From 3d7549ac12e155543f3fc7fb30f7f1ed59cba73b Mon Sep 17 00:00:00 2001 From: sovello Date: Tue, 26 May 2015 15:18:14 -0400 Subject: [PATCH 1/6] simple plots and first exploratory analysis for data working, though the plots need some polishing --- consumer_complains.ipynb | 660 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 660 insertions(+) create mode 100644 consumer_complains.ipynb diff --git a/consumer_complains.ipynb b/consumer_complains.ipynb new file mode 100644 index 0000000..d895494 --- /dev/null +++ b/consumer_complains.ipynb @@ -0,0 +1,660 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 115, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import math" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ccdata = pd.read_csv('consumer_complains.csv', engine=\"python\")" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Complaint IDProductSub-productIssueSub-issueStateZIP codeSubmitted viaDate receivedDate sent to companyCompanyCompany responseTimely response?Consumer disputed?
01388734MortgageConventional adjustable mortgage (ARM)Loan servicing, payments, escrow accountNaNVA22204Web05/22/201505/22/2015Green Tree Servicing, LLCClosed with explanationYesNaN
11389303Consumer loanVehicle loanTaking out the loan or leaseNaNMO63304Web05/22/201505/22/2015Ally Financial Inc.In progressYesNaN
21389676Consumer loanVehicle leaseProblems when you are unable to payNaNFL33414Web05/22/201505/22/2015Ally Financial Inc.In progressYesNaN
31388406MortgageConventional fixed mortgageLoan servicing, payments, escrow accountNaNNC27615Web05/22/201505/22/2015Navy FCUIn progressYesNaN
41388470Consumer loanInstallment loanManaging the loan or leaseNaNMA1474Phone05/22/201505/22/2015Santander Bank USIn progressYesNaN
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" + ], + "text/plain": [ + " Complaint ID Product Sub-product \\\n", + "0 1388734 Mortgage Conventional adjustable mortgage (ARM) \n", + "1 1389303 Consumer loan Vehicle loan \n", + "2 1389676 Consumer loan Vehicle lease \n", + "3 1388406 Mortgage Conventional fixed mortgage \n", + "4 1388470 Consumer loan Installment loan \n", + "\n", + " Issue Sub-issue State ZIP code \\\n", + "0 Loan servicing, payments, escrow account NaN VA 22204 \n", + "1 Taking out the loan or lease NaN MO 63304 \n", + "2 Problems when you are unable to pay NaN FL 33414 \n", + "3 Loan servicing, payments, escrow account NaN NC 27615 \n", + "4 Managing the loan or lease NaN MA 1474 \n", + "\n", + " Submitted via Date received Date sent to company Company \\\n", + "0 Web 05/22/2015 05/22/2015 Green Tree Servicing, LLC \n", + "1 Web 05/22/2015 05/22/2015 Ally Financial Inc. \n", + "2 Web 05/22/2015 05/22/2015 Ally Financial Inc. \n", + "3 Web 05/22/2015 05/22/2015 Navy FCU \n", + "4 Phone 05/22/2015 05/22/2015 Santander Bank US \n", + "\n", + " Company response Timely response? Consumer disputed? \n", + "0 Closed with explanation Yes NaN \n", + "1 In progress Yes NaN \n", + "2 In progress Yes NaN \n", + "3 In progress Yes NaN \n", + "4 In progress Yes NaN " + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ccdata.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Complaint IDProductSub-productIssueSub-issueStateZIP codeSubmitted viaDate receivedDate sent to companyCompanyCompany responseTimely response?Consumer disputed?
3958482352Credit cardNaNCredit determinationNaNNY13350Web12/01/201112/05/2011Capital OneClosed without reliefYesYes
3958492366Credit cardNaNCredit reportingNaNFL33415Referral12/01/201112/06/2011CitibankClosed without reliefYesYes
3958502368Credit cardNaNCredit line increase/decreaseNaNFL32792Web12/01/201112/05/2011CitibankClosed without reliefYesNo
3958512371Credit cardNaNOther feeNaNHI96813Web12/01/201112/19/2011Capital OneClosed without reliefYesNo
3958522374Credit cardNaNPayoff processNaNCA94108Phone12/01/201112/05/2011Capital OneClosed without reliefYesYes
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" + ], + "text/plain": [ + " Complaint ID Product Sub-product Issue \\\n", + "395848 2352 Credit card NaN Credit determination \n", + "395849 2366 Credit card NaN Credit reporting \n", + "395850 2368 Credit card NaN Credit line increase/decrease \n", + "395851 2371 Credit card NaN Other fee \n", + "395852 2374 Credit card NaN Payoff process \n", + "\n", + " Sub-issue State ZIP code Submitted via Date received \\\n", + "395848 NaN NY 13350 Web 12/01/2011 \n", + "395849 NaN FL 33415 Referral 12/01/2011 \n", + "395850 NaN FL 32792 Web 12/01/2011 \n", + "395851 NaN HI 96813 Web 12/01/2011 \n", + "395852 NaN CA 94108 Phone 12/01/2011 \n", + "\n", + " Date sent to company Company Company response \\\n", + "395848 12/05/2011 Capital One Closed without relief \n", + "395849 12/06/2011 Citibank Closed without relief \n", + "395850 12/05/2011 Citibank Closed without relief \n", + "395851 12/19/2011 Capital One Closed without relief \n", + "395852 12/05/2011 Capital One Closed without relief \n", + "\n", + " Timely response? Consumer disputed? \n", + "395848 Yes Yes \n", + "395849 Yes Yes \n", + "395850 Yes No \n", + "395851 Yes No \n", + "395852 Yes Yes " + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ccdata.tail()" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#change_indices to get data for different variables\n", + "ccdata_bydate = ccdata\n", + "ccdata_byproduct = ccdata\n", + "ccdata_bycompany = ccdata" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ccdata_bydate.index = pd.to_datetime(ccdata_bydate['Date received'], format=\"%m/%d/%Y\")" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'FigureCanvasAgg' object has no attribute 'invalidate'", + 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date formatter, locators and rescale limits\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 67\u001b[0;31m \u001b[0mformat_dateaxis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfreq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 69\u001b[0m \u001b[0;31m# x and y coord info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/pandas/tseries/plotting.py\u001b[0m in \u001b[0;36mformat_dateaxis\u001b[0;34m(subplot, freq)\u001b[0m\n\u001b[1;32m 224\u001b[0m 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"\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/matplotlib/backends/backend_macosx.py\u001b[0m in \u001b[0;36mdraw_if_interactive\u001b[0;34m()\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_active\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m \u001b[0mfigManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvalidate\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 238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + 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m7ePkX7A+YC1gcbsCiOBJYC7wwTqqHwn8aKChnRGsBg4BDpQ4tI5jvREP8zTr\nFM1L/pI2kfQzSXdKWiRpvKRNJc2TdJekqyRtUlX/OElLJC2WNLGqfJykhWnbjLzxDIfEVRJH1VF1\nb2BeCRJgza4fiZcBB5A9HDagCB4B9gdOScNBq/ffVOJAif+SWAzMIbvhbGYlV8+yssNp+c8ALouI\nncgmOVsMHAvMi4gdyboajgWQNBY4mOxJ1UnATEmVuWxOA6ZERB/QJ2nSMGJqWFpNa3fgOImP1aje\n7v7+il8DL5d4wxB1PgxcFjF0N00EC4GjgJ9LTJaYLnETsBT4GHAv8AHgFRGcUkj0ZtYKjw21MVfy\nlzQS2CMizgCIiNUR8TgwmaxVSvq9f3q9HzA7IlZFxFKyB4XGS9oK2DgiFqR6Z1ft0ypjgXvIRvF8\nVeKjA1VKN0Yn0N7+fgBSN845DNL6T/cmjqTfjd4hjvczYCbwOeDvwL8Dm0WwbwQnRXDLMJ4KNrP2\nWDnUxrzTO2wH/EXSmcDOwM3Ap4EtIqIy78sKYIv0ehRwfdX+y4CtyVabWVZVvjyVt9IuwK0RLJHY\nC7hGYnXEi7o4dgWWprHyZXA28BuJL6b++2p7pN/X1nuwCKYD04sKzszarinJf23gTcD/jYgbJZ1C\n6uKpiIiQVFjfuKRpVX/Oj4j5BR16F9IavBH8ScpG86QPgNlV9crS5QM8H+u9wD7AL/tt/gTZjd52\n35swsxaSNIE0QzActdlQdfMm/2XAsoi4Mf39M+A44CFJW0bEQ6lLp9JKXg6Mrtp/m3SM5el1dfny\ngU4YEdNyxlrLLsAvXjgPiyQmAvPSB8BP06a9ga83KYa8Kjd+n0/+Eq8A9gWObldQZtYeqVE8H0Bi\nBzitb7C6ufr8I+Ih4AFJO6aivYA/ks0cWemHPhy4OL2eCxwiaV1J25ENmVyQjvNEGikk4LCqfZou\n9Y3vDNxWXR7BHWQ3pr8vcYDES1O9urtRWuQCYJ80sqfiI8DFEUN/5TOzrteUbh+ATwLnSloX+DPw\nUbIx8HMkTSEbLXIQQEQskjQHWASsBqZGRKVLYirZcMQRZKOHrhhGTI3aFnh6oBExEdwm8S6ypRYv\nBG6oZ/hUK0WwUuJKsvH6p6V1hY+Eusbtm1l3GzL564UcXF6SIiIKX+RcYj/g4xG8e4g6byEb4XNC\nuilaKhLvBv4jgt3SDeuTgDe6v9+st2WTOuqJwXJnry/m8vzN3sFEcKPELlCaUT79XQmcLvFq0jw+\nTvxmFsGtJvVYAAAKrElEQVSTGqLJ3OvTO9RM/gAR3BvB31oQT8PSMM9zyUZbvTO9NjMbkpN/Hcm/\nA8wiu9F7QZr7x8xsSD2b/NNi5JuR3azuaBHcDpwP/KDdsZhZZ+jlPv+dyRZh74ppCyL4QLtjMLPO\n0bMtf7qny8fMrGG9nPx3xsnfzHpULyd/t/zNrGf15ENeaQ7/x8imLX66qOOamZXJULmzV1v+ryGb\nntmJ38x6Uq8m/13oN5mbmVkv6eXk7/5+M+tZTv5mZj2o55J/1Rz+Tv5m1rN6LvmTrRb2bAQratY0\nM+tSvZj83eVjZj3Pyd/MrAf1avL3ME8z62m9mvzd8jezntZTyV9iJLAlsKTdsZiZtVNPJX/gDWRz\n+P+z3YGYmbVTryV/j+83M6P3kr/7+83MGGbyl7SWpFskXZr+3lTSPEl3SbpK0iZVdY+TtETSYkkT\nq8rHSVqYts0YTjx18EgfMzOG3/I/BlgEVBYFOBaYFxE7Alenv5E0FjgYGAtMAmZKqswxfRowJSL6\ngD5Jk4YZ04Ak1knnX9iM45uZdZLcyV/SNsC7gJ8AlUQ+GZiVXs8C9k+v9wNmR8SqiFgK3A2Ml7QV\nsHFELEj1zq7ap2ivBh6I4KkmHd/MrGMMp+X/PeDzwHNVZVtERGXOnBXAFun1KGBZVb1lwNYDlC9P\n5c3g/n4zs2TtPDtJeg/wcETcImnCQHUiIiQVtkakpGlVf86PiPkNHsLJ38y6WsrHE+qpmyv5A28F\nJkt6F7A+8FJJ5wArJG0ZEQ+lLp2HU/3lwOiq/bcha/EvT6+ry5cPdMKImJYz1oqdgZOHeQwzs9JK\njeL5lb8lHT9Y3VzdPhHxpYgYHRHbAYcA10TEYcBc4PBU7XDg4vR6LnCIpHUlbQf0AQsi4iHgCUnj\n0w3gw6r2KUyaw98tfzOzJG/Lv79K9863gTmSpgBLgYMAImKRpDlkI4NWA1MjorLPVOAsYARwWURc\nUVBM1UalGB9qwrHNzDqOXsjB5SUpIkK1aw62P+8GjolgYs3KZmZdYqjc2StP+LrLx8ysipO/mVkP\n6vrkn57sHYeTv5nZ87o2+UtsIPFJsqeJ/wTc1eaQzMxKo+uSv8TLJL4C3Au8HTgogn0jWN3m0MzM\nSqNrkr/EKImTgD8D2wMTIjgwghvaHJqZWel0fPKX2FDix8AdZM8t7BLBRyO4s82hmZmVVlEPebXT\n94CXAztG8Nd2B2Nm1gk6OvlLvB94B/DGCJ5sdzxmZp2iY5O/xLbATOA9TvxmZo3pyD5/ibWA/wFO\njmBBrfpmZramjkz+wJeAVcCJ7Q7EzKwTdVy3j8RbgaOBcRFrrCJmZmZ16qiWv8RI4FzgyIiBF30x\nM7PaOmZKZ4iXAOcBj0ZwdLtjMjMru6GmdO6kbp/DgdcDb2l3IGZmna6TWv5/Bd4RwcJ2x2Nm1gm6\nZTGXaU78ZmbF6KSW/0siKH+wZmYl0RUtfyd+M7PidEzyNzOz4jj5m5n1oFzJX9JoSb+W9EdJd0j6\nVCrfVNI8SXdJukrSJlX7HCdpiaTFkiZWlY+TtDBtmzH8t2RmZrXkbfmvAj4TEa8FdgOOlrQTcCww\nLyJ2BK5OfyNpLHAwMBaYBMyUVLkJcRowJSL6gD5JkxoNRtKEnO/DCuTrUA6+DuVQ9uuQK/lHxEMR\ncWt6/RRwJ7A1MBmYlarNAvZPr/cDZkfEqohYSrao+nhJWwEbR0RlZs6zq/ZpxIQ878MKN6HdARjg\n61AWE9odwFCG3ecvaQzwRuAGYIuIWJE2rQC2SK9HAcuqdltG9mHRv3x5Km/UmDrinNDJ28sQQx0x\njqmxve0x+jq0JgZfB6AE12Eow0r+kjYCLgSOiYg1FlSJ7AGCVg3PHFNHnQkdvr0MMdTaPqbG9lbE\n0OztZYih1vYxNba3IoZmby9DDLW2j6mxvRUxDC4icv0A6wBXAp+uKlsMbJlebwUsTq+PBY6tqncF\nMB7YErizqvwDwA8HOFf4xz/+8Y9/Gv8ZLIfnmtgt3aw9HVgUEadUbZpLNgHb9PT74qry8ySdTNat\n0wcsiIiQ9ISk8cAC4DDg1P7nG+wJNTMzyyfX9A6Sdgd+C9xO9ukCcBxZAp8DbAssBQ6KiMfSPl8C\njgBWk3UTXZnKxwFnASOAyyLiU/nfjpmZ1aMj5vYxM7NiddwTvpKeancMRan1XiTNT9+MSqdbrkMn\nXwPwdSiLTrwOHZf8eaGbqRvUei9RR512KWtcjerkawDljq0Rvg4t1onJH0kbSvqVpJsl3S5pciof\nI+lOST9O005cKWn9dsc7FEl7Srq06u8fSDq8nTHVq1uuQydfA/B1KItOuw4dmfyBZ4ADImIc8A7g\nu1XbdgB+EBGvAx4D3teG+Iaj7C2cat16HTrpGoCvQ1l01HXopDV8q70E+JakPYDngFGSNk/b7o2I\n29Prm6nvQQvLx9ehHHwdyqGjrkOnJv9Dgc2AN0XEPyXdC1S+Rv2jqt4/yYaQltlq1vwGVvZ4q3XL\ndejkawC+DmXRUdehU7t9RgIPp//Abwde2e6AhuE+YKykdZVNgf2OdgfUgG65Dp18DcDXoSw66jp0\nVMtf0tpkn6DnApdKuh24iWxW0Yr+fYSl7DOsvJeIWCZpDnAHcC/wh/ZGVlu3XIdOvgbg61AWnXod\nOuohL0k7Az+KiN3aHctwdfJ76eTYq3X6++j0+Cs6/X10avwd0+0j6RPAecBX2h3LcHXye+nk2Kt1\n+vvo9PgrOv19dHL8HdXyNzOzYnRMy9/MzIpTyuSvBheIT+W/lvSkpO9XHWeEpF+mp+vukPStdr2n\nTlTUdUjbrpB0azrW6ZLWacd76kRFXoeqY86VtLCV76PTFfzvYb6kxZJuST+btfr9lDL50+AC8cDf\nyfrcPjfAsU6MiJ3Ilpr8V+VYIL6HFXkd3h8Ru6RjjQQObnr03aPI64CkA4EnKcGIkw5T5HUI4IMR\n8cb089fmh7+mUib/RheIj4inI+J3rPkgBRHxTET8Jr1eRTZ0LM8awT2pqOtQtT+pxb8u0PL/2TtV\nkddB2dKrnwG+CXiRpAYUeR2Stv73L2Xyr6b6FoivGLQlk76KvZfsk9kaVMR1kHRlqv9MRFzRnEi7\nWwHX4RvAScDTTQqxJxSUl2alLp+2jBQqdfJXQQvEp4cwZgMzImJp0XF2u6KuQ0TsQ7a283rqoNka\ny2K410HSLsCrIuIS3OrPraB/D4emSd72APaQdFjxkQ6ttMk/dQ9cCJwTEZW1gFdI2jJt3wp4uM7D\n/Rj4U0S8aH1gG1rB14GI+Ec63luKjrWbFXQddgPerGzOmWuBHSVd06yYu1FR/x4i4sH0+ymy5wR2\nbU7Egytl8pdqLhAPay4Q//yuAxzrm8BLyfo5rQFFXQdl85xvlV6vDbwHuKUpQXehoq5DRPwwIraO\niO2A3YG7IqLT5s9pmwL/PaxVGd2TPkzeC7R85FUpH/JSvgXilwIbk91MfAzYG3gKuJ/sxsyz6Tjf\nj4gzWvE+Ol2B1+FR4BfAemT/EK4EvhBl/J+vhAq4DiuBiRGxuOqYY4C5EfGGVryHblDgv4f703HW\nAdYC5gH/3up/D6VM/mZm1lyl7PYxM7PmcvI3M+tBTv5mZj3Iyd/MrAc5+ZuZ9SAnfzOzHuTkb2bW\ng5z8zcx60P8HlYHNDkqxWoYAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure()\n", + "ccdata_bydate['Date received'].resample(\"M\", how=[\"count\"]).plot()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ccdata_bydate.index.to_series().map(lambda d: d.weekday())\n", + "ccdata_bydate[\"weekday\"] = ccdata_bydate.index.to_series().map(lambda d: d.weekday())" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "weekday = [\"Sa\", \"Su\", \"M\", \"Tu\", \"W\", \"Th\", \"F\"]\n", + "data_byweekday = ccdata_bydate.weekday.