\n", + "(12, '2017-06-06 13:53:14.754985', 'Monitor', 64.0)\n", + "(13, '2017-06-06 13:53:15.763645', 'Monitor', 77.0)\n", + "(14, '2017-06-06 13:53:16.771173', 'Monitor', 94.0)\n", + "(15, '2017-06-06 13:53:17.778486', 'Monitor', 70.0)\n", + "(16, '2017-06-06 13:53:18.782498', 'Monitor', 65.0)\n", + "(17, '2017-06-06 13:53:19.794125', 'Monitor', 61.0)\n", + "(18, '2017-06-06 13:53:20.805552', 'Monitor', 61.0)\n", + "(19, '2017-06-06 13:53:21.817571', 'Monitor', 89.0)\n", + "(20, '2017-06-06 13:53:22.829989', 'Monitor', 73.0)\n" ] } ], @@ -127,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": { "collapsed": true }, @@ -138,25 +141,24 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(10, '2016-05-02 14:32:11', 'Teclado', 90.0)\n", - "(11, '2016-05-23 14:13:21.779164', 'Monitor', 70.0)\n", - "(13, '2016-05-23 14:13:23.791211', 'Monitor', 50.0)\n", - "(14, '2016-05-23 14:13:24.796350', 'Monitor', 92.0)\n", - "(15, '2016-05-23 14:13:25.802804', 'Monitor', 91.0)\n", - "(16, '2016-05-23 14:13:26.805365', 'Monitor', 62.0)\n", - "(17, '2016-05-23 14:13:27.810955', 'Monitor', 83.0)\n", - "(18, '2016-05-23 14:13:28.813340', 'Monitor', 82.0)\n", - "(19, '2016-05-23 14:13:29.819722', 'Monitor', 98.0)\n", - "(20, '2016-05-23 14:13:30.825445', 'Monitor', 71.0)\n" + "(11, '2017-06-06 13:53:13.750298', 'Monitor', 94.0)\n", + "(12, '2017-06-06 13:53:14.754985', 'Monitor', 64.0)\n", + "(13, '2017-06-06 13:53:15.763645', 'Monitor', 77.0)\n", + "(14, '2017-06-06 13:53:16.771173', 'Monitor', 94.0)\n", + "(15, '2017-06-06 13:53:17.778486', 'Monitor', 70.0)\n", + "(16, '2017-06-06 13:53:18.782498', 'Monitor', 65.0)\n", + "(17, '2017-06-06 13:53:19.794125', 'Monitor', 61.0)\n", + "(18, '2017-06-06 13:53:20.805552', 'Monitor', 61.0)\n", + "(19, '2017-06-06 13:53:21.817571', 'Monitor', 89.0)\n", + "(20, '2017-06-06 13:53:22.829989', 'Monitor', 73.0)\n" ] } ], @@ -195,9 +197,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte6 - Criando Gr\303\241ficos com Matplotlib e SQLite.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte6 - Criando Gr\303\241ficos com Matplotlib e SQLite.ipynb" index b8d7744e..30a94344 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte6 - Criando Gr\303\241ficos com Matplotlib e SQLite.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte6 - Criando Gr\303\241ficos com Matplotlib e SQLite.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import sqlite3\n", @@ -102,9 +107,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -112,6 +115,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -170,6 +174,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -239,6 +246,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -295,8 +311,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -429,10 +446,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -588,8 +605,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -710,6 +727,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -718,7 +736,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -729,8 +747,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -819,12 +838,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -873,7 +889,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -919,9 +935,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte7 - Criando um Banco de Dados no MongoDB.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte7 - Criando um Banco de Dados no MongoDB.ipynb" index ed38bdf6..999d4c85 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte7 - Criando um Banco de Dados no MongoDB.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte7 - Criando um Banco de Dados no MongoDB.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,24 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: pymongo in /Users/dmpm/anaconda/lib/python3.6/site-packages\r\n" + ] + } + ], + "source": [ + "!pip install pymongo" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "# Importamos o MongoClient para conectar nossa aplicação ao MongoDB\n", @@ -38,10 +60,8 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ "# Estabelecemos a conexão ao Banco de Dados\n", @@ -50,10 +70,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -61,7 +79,7 @@ "pymongo.mongo_client.MongoClient" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -72,7 +90,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "collapsed": true }, @@ -85,10 +103,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { @@ -96,7 +112,7 @@ "pymongo.database.Database" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -107,10 +123,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "# Uma coleção é um grupo de documentos armazenados no MongoDB \n", @@ -120,10 +134,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { @@ -131,7 +143,7 @@ "pymongo.collection.Collection" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -149,7 +161,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "collapsed": true }, @@ -167,10 +179,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [], "source": [ "post1 = {\"codigo\": \"ID-9987725\",\n", @@ -181,10 +191,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { @@ -192,7 +200,7 @@ "dict" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -203,7 +211,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { "collapsed": true }, @@ -214,10 +222,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": true - }, + "execution_count": 13, + "metadata": {}, "outputs": [], "source": [ "post_id = collection.insert_one(post1)" @@ -225,18 +231,16 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "ObjectId('5743893d90849967d4b272ad')" + "ObjectId('593717bcb093150d2b962e40')" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -247,18 +251,16 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -297,9 +299,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "post_id = collection.insert_one(post2).inserted_id" @@ -308,14 +308,12 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "ObjectId('5743898490849967d4b272ae')" + "ObjectId('593717bcb093150d2b962e41')" ] }, "execution_count": 19, @@ -330,16 +328,14 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'_id': ObjectId('5743898490849967d4b272ae'),\n", + "{'_id': ObjectId('593717bcb093150d2b962e41'),\n", " 'codigo': 'ID-2209876',\n", - " 'data_cadastro': datetime.datetime(2016, 5, 23, 22, 51, 45, 913000),\n", + " 'data_cadastro': datetime.datetime(2017, 6, 6, 20, 59, 40, 322000),\n", " 'marcas': ['samsung', 'panasonic', 'lg'],\n", " 'prod_name': 'Televisor'}" ] @@ -356,16 +352,14 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'_id': ObjectId('5743893d90849967d4b272ad'), 'prod_name': 'Geladeira', 'marcas': ['brastemp', 'consul', 'elecrolux'], 'data_cadastro': datetime.datetime(2016, 5, 23, 22, 49, 59, 563000), 'codigo': 'ID-9987725'}\n", - "{'_id': ObjectId('5743898490849967d4b272ae'), 'prod_name': 'Televisor', 'marcas': ['samsung', 'panasonic', 'lg'], 'data_cadastro': datetime.datetime(2016, 5, 23, 22, 51, 45, 913000), 'codigo': 'ID-2209876'}\n" + "{'_id': ObjectId('593717bcb093150d2b962e40'), 'codigo': 'ID-9987725', 'prod_name': 'Geladeira', 'marcas': ['brastemp', 'consul', 'elecrolux'], 'data_cadastro': datetime.datetime(2017, 6, 6, 20, 59, 40, 258000)}\n", + "{'_id': ObjectId('593717bcb093150d2b962e41'), 'codigo': 'ID-2209876', 'prod_name': 'Televisor', 'marcas': ['samsung', 'panasonic', 'lg'], 'data_cadastro': datetime.datetime(2017, 6, 6, 20, 59, 40, 322000)}\n" ] } ], @@ -378,9 +372,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -401,9 +393,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -452,9 +442,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte8 - Retornando Dados do MongoDB.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte8 - Retornando Dados do MongoDB.ipynb" index 4cc5b307..aa5c0b2a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte8 - Retornando Dados do MongoDB.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte8 - Retornando Dados do MongoDB.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importamos o Módulo PyMongo\n", @@ -31,9 +36,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando a conexão com o MongoDB (neste caso, conexão padrão)\n", @@ -43,14 +46,12 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['bigdatadb', 'cadastrodb', 'local', 'names', 'twitterdb']" + "['admin', 'cadastrodb', 'local']" ] }, "execution_count": 3, @@ -66,9 +67,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Definindo o objeto db\n", @@ -78,9 +77,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -101,9 +98,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -124,9 +119,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -147,14 +140,12 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -177,14 +168,12 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'_id': ObjectId('57438b38908499681e811f2f'),\n", + "{'_id': ObjectId('593717e4b093150d370361b9'),\n", " 'by': 'Data Science Academy',\n", " 'descricao': 'MongoDB é um Banco de Dados NoSQL',\n", " 'likes': 100,\n", @@ -206,9 +195,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Preparando um documento\n", @@ -218,14 +205,12 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 11, @@ -254,14 +239,12 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -277,17 +260,15 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'url': 'http://www.datascienceacademy.com.br', 'titulo': 'MongoDB com Python', '_id': ObjectId('57438b38908499681e811f2f'), 'descricao': 'MongoDB é um Banco de Dados NoSQL', 'likes': 100, 'by': 'Data Science Academy', 'tags': ['mongodb', 'database', 'NoSQL']}\n", - "{'twitter': '@barack', '_id': ObjectId('57438bb0908499681e811f30'), 'Nome': 'Barack', 'sobrenome': 'Obama'}\n", - "{'Site': 'http://www.datascienceacademy.com.br', '_id': ObjectId('57438bcb908499681e811f31'), 'facebook': 'facebook.com/dsacademybr'}\n" + "{'_id': ObjectId('593717e4b093150d370361b9'), 'titulo': 'MongoDB com Python', 'descricao': 'MongoDB é um Banco de Dados NoSQL', 'by': 'Data Science Academy', 'url': 'http://www.datascienceacademy.com.br', 'tags': ['mongodb', 'database', 'NoSQL'], 'likes': 100}\n", + "{'_id': ObjectId('593717e4b093150d370361ba'), 'Nome': 'Barack', 'sobrenome': 'Obama', 'twitter': '@barack'}\n", + "{'_id': ObjectId('593717e4b093150d370361bb'), 'Site': 'http://www.datascienceacademy.com.br', 'facebook': 'facebook.com/dsacademybr'}\n" ] } ], @@ -300,9 +281,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Conectando a uma coleção\n", @@ -312,9 +291,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -334,9 +311,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -357,9 +332,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Encontrando um único documento\n", @@ -369,14 +342,12 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'_id': ObjectId('57438b38908499681e811f2f'),\n", + "{'_id': ObjectId('593717e4b093150d370361b9'),\n", " 'by': 'Data Science Academy',\n", " 'descricao': 'MongoDB é um Banco de Dados NoSQL',\n", " 'likes': 100,\n", @@ -425,9 +396,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte9 - Stream de Dados do Twitter com MongoDB, Pandas e Scikit Learn.ipynb" "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte9 - Stream de Dados do Twitter com MongoDB, Pandas e Scikit Learn.ipynb" index 2f573c1d..139e5332 100644 --- "a/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte9 - Stream de Dados do Twitter com MongoDB, Pandas e Scikit Learn.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo06/Jupyter Notebook Parte9 - Stream de Dados do Twitter com MongoDB, Pandas e Scikit Learn.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -26,9 +33,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando os módulos Tweepy, Datetime e Json\n", @@ -97,9 +102,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando as chaves de autenticação\n", @@ -109,9 +112,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "auth.set_access_token(access_token, access_token_secret)" @@ -120,9 +121,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma classe para capturar os stream de dados do Twitter e \n", @@ -154,9 +153,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando o objeto mystream\n", @@ -166,9 +163,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando do PyMongo o módulo MongoClient\n", @@ -226,9 +221,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Iniciando o filtro e gravando os tweets no MongoDB\n", @@ -256,9 +249,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Verificando um documento no collection\n", @@ -268,9 +259,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# criando um dataset com dados retornados do MongoDB\n", @@ -294,9 +283,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando um dataframe a partir do dataset \n", @@ -306,9 +293,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Imprimindo o dataframe\n", @@ -318,9 +303,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo Scikit Learn\n", @@ -330,9 +313,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Usando o método CountVectorizer para criar uma matriz de documentos\n", @@ -343,9 +324,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Contando o número de ocorrências das principais palavras em nosso dataset\n", @@ -386,9 +365,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo06/dsa.db" "b/JupyterNotebooks/Cap\303\255tulo06/dsa.db" index 80f9332b..3e986fc0 100644 Binary files "a/JupyterNotebooks/Cap\303\255tulo06/dsa.db" and "b/JupyterNotebooks/Cap\303\255tulo06/dsa.db" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo06/escola.db" "b/JupyterNotebooks/Cap\303\255tulo06/escola.db" index 59e28251..43ca7c48 100644 Binary files "a/JupyterNotebooks/Cap\303\255tulo06/escola.db" and "b/JupyterNotebooks/Cap\303\255tulo06/escola.db" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Datetime.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Datetime.ipynb" index c34e3c4c..428838a8 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Datetime.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Datetime.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -20,9 +27,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import datetime" @@ -30,10 +35,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "agora = datetime.datetime.now()" @@ -41,18 +44,16 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 3, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "datetime.datetime(2016, 5, 30, 20, 16, 1, 751134)" + "datetime.datetime(2017, 6, 6, 14, 6, 15, 372215)" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -63,10 +64,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [], "source": [ "t = datetime.time(7, 43, 28)" @@ -74,10 +73,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -93,10 +90,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -118,10 +113,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -137,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": true }, @@ -148,20 +141,18 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "2016-05-30\n", - "ctime: Mon May 30 00:00:00 2016\n", - "Ano: 2016\n", - "Mês : 5\n", - "Dia : 30\n" + "2017-06-06\n", + "ctime: Tue Jun 6 00:00:00 2017\n", + "Ano: 2017\n", + "Mês : 6\n", + "Dia : 6\n" ] } ], @@ -175,10 +166,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -195,10 +184,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -215,10 +202,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { @@ -226,7 +211,7 @@ "datetime.timedelta(366)" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -267,9 +252,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Enumerate.