priyankamandikal/mozilla_feedback_analyzer.ipynb

## mozilla_feedback_analyzer.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mozilla Feedback Analysis\n",
    "\n",
    "\n",
    "Mozilla Firefox releases various versions of its web browser over time. These versions are run on different platforms by users around the world. Some versions may make users happy, while some others, not so much. There is a huge amount of feedback that is generated by users across platforms and versions.\n",
    "#### How do we make sense of this feedback? <br/>How can Mozilla analyze this data in order to cater to users' growing needs and tackle issues swiftly? \n",
    "\n",
    "In this project, the aim is to analyze the feedback data and find interesting behaviours associated with it. <br/>\n",
    "The feedback is available at the following link. <br/>\n",
    "https://input.mozilla.org/en-US/?product=Firefox<br/><br/>\n",
    "\n",
    "## Part 1: Web Scraping\n",
    "\n",
    "### Task: Scrape data from the site\n",
    "### Completed: Scraped a week's worth of data (200 pages) using BeautifulSoup\n",
    "Since the data is not readily available in the form of a table, it is necessary to scrape relevant information from the website. As a sample dataset to play around with, I scraped a week's worth of data (around 200 pages) using BeautifulSoup, a Python library for pulling data out of HTML and XML files.<br/><br/>\n",
    "The code for scraping is as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nimport requests\\nfrom pattern import web\\nfrom bs4 import BeautifulSoup\\nimport traceback\\n\\n#base url with GET dictionary\\nurl = \\'https://input.mozilla.org/en-US\\'\\nfeedback1 = open(\\'feedback1.txt\\',\\'a\\')\\nfor i in xrange(1,203): \\n#feedback1 - 1st 202 pages are valid as of 19th Oct 8:30AM IST\\n\\ttry:\\n\\t\\tparams = dict(product=\\'Firefox\\', page=i)\\n\\t\\tr = requests.get(url, params=params)\\n\\t\\tbs = BeautifulSoup(r.text)\\n\\t\\tfor opinion in bs.findAll(\\'li\\',\\'opinion\\'):\\n\\t\\t\\tsenti = opinion.find(\\'span\\',\\'sprite\\').contents[0]\\n\\t\\t\\tdatetime = opinion.find(\\'time\\')[\\'datetime\\']\\n\\t\\t\\ttime = opinion.find(\\'time\\').string #not a very useful value. We want the absolute date and time\\n\\t\\t\\t#to remove whitespaces on either side of s tring, just do for e.g. time.strip()\\n\\t\\t\\tversion = time.find_next(\\'a\\').find_next(\\'a\\').contents[0]\\n\\t\\t\\tplatform = version.find_next(\\'a\\').contents[0]\\n\\t\\t\\tlocale = platform.find_next(\\'a\\').contents[0]\\n\\t\\t\\tfeedback1.write(senti+\\'\\t\\'+datetime+\\'\\t\\'+version+\\'\\t\\'+platform+\\'\\t\\'+locale+\\'\\n\\')\\n\\texcept:\\n\\t\\t#the try catch block was added beacuse ceratin opinions in a page were geving errors as\\n\\t\\t#certain characters couldn\\'t be encoded by ascii codec. E.g. (Norwegian Bokmal), the \\'a\\' was different\\n\\t\\tprint \"Error while retreiving page \", i\\n\\t\\tprint traceback.format_exc()\\n\\t\\tcontinue\\n\\nfeedback1.close()\\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#I have commented out the scraping code here.\n",
    "\n",
    "'''\n",
    "import requests\n",
    "from pattern import web\n",
    "from bs4 import BeautifulSoup\n",
    "import traceback\n",
    "\n",
    "#base url with GET dictionary\n",
    "url = 'https://input.mozilla.org/en-US'\n",
    "feedback1 = open('feedback1.txt','a')\n",
    "for i in xrange(1,203): \n",
    "#feedback1 - 1st 202 pages are valid as of 19th Oct 8:30AM IST\n",
    "\ttry:\n",
    "\t\tparams = dict(product='Firefox', page=i)\n",
    "\t\tr = requests.get(url, params=params)\n",
    "\t\tbs = BeautifulSoup(r.text)\n",
    "\t\tfor opinion in bs.findAll('li','opinion'):\n",
    "\t\t\tsenti = opinion.find('span','sprite').contents[0]\n",
    "\t\t\tdatetime = opinion.find('time')['datetime']\n",
    "\t\t\ttime = opinion.find('time').string #not a very useful value. We want the absolute date and time\n",
    "\t\t\t#to remove whitespaces on either side of s tring, just do for e.g. time.strip()\n",
    "\t\t\tversion = time.find_next('a').find_next('a').contents[0]\n",
    "\t\t\tplatform = version.find_next('a').contents[0]\n",
    "\t\t\tlocale = platform.find_next('a').contents[0]\n",
    "\t\t\tfeedback1.write(senti+'\\t'+datetime+'\\t'+version+'\\t'+platform+'\\t'+locale+'\\n')\n",
    "\texcept:\n",
    "\t\t#the try catch block was added beacuse ceratin opinions in a page were geving errors as\n",
    "\t\t#certain characters couldn't be encoded by ascii codec. E.g. (Norwegian Bokmal), the 'a' was different\n",
    "\t\tprint \"Error while retreiving page \", i\n",
    "\t\tprint traceback.format_exc()\n",
    "\t\tcontinue\n",
    "\n",
    "feedback1.close()\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sad\t2015-10-18-08:00\t41.0\tLinux\tEnglish (US)\r\n",
      "Sad\t2015-10-18-08:00\t41.0\tWindows XP\tVietnamese\r\n",
      "Happy\t2015-10-18-08:00\t41.0.2\tWindows 7\tEnglish (US)\r\n",
      "Sad\t2015-10-18-08:00\t37.0\tWindows 7\tEnglish (US)\r\n",
      "Sad\t2015-10-18-08:00\t38.3.0\tWindows 7\tEnglish (US)\r\n",