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_byweekday.index = weekday" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 2517\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2518\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2519\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 2520\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2521\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/pandas/tools/plotting.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m 2322\u001b[0m \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2323\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2324\u001b[0;31m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\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 2325\u001b[0m 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\u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 43\u001b[0;31m \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 44\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/matplotlib/backends/backend_macosx.py\u001b[0m in \u001b[0;36mdraw_if_interactive\u001b[0;34m()\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_active\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m \u001b[0mfigManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvalidate\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 238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAttributeError\u001b[0m: 'FigureCanvasAgg' object has no attribute 'invalidate'" + ] + }, + { + "data": { + "image/png": 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W2PhB6IMYX/GplOBD9LEy/Tleg/fXiblJ5noIqfxS5+Qs+D6NQWrbEE7eSrmi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\nA4AqH1Ud81EPMXOCnxNS/uT7mYymOU+USDQGqz8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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ccdata_byproduct['Product'].groupby(ccdata_byproduct.index).count().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ccdata_bycompany.index = ccdata_bycompany['Company']" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cplot = ccdata_bycompany['Company'].groupby(ccdata_bycompany.index).count().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Plots" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.4.3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} From f6fc3207c6a660c0803ec571594a3c8344376cd9 Mon Sep 17 00:00:00 2001 From: sovello Date: Tue, 26 May 2015 18:54:56 -0400 Subject: [PATCH 2/6] initial push for hard mode. complains not seen on combined plot as they are too small numbers --- complaints_by_state.ipynb | 1133 +++++++++++++++++++++++++++++++++++++ pop_density_us.csv | 57 ++ state_table.csv | 74 +++ 3 files changed, 1264 insertions(+) create mode 100644 complaints_by_state.ipynb create mode 100644 pop_density_us.csv create mode 100644 state_table.csv diff --git a/complaints_by_state.ipynb b/complaints_by_state.ipynb new file mode 100644 index 0000000..e997268 --- /dev/null +++ b/complaints_by_state.ipynb @@ -0,0 +1,1133 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ccdata = pd.read_csv('consumer_complains.csv', engine=\"python\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "#population data credits: http://www.census.gov/2010census/data/ \n", + "popn_data = pd.read_csv('pop_density_us.csv', engine=\"python\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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# POPULATION DENSITY DATA PROVIDED BY U.S. CENSUS.Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9...Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33
0# DENSITY EXPRESSED AS PEOPLE PER SQUARE MILE.NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1# DENSITY RANKING EXPRESSED IN ORDER OF MOST D...NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2STATE_OR_REGION1910_POPULATION1920_POPULATION1930_POPULATION1940_POPULATION1950_POPULATION1960_POPULATION1970_POPULATION1980_POPULATION1990_POPULATION...1920_RANK1930_RANK1940_RANK1950_RANK1960_RANK1970_RANK1980_RANK1990_RANK2000_RANK2010_RANK
3United States92228531106021568123202660132165129151325798179323175203211926226545805248709873...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4Alabama213809323481742646248283296130617433266740344416538938884040587...25242324282828272829
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# POPULATION DENSITY DATA PROVIDED BY U.S. CENSUS.Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9...Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33
51Washington114199013566211563396173619123789632853214340916941321564866692...37373735323030302727
52West Virginia122111914637011729205190197420055521860421174423719496441793477...15151515222727283131
53Wisconsin233386026320672939006313758734345753951777441773147057674891769...24222223252426262625
54Wyoming145965194402225565250742290529330066332416469557453588...50505050505151515151
55Puerto Rico111801212998091543913186925522107032349544271203331965203522037...5552443333
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" + ], + "text/plain": [ + " # POPULATION DENSITY DATA PROVIDED BY U.S. CENSUS. Unnamed: 1 Unnamed: 2 \\\n", + "51 Washington 1141990 1356621 \n", + "52 West Virginia 1221119 1463701 \n", + "53 Wisconsin 2333860 2632067 \n", + "54 Wyoming 145965 194402 \n", + "55 Puerto Rico 1118012 1299809 \n", + "\n", + " Unnamed: 3 Unnamed: 4 Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 \\\n", + "51 1563396 1736191 2378963 2853214 3409169 4132156 \n", + "52 1729205 1901974 2005552 1860421 1744237 1949644 \n", + "53 2939006 3137587 3434575 3951777 4417731 4705767 \n", + "54 225565 250742 290529 330066 332416 469557 \n", + "55 1543913 1869255 2210703 2349544 2712033 3196520 \n", + "\n", + " Unnamed: 9 ... Unnamed: 24 Unnamed: 25 Unnamed: 26 Unnamed: 27 \\\n", + "51 4866692 ... 37 37 37 35 \n", + "52 1793477 ... 15 15 15 15 \n", + "53 4891769 ... 24 22 22 23 \n", + "54 453588 ... 50 50 50 50 \n", + "55 3522037 ... 5 5 5 2 \n", + "\n", + " Unnamed: 28 Unnamed: 29 Unnamed: 30 Unnamed: 31 Unnamed: 32 Unnamed: 33 \n", + "51 32 30 30 30 27 27 \n", + "52 22 27 27 28 31 31 \n", + "53 25 24 26 26 26 25 \n", + "54 50 51 51 51 51 51 \n", + "55 4 4 3 3 3 3 \n", + "\n", + "[5 rows x 34 columns]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "popn_data.tail()" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# headers start on the 3rd column, so re-read, and use data on \n", + "popn_data = pd.read_csv('pop_density_us.csv', engine=\"python\", header=3)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['STATE_OR_REGION', '1910_POPULATION', '1920_POPULATION',\n", + " '1930_POPULATION', '1940_POPULATION', '1950_POPULATION',\n", + " '1960_POPULATION', '1970_POPULATION', '1980_POPULATION',\n", + " '1990_POPULATION', '2000_POPULATION', '2010_POPULATION',\n", + " '1910_DENSITY', '1920_DENSITY', '1930_DENSITY', '1940_DENSITY',\n", + " '1950_DENSITY', '1960_DENSITY', '1970_DENSITY', '1980_DENSITY',\n", + " '1990_DENSITY', '2000_DENSITY', '2010_DENSITY', '1910_RANK',\n", + " '1920_RANK', '1930_RANK', '1940_RANK', '1950_RANK', '1960_RANK',\n", + " '1970_RANK', '1980_RANK', '1990_RANK', '2000_RANK', '2010_RANK'], dtype=object)" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "popn_data.columns.values" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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STATE_OR_REGION1910_POPULATION1920_POPULATION1930_POPULATION1940_POPULATION1950_POPULATION1960_POPULATION1970_POPULATION1980_POPULATION1990_POPULATION...1920_RANK1930_RANK1940_RANK1950_RANK1960_RANK1970_RANK1980_RANK1990_RANK2000_RANK2010_RANK
0United States92228531106021568123202660132165129151325798179323175203211926226545805248709873...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1Alabama213809323481742646248283296130617433266740344416538938884040587...25242324282828272829
2Alaska64356550365927872524128643226167300382401851550043...52525252525252525252
3Arizona2043543341624355734992617495871302161177090027182153665228...49474747434342393835
4Arkansas157444917522041854482194938719095111786272192329522864352350725...31323234363737373636
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" + ], + "text/plain": [ + " STATE_OR_REGION 1910_POPULATION 1920_POPULATION 1930_POPULATION \\\n", + "0 United States 92228531 106021568 123202660 \n", + "1 Alabama 2138093 2348174 2646248 \n", + "2 Alaska 64356 55036 59278 \n", + "3 Arizona 204354 334162 435573 \n", + "4 Arkansas 1574449 1752204 1854482 \n", + "\n", + " 1940_POPULATION 1950_POPULATION 1960_POPULATION 1970_POPULATION \\\n", + "0 132165129 151325798 179323175 203211926 \n", + "1 2832961 3061743 3266740 3444165 \n", + "2 72524 128643 226167 300382 \n", + "3 499261 749587 1302161 1770900 \n", + "4 1949387 1909511 1786272 1923295 \n", + "\n", + " 1980_POPULATION 1990_POPULATION ... 1920_RANK 1930_RANK 1940_RANK \\\n", + "0 226545805 248709873 ... NaN NaN NaN \n", + "1 3893888 4040587 ... 25 24 23 \n", + "2 401851 550043 ... 52 52 52 \n", + "3 2718215 3665228 ... 49 47 47 \n", + "4 2286435 2350725 ... 31 32 32 \n", + "\n", + " 1950_RANK 1960_RANK 1970_RANK 1980_RANK 1990_RANK 2000_RANK 2010_RANK \n", + "0 NaN NaN NaN NaN NaN NaN NaN \n", + "1 24 28 28 28 27 28 29 \n", + "2 52 52 52 52 52 52 52 \n", + "3 47 43 43 42 39 38 35 \n", + "4 34 36 37 37 37 36 36 \n", + "\n", + "[5 rows x 34 columns]" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# using the most recent census data (2010_POPULATION)\n", + "popn_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,\n", + " 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n", + " 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,\n", + " 51, 52],\n", + " dtype='int64')" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "popn_data.index" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "popn_data.index = popn_data.STATE_OR_REGION" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pop2010 = popn_data.loc[:,['STATE_OR_REGION','2010_POPULATION']] # STATE_OR_REGION COUNT\n", + "pop2010.columns = ['STATE_OR_REGION','POPULATION']" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Complaint IDProductSub-productIssueSub-issueStateZIP codeSubmitted viaDate receivedDate sent to companyCompanyCompany responseTimely response?Consumer disputed?
01388734MortgageConventional adjustable mortgage (ARM)Loan servicing, payments, escrow accountNaNVA22204Web05/22/201505/22/2015Green Tree Servicing, LLCClosed with explanationYesNaN
11389303Consumer loanVehicle loanTaking out the loan or leaseNaNMO63304Web05/22/201505/22/2015Ally Financial Inc.In progressYesNaN
21389676Consumer loanVehicle leaseProblems when you are unable to payNaNFL33414Web05/22/201505/22/2015Ally Financial Inc.In progressYesNaN
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" + ], + "text/plain": [ + " Complaint ID Product Sub-product \\\n", + "0 1388734 Mortgage Conventional adjustable mortgage (ARM) \n", + "1 1389303 Consumer loan Vehicle loan \n", + "2 1389676 Consumer loan Vehicle lease \n", + "\n", + " Issue Sub-issue State ZIP code \\\n", + "0 Loan servicing, payments, escrow account NaN VA 22204 \n", + "1 Taking out the loan or lease NaN MO 63304 \n", + "2 Problems when you are unable to pay NaN FL 33414 \n", + "\n", + " Submitted via Date received Date sent to company Company \\\n", + "0 Web 05/22/2015 05/22/2015 Green Tree Servicing, LLC \n", + "1 Web 05/22/2015 05/22/2015 Ally Financial Inc. \n", + "2 Web 05/22/2015 05/22/2015 Ally Financial Inc. \n", + "\n", + " Company response Timely response? Consumer disputed? \n", + "0 Closed with explanation Yes NaN \n", + "1 In progress Yes NaN \n", + "2 In progress Yes NaN " + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ccdata.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['CA', 'FL', 'TX', 'NY', 'GA', 'NJ', 'PA', 'IL', 'VA', 'MD', 'OH', 'NC',\n", + " 'MI', 'AZ', 'MA', 'WA', 'CO', 'TN', 'Unspecified', 'MO', 'CT', 'SC',\n", + " 'OR', 'MN', 'NV', 'WI', 'IN', 'AL', 'LA', 'KY', 'OK', 'DC', 'NH', 'DE',\n", + " 'UT', 'KS', 'NM', 'MS', 'AR', 'IA', 'HI', 'RI', 'ME', 'ID', 'NE', 'WV',\n", + " 'PR', 'VT', 'MT', 'SD', 'AK', 'WY', 'ND', 'AE', 'AP', 'VI', 'GU', 'FM',\n", + " 'MH', 'MP', 'AS', 'AA', 'PW'],\n", + " dtype='object')" + ] + }, + "execution_count": 145, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ccdata2 = ccdata.loc[:,['State']]\n", + "ccdata2.fillna('Unspecified', inplace=True)\n", + "ccdata_counts = ccdata2.State.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#state_names\n", + "state_names = pd.read_csv('state_table.csv', engine=\"python\")" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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01AlabamaALUSAstate10currentoccupiedNaN1Ala.IV3South6East South Central11
12AlaskaAKUSAstate10currentoccupiedNaN2AlaskaX4West9Pacific9
23ArizonaAZUSAstate10currentoccupiedNaN4Ariz.IX4West8Mountain9
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IX 4 \n", + "\n", + " census_region_name census_division census_division_name circuit_court \n", + "0 South 6 East South Central 11 \n", + "1 West 9 Pacific 9 \n", + "2 West 8 Mountain 9 " + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "state_names.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "state_names = state_names.loc[:,['name','abbreviation']]\n", + "state_names.index = state_names['abbreviation']" + ] + }, + { + "cell_type": "code", + "execution_count": 225, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 225, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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apuB1nAqKpsDPTAHqEg4gmvRX2DHVQDvagt09PpGmg9X+ilI3+sXotqeel/Vx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\n+GVp80AaxqgP449fNkBbw6d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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import math\n", + "#popn2010 state_or_region pop (fullname, number)\n", + "#ccdata_counts state_name count (abbr, number)\n", + "#state_names fullname abbreviation\n", + "concatenated = pd.concat([state_names, ccdata_counts], axis=1, join='inner')\n", + "concatenated.columns = ['STATE', 'ABBREVIATION', 'COMPLAINS COUNTS']\n", + "concatenated.index = concatenated['STATE']\n", + "concatenated = pd.concat([concatenated, pop2010], axis=1, join='inner')\n", + "concatenated.index = concatenated['ABBREVIATION']\n", + "concatenated.plot(kind='area')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.4.3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/pop_density_us.csv b/pop_density_us.csv new file mode 100644 index 0000000..14fc417 --- /dev/null +++ b/pop_density_us.csv @@ -0,0 +1,57 @@ +# POPULATION DENSITY DATA PROVIDED BY U.S. CENSUS.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +# DENSITY EXPRESSED AS PEOPLE PER SQUARE MILE.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +# DENSITY RANKING EXPRESSED IN ORDER OF MOST DENSE (1) TO LEAST DENSE (52).,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +STATE_OR_REGION,1910_POPULATION,1920_POPULATION,1930_POPULATION,1940_POPULATION,1950_POPULATION,1960_POPULATION,1970_POPULATION,1980_POPULATION,1990_POPULATION,2000_POPULATION,2010_POPULATION,1910_DENSITY,1920_DENSITY,1930_DENSITY,1940_DENSITY,1950_DENSITY,1960_DENSITY,1970_DENSITY,1980_DENSITY,1990_DENSITY,2000_DENSITY,2010_DENSITY,1910_RANK,1920_RANK,1930_RANK,1940_RANK,1950_RANK,1960_RANK,1970_RANK,1980_RANK,1990_RANK,2000_RANK,2010_RANK +United States,92228531,106021568,123202660,132165129,151325798,179323175,203211926,226545805,248709873,281421906,308745538,26,29.9,34.7,37.2,42.6,50.6,57.5,64.1,70.4,79.7,87.4,,,,,,,,,,, +Alabama,2138093,2348174,2646248,2832961,3061743,3266740,3444165,3893888,4040587,4447100,4779736,42.2,46.4,52.3,55.9,60.5,64.5,68,76.9,79.8,87.8,94.4,25,25,24,23,24,28,28,28,27,28,29 +Alaska,64356,55036,59278,72524,128643,226167,300382,401851,550043,626932,710231,0.1,0.1,0.1,0.1,0.2,0.4,0.5,0.7,1,1.1,1.2,52,52,52,52,52,52,52,52,52,52,52 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0000000..ca1b25e --- /dev/null +++ b/state_table.csv @@ -0,0 +1,74 @@ +id,name,abbreviation,country,type,sort,status,occupied,notes,fips_state,assoc_press,standard_federal_region,census_region,census_region_name,census_division,census_division_name,circuit_court +"1","Alabama","AL","USA","state","10","current","occupied","","1","Ala.","IV","3","South","6","East South Central","11" +"2","Alaska","AK","USA","state","10","current","occupied","","2","Alaska","X","4","West","9","Pacific","9" +"3","Arizona","AZ","USA","state","10","current","occupied","","4","Ariz.","IX","4","West","8","Mountain","9" +"4","Arkansas","AR","USA","state","10","current","occupied","","5","Ark.","VI","3","South","7","West South Central","8" +"5","California","CA","USA","state","10","current","occupied","","6","Calif.","IX","4","West","9","Pacific","9" +"6","Colorado","CO","USA","state","10","current","occupied","","8","Colo.","VIII","4","West","8","Mountain","10" 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Lighthouse possibly occupied.","","","","","","","","" +"84","Armed Forces Americas","AA","USA","military","15","current","occupied","Serves all of the Americas except for Canada.","","","","","","","","" +"85","Armed Forces Europe","AE","USA","military","15","current","occupied","Serves Europe, Canada, Africa and the Middle East","","","","","","","","" +"86","Armed Forces Pacific","AP","USA","military","15","current","occupied","Serves Asia and the Pacific","","","","","","","","" From 03c1f83b3eff16cfa237aba743e2758abf22cd12 Mon Sep 17 00:00:00 2001 From: sovello Date: Tue, 26 May 2015 20:35:12 -0400 Subject: [PATCH 3/6] testing visualization with folium --- complaints_by_state.ipynb | 161 ++++++++++++++++++++++++++++++++++---- data.json | 1 + index.html | 134 +++++++++++++++++++++++++++++++ us-states.json | 52 ++++++++++++ us_states.html | 154 ++++++++++++++++++++++++++++++++++++ 5 files changed, 485 insertions(+), 17 deletions(-) create mode 100644 data.json create mode 100644 index.html create mode 100644 us-states.json create mode 100644 us_states.html diff --git a/complaints_by_state.ipynb b/complaints_by_state.ipynb index e997268..6f7ce4b 100644 --- a/complaints_by_state.ipynb +++ b/complaints_by_state.ipynb @@ -2,14 +2,17 @@ "cells": [ { "cell_type": "code", - "execution_count": 8, + "execution_count": 304, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ "import pandas as pd\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "import folium\n", + "\n", + "#plt.set_option('display.mpl_style', 'default')" ] }, { @@ -1060,30 +1063,112 @@ }, { "cell_type": "code", - "execution_count": 225, + "execution_count": 233, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def density(value1, value2):\n", + " return round(value1/value2, 2)" + ] + }, + { + "cell_type": "code", + "execution_count": 310, "metadata": { "collapsed": false }, "outputs": [ { "data": { + "text/html": [ + "
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STATEABBREVIATIONCOMPLAINS COUNTSSTATE_OR_REGIONPOPULATION
ABBREVIATION
ALAlabamaAL3842Alabama4779736
AKAlaskaAK478Alaska710231
AZArizonaAZ8678Arizona6392017
ARArkansasAR1670Arkansas2915918
CACaliforniaCA58603California37253956
\n", + "