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Enumerate.ipynb" index 7d5d792a..04096051 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Enumerate.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Enumerate.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma lista\n", @@ -31,14 +36,12 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -53,9 +56,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -75,9 +76,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -99,9 +98,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -134,9 +131,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -156,9 +151,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -192,9 +185,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -249,9 +240,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Erros-e-Exce\303\247\303\265es.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Erros-e-Exce\303\247\303\265es.ipynb" index d9b22cd2..09e72ae8 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Erros-e-Exce\303\247\303\265es.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Erros-e-Exce\303\247\303\265es.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "SyntaxError", @@ -54,9 +59,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -74,9 +77,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "ZeroDivisionError", @@ -106,9 +107,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -129,9 +128,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -152,9 +149,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -179,9 +174,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -205,9 +198,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -252,17 +243,15 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite um número: 2\n", + "Digite um número: 45\n", "Obrigado!\n", - "2\n" + "45\n" ] } ], @@ -292,34 +281,15 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite um número: q\n", - "Você não digitou um número!\n", - "Tente novamente. Digite um número: w\n", - "Obrigado!\n" - ] - }, - { - "ename": "ValueError", - "evalue": "invalid literal for int() with base 10: 'w'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36maskint\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Digite um número: \"\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 4\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'q'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mValueError\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[0maskint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m\u001b[0m in \u001b[0;36maskint\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Você não digitou um número!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Tente novamente. Digite um número: \"\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 7\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mprint\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Obrigado!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'w'" + "Digite um número: 23\n", + "Obrigado!\n", + "23\n" ] } ], @@ -353,24 +323,13 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Digite um número: q\n", - "Você não digitou um número!\n", - "Fim da execução!\n", - "Digite um número: w\n", - "Você não digitou um número!\n", - "Fim da execução!\n", - "Digite um número: r\n", - "Você não digitou um número!\n", - "Fim da execução!\n", - "Digite um número: 4\n", + "Digite um número: 90\n", "Obrigado por digitar um número!\n", "Fim da execução!\n" ] @@ -383,9 +342,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -413,7 +370,7 @@ "source": [ "Uma lista completa de exceções em Python, pode ser encontrada aqui:\n", "\n", - "https://docs.python.org/3.5/library/exceptions.html\n" + "https://docs.python.org/3.6/library/exceptions.html\n" ] }, { @@ -447,9 +404,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Filter.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Filter.ipynb" index 0b5a4f37..8e963d2f 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Filter.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Filter.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -20,7 +27,7 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -35,9 +42,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -60,7 +65,7 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -70,9 +75,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -92,14 +95,12 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -114,9 +115,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -136,9 +135,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -158,9 +155,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -208,9 +203,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-List Comprehensions.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-List Comprehensions.ipynb" index f5e2f82b..61e9132e 100755 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-List Comprehensions.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-List Comprehensions.ipynb" @@ -11,6 +11,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -33,9 +40,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -56,9 +61,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -90,9 +93,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -124,9 +125,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -146,9 +145,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -173,9 +170,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Operações aninhadas\n", @@ -185,9 +180,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -235,9 +228,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Manipula\303\247\303\243o de Arquivos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Manipula\303\247\303\243o de Arquivos.ipynb" index 5ff7e898..1c889f79 100755 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Manipula\303\247\303\243o de Arquivos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Manipula\303\247\303\243o de Arquivos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -39,9 +46,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "texto = \"Cientista de Dados é a profissão que mais tem crescido ultimamente.\\n\"\n", @@ -52,9 +57,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -73,9 +76,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo os\n", @@ -85,9 +86,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando um arquivo (no mesmo diretório onde está o Jupyter Notebook)\n", @@ -97,9 +96,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Gravando os dados no arquivo\n", @@ -110,9 +107,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Fechando o arquivo\n", @@ -122,9 +117,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -141,9 +134,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -178,9 +169,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "with open('cientista.txt','r') as arquivo:\n", @@ -190,9 +179,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -209,9 +196,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -228,9 +213,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "with open('cientista.txt','w') as arquivo:\n", @@ -242,9 +225,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -273,9 +254,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo csv\n", @@ -285,9 +264,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "with open('numeros.csv','w') as arquivo:\n", @@ -300,9 +277,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -324,9 +299,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -353,9 +326,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -378,9 +349,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -412,9 +381,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando um dicionário\n", @@ -427,17 +394,15 