      "Happy\t2015-10-18-08:00\t8.0\tLinux\tSpanish (Spain)\r\n",
      "Sad\t2015-10-18-08:00\t41.0.2\tWindows 7\tEnglish (US)\r\n",
      "Sad\t2015-10-18-08:00\t41.0\tWindows 10\tEnglish (US)\r\n",
      "Sad\t2015-10-18-08:00\t41.0.2\tWindows XP\tGerman\r\n",
      "Sad\t2015-10-18-08:00\t41.0.2\tWindows 8.1\tSpanish (Spain)\r\n"
     ]
    }
   ],
   "source": [
    "# Scraped data has been sevd in feedback2.txt\n",
    "!head feedback2.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Converting the data into a dataframe\n",
    "\n",
    "It is extremely important to convert the data into the right format to be able to perform operations on it. \n",
    "#### I'm using Pandas (a Python data analysis toolkit) for dataframe related operations. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pylab as P\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rows: 3760\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentiment</th>\n",
       "      <th>date</th>\n",
       "      <th>version</th>\n",
       "      <th>platform</th>\n",
       "      <th>locale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sad</td>\n",
       "      <td>2015-10-18-08:00</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Linux</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sad</td>\n",
       "      <td>2015-10-18-08:00</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Windows XP</td>\n",
       "      <td>Vietnamese</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Happy</td>\n",
       "      <td>2015-10-18-08:00</td>\n",
       "      <td>41.0.2</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sad</td>\n",
       "      <td>2015-10-18-08:00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sad</td>\n",
       "      <td>2015-10-18-08:00</td>\n",
       "      <td>38.3.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sentiment              date version    platform        locale\n",
       "0       Sad  2015-10-18-08:00    41.0       Linux  English (US)\n",
       "1       Sad  2015-10-18-08:00    41.0  Windows XP    Vietnamese\n",
       "2     Happy  2015-10-18-08:00  41.0.2   Windows 7  English (US)\n",
       "3       Sad  2015-10-18-08:00    37.0   Windows 7  English (US)\n",
       "4       Sad  2015-10-18-08:00  38.3.0   Windows 7  English (US)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names = ['sentiment', 'date', 'version', 'platform', 'locale']\n",
    "data = pd.read_csv('feedback2.txt', delimiter='\\t', names=names).dropna()\n",
    "print \"Number of rows: %i\" % data.shape[0]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we have the data in the right format.<br/>\n",
    "For the next part, I'm using an ad-hoc way for dealing with the datetime column. I am going to extract only the day. However, I'll learn how to use the actual date in later analysis that I perform in the future. For now, this is a dirty way, but suffices for the sample dataset that I have scraped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentiment</th>\n",
       "      <th>date</th>\n",
       "      <th>version</th>\n",
       "      <th>platform</th>\n",
       "      <th>locale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Linux</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Windows XP</td>\n",
       "      <td>Vietnamese</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Happy</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0.2</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>38.3.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sentiment  date version    platform        locale\n",
       "0       Sad    18    41.0       Linux  English (US)\n",
       "1       Sad    18    41.0  Windows XP    Vietnamese\n",
       "2     Happy    18  41.0.2   Windows 7  English (US)\n",
       "3       Sad    18    37.0   Windows 7  English (US)\n",
       "4       Sad    18  38.3.0   Windows 7  English (US)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extracting the exact day from date\n",
    "# This is not a good practice since I'm just extracting the date\n",
    "# Ideally we should be extracting the entire date to compare them. Will do that later.\n",
    "\n",
    "data.date = [int(d.split('-')[2]) for d in data.date]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentiment</th>\n",
       "      <th>version</th>\n",
       "      <th>platform</th>\n",
       "      <th>locale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3760</td>\n",
       "      <td>3760</td>\n",
       "      <td>3760</td>\n",
       "      <td>3760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>69</td>\n",
       "      <td>31</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Sad</td>\n",
       "      <td>41.0.1</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>3134</td>\n",
       "      <td>1546</td>\n",
       "      <td>1382</td>\n",
       "      <td>2090</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sentiment version   platform        locale\n",
       "count       3760    3760       3760          3760\n",
       "unique         2      69         31            48\n",