" + ], "text/plain": [ - "" + " STATE ABBREVIATION COMPLAINS COUNTS STATE_OR_REGION \\\n", + "ABBREVIATION \n", + "AL Alabama AL 3842 Alabama \n", + "AK Alaska AK 478 Alaska \n", + "AZ Arizona AZ 8678 Arizona \n", + "AR Arkansas AR 1670 Arkansas \n", + "CA California CA 58603 California \n", + "\n", + " POPULATION \n", + "ABBREVIATION \n", + "AL 4779736 \n", + "AK 710231 \n", + "AZ 6392017 \n", + "AR 2915918 \n", + "CA 37253956 " ] }, - "execution_count": 225, + "execution_count": 310, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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apuB1nAqKpsDPTAHqEg4gmvRX2DHVQDvagt09PpGmg9X+ilI3+sXotqeel/Vx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\n+GVp80AaxqgP449fNkBbw6d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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -1096,7 +1181,49 @@ "concatenated.index = concatenated['STATE']\n", "concatenated = pd.concat([concatenated, pop2010], axis=1, join='inner')\n", "concatenated.index = concatenated['ABBREVIATION']\n", - "concatenated.plot(kind='area')" + "(concatenated['COMPLAINS COUNTS']*10000 / concatenated['POPULATION'].astype(float)).plot(kind='bar', \n", + " figsize=(20,10))" + ] + }, + { + "cell_type": "code", + "execution_count": 312, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "concatenated['per_capita'] = concatenated['COMPLAINS COUNTS']*10000 / concatenated['POPULATION'].astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 318, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#concatenated = concatenated.loc[:,['ABBREVIATION','per_capita']]\n", + "#concatenated.plot(kind='bar', colormap='cubehelix', figsize=(20,10))\n", + "#concatenated.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 319, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "map = folium.Map(location=[48, -102], zoom_start=3)\n", + "map.geo_json(geo_path='us-states.json', data=concatenated,\n", + " columns=['ABBREVIATION', 'per_capita'],\n", + " key_on='feature.id',\n", + " fill_color='YlGn', fill_opacity=0.7, line_opacity=0.2,\n", + " legend_name='Complaints Per Capita')\n", + "map.create_map(path='us_states.html')" ] }, { diff --git a/data.json b/data.json new file mode 100644 index 0000000..4d66285 --- /dev/null +++ b/data.json @@ -0,0 +1 @@ +[{"NE": 6.871663068397413, "AZ": 13.576309324584086, "CO": 13.50514078194606, "NJ": 18.327109039303703, "WA": 11.99189833059213, "FL": 20.23103709262812, "WI": 7.865326202666931, "CA": 15.730678374130253, "KY": 6.390332967919053, "NM": 9.26097245552718, "NC": 11.400576142813112, "SC": 10.280271995890486, "MT": 6.620073477762112, "NY": 13.95079869019164, "WY": 7.15013147015929, "IA": 5.285004538210418, "UT": 7.547347302800225, "PR": 2.230400057544858, "CT": 13.312453467267396, "AK": 6.73020467988584, "VA": 15.917962500799897, "NH": 16.711356886218447, "OK": 6.834870957156502, "ID": 8.34406110812704, "AR": 5.7271843721256905, "GA": 17.63585049959985, "MD": 22.031498114159188, "TN": 9.1237065885295, "MA": 12.325072174981203, "DE": 23.442702915804503, "LA": 8.133018865427324, "MS": 5.914473677559071, "MN": 8.610604410884392, "IL": 10.76174579708934, "RI": 13.55733174230239, "ME": 10.554359846457402, "ND": 4.817192023086839, "VT": 11.266642268925962, "MO": 8.687699816678347, "IN": 6.6180305937781565, "MI": 10.905901064789894, "SD": 6.669286889876932, "WV": 5.380481534208961, "OH": 10.681745527067818, "PA": 11.16956122943584, "HI": 10.54178450210652, "NV": 16.878037111685725, "OR": 12.168911380986115, "KS": 6.683915631950729, "AL": 8.038100849084552, "TX": 11.43899712557616}] \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 0000000..0dcdbb7 --- /dev/null +++ b/index.html @@ -0,0 +1,134 @@ + + + + + + + + + + + + + + +
+ + + + diff --git a/us-states.json b/us-states.json new file mode 100644 index 0000000..3516c05 --- /dev/null +++ b/us-states.json @@ -0,0 +1,52 @@ +{"type":"FeatureCollection","features":[ 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+ + + \ No newline at end of file From 7f712bd44f3a4b422d270287535c7943cebf8854 Mon Sep 17 00:00:00 2001 From: sovello Date: Tue, 26 May 2015 21:00:16 -0400 Subject: [PATCH 4/6] add per-capita-data dataframe --- per_capita_data.csv | 52 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 per_capita_data.csv diff --git a/per_capita_data.csv b/per_capita_data.csv new file mode 100644 index 0000000..fdbf1ed --- /dev/null +++ b/per_capita_data.csv @@ -0,0 +1,52 @@ +ABBREVIATION,STATE,ABBREVIATION,COMPLAINS COUNTS,STATE_OR_REGION,POPULATION,per_capita +AL,Alabama,AL,3842,Alabama,4779736,8.038100849084552 +AK,Alaska,AK,478,Alaska,710231,6.73020467988584 +AZ,Arizona,AZ,8678,Arizona,6392017,13.576309324584086 +AR,Arkansas,AR,1670,Arkansas,2915918,5.7271843721256905 +CA,California,CA,58603,California,37253956,15.730678374130253 +CO,Colorado,CO,6792,Colorado,5029196,13.50514078194606 +CT,Connecticut,CT,4758,Connecticut,3574097,13.312453467267396 +DE,Delaware,DE,2105,Delaware,897934,23.442702915804503 +FL,Florida,FL,38037,Florida,18801310,20.23103709262812 +GA,Georgia,GA,17085,Georgia,9687653,17.63585049959985 +HI,Hawaii,HI,1434,Hawaii,1360301,10.54178450210652 +ID,Idaho,ID,1308,Idaho,1567582,8.34406110812704 +IL,Illinois,IL,13808,Illinois,12830632,10.76174579708934 +IN,Indiana,IN,4291,Indiana,6483802,6.6180305937781565 +IA,Iowa,IA,1610,Iowa,3046355,5.285004538210418 +KS,Kansas,KS,1907,Kansas,2853118,6.683915631950729 +KY,Kentucky,KY,2773,Kentucky,4339367,6.390332967919053 +LA,Louisiana,LA,3687,Louisiana,4533372,8.133018865427324 +ME,Maine,ME,1402,Maine,1328361,10.554359846457402 +MD,Maryland,MD,12720,Maryland,5773552,22.031498114159188 +MA,Massachusetts,MA,8070,Massachusetts,6547629,12.325072174981203 +MI,Michigan,MI,10779,Michigan,9883640,10.905901064789894 +MN,Minnesota,MN,4567,Minnesota,5303925,8.610604410884392 +MS,Mississippi,MS,1755,Mississippi,2967297,5.914473677559071 +MO,Missouri,MO,5203,Missouri,5988927,8.687699816678347 +MT,Montana,MT,655,Montana,989415,6.620073477762112 +NE,Nebraska,NE,1255,Nebraska,1826341,6.871663068397413 +NV,Nevada,NV,4558,Nevada,2700551,16.878037111685725 +NH,New Hampshire,NH,2200,New Hampshire,1316470,16.711356886218447 +NJ,New Jersey,NJ,16113,New Jersey,8791894,18.327109039303703 +NM,New Mexico,NM,1907,New Mexico,2059179,9.26097245552718 +NY,New York,NY,27034,New York,19378102,13.95079869019164 +NC,North Carolina,NC,10871,North Carolina,9535483,11.400576142813112 +ND,North Dakota,ND,324,North Dakota,672591,4.817192023086839 +OH,Ohio,OH,12323,Ohio,11536504,10.681745527067818 +OK,Oklahoma,OK,2564,Oklahoma,3751351,6.834870957156502 +OR,Oregon,OR,4662,Oregon,3831074,12.168911380986115 +PA,Pennsylvania,PA,14188,Pennsylvania,12702379,11.16956122943584 +RI,Rhode Island,RI,1427,Rhode Island,1052567,13.55733174230239 +SC,South Carolina,SC,4755,South Carolina,4625364,10.280271995890486 +SD,South Dakota,SD,543,South Dakota,814180,6.669286889876932 +TN,Tennessee,TN,5790,Tennessee,6346105,9.1237065885295 +TX,Texas,TX,28764,Texas,25145561,11.43899712557616 +UT,Utah,UT,2086,Utah,2763885,7.547347302800225 +VT,Vermont,VT,705,Vermont,625741,11.266642268925962 +VA,Virginia,VA,12736,Virginia,8001024,15.917962500799897 +WA,Washington,WA,8064,Washington,6724540,11.99189833059213 +WV,West Virginia,WV,997,West Virginia,1852994,5.380481534208961 +WI,Wisconsin,WI,4473,Wisconsin,5686986,7.865326202666931 +WY,Wyoming,WY,403,Wyoming,563626,7.15013147015929 +PR,Puerto Rico,PR,831,Puerto Rico,3725789,2.230400057544858 From 5ffd16d84b6c4cdfd6deb33e66609b9083dfdcc8 Mon Sep 17 00:00:00 2001 From: sovello Date: Tue, 26 May 2015 21:44:49 -0400 Subject: [PATCH 5/6] nightmare working but using a map, not a graph --- complaints_by_state.ipynb | 221 +++++++++++++++----------------------- us-states.json | 52 --------- us_states.html | 2 +- 3 files changed, 87 insertions(+), 188 deletions(-) delete mode 100644 us-states.json diff --git a/complaints_by_state.ipynb b/complaints_by_state.ipynb index 6f7ce4b..16f1231 100644 --- a/complaints_by_state.ipynb +++ b/complaints_by_state.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 304, + "execution_count": 326, "metadata": { "collapsed": false }, @@ -11,13 +11,12 @@ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import folium\n", - "\n", "#plt.set_option('display.mpl_style', 'default')" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 327, "metadata": { "collapsed": false }, @@ -28,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 328, "metadata": { "collapsed": false }, @@ -39,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 329, "metadata": { "collapsed": true }, @@ -51,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 331, "metadata": { "collapsed": false }, @@ -252,7 +251,7 @@ "[5 rows x 34 columns]" ] }, - "execution_count": 12, + "execution_count": 331, "metadata": {}, "output_type": "execute_result" } @@ -263,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 332, "metadata": { "collapsed": false }, @@ -457,7 +456,7 @@ "[5 rows x 34 columns]" ] }, - "execution_count": 15, + "execution_count": 332, "metadata": {}, "output_type": "execute_result" } @@ -468,7 +467,7 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 333, "metadata": { "collapsed": false }, @@ -480,7 +479,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 334, "metadata": { "collapsed": false }, @@ -499,7 +498,7 @@ " '1970_RANK', '1980_RANK', '1990_RANK', '2000_RANK', '2010_RANK'], dtype=object)" ] }, - "execution_count": 83, + "execution_count": 334, "metadata": {}, "output_type": "execute_result" } @@ -510,7 +509,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 335, "metadata": { "collapsed": false }, @@ -704,7 +703,7 @@ "[5 rows x 34 columns]" ] }, - "execution_count": 84, + "execution_count": 335, "metadata": {}, "output_type": "execute_result" } @@ -716,7 +715,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 336, "metadata": { "collapsed": false }, @@ -731,7 +730,7 @@ " dtype='int64')" ] }, - "execution_count": 85, + "execution_count": 336, "metadata": {}, "output_type": "execute_result" } @@ -742,7 +741,7 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 337, "metadata": { "collapsed": false }, @@ -753,7 +752,7 @@ }, { "cell_type": "code", - "execution_count": 195, + "execution_count": 338, "metadata": { "collapsed": false }, @@ -765,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": 339, "metadata": { "collapsed": false, "scrolled": true @@ -873,7 +872,7 @@ "2 In progress Yes NaN " ] }, - "execution_count": 128, + "execution_count": 339, "metadata": {}, "output_type": "execute_result" } @@ -884,28 +883,11 @@ }, { "cell_type": "code", - "execution_count": 145, + "execution_count": 340, "metadata": { "collapsed": false }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['CA', 'FL', 'TX', 'NY', 'GA', 'NJ', 'PA', 'IL', 'VA', 'MD', 'OH', 'NC',\n", - " 'MI', 'AZ', 'MA', 'WA', 'CO', 'TN', 'Unspecified', 'MO', 'CT', 'SC',\n", - " 'OR', 'MN', 'NV', 'WI', 'IN', 'AL', 'LA', 'KY', 'OK', 'DC', 'NH', 'DE',\n", - " 'UT', 'KS', 'NM', 'MS', 'AR', 'IA', 'HI', 'RI', 'ME', 'ID', 'NE', 'WV',\n", - " 'PR', 'VT', 'MT', 'SD', 'AK', 'WY', 'ND', 'AE', 'AP', 'VI', 'GU', 'FM',\n", - " 'MH', 'MP', 'AS', 'AA', 'PW'],\n", - " dtype='object')" - ] - }, - "execution_count": 145, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "ccdata2 = ccdata.loc[:,['State']]\n", "ccdata2.fillna('Unspecified', inplace=True)\n", @@ -914,7 +896,7 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": 341, "metadata": { "collapsed": false }, @@ -926,7 +908,7 @@ }, { "cell_type": "code", - "execution_count": 133, + "execution_count": 342, "metadata": { "collapsed": false }, @@ -1040,7 +1022,7 @@ "2 West 8 Mountain 9 " ] }, - "execution_count": 133, + "execution_count": 342, "metadata": {}, "output_type": "execute_result" } @@ -1051,7 +1033,7 @@ }, { "cell_type": "code", - "execution_count": 157, + "execution_count": 343, "metadata": { "collapsed": false }, @@ -1063,7 +1045,7 @@ }, { "cell_type": "code", - "execution_count": 233, + "execution_count": 344, "metadata": { "collapsed": true }, @@ -1075,100 +1057,30 @@ }, { "cell_type": "code", - "execution_count": 310, + "execution_count": 345, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "text/html": [ - "
