{ "cells": [ { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from matplotlib import pyplot as plt" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import sqlalchemy\n", "import pandas as pd\n", "\n", "import os.path" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from IPython.core.display import display, HTML" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "engine = sqlalchemy.create_engine(open(os.path.expanduser('~/.sqlconninfo')).read())" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " count\n", "0 75006861" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "z = pd.read_sql('select count(*) from subway_ingest;', engine)\n", "z" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "z = pd.read_sql('select ca, unit, scp, station, linename from subway_ingest;', engine)" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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ca
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6R229
7R229
8R229
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12R229
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15R229
16R229
17R229
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19R229
20R229
21R229
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23R229
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27R229
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......
75006831R229
75006832R229
75006833R229
75006834R229
75006835R229
75006836R229
75006837R229
75006838R229
75006839R229
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75006841R229
75006842R229
75006843R229
75006844R229
75006845R229
75006846R229
75006847R229
75006848R229
75006849R229
75006850R229
75006851R229
75006852R229
75006853R229
75006854R229
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75006856R229
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75006860R229
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75006861 rows × 1 columns

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" ], "text/plain": [ " ca\n", "0 R229\n", "1 R229\n", "2 R229\n", "3 R229\n", "4 R229\n", "5 R229\n", "6 R229\n", "7 R229\n", "8 R229\n", "9 R229\n", "10 R229\n", "11 R229\n", "12 R229\n", "13 R229\n", "14 R229\n", "15 R229\n", "16 R229\n", "17 R229\n", "18 R229\n", "19 R229\n", "20 R229\n", "21 R229\n", "22 R229\n", "23 R229\n", "24 R229\n", "25 R229\n", "26 R229\n", "27 R229\n", "28 R229\n", "29 R229\n", "... ...\n", "75006831 R229\n", "75006832 R229\n", "75006833 R229\n", "75006834 R229\n", "75006835 R229\n", "75006836 R229\n", "75006837 R229\n", "75006838 R229\n", "75006839 R229\n", "75006840 R229\n", "75006841 R229\n", "75006842 R229\n", "75006843 R229\n", "75006844 R229\n", "75006845 R229\n", "75006846 R229\n", "75006847 R229\n", "75006848 R229\n", "75006849 R229\n", "75006850 R229\n", "75006851 R229\n", "75006852 R229\n", "75006853 R229\n", "75006854 R229\n", "75006855 R229\n", "75006856 R229\n", "75006857 R229\n", "75006858 R229\n", "75006859 R229\n", "75006860 R229\n", "\n", "[75006861 rows x 1 columns]" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "z" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": true }, "outputs": [], "source": [ "z2 = pd.read_sql(\"select * from subway_ingest where ca='N062' and unit='R011' and scp='01-03-00' ORDER BY endtime;\", engine)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [], "source": [ "z3 = z2[1:].copy()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [], "source": [ "z3.cumul_entries = z2.cumul_entries.values[1:] - z2.cumul_entries.values[:-1]" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": true }, "outputs": [], "source": [ "z3.cumul_exits = z2.cumul_exits.values[1:] - z2.cumul_exits.values[:-1]" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "collapsed": false }, "outputs": [], "source": [ "z4 = z3['endtime cumul_entries cumul_exits'.split()].groupby('endtime').sum()" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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5XbqUfOG84uhzSYJGFV4REZEycg4yMqBZM7jkktK/XkOaRSRaxoyBn36CPn3Kdx19LknQ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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(z4.index.values, z4.cumul_entries.values\n", " )\n", "plt.plot(z4.index.values, z4.cumul_exits.values\n", " )\n", "# plt.ylim(0, 700)\n", "plt.xlim('2010-04-01', '2010-06-01')\n", "plt.gcf().set_size_inches(11, 4)" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "dtype('\n", " \n", " \n", " \n", " turnstile_id\n", " endtime\n", " ca\n", " unit\n", " scp\n", " station\n", " linename\n", " division\n", " description\n", " cumul_entries\n", " cumul_exits\n", " \n", " \n", " \n", " \n", " 1\n", " 50620\n", " 2010-04-17 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 35\n", " 6\n", " \n", " \n", " 2\n", " 50621\n", " 2010-04-17 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 26\n", " 18\n", " \n", " \n", " 3\n", " 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01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 189\n", " 157\n", " \n", " \n", " 101\n", " 499487\n", " 2010-05-08 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 212\n", " 151\n", " \n", " \n", " 102\n", " 499488\n", " 2010-05-09 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 188\n", " 109\n", " \n", " \n", " 103\n", " 499489\n", " 2010-05-09 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 29\n", " 17\n", " \n", " \n", " 104\n", " 499490\n", " 2010-05-09 