       "top          Sad  41.0.1  Windows 7  English (US)\n",
       "freq        3134    1546       1382          2090"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['sentiment', 'version', 'platform', 'locale']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we can infer that majority of the feedabck has been negative.<br/>\n",
    "The top version, platform and locale from where feedback has been coming can also be seen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3760.000000\n",
       "mean       14.633511\n",
       "std         2.175523\n",
       "min        11.000000\n",
       "25%        13.000000\n",
       "50%        15.000000\n",
       "75%        16.000000\n",
       "max        18.000000\n",
       "Name: date, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['date'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 3: Analyze the data and make some Basic plots\n",
    "\n",
    "We can now look at answering some questions that we may have regarding the given data.<br/>\n",
    "What exactly are we looking for? Some questions instantly come to mind.<br/>\n",
    "#### 1. Which version is causing a lot of problems?\n",
    "#### 2. Which platform is causing the most problems?\n",
    "#### 3. Which localities are users sending in feedback from?\n",
    "#### 4. How is the positive feedback characterized?\n",
    "#### 5. Which day has had maximum feedback coming in?\n",
    "\n",
    "Although the above are important questions, we may want to dig a little deeper into the data to find certain<br/>\n",
    "correlations between attributes.\n",
    "#### 6. Is there any correlation between specific versions causing problems when used on certain platforms?\n",
    "#### 7. Which versions and platforms go well together? \n",
    "<br/>\n",
    "I will be using Matplotlib, a Python graph-plotting library.<br/><br/>\n",
    "I have written a custom function that will be used with the matplotlib to make certain modifications to the in-built graphs. This makes the graphs simple and pretty by removing uneccesary borders, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Custom function to make graphs simple and pretty\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "#tell pandas to display wide tables as pretty HTML tables\n",
    "pd.set_option('display.width', 500)\n",
    "pd.set_option('display.max_columns', 100)\n",
    "\n",
    "#--------------------------To remove borders from the matplotlib plots-------------------------\n",
    "def remove_border(axes=None, top=False, right=False, left=True, bottom=True):\n",
    "    \"\"\"\n",
    "    Minimize chartjunk by stripping out unnecesasry plot borders and axis ticks\n",
    "    \n",
    "    The top/right/left/bottom keywords toggle whether the corresponding plot border is drawn\n",
    "    \"\"\"\n",
    "    ax = axes or plt.gca()\n",
    "    ax.spines['top'].set_visible(top)\n",
    "    ax.spines['right'].set_visible(right)\n",
    "    ax.spines['left'].set_visible(left)\n",
    "    ax.spines['bottom'].set_visible(bottom)\n",
    "    \n",
    "    #turn off all ticks\n",
    "    ax.yaxis.set_ticks_position('none')\n",
    "    ax.xaxis.set_ticks_position('none')\n",
    "    \n",
    "    #now re-enable visibles\n",
    "    if top:\n",
    "        ax.xaxis.tick_top()\n",
    "    if bottom:\n",
    "        ax.xaxis.tick_bottom()\n",
    "    if left:\n",
    "        ax.yaxis.tick_left()\n",
    "    if right:\n",
    "        ax.yaxis.tick_right()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Feedback over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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imkt2JN+lRDH9K8U0tGj6/1KaVjSVfVd3AvOBeemPvlOpvyugJXBX+g1nAWWl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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f9a7dd90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#negative and positive feedback over time\n",
    "#resources: http://matplotlib.org/examples/pylab_examples/histogram_demo_extended.html\n",
    "#           http://matplotlib.org/examples/statistics/histogram_demo_multihist.html\n",
    "\n",
    "#Happy gives KeyError without .values\n",
    "\n",
    "fig = plt.figure(1)\n",
    "plt.hist([[data[data.sentiment=='Sad'].date],[data[data.sentiment=='Happy'].date]],\n",
    "         bins=np.arange(11,21), \n",
    "         color=['crimson','chartreuse'],\n",
    "         label=['Negative','Positive'])\n",
    "plt.xlabel('Date (day of October 2015)')\n",
    "plt.title('Feedback over Time')\n",
    "plt.legend(prop={'size': 10})\n",
    "remove_border()\n",
    "\n",
    "#handles, labels = ax.get_legend_handles_labels()\n",
    "fig.savefig('fig1.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We observe that positive feedback has been low and almost constant on all days.<br/>\n",
    "Negative feedback has slightly varied with time, peaking on 16-10-2015.<br/>\n",
    "We can assume a bias in the result because not everyone reports positive feedback, but problems are immediately reported by users.<br/>\n",
    "So we need to place more emphasis on negative feedback in our analysis in order to pinpoint areas which Mozilla needs to focus on, in order to fix issues.\n",
    "### Which versions are popular?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cZN5RlvPdkiRNK/OjJGmUdljmdL8EHJ3kKcA9gHsnOR1Yn2Svqroxyd7ATf34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\n1ACLN0mSJElqgMWbJEmSJDXg/wFRfhLMVuBbUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f9918d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Finding the versions with the most number of positive and negative feedbacks.I am ignoring the ones which \n",
    "#have a count of <20. I am also ignoring the 'Unknown' column.\n",
    "#Resources: http://pandas.pydata.org/pandas-docs/version/0.13.1/visualization.html\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(15,5))\n",
    "\n",
    "data[(data.sentiment=='Sad') & (data.version!='Unknown')].version.value_counts()[:9].plot(kind=\"bar\",\n",
    "                                                                                        ax=axes[0],color='crimson')\n",
    "axes[0].set_xlabel('Version')\n",
    "axes[0].set_title('Versions with negative feedback')\n",
    "remove_border(axes=axes[0])\n",
    "\n",
    "\n",
    "data[(data.sentiment=='Happy') & (data.version!='Unknown')].version.value_counts()[:9].plot(kind=\"bar\",\n",
    "                                                                                    ax=axes[1],color='chartreuse')\n",
    "plt.ylim([0,1400])\n",
    "axes[1].set_xlabel('Version')\n",
    "axes[1].set_title('Versions with postive feedback')\n",
    "remove_border(axes=axes[1])\n",
    "\n",
    "fig.savefig('fig2.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We find that the versoin causin maximum problems is also the one with the most positive feedback.<br/>\n",
    "This is true for other versions as well. So it is safe to assume that Version 41.0.1 seems to be the most\n",
    "popular version amongst users, as it generates the most feedback (positive and negative) overall. But as I had already mentioned, the positive feedback doesn't really help us as the number is small. We may have to look into the text to see if there's any information in there."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which platforms are causing problems or are compatible?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kSQ2weJMkSZKkBli8SZIkSVIDLN4kSZIkqQEWb5IkSZLUAIs3SZIkSWqAxZsk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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f97da390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Finding the platforms with the most number of positive and negative feedbacks.I am ignoring the ones \n",
    "#with a low count value. I am also ignoring the 'Unknown' column.\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(15,5))\n",
    "\n",
    "data[(data.sentiment=='Sad') & (data.platform!='Unknown')].platform.value_counts()[:8].plot(kind=\"bar\",\n",
    "                                                                                        ax=axes[0],color='crimson')\n",
    "axes[0].set_xlabel('Platform')\n",
    "axes[0].set_title('Platforms with negative feedback')\n",
    "remove_border(axes=axes[0])\n",
    "\n",
    "\n",
    "data[(data.sentiment=='Happy') & (data.platform!='Unknown')].platform.value_counts()[:8].plot(kind=\"bar\",\n",
    "                                                                                    ax=axes[1],color='chartreuse')\n",
    "plt.ylim([0,1200])\n",
    "axes[1].set_xlabel('Platform')\n",
    "axes[1].set_title('Platforms with postive feedback')\n",
    "remove_border(axes=axes[1])\n",
    "\n",
    "fig.savefig('fig3.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Windows platforms seem to be generating the most problems. One thing to note here is that platform count is not directly proportional to the percentag of those platform users facing the problem. This is because the number of overall users for a platform varies. <br/><br/>\n",
    "For e.g. Windows 7 problems > Windows 8.1 problems<br/>\n",
    "But this does not imply that %(7 users facing problems) > %(8 users facing problems)<br/>\n",
    "Because the number of 8 users may be much lesser than 7 users leading to lower feedback count.<br/><br/>\n",
    "While dealing with the issues, Mozilla probably needs to assign equal importance to 8 users so that it doesn't lose out on the 8 userbase."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Where is feedback coming in from?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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evw7YY5HPLUnSKDNHSpKWxWKLt22ABwNvqaoHAz+h7/4xqaoKqFn2Mds2SZJa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\n5uOv6Ga0mbQt3RfjHYB3Mfpfju+ma4B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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f961a210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Finding the locations with the most number of positive and negative feedbacks.I am ignoring the ones \n",
    "#with a low count value. I am also ignoring the 'Unknown' column.\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(15,5))\n",