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STATEABBREVIATIONCOMPLAINS COUNTSSTATE_OR_REGIONPOPULATION
ABBREVIATION
ALAlabamaAL3842Alabama4779736
AKAlaskaAK478Alaska710231
AZArizonaAZ8678Arizona6392017
ARArkansasAR1670Arkansas2915918
CACaliforniaCA58603California37253956
\n", - "
" - ], "text/plain": [ - " STATE ABBREVIATION COMPLAINS COUNTS STATE_OR_REGION \\\n", - "ABBREVIATION \n", - "AL Alabama AL 3842 Alabama \n", - "AK Alaska AK 478 Alaska \n", - "AZ Arizona AZ 8678 Arizona \n", - "AR Arkansas AR 1670 Arkansas \n", - "CA California CA 58603 California \n", - "\n", - " POPULATION \n", - "ABBREVIATION \n", - "AL 4779736 \n", - "AK 710231 \n", - "AZ 6392017 \n", - "AR 2915918 \n", - "CA 37253956 " + "" ] }, - "execution_count": 310, + "execution_count": 345, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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5SbV25nZJG4ek3HVlDtPoAQAAAGCZYRo9SevmEnO7GIc8acdMbl9uUq2duV3S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\n0tO3n3/u2ZdOmq3RAwAAAHCG7t5/sP3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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -1187,18 +1099,19 @@ }, { "cell_type": "code", - "execution_count": 312, + "execution_count": 346, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "concatenated['per_capita'] = concatenated['COMPLAINS COUNTS']*10000 / concatenated['POPULATION'].astype(float)" + "concatenated['per_capita'] = concatenated['COMPLAINS COUNTS']*10000 / concatenated['POPULATION'].astype(float)\n", + "concatenated.to_csv('per_capita_data.csv')" ] }, { "cell_type": "code", - "execution_count": 318, + "execution_count": 347, "metadata": { "collapsed": false }, @@ -1206,24 +1119,62 @@ "source": [ "#concatenated = concatenated.loc[:,['ABBREVIATION','per_capita']]\n", "#concatenated.plot(kind='bar', colormap='cubehelix', figsize=(20,10))\n", - "#concatenated.head()" + "#concatenated.head()\n", + "#http://bit.ly/ccweek7code\n", + "from IPython.display import HTML\n", + "\n", + "\n", + "def inline_map(map):\n", + " \"\"\"\n", + " Embeds the HTML source of the map directly into the IPython notebook.\n", + " \n", + " This method will not work if the map depends on any files (json data). Also this uses\n", + " the HTML5 srcdoc attribute, which may not be supported in all browsers.\n", + " \"\"\"\n", + " map._build_map()\n", + " return HTML(''.format(srcdoc=map.HTML.replace('\"', '"')))\n", + "\n", + "def embed_map(map, path=\"map.html\"):\n", + " \"\"\"\n", + " Embeds a linked iframe to the map into the IPython notebook.\n", + " \n", + " Note: this method will not capture the source of the map into the notebook.\n", + " This method should work for all maps (as long as they use relative urls).\n", + " \"\"\"\n", + " map.create_map(path=path)\n", + " return HTML(''.format(path=path))" ] }, { "cell_type": "code", - "execution_count": 319, + "execution_count": 325, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 325, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "map = folium.Map(location=[48, -102], zoom_start=3)\n", - "map.geo_json(geo_path='us-states.json', data=concatenated,\n", + "map.geo_json(geo_path='maped-us-states.json', data=concatenated,\n", " columns=['ABBREVIATION', 'per_capita'],\n", " key_on='feature.id',\n", " fill_color='YlGn', fill_opacity=0.7, line_opacity=0.2,\n", " legend_name='Complaints Per Capita')\n", - "map.create_map(path='us_states.html')" + "#map.create_map(path='us_states.html')\n", + "embed_map(map,'us_states.html')" ] }, { diff --git a/us-states.json b/us-states.json deleted file mode 100644 index 3516c05..0000000 --- a/us-states.json +++ /dev/null @@ -1,52 +0,0 @@ -{"type":"FeatureCollection","features":[ -{"type":"Feature","id":"AL","properties":{"name":"Alabama"},"geometry":{"type":"Polygon","coordinates":[[[-87.359296,35.00118],[-85.606675,34.984749],[-85.431413,34.124869],[-85.184951,32.859696],[-85.069935,32.580372],[-84.960397,32.421541],[-85.004212,32.322956],[-84.889196,32.262709],[-85.058981,32.13674],[-85.053504,32.01077],[-85.141136,31.840985],[-85.042551,31.539753],[-85.113751,31.27686],[-85.004212,31.003013],[-85.497137,30.997536],[-87.600282,30.997536],[-87.633143,30.86609],[-87.408589,30.674397],[-87.446927,30.510088],[-87.37025,30.427934],[-87.518128,30.280057],[-87.655051,30.247195],[-87.90699,30.411504],[-87.934375,30.657966],[-88.011052,30.685351],[-88.10416,30.499135],[-88.137022,30.318396],[-88.394438,30.367688],[-88.471115,31.895754],[-88.241084,33.796253],[-88.098683,34.891641],[-88.202745,34.995703],[-87.359296,35.00118]]]}}, 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+++++++++++++++++++++++++++++++++++--- 1 file changed, 1382 insertions(+), 91 deletions(-) diff --git a/consumer_complains.ipynb b/consumer_complains.ipynb index d895494..30b2ce1 100644 --- a/consumer_complains.ipynb +++ b/consumer_complains.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 115, + "execution_count": 1, "metadata": { "collapsed": false }, @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 3, "metadata": { "collapsed": false }, @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 4, "metadata": { "collapsed": false }, @@ -187,7 +187,7 @@ "4 In progress Yes NaN " ] }, - "execution_count": 56, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -198,7 +198,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 5, "metadata": { "collapsed": false }, @@ -347,7 +347,7 @@ "395852 Yes Yes " ] }, - "execution_count": 57, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -358,7 +358,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 6, "metadata": { "collapsed": false }, @@ -372,7 +372,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 7, "metadata": { "collapsed": true }, @@ -383,35 +383,25 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { - "ename": "AttributeError", - "evalue": "'FigureCanvasAgg' object has no attribute 'invalidate'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in 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\u001b[0;34m=\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_active\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m \u001b[0mfigManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvalidate\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 238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'FigureCanvasAgg' object has no attribute 'invalidate'" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" }, { "data": { "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -419,9 +409,9 @@ }, { "data": { - "image/png": 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m7ePkX7A+YC1gcbsCiOBJYC7wwTqqHwn8aKChnRGsBg4BDpQ4tI5jvREP8zTr\nFM1L/pI2kfQzSXdKWiRpvKRNJc2TdJekqyRtUlX/OElLJC2WNLGqfJykhWnbjLzxDIfEVRJH1VF1\nb2BeCRJgza4fiZcBB5A9HDagCB4B9gdOScNBq/ffVOJAif+SWAzMIbvhbGYlV8+yssNp+c8ALouI\nncgmOVsMHAvMi4gdyboajgWQNBY4mOxJ1UnATEmVuWxOA6ZERB/QJ2nSMGJqWFpNa3fgOImP1aje\n7v7+il8DL5d4wxB1PgxcFjF0N00EC4GjgJ9LTJaYLnETsBT4GHAv8AHgFRGcUkj0ZtYKjw21MVfy\nlzQS2CMizgCIiNUR8TgwmaxVSvq9f3q9HzA7IlZFxFKyB4XGS9oK2DgiFqR6Z1ft0ypjgXvIRvF8\nVeKjA1VKN0Yn0N7+fgBSN845DNL6T/cmjqTfjd4hjvczYCbwOeDvwL8Dm0WwbwQnRXDLMJ4KNrP2\nWDnUxrzTO2wH/EXSmcDOwM3Ap4EtIqIy78sKYIv0ehRwfdX+y4CtyVabWVZVvjyVt9IuwK0RLJHY\nC7hGYnXEi7o4dgWWprHyZXA28BuJL6b++2p7pN/X1nuwCKYD04sKzszarinJf23gTcD/jYgbJZ1C\n6uKpiIiQVFjfuKRpVX/Oj4j5BR16F9IavBH8ScpG86QPgNlV9crS5QM8H+u9wD7AL/tt/gTZjd52\n35swsxaSNIE0QzActdlQdfMm/2XAsoi4Mf39M+A44CFJW0bEQ6lLp9JKXg6Mrtp/m3SM5el1dfny\ngU4YEdNyxlrLLsAvXjgPiyQmAvPSB8BP06a9ga83KYa8Kjd+n0/+Eq8A9gWObldQZtYeqVE8H0Bi\nBzitb7C6ufr8I+Ih4AFJO6aivYA/ks0cWemHPhy4OL2eCxwiaV1J25ENmVyQjvNEGikk4LCqfZou\n9Y3vDNxWXR7BHWQ3pr8vcYDES1O9urtRWuQCYJ80sqfiI8DFEUN/5TOzrteUbh+ATwLnSloX+DPw\nUbIx8HMkTSEbLXIQQEQskjQHWASsBqZGRKVLYirZcMQRZKOHrhhGTI3aFnh6oBExEdwm8S6ypRYv\nBG6oZ/hUK0WwUuJKsvH6p6V1hY+Eusbtm1l3GzL564UcXF6SIiIKX+RcYj/g4xG8e4g6byEb4XNC\nuilaKhLvBv4jgt3SDeuTgDe6v9+st2WTOuqJwXJnry/m8vzN3sFEcKPELlCaUT79XQmcLvFq0jw+\nTvxmFsGtJvVYAAAKrElEQVSTGqLJ3OvTO9RM/gAR3BvB31oQT8PSMM9zyUZbvTO9NjMbkpN/Hcm/\nA8wiu9F7QZr7x8xsSD2b/NNi5JuR3azuaBHcDpwP/KDdsZhZZ+jlPv+dyRZh74ppCyL4QLtjMLPO\n0bMtf7qny8fMrGG9nPx3xsnfzHpULyd/t/zNrGf15ENeaQ7/x8imLX66qOOamZXJULmzV1v+ryGb\nntmJ38x6Uq8m/13oN5mbmVkv6eXk7/5+M+tZTv5mZj2o55J/1Rz+Tv5m1rN6LvmTrRb2bAQratY0\nM+tSvZj83eVjZj3Pyd/MrAf1avL3ME8z62m9mvzd8jezntZTyV9iJLAlsKTdsZiZtVNPJX/gDWRz\n+P+z3YGYmbVTryV/j+83M6P3kr/7+83MGGbyl7SWpFskXZr+3lTSPEl3SbpK0iZVdY+TtETSYkkT\nq8rHSVqYts0YTjx18EgfMzOG3/I/BlgEVBYFOBaYFxE7Alenv5E0FjgYGAtMAmZKqswxfRowJSL6\ngD5Jk4YZ04Ak1knnX9iM45uZdZLcyV/SNsC7gJ8AlUQ+GZiVXs8C9k+v9wNmR8SqiFgK3A2Ml7QV\nsHFELEj1zq7ap2ivBh6I4KkmHd/MrGMMp+X/PeDzwHNVZVtERGXOnBXAFun1KGBZVb1lwNYDlC9P\n5c3g/n4zs2TtPDtJeg/wcETcImnCQHUiIiQVtkakpGlVf86PiPkNHsLJ38y6WsrHE+qpmyv5A28F\nJkt6F7A+8FJJ5wArJG0ZEQ+lLp2HU/3lwOiq/bcha/EvT6+ry5cPdMKImJYz1oqdgZOHeQwzs9JK\njeL5lb8lHT9Y3VzdPhHxpYgYHRHbAYcA10TEYcBc4PBU7XDg4vR6LnCIpHUlbQf0AQsi4iHgCUnj\n0w3gw6r2KUyaw98tfzOzJG/Lv79K9863gTmSpgBLgYMAImKRpDlkI4NWA1MjorLPVOAsYARwWURc\nUVBM1UalGB9qwrHNzDqOXsjB5SUpIkK1aw62P+8GjolgYs3KZmZdYqjc2StP+LrLx8ysipO/mVkP\n6vrkn57sHYeTv5nZ87o2+UtsIPFJsqeJ/wTc1eaQzMxKo+uSv8TLJL4C3Au8HTgogn0jWN3m0MzM\nSqNrkr/EKImTgD8D2wMTIjgwghvaHJqZWel0fPKX2FDix8AdZM8t7BLBRyO4s82hmZmVVlEPebXT\n94CXAztG8Nd2B2Nm1gk6OvlLvB94B/DGCJ5sdzxmZp2iY5O/xLbATOA9TvxmZo3pyD5/ibWA/wFO\njmBBrfpmZramjkz+wJeAVcCJ7Q7EzKwTdVy3j8RbgaOBcRFrrCJmZmZ16qiWv8RI4FzgyIiBF30x\nM7PaOmZKZ4iXAOcBj0ZwdLtjMjMru6GmdO6kbp/DgdcDb2l3IGZmna6TWv5/Bd4RwcJ2x2Nm1gm6\nZTGXaU78ZmbF6KSW/0siKH+wZmYl0RUtfyd+M7PidEzyNzOz4jj5m5n1oFzJX9JoSb+W9EdJd0j6\nVCrfVNI8SXdJukrSJlX7HCdpiaTFkiZWlY+TtDBtmzH8t2RmZrXkbfmvAj4TEa8FdgOOlrQTcCww\nLyJ2BK5OfyNpLHAwMBaYBMyUVLkJcRowJSL6gD5JkxoNRtKEnO/DCuTrUA6+DuVQ9uuQK/lHxEMR\ncWt6/RRwJ7A1MBmYlarNAvZPr/cDZkfEqohYSrao+nhJWwEbR0RlZs6zq/ZpxIQ878MKN6HdARjg\n61AWE9odwFCG3ecvaQzwRuAGYIuIWJE2rQC2SK9HAcuqdltG9mHRv3x5Km/UmDrinNDJ28sQQx0x\njqmxve0x+jq0JgZfB6AE12Eow0r+kjYCLgSOiYg1FlSJ7AGCVg3PHFNHnQkdvr0MMdTaPqbG9lbE\n0OztZYih1vYxNba3IoZmby9DDLW2j6mxvRUxDC4icv0A6wBXAp+uKlsMbJlebwUsTq+PBY6tqncF\nMB7YErizqvwDwA8HOFf4xz/+8Y9/Gv8ZLIfnmtgt3aw9HVgUEadUbZpLNgHb9PT74qry8ySdTNat\n0wcsiIiQ9ISk8cAC4DDg1P7nG+wJNTMzyyfX9A6Sdgd+C9xO9ukCcBxZAp8DbAssBQ6KiMfSPl8C\njgBWk3UTXZnKxwFnASOAyyLiU/nfjpmZ1aMj5vYxM7NiddwTvpKeancMRan1XiTNT9+MSqdbrkMn\nXwPwdSiLTrwOHZf8eaGbqRvUei9RR512KWtcjerkawDljq0Rvg4t1onJH0kbSvqVpJsl3S5pciof\nI+lOST9O005cKWn9dsc7FEl7Srq06u8fSDq8nTHVq1uuQydfA/B1KItOuw4dmfyBZ4ADImIc8A7g\nu1XbdgB+EBGvAx4D3teG+Iaj7C2cat16HTrpGoCvQ1l01HXopDV8q70E+JakPYDngFGSNk/b7o2I\n29Prm6nvQQvLx9ehHHwdyqGjrkOnJv9Dgc2AN0XEPyXdC1S+Rv2jqt4/yYaQltlq1vwGVvZ4q3XL\ndejkawC+DmXRUdehU7t9RgIPp//Abwde2e6AhuE+YKykdZVNgf2OdgfUgG65Dp18DcDXoSw66jp0\nVMtf0tpkn6DnApdKuh24iWxW0Yr+fYSl7DOsvJeIWCZpDnAHcC/wh/ZGVlu3XIdOvgbg61AWnXod\nOuohL0k7Az+KiN3aHctwdfJ76eTYq3X6++j0+Cs6/X10avwd0+0j6RPAecBX2h3LcHXye+nk2Kt1\n+vvo9PgrOv19dHL8HdXyNzOzYnRMy9/MzIpTyuSvBheIT+W/lvSkpO9XHWeEpF+mp+vukPStdr2n\nTlTUdUjbrpB0azrW6ZLWacd76kRFXoeqY86VtLCV76PTFfzvYb6kxZJuST+btfr9lDL50+AC8cDf\nyfrcPjfAsU6MiJ3Ilpr8V+VYIL6HFXkd3h8Ru6RjjQQObnr03aPI64CkA4EnKcGIkw5T5HUI4IMR\n8cb089fmh7+mUib/RheIj4inI+J3rPkgBRHxTET8Jr1eRTZ0LM8awT2pqOtQtT+pxb8u0PL/2TtV\nkddB2dKrnwG+CXiRpAYUeR2Stv73L2Xyr6b6FoivGLQlk76KvZfsk9kaVMR1kHRlqv9MRFzRnEi7\nWwHX4RvAScDTTQqxJxSUl2alLp+2jBQqdfJXQQvEp4cwZgMzImJp0XF2u6KuQ0TsQ7a283rqoNka\ny2K410HSLsCrIuIS3OrPraB/D4emSd72APaQdFjxkQ6ttMk/dQ9cCJwTEZW1gFdI2jJt3wp4uM7D\n/Rj4U0S8aH1gG1rB14GI+Ec63luKjrWbFXQddgPerGzOmWuBHSVd06yYu1FR/x4i4sH0+ymy5wR2\nbU7Egytl8pdqLhAPay4Q//yuAxzrm8BLyfo5rQFFXQdl85xvlV6vDbwHuKUpQXehoq5DRPwwIraO\niO2A3YG7IqLT5s9pmwL/PaxVGd2TPkzeC7R85FUpH/JSvgXilwIbk91MfAzYG3gKuJ/sxsyz6Tjf\nj4gzWvE+Ol2B1+FR4BfAemT/EK4EvhBl/J+vhAq4DiuBiRGxuOqYY4C5EfGGVryHblDgv4f703HW\nAdYC5gH/3up/D6VM/mZm1ly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HYUFcU9dx2pWa0jrnjfP/GPBXM3seQNJVwH8AT0tax8yeji6dSi6XeYTp+RXW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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -430,12 +420,12 @@ ], "source": [ "plt.figure()\n", - "ccdata_bydate['Date received'].resample(\"M\", how=[\"count\"]).plot()\n" + "ccdata_bydate['Complaint ID'].resample(\"M\", how=[\"count\"]).plot()\n" ] }, { "cell_type": "code", - "execution_count": 120, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -447,7 +437,7 @@ }, { "cell_type": "code", - "execution_count": 121, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -459,7 +449,7 @@ }, { "cell_type": "code", - "execution_count": 122, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -470,7 +460,7 @@ }, { "cell_type": "code", - "execution_count": 123, + "execution_count": 12, "metadata": { "collapsed": false }, @@ -478,10 +468,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 123, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, @@ -489,7 +479,7 @@ "data": { "image/png": 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YXHpmZrtkHvApid3KDqRsQ5oTkDQJOBZ4AJgQEZvTS5uBCWn5AIoHPPfYQFE0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\nzEXAzKyDuQiYmXUwFwEzsw72/wHj/L/oEhQ6ewAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -501,15 +491,19 @@ ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": true + }, + "outputs": [], "source": [ - "###The mean number of complaints by day of weekday" + "ccdata_byproduct.index = ccdata_byproduct['Product']" ] }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 15, "metadata": { "collapsed": false }, @@ -517,61 +511,61 @@ { "data": { "text/plain": [ - "56551" + "" ] }, - "execution_count": 119, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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WVOfE1cT/BtX3O5mxGvgXIY5sQ+E+uPTxFpzTJnHe18EUW2prCf60U4C7zXgt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\n49pZP7AVYlCWkqSBc9LHDVw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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "math.ceil(data_byweekday.mean(axis=0))" + "ccdata_byproduct['Product'].groupby(ccdata_byproduct.index).count().plot()" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 17, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ - "ccdata_byproduct.index = ccdata_byproduct['Product']" + "ccdata_bycompany.index = ccdata_bycompany['Company']" ] }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { - "ename": "AttributeError", - "evalue": "'FigureCanvasAgg' object has no attribute 'invalidate'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in 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\u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/matplotlib/backends/backend_macosx.py\u001b[0m in \u001b[0;36mdraw_if_interactive\u001b[0;34m()\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_active\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfigManager\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m \u001b[0mfigManager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvalidate\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 238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'FigureCanvasAgg' object has no attribute 'invalidate'" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" }, { "data": { - "image/png": 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W2PhB6IMYX/GplOBD9LEy/Tleg/fXiblJ5noIqfxS5+Qs+D6NQWrbEE7eSrmi\nhpxZWv4QqYYvV0/Vi2aV0WWV963XML+P0gSvWgaUWPCPbn/tnh9KN+ZlwQ9BjOANudV/PKYheL8m\nqB+cfgWM9SRS5NyHLHIWdld+fjumjefILqXB95GNSqQNn9Zf3yO04H0DYgjf71QPpI8Fn6v/1DmV\n4OeMLqu8LznNwt96Hugi+NAF0O7Bk1MMuantM/WDF+ED7YShf02cc5BLn3u2s9LgYbys3oL3jc7T\n3XaK1Eq05hINPiXRpEgpFh8nR2ClMkUf0psFwecGTGPvRapH00eDL+npLEaDF5GNIvJZEXlXu32E\niGwXkYtF5P0isi1I+wIRuURELhKRh0xz3SXArAk+5bWwaMTKEb4z1wb/95Gtchb8ykzBNh7MybAS\nG+Y3OvKNlfeBwH2BRyXO8ZEtc9Phc+hrwYd5G8HbtXO9ivDcLuIaqsF3Xa9EopmmZ1AyWN6nUSi1\nlsMQEr6XEXu/UyTdZ8A0p9vnJJpV0eCfTTM92wpwJrBdVU+icRM8E0BETgEeC5wCnA68WkTWcu+h\nD8GXEN+yeuV0WfDhAg0lL1ysS+/z9lPBw9mwdxfhVqGVLcI9RDg2Vl6RlTy2BPtu5a7pI0SeN1Eo\n4eGx/IHvAd935c0R/CVhtsH/RvB2binBe0zjRRPCW/Bdg4cx6zx3nVJi7NPo5FA6eJsj+JIyDCHr\nIVLZ/C14ETmOJo7H3zN6Ic4Azmn/P4eR1fRI4FxV3aOqO4EvA/cceu0lwMwJXoQHivDTU5RpHlCY\nkC2mIfixtCLc1UVsjBF8OFFoA7CT8TU/Pwm8KSxvAOtBhoTpJ6B5go9Z+j+VyH8jI59wa4hWCF6E\nWwJHB+ljMgj0J3hL5ycklXT3p9HgS0ipj3dIqcYfwzRpcxKNL1vOgjek7jlG8F0NYMk5xRZ8Tgvt\nwl8Cz2fcLe5IVbUoeLuBI9v/jwH+O0i3C1asrrWIeUg0HyC/nNgiEMaOMXe01IITD+yRr713n44c\n8wS/V4R/c8e8l5ERpP/ILfTAwZF9hlyM919rf1PP5caMLHi7RmjBf82lD+srNK68RBNbaCKED2u7\nn3Hrs0S7LiHIPo2Bz79EppiHRJNL27X2a1+Jxuc/RE/P1W2u13WcCBtU83U1yIIXkYcDV6jqZ0nc\nuKoqZa3qWkQXwXetz+mxrIOsRjjhwGmK4G8/IF+P0II3otwB/Gz7v9WTXwzZx1vxCHV2P80+R/D3\nb39tMNnv2BHLAAAgAElEQVTn78P+Qt7zJkwb1qMNrtq5scWec+hjNZeQkX+/u4i3hJRi6Ut7CLlr\n9mnUugg+Nsi6WhJNjqhjaZ8P/HLmHGC4Bf9TwBki8jM0L+dhIvJGYLeIHKWql4vI0cAVbfrLGA9c\ndVy7bwIiclawuUNVdwwsYyRvjgCuUx0bHByUVZDnV1X5MXc8FZ2wM78lQ2x2alhWZWQ99oHl588N\nCd6s2JCcUwTvF7XwCC1i/yGVrNKU61nNguC9ROMni3mkCNjffx+JJoYSGcGjRK7oamRmLdH00eBT\nbpJDLPhpNfhM/e8AXvkkkbefkCnXMAteVX9fVY9X1VsDjwM+pKpPAt4JPLlN9mTgHe3/7wQeJyJb\nROTWNNOtP5nI+6zgb8eQ8mXwXSKDaAMQPuyJhR8yabvSLBvRx1wffYyP3hEXGVmsP3LHw7xi1slQ\ngg9dIQX4drBd4tbpZzWG6EPwpRp8yWSxMI8+XhxdBBNLO0Si6UNcfcrU5zr+ekMsePuNceU0ZF1y\nz5n6PxV428eNKyNlSxZ6COzCLwEeLCIX0wxmvQRAVS+kIdYLgfcAz2wlnEXgxBnkMcuZrGEa772w\naFh5chb8IIIX4cFMdn9fzoiMnxA5397XoyPHcghJN/yIv0bZZKZU4CnoR/ApDd5gPepSgvf5lhBk\nibWc8qIp6Sn0sfb7lMljXha8L7fNbM3Npu3T0ykl+hCpfDvXLZ5mkLUpjepHgI+0/1/JuIdDmO5F\nwIumvd4McNIM8pja0hbhcEYeG8tuwecIfggOAt4f2X8aoyicH2fkveLLcxcR3gArUSqtJ5Aik62w\nMsPYW2klFnxOh52FROPP7ZJoUvn2sQZLrP0++c+yLNOUKYbUdTxmPcjah+CHjJt0eVtNT/AHKGZB\nxI8CXt/+v6xzAsYkGhEeR+OSeAWNW2CJdRZDzvIwcvMRKMPyHEYzr8Ianm+JcDZwy0SeoZeKJ/hO\nK4iRBR97TkMlmlhedm7JuECYX4kVOEQGmYVEEytTqgcwzfhADt4aLyH4Eg2+q7Ec0uj0aQg7391l\nJZZlxywI/pvB/6tuuYvw8yLNiyPCNpGJ1ZdgUqI5g/FV6bss+Hcl9udeTJMnYivchwOwfvm25zM5\nK9Vfzwyakg8wRGwxE7+whSFG8LG0MSu9rxeN1+D76NE5YikNVRDDEI1/iKwzpDHokmhyXjQ5rhxy\nH32eWarR7LTgK8EPwyw0+D2RNKupwd89+P/HgTtG0qTiy3S9wCnr6j/b3xyB5QjeynMw4/Xa9R6H\nBB9+xKX1HHMXTa2LmiP48CP269WG1zmIvO5vSA2yTjPIF6JU585p8Ll8V0uiKSXeaSWaEimoj0ST\nOqda8HPGLCzu2GzXRWnwqev6AFp9P3g/4euTNPLOzTNlMYKPaeNWHj8RqJTgNxK30rpwl0iZzDe+\nhOC9NPBt4nUQ9hByrpldfurTWvCl58QwpAGZRgrqMy5Q4kXjy52z4PtINKl4U7m67JLgOiX2SvDD\nMAsiDh/OogdXuwi+q8tuuMyl8++X0BDXzTJlsW5njODFpfH7m41mFakQfS34r7vtZ7W/YcPi10W1\n380iE9a5J5bvE/84w8bBLPjvJcoYXnOIBpyrg75eNLky5XoTfc5JXadPYzaNRFMSZTTVuMUwzbOy\n7Urwc0IXIYfHx9wyRbiRCCcw/nAW8RxMfz/ZX1+EW4jwH6R7FqkP3X8cKxa8CKcw+oBi8oRhi/sN\nsYGyRayfIzLmgWME/wXiH7EPX5D62MKGKbW49EHAbhGOC9KWSgSbGd2fEcuuRFqYzg9+FnKCT5dL\nO6veRFfZYmm8Bt9HorHfkmiSqbqNoU8jVgl+lSFMkkKIXMX/IXApeYlmNTR4w4VM+pXfiSbcQl8L\n3r+I4fv1RcoI3qzYlERzdbB9aeQ60Exo+89g2wj+SOIE7+8jVf+3iKTx9/yy9je0xrsWkTCEwctK\n5JAuDT6GWUg0OZTk39XIlLz/fRqzUgs+p8HnuLKkge3qFfWppyrRJPAdGI+OKMIh5k3SA6FWF0Nu\ndNt8tsOHc7JLky1PGzK3xL2vFKkXpYvgUxZ8SoN/bpvmSNIwyz1G8A9jfPDRyh0j+BB+JmsXwceI\n7BrGdfMugvEzfnNpw7LZ+9FlbYb5pPLtQzC+HLE0JfdR0luZRntP5ZFLU9qDGjrI2uc6feQuQyrf\nSvAO721/w4c1IQW0MWtyyBH8fhjrnnuYe2Qs4mTyJRLh20Es851MP2lMEv/H0vQleIMPzWtpctES\nzfKNSTRWFhu0tEbAv8dh3VzFpLdBquueGjiFRje/abDd9TFv6ZHWEMZCmYU1O1SDxx2bl0Tjz5lG\noonVaUraSNV/bHymzyBrSeM5i/GMSvAJGFFNLJwrMlZZ3xUht+pUjuC/BpyQOTdmwZfgZoxb+rmB\nSqCZuSnCqe0koBxS4Y2nlWhi6Orm5yx4K8tVLm3uPd7DeIOSs+At1HWs/HtdmVIf9Q/b31zaIRpw\nDCk/+JLufu5Zdnl8DCHr1ZJoctcp0eB9mllJNB4ljWdXPVWCd4gRfOhbHSLnypcj+B+St1Dt4aQm\n5eQQ63LnsI8mHtDzO9JtgTHpytfTUIkmBktzTeK4DUqXWPAlBL+X8R5VjuBz5d9H3iq3c2JeQCnS\n8IgRTE5CMZSQRWkjncu3z/MdYqnmrP5Ur2GW4w19JZo+jabHLBqzznUnKsGP9qW68al8UseVfMXb\n9XLT0XN5G7LPTmQlTktJXJOU1NHXgvfHr2MSuWMhcgRv19ka7EvBk2msG+4/5pS2nNPV7Tc2Oczn\nW0IwJRp8qiy56/SRTkq18phEM8Qy7VPuEtLuS/BD3SRT+Zc0niW9rirRFKIPwXflk9Pgc/Vq1+sb\nUAp3TRHhMBHukEhr8fdTs0bDvOzeY37r4a9hFhZ8F3GlYrqEdW8Naa6+YwSf+vBz5S8leMMhPdIa\nSiWarolOOQyx9lPnxLy+ptGY+5B1n8ahT/2nZJ1Ze9H0uedUmSrBO+QI/mAAEU4tzGflgbg1S2dh\nwZdgA41L3gWJ42YBlzRc4UxPfw2YrQZfYt3kEBt7KPn4wrQpK63Lgt/otsNff85NMmlLCKYPaZdY\njl2NQuycPiTalW/Ogu+jR3cRfCzaaapOP+XK3teC78p/VhJN6l4rwTvkNHgjuWe3v/8ksuJ1E8sn\nJZd4IkiVYWoLHrLePvbw92bSGIYS/Dwt+BxipJ2Ct+DDYGl9LfgYwadIdYgFHxJMl892iJTnTR9S\nyqFU4oilKdHTp7HCS2Sd0ufc1w++yxrPNZp9JLJU+SvBO5RINOFyfg/N5BM+mLCi1eXvLfwiC16E\nN7jZkJa3YQN569zKVBK0qpTgDSmiKtGaSwj+B5ljsXxjL/qliettjJSvj+Vl6CKLgyJpu0i1dJDV\n0NXwxqxZv52z9kt0Yr9dQvCpMpSUv+tZ5az+rmc21IIvuefS+EExpJ5D52I1ByrBx2aR3k2Ez+KW\nkRNpvF1EEBH+NDgnfCA+dG2UKEV4IfCGdl+XBf8k4HS3zxN8brGKPgRvnh9dGnzXSzkrC/77bvtL\nbtvnH3vRU2UtseDnRfAlEo0nlmnKMsTzIzyvD4GlypKTaFLn9NGjSySmUqmpbzx4f53ShjxWhj7y\nl6XpDCt9oBJ8zIJ/IHBnJiWNP2p/D6EJM2DnKPD3NG6RoQW5n/EFxsPr3TvYl7Pgn9j+5jx7hDKC\nNz//3LM2greGaVo3yRLtMZfGL4qeW1EJ4h43KV09R/A5WaTrXv39hG63pVb5rAZZYwQ/i0G+PtZm\nHwmlD9kNSVtqLc8zVMGQe/Xn+vy7JmRWgg/+NyvQk4mRbOi3bgT/Yprwt16i8T71N4jwaMYbjxIN\n/iARLhDh/MixCYlGhC+KrMSV2ex+t4mshL21chqsofBeKZ7wDSnyyX1AX3bHcmlT+RpKJJoUqW6K\n7MuR6bcj+2Ln+DLFCL5Eopllb2KoBp/ys8+RUKosfSzrIY1NriHx+7pmCeckmj4zWW07N1u8RO7q\nDC/h5N8JHKgEf0i76HO4z4jQW/CHiXAujKQaRgS/n6YOvQUfw10Yl0tKVu05CrgDo8U5vLTkLfxT\ngrRWJrNunwR8JnEdS7PR/W6mecFTL1qfD7TLar4hSJuylmPHvST2rUT+MQt+CMH4MqWIclqJxpc/\nhtRM1hKCH9KApO7VP49YWWZhYefOjd1zXyluVrFocvWfKlufc8L6yQ60HqgE/x+MFn22fUZyX3Xn\n3Al4HCNJZQMjglcmCT71cm5mnOBjM1m9Xn4Xtx0S2RnAMQCtlb+t3W/xUvwqRDdq02oQ0yYsG0xa\n7ptpXqo7twHZUh9kSXe8i+B/GKTtQ/D7GK9/v7iGL1tfDT7m653L3/BTkbQlFvyQWDQlBNNllfd5\nZiXn5PJPWa3TSDQxdBkiHjENPmaNe5Q+31jZ+shesfyzBH+gLbptD+mYyD4jOT+F3j44s7hDgt/f\n/l9iwZcQ/F7GBwwPd8f94K2R+R2An27/3yLC44FfsO329+nBeZ7guyz4X3T7U5JDjgD6yCJ9CN7X\nvxF8SqLp6yaZ+rC7SCNcErHUQu07yNrV4JZY8H5/eF6KWIb0EKa14IdINHSk9ZhWosnVf+k4Vu7d\ni71rleADxF5Ie3BbEmmsMo2Qh1rwmxiXf2Iujl4e6iL4EBY7ZxPw5mD/Fhr549bBvhsDv+LShPnb\n7yaaF/z27bY1KH3ImkSanATRh+A3Ml4v3oL3RJlzkxziuVLirz7rQVZDyrvJHw/LlyKlPhZqjpT6\nNOBdZF1S/mkkoD4a/Kzklj7lT50bfjPZeDQHqkTTbAiHMnJb7CJ4O/4Z4OcZt+BjE2A8vAWfc+0z\n+FHyTSKcl8jfCN7nu4XJxUkOodH3DV6a8RKNIaX5lnzUqQ8nR/A2S9fn58s0a4mm5GPrc04paQ8l\n+FTDFPMW6yNxGPrca4rA9kfSdJF2Lv+Sc0qlGUNfN8muuuwzyN2noaoafAK+wu9Fs3IRjIgxRfB2\n/BQa//TQgo/FKPHYSrdPurfg/UDsNkZyiceLgzQhNhTkm/KeCT1OIG0xlhBAKk3sA0o1Bp9I5B+z\n4FNadombZOye/TVLPWNiZchFk+xLSrEyxOo/9V7H0NUYTKvBd51DYrtvmVL13qeBzUk0XZ4x0/SK\nwvNz70Ql+AC+wkMdvJTgoXnooQWfmzFo2EY3wfsP31vjN6UbsQfuCf5v3ba33L1EY0i9cCkyLem6\n5yz40rQhwafkEPstcZPsY42XEFjpwGksVEGMjPxzSDU2OQ24hIBT1mYOOcs9lW/JdbpkHUOJF02q\n/ocSfOpd6OsRkytbeE74Wwk+gK/wMG57l0TjZ6uGFnzspfK4Cd31nXtZoYzgY5OfPMFvYTxImRHk\nVhG2MjnI6svTJdGUWPC5c1IWVypt+JJ76SdnwZdadmHaEmLf6bb7SDR9vGhSEk2MYDa4YyXWfqkE\nl2vI+2jLsz5nlgQfI+tUPYX5+bSGPo1mqiHcSyX4MQyx4H2sGhgRfB8L/jDGPVli6HrYJQRfMqtz\nL+PP3gj9d2jitHdp8LP0oumjnabyzUV5LJnJmiPV0hmgsXtNlamPRFBCACUE7wfjSqzNPta+Pydn\nyXfp0D5diK76H/rO+XNyEmJpmaat0653bw91kHUMJRb8g10aq8BwZuKDGbfgcxq8PZwNkX0edu7V\nieOpVaBCKztnwVucHV9m+99i35hV4C14S5f6eHMva5d0EvsYSj5Q301Nkbb9TusmWULw/v7nPZM1\n1QMpseBL0EeW6iPr9OkBdsk5uXMMfSSmPhZ8H4L31ylpNA3+nvdQLfgx+AoPSdsI/udcGqujV7j9\npRa897OH8VmbIbpirqQeZijB5AjeVlHyBG+NmMVaf0T7u4U8wU9jGZV8mKUSTcyCT8WieThpkiiR\navpIKKm0fQg+Z9kZ7Pn6/HNeNP6cIb0WItt9nm8fsk7lMYTg++jcfWYSD7HgS8qUqq9K8IZ2Ee0T\n3O7QgvfxYwypOgotePOLh3T3PCReT/C2iHQXwaQeZpg+JtHYxxwO8sasO4MtOH4Y4y/ew9rfPl12\nX8YSC7WPhOIt+K4B35+KHMuVKTWgmfvwu/ItIfgS//ouDT7ERnfMu5PG0CUnDJ3dmSLePmRXItH0\n6SH4c0qec1eZph1kLZFoKsG3eB9wW7cvJPhY7JAcvAWf+nhtO3RNNIK/sP291qVNvYCp+M9h+hzB\nx6xxmNTxrCHYQrwuuiz4Eu00R3apDyZGel1kkWoUStN69JEpUj75OYIfEqogVaZcI74nkxZ3bBpr\ns8TCnkb66dNTGPJ8Swi+pP59mfo8X38d+62DrB24UWJ/KHmkFn82gj8UOJLuFjkMD2wEn/L4SCH1\nMMNr5iSa8GUN8/LvQXj/ObJOSSm5Mvb5MEsIOEXwucVHhhB8V/lj56Seb6qeYoZCiUTj878hks5r\n8DmX3b7jDiUSzTQSUO6afc4p6RXNW6JJlW1IL7gOsnYgRfD28u9lMra7wSQagPeQJrmcBd+nOw5p\ngg8fckjw4X2E14Hxhmsj4x98eCxGRl0DpjF0fcyxcYwSDT5V37kPPyUfxJ5DF5nm8u9L8DGJpgS+\np/Dd9jfmReN7F32s5hIyGkJcQ6zamPSTSuO350XwPv8hk6NyDaG/5yrRRHB98H8qZG9IiLFFnmFk\nwROktf0hYi+gkWlfCz4l0YTyUkjwdq8xN0lP8OFKVlsZJrcM0UP7SEAlFnwJmfbJfxprM5W2D8GX\nkJ2/ZwtNUWLBz6rXlTpnCNH3efeGyDrryYKvBO9gRLaX9KpKnoC/G0kTTiuHNKHkCL7kY74o+D98\nmJ+MpIXxRssI3lvwexhvLDYyuYqSHxcIkSKs3IvddU6fxqCE4HN1mvrwh3ThU+WA7rg4HqVeNB6e\n4L8Q5Gfo8rwJ0RX5sMsQCdOUSE1D5JZpJJoc+oSg8Ncp+Q5SVnmf/OdL8CJyvIh8WES+KCL/IyK/\n3e4/QkS2i8jFIvJ+EdkWnPMCEblERC4SkYekc587jLj2kCb4ve439mL4SUD+4b7X7Q/RNdsyRHh+\nzFvEI5wMZVKQv48bmLTgr3VpzKUyVv5ZWEYlsk6pm2TJdSzdpXSXPyfRlFiQXRJTiQVfUj8pC/I9\nNO/2UA3eI0V2fRrnIVZ/nzLl3o0++aca/RxS+ZZY8H0aQP87Nwt+D/BcVb0dTcCuZ4nIycCZwHZV\nPQn4YLuNiJwCPJZRoK5Xi8iieg8hwftwvATHIO8qtZnxh1ISj8WnLbE2UwOjqQ8/JPjUdW5gXMrZ\nwIjQr3NpZ9Ud7yL4mAbvP7LYx5DqMaU+nNh7V0KqKdLOWY6ptCnSODhShhKym9DTVSfWNZiFm2SJ\nNevPjUHcb+p6uXyHSECzJvg+oSJS1+kj1cTKluXRQSSrqper6ufa/6+hWfX+WJpVhs5pk50DPKr9\n/5HAuaq6R1V30qzPec8h154BjOD30ni/xFBiwW8lbsGXkIV/Ify2RNJCnOC9JRau9ervIzwnHJjd\nGKQxCatE4uhDRn3qJ5V/DCkyTZX/VqSJKzcW0nXP0+rFXefk0CcWjcG7SYboilvTp1EoQQnJdUk0\nJfn2qdM+BJ+SgvoQfA6pd28+BB9CRE6gWVruE8CRqrq7PbSbEYEeA+wKTttF0yAsAmah7iEd26XE\ngvcafBdph4g9qK60EJdowkFjj3BQFSatN0Pof+11+xKJZoi1P4Tgcx++f2YlsktJD2EaL5qu1aVi\n6CMNpMpkiBG87etD8F0ac64OSiz5PucMeTeGlKmrtxVLa/l7N9XY+zREook1tLlGZDqCF5FDgLcB\nz1bVsfgpqqqUPai5QWRsFSPDHvcbwj/U1K9PD+kXLvaC9JFoQjL2ES3D3xg8wXviMYQWfIqUQpS6\neg3VQ0uI16ftM3Dt5YrcOV0EH0OqV9GH4HNpSxudmJukGQn+HTD06Ynkzu9jLfvrDLHkS9LO2oL3\naT3Bl/DrXCWawUv2ichmGnJ/o6q+o929W0SOUtXLReRo4Ip2/2WM+5Mf1+6L5XtWsLlDVXfky8Fx\nwHZVTnb7TwQuJu09ECN4WxPVE2P4AdmHIqqojHJPjb7nJJoSy65Losm9EKkGJEbwMVfKrvz7fDgp\n4oqR0RBrP0XwsXP85JAcgQ1pzHzaIRb8LCSaWEA5u/fU8w3XBU493z5SU64H1TWI2Ddfj1RPM4dU\n7y6HFMHnvGgMfaSa4Do7gLeeAJ9/gsjH7pY6YRDBi4gA/wBcqKp/FRx6J/Bk4KXt7zuC/W8Wkb+g\nkWZOJOHmp6pnpa/LacBDVfm9YPfxwE+IsEF17MNJyS/eUg2xjzjBlwxIdRFYLG2JBR/mk4u5Yv+H\nH3WpVR4SvE87pOsYw5CudQnBpyz4HBGkLPiS7nIfa7xvqAIo67WUnhNb8GOTSxubxewJvus553pq\n/voxlLxHqbLknvO8LXh7j7oIfh+TXOvL5PeH50fu+VTg1IuB81T5VxH541gBh0o09wF+CXiAiHy2\n/TsdeAnwYBG5GDit3UZVLwTOo4m98h7gma2EMwGRbKPzBOB33T6rzKPc/lRo3S4LHtISSvgwutzn\nSqzyEjkhJN6YRBO+gCnJweutvkyhBt+nUeuy8GJp+1izJXq6/6hKCHIWBF8yCN1V/hh5lOTvy+TT\nlkg06vYbYoZP1/PNkWpJ+f11cj21VJlimIbgS6x+31jaOV6iCYMLDum1GGLcktXgB1nwqvox0o3D\ngxLnvAh4UUH2fw38euJYLO7ClvBXhA8AD2TkwYMIRwfpYxa8Wb5+oC5n+aZ00JKPuM+AbFiWLonG\nJCSbqZrqIfgyhRp8rlHzKJGjutKm7iP8LSHTPhq8J7ncOfacN7g0JZZjV12Gkh8uTR8yKmmMrfz+\nm0+9x+G1U4ZBDH3Sps4tMRT6kLRhXha8r38jdHPDvp7JsCh9CD71HObvRTMH3EWEXxfhFpFjsfKa\nP7dV9gPb3xsDiHAITW/CELPg97tjpYOsIVKW6RCJRiJp/aSGlEQTHktZ430s+D4fQ4l2mvot0eBz\nddkl0YTwpJpqnEOkJBpDjOBT9+q9VEKUNJZZ40I1+h4ZfO/l+4m8wjTTyGsldZo6JzdRq6QhGWLB\n99Hg7Xs0QvcWvMnEoafbzh5l6opFsyYJfgvNotC/EjkWe2HNgveWic1SvRp4XrA/5kVjFecJvsSC\nfxqNb71/UCVWeYmcEOYXs+BzBJ8aMPVlyg2yxspf2nsZqof2IRRDyk0ydu4sJJohclSOeA1DLPgu\nbTx8hqHMdzPga+6csGebWsErJ9GkyhQbD0iVM5bflh5pfb5DCL5EorG69EaKJ3jbvjHwB4mypeJM\nhfDf8ZoleIjLRxsA2oWhu9LfJPj/rsH/MYnGE3yKKGME/x3yy8CVWGk5CzIsW5dEk5IGuiz4nJtk\nyQdU0h3vsuBj+fZpAGfhJhm7H+/x0acxSDXyue+uT/4pDR63P7z+ijylyncZzQvx54RpS3o49Ehj\nsPL7wUqfF0yG7R4i5/QZ1zCUWPD+Okbo9wXubtuqXKs6FtQPRta9NQa5+7Bz56vBzxlG3kmCB34Q\npEulf3Eifz/wCNNJNN61ssS66RrEjT00T/CxjzdF8CUafEmvxTDEi6ZPA9hlWcfknK5GLERK947V\nzxANPlU/hhKCLyEjQ2rSkuVxNk3E0ecx2biVELwPb92H4EsIf6tLE3t23lou6U34YyWGyBCC92mN\n0L8AIBKdjGhlM1fym0TSeFnKx4dakxb8j7W/sS6LVX7Ymtv/DxFZCfCVQx8NPqdHh9bTBtKSRh8L\nPmfN+giQMY3Q30epBj/UD96XseRjm4bgc41N18B1H4mmz3VKGjV/zrQWPO7YlYm0ewFU+QNVfqfd\n5xs3swo/G57Twt43rzH36dWVWMsp+csQk1PnJdH0WZw89R5d4dLFCN6WCLV7/yjwGVc2CwNuxP4D\nd701SfCGnAUfwgj+bOChwPc68p1mkDXWdU/JILmPISUB5V68vYxbF0M0+BSBSSTtEImmZMArRaa5\nBT/6lCX1Mfch+JgF3zX41sflcVYEb2WycNY+31iZvI+7EfzzaFyNQ4K3b9AIqkvrD//PvQupyYcp\nuSG2SP0QiWYIwZdo8MZBlvbbqmP34sv/NWA78GDa2FGq/Kkqd2O8DqwRsDWbL3Bl2896JXgRNojw\nFSaXqNtGHjkNPhWDJifRpEiohIxSA4IhfOPjr5v7uFJli10n1XsZoq/n0pQ0Cn2sfU/AXfo3pN0k\ncx911yDrdZG0qfxLYrj0IXh7b3101JhP+67Ytir7VdnN+L0bgXURfIg+jb6V367TpWnHru23fxQ5\nZpE1fZms3n4YKVMJwVt5zQUyZYicDfzFSqGUE1T5D1U+wHhwQA8j+CtpXMe/0W6Hg9/zi0UzZ3RZ\n8DelkXNSE5pS8AQG3ZZvjOA9kZRos7h9JXqr15hzH5A/lpKYYh/dLCz4PvecO6dPWg+vlecseBJp\nY/XjPUp8mfzgWSw/2/Y9iBAlxBg75zWMLw4Dk+R0BPBb4bVVucxZmzGJxogw1zB5lKSx/IzIUvUf\ns+B9Y2AIY2J5Ccvna7Ppw3NShkKIM911jeCjz0yVfw0kMo/L3XbICfaeXK7KawP3161B2nVlwYcv\n4i+0v7kWMMSX3XZOu05Z7jErbYhmnWpQch91lxtgLv+UfBSiD8GnrJwhGvy0FnyqbLlzurxoYg15\n1zmxdyNV77nvrvSd2AN81fJV5RnApxN5tYm4inz0UX+OJ9GUhd1XojFYPZnW/KX29xMuXVhmPw6n\nLs1Y0MMWRvDfdvv/CLgdI207zD8ZKlyVlzLeEHZZ8Dm8hfElN33Y7jsB73bnrAuCjw2yhuU91P0C\nfDOTnxFkyiUr3Jciu9jHMUSDn8aCLxkX8ERVIrd06fYxlJApLk2KtGMafEl333dRuyYkwTA3SXv3\nUrSLIxgAABc8SURBVM95VgRf8k4A3IKRkWNkcBHws0GanLyQyjckQU/oXr/PocTgsXr4StuL+HC7\n/S6agISGZwC/6s71/GAkHhK8Eaf5+n+l/f06gCo3qHIh8MxImaxOUxJISPB+wDQ24z4KVVR1jFeM\np65tj18QWO4Gk5yUDg5fRjdJQ5dEc/P2NyT4WFfOYA8kRvApYvS/MUuiS4PPkXbq3NyA4166F8VO\nEXzunC7PmxCpgUd//RBdBJ9DiTTjy5YjyK7wADFitHNSi1Xnene55+tRNO6g2jgTiHBT2kG4lghC\nay+mwXfV4WNoesU7mSTREoI3orVvxdKGUkTYaB5EW6eqXCfCLmCvKpeJNCSrynsARPj7yH3YN28D\nkV8C7t/+fwgN+a64YaoiImwAzl/JSPmgCOcCjw/KZuekxvSsbl9B4wHzIEac5X32+8Dy/UPglpHj\nBwO25Oma1uC7LPgj2t+Q4HPrTHoLPkRqUKwPwfcZlEwNsuY+nBTx5si0zzldvvMxdJFeiD5WOYk0\nJYOsfTT4VFlyfvAlFrwh9Xz7eNFk3ydVroxYeP76Y6e4X5/fVaorFq8n9JTuHcJ6AL63uyOSdoMq\n14dRYFU5XnWljr8SO6f9vYzGyrcJQtZ7fw6shDk5RJXrGB9EtQFlL2cZLJ8bAQ8DPp5I9xTgqao8\nW5W3tvtmRvCq/J0qf+QPtvdjq9LtB/5WJLn06FITfJcGbxMDQg0+1yX1BB++pCnXqHlJNClCiZ3j\nR/xLiDclNeXOGTLI6gl+GokmRKnGH4Od6y3IECkvGj+hJ8wvFVjKtndGrpPyTPKNUIiSey6VAHIW\nfFdd/ln7F6b1hP9Ntw3Noubg6l+VNzPpENHFP78LPM7ts+99iyqXAa+msbzfBNy5bTCskblxe22r\nh0NJw57zB9vfg1V5L04VsAFpVd6uyutdHpvaMl/KcMSemUdI8NCsmBfFWiP4sLzWDQsJPmfteIkm\nRvApy30aiSaGPgOOhpj3T1f+fQZx+0g0Bqs3T/AxKSJ1j7G0qTCyucbAb5tFnSN4n79vRMP8/L3a\nOaaH/gmsRC1NuWra+2N5xax+/26EmrKdHw7K5ZBrQLJorce/CXa9EfiQy+NVNAOiVtbjGenoE2VU\nXSEmu+8s/6iyS5W3uN2HtL9b2jSXqfLPquxT5fNBuk/A2DbkXag3tPl9pN32A6cl2KPK/6eaVRK6\n0Ifg7TkcnEq41Bq8CA8ELlFtBkUYPdwvAHdo/w9b5ZA8rmQk40Degu8anLTtWFznlL46RIO38sfI\nrssdM3btPpEhU41aiQafsuDD9ys1oJnDEIkmZcHHJBp/nViPzUcr9XV5NUD7UV8u482N1YtZvkZs\nFsEx5lrpxzW+G0mT/KAdXgAr8oGhT29ope5U+eVWu34+NEthtlb5m0W4EDhatfGpb+vAPFNuHcnX\n+3P3wdU0PNAlg/x0ZF8pWT+FkaRU6q56JybdVIeghOB9TJpkg7/sFvwHGK0KBaMwBqElnZJormUc\n9rHlpJ8u75M+BI/bH9tXonf7D75kwLTrPnIafJ9GwUjPXjifNhxHSUkPQ3o6MfjG0d6RWOOT0uC9\nBW95/Drjnhbhda5hEt6LxhaYt3oyKzdmwRvsXQsJvkTDHyVWLlblXLe7j3/92HVb7fplTD6zq8YS\nNzKGDfa+Bfg/Lr0t19mXf/6FZr0I6CD41kMm/F5vCfxr5pSV71aVc4JxiKL6ar1dck4epRhiwScJ\nfpkteCOHkDBv1v6GFbmN0aSAmHZqyEk0XV40JQRf4kliSEkzOWu5j0dMlx98TMPt4ybpZQtP8F6z\nDfNJNTIl9RW7Z18/ViZP8OGH00XwY5KKKq+FFcvUzrXfHMHvo7EEbUKN5XeuCP8G/FfmXLOAz4+k\nmQaDLPiOdLGGyuryM6r8mztmnja9CF6VxwCI8GeMfOZLz/1GR5JUWcL3/7REmlmiRN75JnAWI4XC\nLyaygmW04C1Qj18OCyYH9aC5ST/oAJMEb+eY3BO+tP5FTpFprHWdtwXvr1OStiv/GMGnwgXnkCL4\nsAHwdZv6jbl79ZF1uiz4GMH7c/0ga24GpUk3uQG1/ao8APhn4M0EroKqXE3egjeC/xbw73ZaJn0p\n+ljwqffea9lnAU8fO1GjjbzBJKpB/KOKqPLPQ84dgLC+Yl49s0anBd+ON/wfRu/xIam0y0jwdoO2\nMtOhACIIcYKHfgT/N22eMU+VLmKMDb5No8F7S7vEgi8hXnMLSw2Yxgj+epe2hEzs/bH6j5UttR5s\niXXYR4P3BG/kmSN4Hw7XSzQ5gj8KQJWPk55Nvb9Ns0+VJzI+YzIsYwxh5MBZEPtYmXrCk86/0yzK\nA4AqH1Ud81EPMXOCnxNS/uT7mYymOU+USDQGqz8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8P2bu/yNv75cfvpDxsD3uDXgysGbeXhm4hBST/yRwWC4/HDg6b29JamFXADYBfsPocNIr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\nPm8HHG67zjd2AOTcTtuSvgg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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -579,51 +573,1350 @@ } ], "source": [ - "ccdata_byproduct['Product'].groupby(ccdata_byproduct.index).count().plot()" + "top_ten_comp = ccdata_bycompany.groupby('Company').count().sort_index(by='Complaint ID')[::-1]\n", + "top_ten_comp.loc[:,['Complaint ID']][0:10].plot(kind='bar')" ] }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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VClsDNwCz6P+kOpz0wX4+sAbpMmS3xoe1pK8C+wOvk5qbfpnLJwGnA0sBV9hudG9dAphG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\neDopbaK5EXo1N3MCIGlFepR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FwKS8NvOPSO3iZwNVm7O+DsuG/lPZASwkhhpRv2TPogiF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\ntc0VcMLgjGYAJgoATBQAmCgAMFEAYAFQvYXWDTedLwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "complaints_response = ccdata.loc[:,['Company response', 'Complaint ID']]\n", + "complaints_response.index = complaints_response['Company response']\n", + "complaints_response.groupby('Company response').count().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", "metadata": { "collapsed": true }, - "outputs": [], "source": [ - "ccdata_bycompany.index = ccdata_bycompany['Company']" + "###The mean number of complaints by day of weekday" ] }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 32, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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Date received
01/01/201299790989999999
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1269 rows × 14 columns

\n", + "
" + ], "text/plain": [ - "" + " Complaint ID Product Sub-product Issue Sub-issue State \\\n", + "Date received \n", + "01/01/2012 9 9 7 9 0 9 \n", + "01/01/2013 59 59 34 59 13 59 \n", + "01/01/2014 88 88 50 88 35 88 \n", + "01/01/2015 129 129 76 129 57 129 \n", + "01/02/2012 31 31 17 31 0 31 \n", + "01/02/2013 245 245 171 245 29 244 \n", + "01/02/2014 439 439 285 439 168 429 \n", + "01/02/2015 429 429 292 429 175 428 \n", + "01/03/2012 108 108 62 108 0 105 \n", + "01/03/2013 379 379 266 379 54 376 \n", + "01/03/2014 408 408 282 408 171 408 \n", + "01/03/2015 175 175 109 175 94 173 \n", + "01/04/2012 116 116 71 116 0 116 \n", + "01/04/2013 266 266 203 266 33 264 \n", + "01/04/2014 125 125 78 125 65 125 \n", + "01/04/2015 148 148 94 148 71 147 \n", + "01/05/2012 190 190 108 190 0 189 \n", + "01/05/2013 62 62 38 62 11 62 \n", + "01/05/2014 94 94 57 94 43 94 \n", + "01/05/2015 539 539 384 539 214 530 \n", + "01/06/2012 190 190 138 190 0 190 \n", + "01/06/2013 65 65 37 65 16 65 \n", + "01/06/2014 446 446 319 446 160 437 \n", + "01/06/2015 515 515 347 515 207 512 \n", + "01/07/2012 57 57 35 57 0 57 \n", + "01/07/2013 320 320 252 320 22 315 \n", + "01/07/2014 504 504 349 504 194 490 \n", + "01/07/2015 575 575 373 575 264 570 \n", + "01/08/2012 48 48 33 48 0 48 \n", + "01/08/2013 584 584 484 584 32 574 \n", + "... ... ... ... ... ... ... \n", + "12/24/2013 235 235 152 235 106 228 \n", + "12/24/2014 326 326 210 326 142 323 \n", + "12/25/2011 9 9 3 9 0 9 \n", + "12/25/2012 95 95 70 95 5 95 \n", + "12/25/2013 44 44 29 44 12 42 \n", + "12/25/2014 52 52 32 52 28 52 \n", + "12/26/2011 27 27 12 27 0 27 \n", + "12/26/2012 189 189 136 189 25 187 \n", + "12/26/2013 432 432 287 432 186 422 \n", + "12/26/2014 233 233 146 233 112 232 \n", + "12/27/2011 88 88 43 88 0 88 \n", + "12/27/2012 290 290 202 290 35 287 \n", + "12/27/2013 380 380 268 380 149 373 \n", + "12/27/2014 109 109 68 109 48 109 \n", + "12/28/2011 79 79 44 79 0 78 \n", + "12/28/2012 282 282 202 282 35 278 \n", + "12/28/2013 124 124 67 124 60 120 \n", + "12/28/2014 166 166 99 166 96 165 \n", + "12/29/2011 80 80 41 80 0 74 \n", + "12/29/2012 64 64 37 64 7 64 \n", + "12/29/2013 136 136 89 136 65 136 \n", + "12/29/2014 541 541 352 541 246 535 \n", + "12/30/2011 83 83 35 83 0 80 \n", + "12/30/2012 53 53 28 53 11 53 \n", + "12/30/2013 463 463 300 463 176 453 \n", + "12/30/2014 575 575 344 575 251 568 \n", + "12/31/2011 27 27 20 27 0 27 \n", + "12/31/2012 243 243 182 243 28 241 \n", + "12/31/2013 335 335 211 335 127 316 \n", + "12/31/2014 391 391 211 391 195 383 \n", + "\n", + " ZIP code Submitted via Date sent to company Company \\\n", + "Date received \n", + "01/01/2012 8 9 9 9 \n", + "01/01/2013 59 59 59 59 \n", + "01/01/2014 88 88 88 88 \n", + "01/01/2015 127 129 129 129 \n", + "01/02/2012 31 31 31 31 \n", + "01/02/2013 244 245 245 245 \n", + "01/02/2014 436 439 439 439 \n", + "01/02/2015 427 429 429 429 \n", + "01/03/2012 105 108 108 108 \n", + "01/03/2013 377 379 379 379 \n", + "01/03/2014 407 408 408 408 \n", + "01/03/2015 174 175 175 175 \n", + "01/04/2012 116 116 116 116 \n", + "01/04/2013 264 266 266 266 \n", + "01/04/2014 124 125 125 125 \n", + "01/04/2015 147 148 148 148 \n", + "01/05/2012 189 190 190 190 \n", + "01/05/2013 62 62 62 62 \n", + "01/05/2014 93 94 94 94 \n", + "01/05/2015 533 539 539 539 \n", + "01/06/2012 189 190 190 190 \n", + "01/06/2013 65 65 65 65 \n", + "01/06/2014 439 446 446 446 \n", + "01/06/2015 513 515 515 515 \n", + "01/07/2012 57 57 57 57 \n", + "01/07/2013 312 320 320 320 \n", + "01/07/2014 503 504 504 504 \n", + "01/07/2015 565 575 575 575 \n", + "01/08/2012 48 48 48 48 \n", + "01/08/2013 573 584 584 584 \n", + "... ... ... ... ... \n", + "12/24/2013 228 235 235 235 \n", + "12/24/2014 325 326 326 326 \n", + "12/25/2011 9 9 9 9 \n", + "12/25/2012 95 95 95 95 \n", + "12/25/2013 42 44 44 44 \n", + "12/25/2014 51 52 52 52 \n", + "12/26/2011 27 27 27 27 \n", + "12/26/2012 184 189 189 189 \n", + "12/26/2013 426 432 432 432 \n", + "12/26/2014 231 233 233 233 \n", + "12/27/2011 88 88 88 88 \n", + "12/27/2012 288 290 290 290 \n", + "12/27/2013 376 380 380 380 \n", + "12/27/2014 106 109 109 109 \n", + "12/28/2011 79 79 79 79 \n", + "12/28/2012 273 282 282 282 \n", + "12/28/2013 124 124 124 124 \n", + "12/28/2014 165 166 166 166 \n", + "12/29/2011 76 80 80 80 \n", + "12/29/2012 62 64 64 64 \n", + "12/29/2013 135 136 136 136 \n", + "12/29/2014 537 541 541 541 \n", + "12/30/2011 80 83 83 83 \n", + "12/30/2012 53 53 53 53 \n", + "12/30/2013 454 463 463 463 \n", + "12/30/2014 572 575 575 575 \n", + "12/31/2011 27 27 27 27 \n", + "12/31/2012 241 243 243 243 \n", + "12/31/2013 330 335 335 335 \n", + "12/31/2014 386 391 391 391 \n", + "\n", + " Company response Timely response? Consumer disputed? weekday \n", + "Date received \n", + "01/01/2012 9 9 9 9 \n", + "01/01/2013 59 59 58 59 \n", + "01/01/2014 88 88 84 88 \n", + "01/01/2015 129 129 128 129 \n", + "01/02/2012 31 31 31 31 \n", + "01/02/2013 245 245 242 245 \n", + "01/02/2014 439 439 422 439 \n", + "01/02/2015 429 429 425 429 \n", + "01/03/2012 108 108 105 108 \n", + "01/03/2013 379 379 377 379 \n", + "01/03/2014 408 408 394 408 \n", + "01/03/2015 175 175 171 175 \n", + "01/04/2012 116 116 114 116 \n", + "01/04/2013 266 266 264 266 \n", + "01/04/2014 125 125 123 125 \n", + "01/04/2015 148 148 147 148 \n", + "01/05/2012 190 190 184 190 \n", + "01/05/2013 62 62 62 62 \n", + "01/05/2014 94 94 93 94 \n", + "01/05/2015 539 539 530 539 \n", + "01/06/2012 190 190 183 190 \n", + "01/06/2013 65 65 65 65 \n", + "01/06/2014 446 446 436 446 \n", + "01/06/2015 515 515 506 515 \n", + "01/07/2012 57 57 57 57 \n", + "01/07/2013 320 320 319 320 \n", + "01/07/2014 504 504 485 504 \n", + "01/07/2015 575 575 562 575 \n", + "01/08/2012 48 48 47 48 \n", + "01/08/2013 584 584 582 584 \n", + "... ... ... ... ... \n", + "12/24/2013 235 235 226 235 \n", + "12/24/2014 326 326 320 326 \n", + "12/25/2011 9 9 9 9 \n", + "12/25/2012 95 95 95 95 \n", + "12/25/2013 44 44 43 44 \n", + "12/25/2014 52 52 51 52 \n", + "12/26/2011 27 27 26 27 \n", + "12/26/2012 189 189 188 189 \n", + "12/26/2013 432 432 422 432 \n", + "12/26/2014 233 233 231 233 \n", + "12/27/2011 88 88 84 88 \n", + "12/27/2012 290 290 289 290 \n", + "12/27/2013 380 380 368 380 \n", + "12/27/2014 109 109 108 109 \n", + "12/28/2011 79 79 74 79 \n", + "12/28/2012 282 282 280 282 \n", + "12/28/2013 124 124 117 124 \n", + "12/28/2014 166 166 165 166 \n", + "12/29/2011 80 80 67 80 \n", + "12/29/2012 64 64 64 64 \n", + "12/29/2013 136 136 133 136 \n", + "12/29/2014 541 541 532 541 \n", + "12/30/2011 83 83 79 83 \n", + "12/30/2012 53 53 52 53 \n", + "12/30/2013 463 463 451 463 \n", + "12/30/2014 575 575 563 575 \n", + "12/31/2011 27 27 27 27 \n", + "12/31/2012 243 243 242 243 \n", + "12/31/2013 335 335 327 335 \n", + "12/31/2014 391 391 384 391 \n", + "\n", + "[1269 rows x 14 columns]" ] }, + "execution_count": 32, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "cplot = ccdata_bycompany['Company'].groupby(ccdata_bycompany.index).count().plot()" + "dailymean = ccdata.groupby('Date received').count()\n", + "dailymean" ] }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - }, { "cell_type": "code", "execution_count": null, @@ -631,9 +1924,7 @@ "collapsed": true }, "outputs": [], - "source": [ - "# Plots" - ] + "source": [] } ], "metadata": {