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "similar ['c', 'Modula-3', 'lisp']\n", "nome Guido van Rossum\n", "linguagem Python\n", + "similar ['c', 'Modula-3', 'lisp']\n", "users 1000000\n" ] } @@ -450,9 +415,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo Json\n", @@ -462,14 +425,12 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'{\"similar\": [\"c\", \"Modula-3\", \"lisp\"], \"nome\": \"Guido van Rossum\", \"linguagem\": \"Python\", \"users\": 1000000}'" + "'{\"nome\": \"Guido van Rossum\", \"linguagem\": \"Python\", \"similar\": [\"c\", \"Modula-3\", \"lisp\"], \"users\": 1000000}'" ] }, "execution_count": 23, @@ -485,9 +446,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando um arquivo Json\n", @@ -498,9 +457,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Leitura de arquivos Json\n", @@ -512,15 +469,13 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'similar': ['c', 'Modula-3', 'lisp'], 'nome': 'Guido van Rossum', 'linguagem': 'Python', 'users': 1000000}\n" + "{'nome': 'Guido van Rossum', 'linguagem': 'Python', 'similar': ['c', 'Modula-3', 'lisp'], 'users': 1000000}\n" ] } ], @@ -531,9 +486,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -550,9 +503,7 @@ { "cell_type": "code", "execution_count": 28, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Imprimindo um arquivo Json copiado da internet\n", @@ -565,18 +516,16 @@ { "cell_type": "code", "execution_count": 29, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Título: The Good Man trailer\n", - "URL: http://vimeo.com/57733101\n", + "URL: https://vimeo.com/57733101\n", "Duração: 143\n", - "Número de Visualizações: 5206\n" + "Número de Visualizações: 5382\n" ] } ], @@ -605,9 +554,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Método 1\n", @@ -620,9 +567,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -643,15 +588,13 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{\"similar\": [\"c\", \"Modula-3\", \"lisp\"], \"nome\": \"Guido van Rossum\", \"linguagem\": \"Python\", \"users\": 1000000}" + "{\"nome\": \"Guido van Rossum\", \"linguagem\": \"Python\", \"similar\": [\"c\", \"Modula-3\", \"lisp\"], \"users\": 1000000}" ] } ], @@ -697,9 +640,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Map.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Map.ipynb" index 7ac0d66d..6de5c899 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Map.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Map.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando duas funções\n", @@ -52,14 +57,12 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -76,9 +79,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -99,9 +100,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -123,14 +122,12 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -146,9 +143,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -168,14 +163,12 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -191,9 +184,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -213,9 +204,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Somando os elementos de 2 listas\n", @@ -226,9 +215,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -248,9 +235,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Somando os elementos de 3 listas\n", @@ -262,9 +247,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -312,9 +295,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-M\303\263dulos e Pacotes.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-M\303\263dulos e Pacotes.ipynb" old mode 100644 new mode 100755 index 3b8d1a99..66adc3b3 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-M\303\263dulos e Pacotes.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-M\303\263dulos e Pacotes.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -21,9 +28,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando um módulo em Python\n", @@ -33,9 +38,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -109,9 +112,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -132,9 +133,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando apenas um dos métodos do módulo math\n", @@ -144,9 +143,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -167,9 +164,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -187,9 +182,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -224,9 +217,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -246,9 +237,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -268,9 +257,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import statistics" @@ -290,9 +277,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -312,9 +297,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -345,9 +328,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -367,9 +348,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -397,9 +376,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -416,9 +393,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -438,9 +413,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -457,9 +430,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo request do pacote urllib, usado para trazer url's \n", @@ -483,9 +454,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -516,9 +485,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -536,9 +503,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -607,9 +572,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -708,9 +671,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "df = pd.DataFrame(petrobras)" @@ -719,9 +680,7 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1413,9 +1372,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Debugger.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Debugger.ipynb" index e3754872..bd31d9f0 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Debugger.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Debugger.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "a = [4,5,6]\n", @@ -32,9 +37,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -52,9 +55,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "ename": "TypeError", @@ -76,9 +77,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import pdb" @@ -87,9 +86,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -99,9 +96,13 @@ "--Return--\n", "> (8)()->None\n", "-> pdb.set_trace()\n", + "(Pdb) \n", "(Pdb) a + b\n", - "(Pdb) [4,5,6] + 2\n", - "*** TypeError: can only concatenate list (not \"int\") to list\n" + "(Pdb) resultado2 = a + b\n", + "*** TypeError: can only concatenate list (not \"int\") to list\n", + "(Pdb) print (resultado2)\n", + "*** NameError: name 'resultado2' is not defined\n", + "--KeyboardInterrupt--\n" ] } ], @@ -150,9 +151,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Express\303\265es-Regulares.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Express\303\265es-Regulares.ipynb" index da2bef6d..f87fa049 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Express\303\265es-Regulares.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Python-Express\303\265es-Regulares.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -23,9 +30,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo re (regular expression)\n", @@ -65,9 +70,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -135,9 +138,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -174,9 +175,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "frase_padrao = 'zLzL..zzzLLL...zLLLzLLL...LzLz...dzzzzz...zLLLL'\n", @@ -192,9 +191,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -229,10 +226,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [], "source": [ "frase = 'Esta é uma string com pontuação. Isso pode ser um problema quando fazemos mineração de dados em busca '\\\n", @@ -241,10 +236,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { @@ -282,7 +275,7 @@ " 'frase']" ] }, - "execution_count": 14, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -297,10 +290,8 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [], "source": [ "frase = 'Esta é uma frase de exemplo. Vamos verificar quais padrões serão encontrados.'\n", @@ -313,10 +304,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -393,10 +382,8 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { @@ -404,7 +391,7 @@ "'\\\\b'" ] }, - "execution_count": 17, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -418,10 +405,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { @@ -429,7 +414,7 @@ "'\\x08'" ] }, - "execution_count": 18, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -440,10 +425,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [], "source": [ "frase = 'Esta é uma string com alguns números, como 1287 e um símbolo #hashtag'\n", @@ -459,10 +442,8 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -530,9 +511,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Reduce.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Reduce.ipynb" index 259fb2d7..46ed6acc 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Reduce.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Reduce.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Importando a função reduce do módulo functools\n", @@ -43,9 +48,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -65,9 +68,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Função \n", @@ -79,9 +80,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -103,9 +102,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -121,15 +118,13 @@ ], "source": [ "from IPython.display import Image\n", - "Image('http://github.com/dsacademybr/PythonFundamentos/tree/master/JupyterNotebooks/Cap%C3%ADtulo07/reduce.png')" + "Image('reduce.png')" ] }, { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma lista\n", @@ -139,9 +134,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -174,9 +167,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -196,9 +187,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -248,9 +237,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Zip.ipynb" "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Zip.ipynb" index acdd666a..7637375c 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Zip.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo07/DSA-Python-Cap\303\255tulo7-Zip.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -19,9 +26,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando duas listas\n", @@ -32,14 +37,12 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -55,9 +58,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -78,9 +79,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -101,9 +100,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando duas listas\n", @@ -114,9 +111,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -136,9 +131,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando 2 dicionários\n", @@ -149,14 +142,12 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[('a', 'd'), ('b', 'c')]" + "[('a', 'c'), ('b', 'd')]" ] }, "execution_count": 8, @@ -172,14 +163,12 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[('a', 5), ('b', 4)]" + "[('a', 4), ('b', 5)]" ] }, "execution_count": 9, @@ -195,9 +184,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Criando uma função para trocar valores entre 2 dicionários\n", @@ -213,14 +200,12 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'a': 5, 'b': 4}" + "{'a': 4, 'b': 5}" ] }, "execution_count": 11, @@ -263,9 +248,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo07/dados.json" "b/JupyterNotebooks/Cap\303\255tulo07/dados.json" index b20dc428..6191d72f 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/dados.json" +++ "b/JupyterNotebooks/Cap\303\255tulo07/dados.json" @@ -1 +1 @@ -{"similar": ["c", "Modula-3", "lisp"], "nome": "Guido van Rossum", "linguagem": "Python", "users": 1000000} \ No newline at end of file +{"nome": "Guido van Rossum", "linguagem": "Python", "similar": ["c", "Modula-3", "lisp"], "users": 1000000} \ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo07/json_data.txt" "b/JupyterNotebooks/Cap\303\255tulo07/json_data.txt" index b20dc428..6191d72f 100644 --- "a/JupyterNotebooks/Cap\303\255tulo07/json_data.txt" +++ "b/JupyterNotebooks/Cap\303\255tulo07/json_data.txt" @@ -1 +1 @@ -{"similar": ["c", "Modula-3", "lisp"], "nome": "Guido van Rossum", "linguagem": "Python", "users": 1000000} \ No newline at end of file +{"nome": "Guido van Rossum", "linguagem": "Python", "similar": ["c", "Modula-3", "lisp"], "users": 1000000} \ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Chart-Interativo.html" "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Chart-Interativo.html" index 386e4035..48639efb 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Chart-Interativo.html" +++ "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Chart-Interativo.html" @@ -5,24 +5,44 @@ Bokeh Plot - + - + + -
+
+
+
\ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-GeoJSON.html" "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-GeoJSON.html" index 22f49f4d..0f33ba6a 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-GeoJSON.html" +++ "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-GeoJSON.html" @@ -5,24 +5,44 @@ Bokeh Plot - + - + + -
+
+
+
\ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Interativo.html" "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Interativo.html" index c8142c86..0e39bbb0 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Interativo.html" +++ "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Interativo.html" @@ -5,24 +5,44 @@ Bokeh Plot - + - + + -
+
+
+
\ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Linha.html" "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Linha.html" index 4f46e53d..6200c91e 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Linha.html" +++ "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-Grafico-Linha.html" @@ -5,24 +5,44 @@ Bokeh Plot - + - + + -
+
+
+
\ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-ViolinPlot.html" "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-ViolinPlot.html" index 6cb60de2..321eb5e4 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/Bokeh-ViolinPlot.html" +++ "b/JupyterNotebooks/Cap\303\255tulo08/Bokeh-ViolinPlot.html" @@ -5,24 +5,44 @@ Bokeh Plot - + - + + -
+
+
+
\ No newline at end of file diff --git "a/JupyterNotebooks/Cap\303\255tulo08/Continentes.png" "b/JupyterNotebooks/Cap\303\255tulo08/Continentes.png" new file mode 100644 index 00000000..7a833127 Binary files /dev/null and "b/JupyterNotebooks/Cap\303\255tulo08/Continentes.png" differ diff --git "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Bokeh.ipynb" "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Bokeh.ipynb" index 4c83423f..d7606f88 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Bokeh.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Bokeh.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -20,16 +27,30 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Caso o Bokeh não esteja instalado, executar:\n", - "### pip install bokeh" + "### Caso o Bokeh não esteja instalado, executar:" ] }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already up-to-date: bokeh in /Users/dmpm/anaconda/lib/python3.6/site-packages\r\n" + ] + } + ], + "source": [ + "!pip install bokeh -U" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "# Importando o módulo Bokeh\n", @@ -38,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { "collapsed": true }, @@ -53,18 +74,16 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", - "
\n", + "
\n", " \n", - " Loading BokehJS ...\n", + " Loading BokehJS ...\n", "
" ] }, @@ -80,8 +99,43 @@ " return new Date();\n", " }\n", "\n", - " if (typeof (window._bokeh_onload_callbacks) === \"undefined\") {\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", + " }\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", + " }\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", + " if (window.Bokeh !== undefined) {\n", + " var el = document.getElementById(\"e21d08f3-beae-47a1-835b-ad2a75b6daa6\");\n", + " el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n", + " } else if (Date.now() < window._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", " }\n", "\n", " function run_callbacks() {\n", @@ -120,9 +174,13 @@ " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", - " };\n", + " };var element = document.getElementById(\"e21d08f3-beae-47a1-835b-ad2a75b6daa6\");\n", + " if (element == null) {\n", + " console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e21d08f3-beae-47a1-835b-ad2a75b6daa6' but no matching script tag was found. \")\n", + " return false;\n", + " }\n", "\n", - " var js_urls = ['https://cdn.pydata.org/bokeh/release/bokeh-0.11.1.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.11.1.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-compiler-0.11.1.min.js'];\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", "\n", " var inline_js = [\n", " function(Bokeh) {\n", @@ -130,20 +188,38 @@ " },\n", " \n", " function(Bokeh) {\n", - " Bokeh.$(\"#6cb2911e-4ab9-4f80-b50e-01c5c7f2b681\").text(\"BokehJS successfully loaded\");\n", + " \n", + " },\n", + " \n", + " function(Bokeh) {\n", + " \n", + " document.getElementById(\"e21d08f3-beae-47a1-835b-ad2a75b6daa6\").textContent = \"BokehJS is loading...\";\n", " },\n", " function(Bokeh) {\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.11.1.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.11.1.min.css\");\n", - " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.11.1.min.css\");\n", - " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.11.1.min.css\");\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", " }\n", " ];\n", "\n", " function run_inline_js() {\n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i](window.Bokeh);\n", + " \n", + " if ((window.Bokeh !== undefined) || (force === true)) {\n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i](window.Bokeh);\n", + " }if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < window._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!window._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " window._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"e21d08f3-beae-47a1-835b-ad2a75b6daa6\")).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", @@ -169,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "collapsed": true }, @@ -181,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { "collapsed": true }, @@ -192,10 +268,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { @@ -203,7 +277,7 @@ "bokeh.plotting.figure.Figure" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -214,18 +288,34 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
GlyphRenderer(
id = 'cb0a08a0-b90f-4790-b3d4-ecbb2015b91c', …)
data_source = ColumnDataSource(id='fda763da-444a-493b-9abc-e1338e09c2b4', ...),
glyph = Line(id='b1b71af8-127b-40b3-bd91-c5599b3719ad', ...),
hover_glyph = None,
js_event_callbacks = {},
js_property_callbacks = {},
level = 'glyph',
muted = False,
muted_glyph = None,
name = None,
nonselection_glyph = Line(id='28de3558-e1fb-4a88-9d40-2f52c9265d0b', ...),
selection_glyph = None,
subscribed_events = [],
tags = [],
visible = True,
x_range_name = 'default',
y_range_name = 'default')
\n", + "\n" + ], "text/plain": [ - "" + "GlyphRenderer(id='cb0a08a0-b90f-4790-b3d4-ecbb2015b91c', ...)" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -236,17 +326,17 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", - "
\n", + "
\n", + "
\n", + "
\n", "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

<Bokeh Notebook handle for In[18]>

" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Plots de Séries Temporais com Pandas\n", "import pandas as pd\n", @@ -1310,9 +1596,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Google Maps\n", @@ -1373,9 +1657,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Mapas.ipynb" "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Mapas.ipynb" index 213da98e..c093a5de 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Mapas.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Mapas.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -35,7 +42,7 @@ "metadata": {}, "source": [ "### 1- Acessar o site http://www.lfd.uci.edu/~gohlke/pythonlibs/\n", - "### 2- Baixar o arquivo basemap-1.0.8-cp35-none-win_amd64.whl\n", + "### 2- Baixar o arquivo basemap‑1.1.0‑cp36‑cp36m‑win_amd64.whl\n", "### 3- Colocar o arquivo no diretório de instalação do Anaconda\n", "### 4- No prompt de comando, nevegar até o diretório de instalação do Anaconda e executar\n", "### 5- pip install basemap-1.0.8-cp35-none-win_amd64.whl" @@ -45,15 +52,30 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Usuários Mac e Linux, executar: pip install basemap" + "### Usuários Mac e Linux, executar:" ] }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: basemap in /Users/dmpm/anaconda/lib/python3.6/site-packages\r\n" + ] + } + ], + "source": [ + "!pip install basemap" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "from mpl_toolkits.basemap import Basemap\n", @@ -63,13 +85,24 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true - }, - "outputs": [], + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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gISFV9kR36IhccFuSYN06HBf/gfLcOTIvR2CnVuHiqCU+KQWNqwvuKujgXYnQ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\nRK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Mapa do globo terrestre\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", "map = Basemap(projection = 'ortho', lat_0 = 0, lon_0 = 0)\n", "\n", "# Definindo a cor do globo\n", @@ -86,11 +119,20 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, - "outputs": [], + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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boKOjAxsbG+zatQuPHz9GVlYWsrOzObVilRDISUlJ0NTU5G5o8uTJhX7ZX79+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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Mapa do globo terrestre expandido\n", "from mpl_toolkits.basemap import Basemap\n", @@ -107,11 +149,20 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, - "outputs": [], + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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6eK6/fvmgvg1DEIsZaYE5Q2VYS2Ly5FJuvvn8k44X4PDhMD6fPS2c+nivimnT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\ngIAZwv8CiWCsy+KkB7AAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Cria um mapa usando Basemap\n", "from mpl_toolkits.basemap import Basemap\n", @@ -147,11 +198,20 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, - "outputs": [], + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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fenOsKiIaVfE2jcoH0btlbLvdaBqdDE/YzcrNXUSFkjhjksSph8oIZB7e1cpy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JUYPbWECeF63HIciyIN+BshQUOPoKNb1PGmLKOPhJBqDuDLzKVcymKG5OOMeDdnxruZ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\nhBshQg/k/wHbRScUPsAttgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Plot contour\n", "from mpl_toolkits.basemap import Basemap\n", @@ -194,10 +254,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": true - }, + "execution_count": null, + "metadata": {}, "outputs": [], "source": [ "# Mapas dia e noite\n", @@ -231,7 +289,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": { "collapsed": true }, @@ -272,9 +330,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Plots-e-Graficos.ipynb" "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Plots-e-Graficos.ipynb" index a563b146..7dc0e1e0 100644 --- "a/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Plots-e-Graficos.ipynb" +++ "b/JupyterNotebooks/Cap\303\255tulo08/DSA-Python-Cap\303\255tulo8-Matplotlib-Plots-e-Graficos.ipynb" @@ -9,6 +9,13 @@ "## Download: http://github.com/dsacademybr" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "****** Este Jupyter Notebook foi atualizado para a versão 3.6.1 da Linguagem Python em 05/06/2017 ******" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -42,15 +49,13 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -88,15 +93,13 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -126,15 +129,13 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -205,15 +204,13 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -397,15 +386,13 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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8yVpUNbv8kpISBg0a1GjnzJeCL0QDNGzYsNjFXimO05roiRE+Bj4yBjMh6qRs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\n1tC+PVx0USgQXrrwRs81pJNev8mJJi2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QgK9TU8kJMV6kHJMZQ/Ruz9Y8r6nwYzZSfzMWwNgSE8PWm24ivKiI+7t08Wg/ixYtYu/e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\n+/37DW06PJxJgwc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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -440,15 +427,13 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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i3Bjo3P3UdVCedJNgK73Lo96ZjOYAS3CTpUVFILPcMMwLwO/TIDtg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\nAElFTkSuQmCC\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -487,15 +472,13 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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UxvjDwYPwxBMwb56VIkzIsxKFMb52phRRuLCVIkxYsBKFMb5ipQgT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\nJQpjjDG5skRhjDEmV/8PHq4MHQ++4S0AAAAASUVORK5CYII=\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -562,15 +543,13 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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IEX7BrsSGmlSErF/vN1zedlt44QXYeuvQiaSKtE4qyvr2hauvhldfVYMSSdXy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\nU2T5AAAAAElFTkSuQmCC\n", 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22MPv5P/pp/774cOhYcPQ0UkK6B7U+qqshHHjoE8fePllv3feBRf4j+23Dx2d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\nA+iBPX955TlhAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -599,7 +578,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 28, "metadata": { "collapsed": true }, @@ -612,10 +591,8 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, + "execution_count": 29, + "metadata": {}, "outputs": [ { "data": { @@ -623,6 +600,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -681,6 +659,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -750,6 +731,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -806,8 +796,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -940,10 +931,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -1099,8 +1090,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -1221,6 +1212,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -1229,7 +1221,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -1240,8 +1232,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -1330,12 +1323,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -1384,7 +1374,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -1392,26 +1382,14 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "plt.scatter(np.arange(50), np.random.randn(50))\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": { - "collapsed": false - }, - "outputs": [ + }, { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -1470,6 +1448,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -1539,6 +1520,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -1595,8 +1585,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -1729,10 +1720,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -1888,8 +1879,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -2010,6 +2001,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -2018,7 +2010,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -2029,8 +2021,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -2119,12 +2112,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -2173,7 +2163,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -2184,23 +2174,14 @@ } ], "source": [ - "# Plot e Scatter\n", - "fig = plt.figure()\n", - "\n", - "ax1 = fig.add_subplot(1,2,1)\n", - "ax1.plot(np.random.randn(50), color='red')\n", - "\n", - "ax2 = fig.add_subplot(1,2,2)\n", - "ax2.scatter(np.arange(50), np.random.randn(50))\n", + "plt.scatter(np.arange(50), np.random.randn(50))\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "data": { @@ -2208,6 +2189,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -2266,6 +2248,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -2335,6 +2320,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -2391,8 +2385,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -2525,10 +2520,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -2684,8 +2679,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -2806,6 +2801,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -2814,7 +2810,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -2825,8 +2821,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -2915,12 +2912,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -2969,7 +2963,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -2977,31 +2971,14 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "# Plots diversos\n", - "_, ax = plt.subplots(2,3)\n", - "\n", - "ax[0,1].plot(np.random.randn(50), color = 'green', linestyle = '-')\n", - "ax[1,0].hist(np.random.randn(50))\n", - "ax[1,2].scatter(np.arange(50), np.random.randn(50), color = 'red')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, - "outputs": [ + }, { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -3060,6 +3037,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -3129,6 +3109,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -3185,8 +3174,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -3319,10 +3309,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -3478,8 +3468,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -3600,6 +3590,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -3608,7 +3599,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -3619,8 +3610,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -3709,12 +3701,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -3763,7 +3752,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -3774,28 +3763,21 @@ } ], "source": [ - "# Controle dos eixos\n", - "fig, axes = plt.subplots(1, 3, figsize = (12, 4))\n", - "\n", - "axes[0].plot(x, x**2, x, x**3)\n", - "axes[0].set_title(\"Eixos com range padrão\")\n", + "# Plot e Scatter\n", + "fig = plt.figure()\n", "\n", - "axes[1].plot(x, x**2, x, x**3)\n", - "axes[1].axis('tight')\n", - "axes[1].set_title(\"Eixos menores\")\n", + "ax1 = fig.add_subplot(1,2,1)\n", + "ax1.plot(np.random.randn(50), color='red')\n", "\n", - "axes[2].plot(x, x**2, x, x**3)\n", - "axes[2].set_ylim([0, 60])\n", - "axes[2].set_xlim([2, 5])\n", - "axes[2].set_title(\"Eixos customizados\");" + "ax2 = fig.add_subplot(1,2,2)\n", + "ax2.scatter(np.arange(50), np.random.randn(50))\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 31, + "metadata": {}, "outputs": [ { "data": { @@ -3803,6 +3785,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -3861,6 +3844,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -3930,6 +3916,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -3986,8 +3981,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -4120,10 +4116,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -4279,8 +4275,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -4401,6 +4397,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -4409,7 +4406,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -4420,8 +4417,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -4510,12 +4508,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -4564,7 +4559,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -4572,33 +4567,14 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "# Escala\n", - "fig, axes = plt.subplots(1, 2, figsize=(10,4))\n", - " \n", - "axes[0].plot(x, x**2, x, exp(x))\n", - "axes[0].set_title(\"Escala Padrão\")\n", - "\n", - "axes[1].plot(x, x**2, x, exp(x))\n", - "axes[1].set_yscale(\"log\")\n", - "axes[1].set_title(\"Escala Logaritmica (y)\");" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "collapsed": false - }, - "outputs": [ + }, { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -4657,6 +4633,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -4726,6 +4705,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -4782,8 +4770,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -4916,10 +4905,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -5075,8 +5064,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -5197,6 +5186,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -5205,7 +5195,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -5216,8 +5206,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -5306,12 +5297,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -5360,7 +5348,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -5371,24 +5359,19 @@ } ], "source": [ - "# Grid\n", - "fig, axes = plt.subplots(1, 2, figsize=(10,3))\n", - "\n", - "# Grid padrão\n", - "axes[0].plot(x, x**2, x, x**3, lw = 2)\n", - "axes[0].grid(True)\n", + "# Plots diversos\n", + "_, ax = plt.subplots(2,3)\n", "\n", - "# Grid customizado\n", - "axes[1].plot(x, x**2, x, x**3, lw = 2)\n", - "axes[1].grid(color = 'b', alpha = 0.5, linestyle = 'dashed', linewidth = 0.5)" + "ax[0,1].plot(np.random.randn(50), color = 'green', linestyle = '-')\n", + "ax[1,0].hist(np.random.randn(50))\n", + "ax[1,2].scatter(np.arange(50), np.random.randn(50), color = 'red')\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, + "execution_count": 32, + "metadata": {}, "outputs": [ { "data": { @@ -5396,6 +5379,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -5454,6 +5438,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -5523,6 +5510,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -5579,8 +5575,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -5713,10 +5710,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -5872,8 +5869,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -5994,6 +5991,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -6002,7 +6000,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -6013,8 +6011,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -6103,12 +6102,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -6157,7 +6153,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -6165,37 +6161,14 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "# Gráfico de Linhas Gêmeas\n", - "fig, ax1 = plt.subplots()\n", - "\n", - "ax1.plot(x, x**2, lw=2, color=\"blue\")\n", - "ax1.set_ylabel(\"Area\", fontsize=18, color=\"blue\")\n", - "for label in ax1.get_yticklabels():\n", - " label.set_color(\"blue\")\n", - " \n", - "ax2 = ax1.twinx()\n", - "ax2.plot(x, x**3, lw=2, color=\"red\")\n", - "ax2.set_ylabel(\"Volume\", fontsize=18, color=\"red\")\n", - "for label in ax2.get_yticklabels():\n", - " label.set_color(\"red\")" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, - "outputs": [ + }, { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -6254,6 +6227,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -6323,6 +6299,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -6379,8 +6364,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -6513,10 +6499,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -6672,8 +6658,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -6794,6 +6780,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -6802,7 +6789,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -6813,8 +6800,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -6903,12 +6891,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -6957,7 +6942,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -6968,31 +6953,26 @@ } ], "source": [ - "# Diferentes estilos de Plots\n", - "xx = np.linspace(-0.75, 1., 100)\n", - "n = np.array([0,1,2,3,4,5])\n", - "\n", - "fig, axes = plt.subplots(1, 4, figsize=(12,3))\n", - "\n", - "axes[0].scatter(xx, xx + 0.25*randn(len(xx)))\n", - "axes[0].set_title(\"scatter\")\n", + "# Controle dos eixos\n", + "fig, axes = plt.subplots(1, 3, figsize = (12, 4))\n", "\n", - "axes[1].step(n, n**2, lw=2)\n", - "axes[1].set_title(\"step\")\n", + "axes[0].plot(x, x**2, x, x**3)\n", + "axes[0].set_title(\"Eixos com range padrão\")\n", "\n", - "axes[2].bar(n, n**2, align=\"center\", width=0.5, alpha=0.5)\n", - "axes[2].set_title(\"bar\")\n", + "axes[1].plot(x, x**2, x, x**3)\n", + "axes[1].axis('tight')\n", + "axes[1].set_title(\"Eixos menores\")\n", "\n", - "axes[3].fill_between(x, x**2, x**3, color=\"green\", alpha=0.5);\n", - "axes[3].set_title(\"fill_between\");" + "axes[2].plot(x, x**2, x, x**3)\n", + "axes[2].set_ylim([0, 60])\n", + "axes[2].set_xlim([2, 5])\n", + "axes[2].set_title(\"Eixos customizados\");" ] }, { "cell_type": "code", - "execution_count": 39, - "metadata": { - "collapsed": false - }, + "execution_count": 33, + "metadata": {}, "outputs": [ { "data": { @@ -7000,6 +6980,7 @@ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", + "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", @@ -7058,6 +7039,9 @@ " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", @@ -7127,6 +7111,15 @@ " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", @@ -7183,8 +7176,9 @@ " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", - " canvas.attr('width', width);\n", - " canvas.attr('height', height);\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", @@ -7317,10 +7311,10 @@ "}\n", "\n", "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", - " var x0 = msg['x0'];\n", - " var y0 = fig.canvas.height - msg['y0'];\n", - " var x1 = msg['x1'];\n", - " var y1 = fig.canvas.height - msg['y1'];\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", @@ -7476,8 +7470,8 @@ " this.canvas_div.focus();\n", " }\n", "\n", - " var x = canvas_pos.x;\n", - " var y = canvas_pos.y;\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", "\n", " this.send_message(name, {x: x, y: y, button: event.button,\n", " step: event.step,\n", @@ -7598,6 +7592,7 @@ "};\n", "\n", "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", " fig.root.unbind('remove')\n", "\n", " // Update the output cell to use the data from the current canvas.\n", @@ -7606,7 +7601,7 @@ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", " // the notebook keyboard shortcuts fail.\n", " IPython.keyboard_manager.enable()\n", - " $(fig.parent_element).html('');\n", + " $(fig.parent_element).html('');\n", " fig.close_ws(fig, msg);\n", "}\n", "\n", @@ -7617,8 +7612,9 @@ "\n", "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] = '';\n", + " this.cell_info[1]['text/html'] = '';\n", "}\n", "\n", "mpl.figure.prototype.updated_canvas_event = function() {\n", @@ -7707,12 +7703,9 @@ " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", " }\n", "}\n", "\n", @@ -7761,7 +7754,10412 @@ { "data": { "text/html": [ - "" + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('