    "\n",
    "data[(data.sentiment=='Sad') & (data.locale!='Permalink')].locale.value_counts()[:8].plot(kind=\"bar\",\n",
    "                                                                                    ax=axes[0],color='crimson')\n",
    "axes[0].set_xlabel('Locale')\n",
    "axes[0].set_title('Locales with negative feedback')\n",
    "remove_border(axes=axes[0])\n",
    "\n",
    "\n",
    "data[(data.sentiment=='Happy') & (data.locale!='Permalink')].locale.value_counts()[:8].plot(kind=\"bar\",\n",
    "                                                                                    ax=axes[1],color='chartreuse')\n",
    "plt.ylim([0,1800])\n",
    "axes[1].set_xlabel('Locale')\n",
    "axes[1].set_title('Locales with postive feedback')\n",
    "remove_border(axes=axes[1])\n",
    "\n",
    "fig.savefig('fig4.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Users in USA have a huge share in the providing feedback, both positive and negative.\n",
    "## Part 4: Finding Correlations\n",
    "### Task: Find which version/platform combinations are successful/unsuccessful\n",
    "### Completed: Plotted a heatmap showing the distribution\n",
    "After dabbling with a lot of bar graphs and getting a sense of how the general bahaviour of the data is, it would be interesting to see if there are any correlations between different versions and platforms. The most apt graph for thos purpose would be a heat map. Since the attributes are non-numerical, it is quite a task to get a heatmap out of it. But with a bit of effort (and a LOT of googling), I was successful in getting the desired output!<br/><br/>\n",
    "In the following sections, I have explained in detail how I went about the entire process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#I'm using dummy column to have a lits of 1s as count value for each instance. This is needed for the pivot table.\n",
    "\n",
    "data.insert(len(data.columns), column='dummy', value=[1]*len(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>platform</th>\n",
       "      <th>Android 4.2.2</th>\n",
       "      <th>Android 4.3</th>\n",
       "      <th>Fedora</th>\n",
       "      <th>FreeBSD</th>\n",
       "      <th>Linux</th>\n",
       "      <th>Maemo</th>\n",
       "      <th>OS X</th>\n",
       "      <th>Windows 10</th>\n",
       "      <th>Windows 2000</th>\n",
       "      <th>Windows 7</th>\n",
       "      <th>Windows 8</th>\n",
       "      <th>Windows 8.1</th>\n",
       "      <th>Windows NT</th>\n",
       "      <th>Windows NT 4.10</th>\n",
       "      <th>Windows Vista</th>\n",
       "      <th>Windows XP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform  Android 4.2.2  Android 4.3  Fedora  FreeBSD  Linux  Maemo  OS X  Windows 10  Windows 2000  Windows 7  Windows 8  Windows 8.1  Windows NT  Windows NT 4.10  Windows Vista  Windows XP\n",
       "version                                                                                                                                                                                       \n",
       "10.0                  0            0       0        0      0      0     0           0             0          0          0            0           0                0              0           3\n",
       "11.0                  0            0       0        0      0      0     0           0             0          1          1            0           0                0              0           1\n",
       "12.0                  0            0       0        0      0      0     0           0             0          3          2            0           0                0              0           2\n",
       "13.0                  0            0       0        0      0      0     0           0             0          3          1            0           0                0              0           2\n",
       "14.0                  0            0       0        0      0      0     0           0             0          1          2            0           0                0              0           0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Resources: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.pivot_table.html\n",
    "\n",
    "pt1 = pd.pivot_table(data[(data.sentiment=='Sad') & (data.version!='Unknown') & (data.platform!='Unknown')], \n",
    "                    index='version', values='dummy', columns='platform', aggfunc=np.sum, fill_value=0)\n",
    "pt1.head()\n",
    "#use pt1 to look at the entire pivot table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>platform</th>\n",
       "      <th>Android 4.2.2</th>\n",
       "      <th>Android 4.3</th>\n",
       "      <th>Fedora</th>\n",
       "      <th>FreeBSD</th>\n",
       "      <th>Linux</th>\n",
       "      <th>Maemo</th>\n",
       "      <th>OS X</th>\n",
       "      <th>Windows 10</th>\n",
       "      <th>Windows 2000</th>\n",
       "      <th>Windows 7</th>\n",
       "      <th>Windows 8</th>\n",
       "      <th>Windows 8.1</th>\n",
       "      <th>Windows NT</th>\n",
       "      <th>Windows NT 4.10</th>\n",