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 25\n", " 9\n", " \n", " \n", " 105\n", " 499491\n", " 2010-05-09 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 102\n", " 59\n", " \n", " \n", " 106\n", " 499492\n", " 2010-05-09 16:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 149\n", " 110\n", " \n", " \n", " 107\n", " 499493\n", " 2010-05-09 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 239\n", " 119\n", " \n", " \n", " 108\n", " 499494\n", " 2010-05-10 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 287\n", " 83\n", " \n", " \n", " 109\n", " 499495\n", " 2010-05-10 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 14\n", " 5\n", " \n", " \n", " 110\n", " 499496\n", " 2010-05-10 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 338\n", " 50\n", " \n", " \n", " 111\n", " 499497\n", " 2010-05-10 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 655\n", " 119\n", " \n", " \n", " 112\n", " 499498\n", " 2010-05-10 16:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 259\n", " 120\n", " \n", " \n", " 113\n", " 499499\n", " 2010-05-10 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 341\n", " 311\n", " \n", " \n", " 114\n", " 499500\n", " 2010-05-11 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 139\n", " 66\n", " \n", " \n", " 115\n", " 499501\n", " 2010-05-11 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 5\n", " 2\n", " \n", " \n", " 116\n", " 499502\n", " 2010-05-11 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " RECOVR\n", " 0\n", " 0\n", " \n", " \n", " 117\n", " 499503\n", " 2010-05-11 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " AUD\n", " 319\n", " 31\n", " \n", " \n", " 118\n", " 499504\n", " 2010-05-11 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", 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NULL\n", " NULL\n", " RECOVR\n", " 0\n", " 0\n", " \n", " \n", " 137\n", " 499523\n", " 2010-05-14 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " AUD\n", " 225\n", " 29\n", " \n", " \n", " 138\n", " 499524\n", " 2010-05-14 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 490\n", " 124\n", " \n", " \n", " 139\n", " 499525\n", " 2010-05-14 16:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 231\n", " 140\n", " \n", " \n", " 140\n", " 499526\n", " 2010-05-14 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 409\n", " 350\n", " \n", " \n", " 141\n", " 713696\n", " 2010-05-22 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 10239\n", " 4595\n", " \n", " \n", " 142\n", " 713697\n", " 2010-05-22 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 21\n", " 15\n", " \n", " \n", " 143\n", " 713698\n", " 2010-05-22 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 38\n", " 12\n", " \n", " \n", " 144\n", " 713699\n", " 2010-05-22 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 138\n", " 105\n", " \n", " \n", " 145\n", " 713700\n", " 2010-05-22 16:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 222\n", " 185\n", " \n", " \n", " 146\n", " 713701\n", " 2010-05-22 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 213\n", " 159\n", " \n", " \n", " 147\n", " 713702\n", " 2010-05-23 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 237\n", " 105\n", " \n", " \n", " 148\n", " 713703\n", " 2010-05-23 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 31\n", " 18\n", " \n", " \n", " 149\n", " 713704\n", " 2010-05-23 08:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 14\n", " 8\n", " \n", " \n", " 150\n", " 713705\n", " 2010-05-23 12:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " RECOVR\n", " 93\n", " 63\n", " \n", " \n", " 151\n", " 713706\n", " 2010-05-23 16:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " AUD\n", " 193\n", " 115\n", " \n", " \n", " 152\n", " 713707\n", " 2010-05-23 20:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 274\n", " 168\n", " \n", " \n", " 153\n", " 713708\n", " 2010-05-24 00:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " NULL\n", " REGULAR\n", " 197\n", " 92\n", " \n", " \n", " 154\n", " 713709\n", " 2010-05-24 04:00:00\n", " N062\n", " R011\n", " 01-03-00\n", " NULL\n", " NULL\n", " 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....................................
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163884 rows × 11 columns

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" ], "text/plain": [ " turnstile_id endtime ca unit scp \\\n", "0 50466 2010-04-17 00:00:00 N062 R011 01-00-00 \n", "1 50619 2010-04-17 00:00:00 N062 R011 01-03-00 \n", "2 50769 2010-04-17 00:00:00 N062 R011 01-03-03 \n", "3 50819 2010-04-17 00:00:00 N062 R011 01-03-04 \n", "4 50517 2010-04-17 00:00:00 N062 R011 01-00-01 \n", "5 50568 2010-04-17 00:00:00 N062 R011 01-00-02 \n", "6 50669 2010-04-17 00:00:00 N062 R011 01-03-01 \n", "7 50869 2010-04-17 00:00:00 N062 R011 01-05-00 \n", "8 50719 2010-04-17 00:00:00 N062 R011 01-03-02 \n", "9 50918 2010-04-17 00:00:00 N062 R011 01-05-01 \n", "10 50467 2010-04-17 04:00:00 N062 R011 01-00-00 \n", "11 50620 2010-04-17 04:00:00 N062 R011 01-03-00 \n", "12 50770 2010-04-17 04:00:00 N062 R011 01-03-03 \n", "13 50820 2010-04-17 04:00:00 N062 R011 01-03-04 \n", "14 50468 2010-04-17 04:00:00 N062 R011 01-00-00 \n", "15 50870 2010-04-17 04:00:00 N062 R011 01-05-00 \n", "16 50670 2010-04-17 04:00:00 N062 R011 01-03-01 \n", "17 50518 2010-04-17 04:00:00 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"collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }