07_category_ranking.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "import os\n",
    "import itertools\n",
    "\n",
    "from multiprocessing import Pool\n",
    "from itertools import product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%run config.py\n",
    "%run shared.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "valid = pd.read_pickle(PATH_VALID_DEVICES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Category ranking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**RQ:** What do users see when they open the notification drawer (or the lock screen)? How many notifications are there and from what kind of apps (categories)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "MAX_POSITIONS = 5\n",
    "\n",
    "def get_packages_at_positions(lst):\n",
    "    lst = lst[:MAX_POSITIONS]\n",
    "    result = []\n",
    "    for n in lst:\n",
    "        result.append(n['packageName'])\n",
    "    result += ['_NONE_' for x in range(MAX_POSITIONS - len(result))]\n",
    "    return result\n",
    "\n",
    "def worker_ranking(uuid):\n",
    "    df = pd.read_pickle('%s%s.pkl.gz' % (PATH_DEVICES_DIR, uuid), compression='gzip')\n",
    "    df.Active = df.Active.apply(filter_active)\n",
    "    df.Active = df.Active.apply(get_packages_at_positions)\n",
    "    \n",
    "    result = pd.DataFrame(columns=['UUID', 'Position', 'PackageName', 'Percentage'])\n",
    "    for i in range(MAX_POSITIONS):\n",
    "        counts = df.Active.apply(lambda x: x[i]).value_counts(dropna=False, normalize=True)\n",
    "        for index, value in counts.iteritems():\n",
    "            result = result.append({\n",
    "                'UUID': uuid,\n",
    "                'Position': i + 1,\n",
    "                'PackageName': index,\n",
    "                'Percentage': value\n",
    "            }, ignore_index=True)\n",
    "        \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "uuids = valid.UUID.tolist()\n",
    "\n",
    "p = Pool(NUM_CORES)\n",
    "lst = p.map(worker_ranking, uuids)\n",
    "\n",
    "ranking = pd.concat(lst)\n",
    "ranking = ranking.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UUID</th>\n",
       "      <th>Position</th>\n",
       "      <th>PackageName</th>\n",
       "      <th>Percentage</th>\n",
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       "  </thead>\n",
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       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>427757</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>com.android.mms</td>\n",
       "      <td>0.001020</td>\n",
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       "      <td>device.3952</td>\n",
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      "text/plain": [
       "               UUID Position                 PackageName  Percentage\n",
       "427756  device.3952        3                     android    0.003061\n",
       "427757  device.3952        3             com.android.mms    0.001020\n",
       "427758  device.3952        3  com.android.server.telecom    0.001020\n",
       "427759  device.3952        4                      _NONE_    1.000000\n",
       "427760  device.3952        5                      _NONE_    1.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UUID</th>\n",
       "      <th>Position</th>\n",
       "      <th>PackageName</th>\n",
       "      <th>Percentage</th>\n",
       "      <th>Category</th>\n",
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       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
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       "      <td>SYSTEM</td>\n",
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       "    <tr>\n",
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       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>com.android.mms</td>\n",
       "      <td>0.001020</td>\n",
       "      <td>SMS/IM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427758</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>com.android.server.telecom</td>\n",
       "      <td>0.001020</td>\n",
       "      <td>PHONE</td>\n",
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       "               UUID Position                 PackageName  Percentage Category\n",
       "427756  device.3952        3                     android    0.003061   SYSTEM\n",
       "427757  device.3952        3             com.android.mms    0.001020   SMS/IM\n",
       "427758  device.3952        3  com.android.server.telecom    0.001020    PHONE\n",
       "427759  device.3952        4                      _NONE_    1.000000     NONE\n",
       "427760  device.3952        5                      _NONE_    1.000000     NONE"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking['Category'] = ranking.PackageName.apply(lambda x: category_mapping[x] if x in category_mapping else 'UNKNOWN')\n",
    "ranking.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SYSTEM               92055\n",
       "TOOL                 49608\n",
       "UNKNOWN              47816\n",
       "SMS/IM               41047\n",
       "MEDIA                39277\n",
       "SOCIAL               36065\n",
       "PHONE                22368\n",
       "NONE                 19612\n",
       "SHOPPING             17998\n",
       "GAME                 13940\n",
       "EMAIL                12478\n",
       "CALENDAR/REMINDER    11460\n",
       "NAVIGATION           10987\n",
       "NEWS                  9486\n",
       "HEALTH/FITNESS        3564\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking.Category.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unknown category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "package.0095    45\n",
       "package.0082    42\n",
       "package.0063    41\n",
       "package.0050    41\n",
       "package.0047    41\n",
       "package.0094    40\n",
       "package.0043    40\n",
       "package.0072    40\n",
       "package.0104    40\n",
       "package.0083    40\n",
       "Name: PackageName, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking[(ranking.Category == 'UNKNOWN')].PackageName.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PackageName\n",
       "package.6163    0.536036\n",