       "      <th>Windows Vista</th>\n",
       "      <th>Windows XP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40.0.3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>89</td>\n",
       "      <td>0</td>\n",
       "      <td>124</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0.1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>117</td>\n",
       "      <td>290</td>\n",
       "      <td>0</td>\n",
       "      <td>513</td>\n",
       "      <td>19</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0.2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>206</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "      <td>14</td>\n",
       "      <td>86</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42.0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44.0a1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform  Android 4.2.2  Android 4.3  Fedora  FreeBSD  Linux  Maemo  OS X  Windows 10  Windows 2000  Windows 7  Windows 8  Windows 8.1  Windows NT  Windows NT 4.10  Windows Vista  Windows XP\n",
       "version                                                                                                                                                                                       \n",
       "40.0.3                0            0       0        0      2      0     5          14             0         21          2           10           1                0              2           9\n",
       "41.0                  0            0       0        0     19      0    27          89             0        124          7           25           0                1             12          39\n",
       "41.0.1                1            0       1        0     58      0   117         290             0        513         19          133           0                0             56         153\n",
       "41.0.2                0            1       0        0     11      0    56         206             0        316         14           86           0                0             30          95\n",
       "42.0                  0            1       0        0      2      0    17          47             0         74          8            8           0                0             16          14\n",
       "44.0a1                0            0       0        1      9      0     3          33             0         23          0            5           0                0              2           0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Removing versions having a total negative feedback count of less than 30\n",
    "#Note that I haven't used a for loop since the upper limit is taken to be non-changing in for loops.\n",
    "#But in our case, we keep decrementing nrows every time a row is deleted. So I have used a do-while equivalent\n",
    "#in Python.\n",
    "\n",
    "nrows = len(pt1)\n",
    "i = 0;\n",
    "while True:\n",
    "    row = pt1.ix[i,]\n",
    "    if(row.sum()<30):\n",
    "        pt1.drop(pt1.index[i],inplace=True)\n",
    "        i=i-1 #Because of dropping, indexing of rows changes. So need to read next row from same position\n",
    "        nrows = nrows-1\n",
    "    i = i+1\n",
    "    if(i>=nrows):\n",
    "        break\n",
    "\n",
    "pt1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# You can also plot a heatmap with normed values if needed. Replace pt1 with pt1_norm in the next code snippet.\n",
    "# And uncomment below line.\n",
    "\n",
    "#pt1_norm = (pt1 - pt1.mean()) / (pt1.max() - pt1.min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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ctLAlai0PtJfJPJOvtUzmmXyTmsnmcJmS/ApdA/UU4IfAx+iW6+43ZF1L1WCe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\nEMZhEARBEARBEARBAPwPcAmm5hi0QTgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f9677a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Resources:\n",
    "#http://stackoverflow.com/questions/14391959/heatmap-in-matplotlib-with-pcolor\n",
    "#https://plot.ly/python/heatmaps/\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "heatmap = ax.pcolor(pt1, cmap=plt.cm.Reds, alpha=0.89)\n",
    "\n",
    "# Format\n",
    "fig = plt.gcf()\n",
    "fig.set_size_inches(15,5)\n",
    "\n",
    "# turn off the frame\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "# put the major ticks at the middle of each cell\n",
    "ax.set_yticks(np.arange(pt1.shape[0]) + 0.5, minor=False)\n",
    "ax.set_xticks(np.arange(pt1.shape[1]) + 0.5, minor=False)\n",
    "\n",
    "# want a more natural, table-like display\n",
    "ax.invert_yaxis()\n",
    "ax.xaxis.tick_top()\n",
    "\n",
    "# Set the labels\n",
    "ax.set_xticklabels(pt1.columns, minor=False)\n",
    "ax.set_yticklabels(pt1.index, minor=False)\n",
    "\n",
    "# rotate the x labels\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "ax.grid(False)\n",
    "\n",
    "# Turn off all the ticks\n",
    "ax = plt.gca()\n",
    "\n",
    "for t in ax.xaxis.get_major_ticks():\n",
    "    t.tick1On = False\n",
    "    t.tick2On = False\n",
    "for t in ax.yaxis.get_major_ticks():\n",
    "    t.tick1On = False\n",
    "    t.tick2On = False\n",
    "    \n",
    "# name the axes and plot\n",
    "ax.set_xlabel('Platform')\n",
    "ax.set_ylabel('Version') \n",
    "ax.xaxis.set_label_position('top')\n",
    "plt.title('Heatmap of Version vs Platform having negative feedback',y=-0.08)\n",
    "\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "#lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5,-0.1))\n",
    "#fig.savefig('heatmap.png', bbox_extra_artists=(lgd,), bbox_inches='tight')\n",
    "fig.savefig('fig5.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Voila! Here is our much-waited heatmap!<br/>\n",
    "#### Some observations:\n",
    "1. Version 41.0.1 is in general problematic with a lot of platforms, Windows 7 and 10 in general.<br/>\n",
    "2. Version 41.0.2 (which seems to be an updated version of 41.0.1) has fewer number of issues, but users are still facing problems. So it will have to be looked into.\n",
    "3. Firefox probably works best with Linux, as it has a remarkably low negative feedback count.\n",
    "\n",
    "### Repeating the heatmap process for positive feedback\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>platform</th>\n",
       "      <th>Android 4.2.2</th>\n",
       "      <th>Linux</th>\n",
       "      <th>Maemo</th>\n",
       "      <th>OS X</th>\n",
       "      <th>Windows 10</th>\n",
       "      <th>Windows 7</th>\n",
       "      <th>Windows 8</th>\n",
       "      <th>Windows 8.1</th>\n",
       "      <th>Windows Vista</th>\n",
       "      <th>Windows XP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.0.2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform  Android 4.2.2  Linux  Maemo  OS X  Windows 10  Windows 7  Windows 8  Windows 8.1  Windows Vista  Windows XP\n",
       "version                                                                                                              \n",
       "10.0                  0      0      0     0           0          1          0            0              1           0\n",
       "10.0.2                0      0      0     0           0          1          0            0              0           1\n",
       "11.0                  0      0      0     0           0          3          1            0              0           0\n",
       "12.0                  0      0      0     0           0          2          2            0              0           0\n",
       "13.0                  0      0      0     0           0          2          1            0              0           2"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt2 = pd.pivot_table(data[(data.sentiment=='Happy') & (data.version!='Unknown') & (data.platform!='Unknown')], \n",
    "                    index='version', values='dummy', columns='platform', aggfunc=np.sum, fill_value=0)\n",
    "pt2.head()\n",
    "#use pt2 to look at the entire pivot table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>platform</th>\n",
       "      <th>Android 4.2.2</th>\n",
       "      <th>Linux</th>\n",
       "      <th>Maemo</th>\n",
       "      <th>OS X</th>\n",
       "      <th>Windows 10</th>\n",
       "      <th>Windows 7</th>\n",
       "      <th>Windows 8</th>\n",
       "      <th>Windows 8.1</th>\n",
       "      <th>Windows Vista</th>\n",
       "      <th>Windows XP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40.0.3</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0</th>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0.1</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>48</td>\n",
       "      <td>55</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0.2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>26</td>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42.0</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44.0a1</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8.0</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform  Android 4.2.2  Linux  Maemo  OS X  Windows 10  Windows 7  Windows 8  Windows 8.1  Windows Vista  Windows XP\n",
       "version                                                                                                              \n",
       "40.0                  0      0      0     1           4          3          0            1              0           2\n",
       "40.0.3                0      2      0     1           1          8          0            2              0           5\n",
       "41.0                  0      7      0     3          12         24          2           10              2           9\n",
       "41.0.1                1      9      0    15          48         55          4           17              5          45\n",
       "41.0.2                0      3      0     4          26         34          2            7              4          26\n",
       "42.0                  0      2      0     2           6         23          0            3              5           5\n",
       "44.0a1                0      3      0     1           5          3          1            1              0           0\n",
       "8.0                   0     12      0     0           0          3          0            0              0           2"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Removing versions having a total positive feedback count of less than 20\n",
    "\n",
    "nrows = len(pt2)\n",
    "i = 0;\n",
    "while True:\n",
    "    row = pt2.ix[i,]\n",
    "    if(row.sum()<10):\n",
    "        pt2.drop(pt2.index[i],inplace=True)\n",
    "        i=i-1 #Because of dropping, indexing of rows changes. So need to read next row from same position\n",
    "        nrows = nrows-1\n",
    "    i = i+1\n",
    "    if(i>=nrows):\n",
    "        break\n",
    "\n",
    "pt2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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HlUqSJEmSbA4lSZIkSTaHkiRJkiRsDiVJkiRJ2BxKkiRJkrA5lCRJkiRhcyhJ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\nkY23ldzu/gJwP6EYzwd+ml42QCijS0u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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f44f965e610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Resources:\n",
    "#http://stackoverflow.com/questions/14391959/heatmap-in-matplotlib-with-pcolor\n",
    "#https://plot.ly/python/heatmaps/\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "heatmap = ax.pcolor(pt2, cmap=plt.cm.Greens, alpha=0.89)\n",
    "\n",
    "# Format\n",
    "fig = plt.gcf()\n",
    "fig.set_size_inches(15,5)\n",
    "\n",
    "# turn off the frame\n",
    "ax.set_frame_on(False)\n",
    "\n",
    "# put the major ticks at the middle of each cell\n",
    "ax.set_yticks(np.arange(pt2.shape[0]) + 0.5, minor=False)\n",
    "ax.set_xticks(np.arange(pt2.shape[1]) + 0.5, minor=False)\n",
    "\n",
    "# want a more natural, table-like display\n",
    "ax.invert_yaxis()\n",
    "ax.xaxis.tick_top()\n",
    "\n",
    "# Set the labels\n",
    "ax.set_xticklabels(pt2.columns, minor=False)\n",
    "ax.set_yticklabels(pt2.index, minor=False)\n",
    "\n",
    "# rotate the x labels\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "ax.grid(False)\n",
    "\n",
    "# Turn off all the ticks\n",
    "ax = plt.gca()\n",
    "\n",
    "for t in ax.xaxis.get_major_ticks():\n",
    "    t.tick1On = False\n",
    "    t.tick2On = False\n",
    "for t in ax.yaxis.get_major_ticks():\n",
    "    t.tick1On = False\n",
    "    t.tick2On = False\n",
    "    \n",
    "# name the axes and plot\n",
    "ax.set_xlabel('Platform')\n",
    "ax.set_ylabel('Version') \n",
    "ax.xaxis.set_label_position('top')\n",
    "plt.title('Heatmap of Version vs Platform having positive feedback',y=-0.08)\n",
    "\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "#lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5,-0.1))\n",
    "#fig.savefig('heatmap.png', bbox_extra_artists=(lgd,), bbox_inches='tight')\n",
    "fig.savefig('fig6.png', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We notice a similar trend in this heatmap as well. But it should be noted that positive count is much lesser than the negative one. A heatmap is always relative to the data that is used for plotting it.\n",
    "\n",
    "<br/><br/>Finally we need to delete the dummy column that we had created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentiment</th>\n",
       "      <th>date</th>\n",
       "      <th>version</th>\n",
       "      <th>platform</th>\n",
       "      <th>locale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Linux</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Windows XP</td>\n",
       "      <td>Vietnamese</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Happy</td>\n",
       "      <td>18</td>\n",
       "      <td>41.0.2</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sad</td>\n",
       "      <td>18</td>\n",
       "      <td>38.3.0</td>\n",
       "      <td>Windows 7</td>\n",
       "      <td>English (US)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sentiment  date version    platform        locale\n",
       "0       Sad    18    41.0       Linux  English (US)\n",
       "1       Sad    18    41.0  Windows XP    Vietnamese\n",
       "2     Happy    18  41.0.2   Windows 7  English (US)\n",
       "3       Sad    18    37.0   Windows 7  English (US)\n",
       "4       Sad    18  38.3.0   Windows 7  English (US)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#deleting the dummy column\n",
    "\n",
    "data.drop('dummy', axis=1, inplace=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Final Thoughts\n",
    " In this analysis, a Mozilla Firefox feedback data was analyzed and certain insights were drawn into user behaviour and version/platform dependency. \n",
    " \n",
    "#### Further Analysis:\n",
    "1. I hope to scrape a larger amount of data (3 months' worth) and run the analysis again.<br/>\n",
    "2. It might help to explore some group properties<br/>\n",
    "3. An extensive time-series analysis can be performed for data over a longer period of time to determine whether issues have been resolved or new ones have cropped up after a version update<br/>"
   ]
  }
 ],
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