       "package.7589    0.492343\n",
       "package.5567    0.483115\n",
       "package.5269    0.472335\n",
       "package.5940    0.467033\n",
       "package.4599    0.405332\n",
       "package.7037    0.385488\n",
       "package.7816    0.367729\n",
       "package.4409    0.325232\n",
       "package.4753    0.322331\n",
       "Name: Percentage, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking[(ranking.Category == 'UNKNOWN')] \\\n",
    "    .groupby('PackageName') \\\n",
    "    .Percentage.mean() \\\n",
    "    .sort_values(ascending=False) \\\n",
    "    .head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "package.0095    45\n",
       "package.0082    42\n",
       "package.0063    41\n",
       "package.0050    41\n",
       "package.0047    41\n",
       "package.0094    40\n",
       "package.0043    40\n",
       "package.0072    40\n",
       "package.0104    40\n",
       "package.0083    40\n",
       "Name: PackageName, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking[(ranking.Category == 'UNKNOWN')].PackageName.apply(lambda x: '.'.join(x.split('.')[:4])).value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Category distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "      <td>com.android.mms</td>\n",
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       "      <td>SMS/IM</td>\n",
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       "      <td>device.3952</td>\n",
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      "text/plain": [
       "               UUID Position                 PackageName  Percentage Category\n",
       "427756  device.3952        3                     android    0.003061   SYSTEM\n",
       "427757  device.3952        3             com.android.mms    0.001020   SMS/IM\n",
       "427758  device.3952        3  com.android.server.telecom    0.001020    PHONE\n",
       "427759  device.3952        4                      _NONE_    1.000000     NONE\n",
       "427760  device.3952        5                      _NONE_    1.000000     NONE"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
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      ],
      "text/plain": [
       "                      NONE  SYSTEM  SMS/IM  PHONE  TOOL  GAME  \\\n",
       "UUID        Position                                            \n",
       "device.3952 1          NaN     NaN     NaN    NaN   NaN   NaN   \n",
       "            2          NaN     NaN     NaN    NaN   NaN   NaN   \n",
       "            3          NaN     NaN     NaN    NaN   NaN   NaN   \n",
       "            4          NaN     NaN     NaN    NaN   NaN   NaN   \n",
       "            5          NaN     NaN     NaN    NaN   NaN   NaN   \n",
       "\n",
       "                      CALENDAR/REMINDER  UNKNOWN  SOCIAL  SHOPPING  \\\n",
       "UUID        Position                                                 \n",
       "device.3952 1                       NaN      NaN     NaN       NaN   \n",
       "            2                       NaN      NaN     NaN       NaN   \n",
       "            3                       NaN      NaN     NaN       NaN   \n",
       "            4                       NaN      NaN     NaN       NaN   \n",
       "            5                       NaN      NaN     NaN       NaN   \n",
       "\n",
       "                      HEALTH/FITNESS  MEDIA  NEWS  NAVIGATION  EMAIL  \n",
       "UUID        Position                                                  \n",
       "device.3952 1                    NaN    NaN   NaN         NaN    NaN  \n",
       "            2                    NaN    NaN   NaN         NaN    NaN  \n",
       "            3                    NaN    NaN   NaN         NaN    NaN  \n",
       "            4                    NaN    NaN   NaN         NaN    NaN  \n",
       "            5                    NaN    NaN   NaN         NaN    NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking2 = pd.DataFrame(list(product(ranking.UUID.unique(), range(1, MAX_POSITIONS + 1))),\n",
    "             columns=['UUID', 'Position'])\n",
    "\n",
    "for category in ranking.Category.unique():\n",
    "    ranking2[category] = pd.Series()\n",
    "\n",
    "ranking2 = ranking2.set_index(['UUID', 'Position'])\n",
    "    \n",
    "ranking2.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UUID</th>\n",
       "      <th>Position</th>\n",
       "      <th>Category</th>\n",
       "      <th>Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186434</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>PHONE</td>\n",
       "      <td>0.001020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186435</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>SMS/IM</td>\n",
       "      <td>0.001020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186436</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>3</td>\n",
       "      <td>SYSTEM</td>\n",
       "      <td>0.003061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186437</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>4</td>\n",
       "      <td>NONE</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186438</th>\n",
       "      <td>device.3952</td>\n",
       "      <td>5</td>\n",
       "      <td>NONE</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               UUID  Position Category  Percentage\n",
       "186434  device.3952         3    PHONE    0.001020\n",
       "186435  device.3952         3   SMS/IM    0.001020\n",
       "186436  device.3952         3   SYSTEM    0.003061\n",
       "186437  device.3952         4     NONE    1.000000\n",
       "186438  device.3952         5     NONE    1.000000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ranking.groupby(['UUID', 'Position', 'Category'], as_index=False).sum()\n",
    "g.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "10000\n",
      "20000\n",
      "30000\n",
      "40000\n",
      "50000\n",
      "60000\n",
      "70000\n",
      "80000\n",
      "90000\n",
      "100000\n",
      "110000\n",
      "120000\n",
      "130000\n",
      "140000\n",
      "150000\n",
      "160000\n",
      "170000\n",
      "180000\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>NONE</th>\n",
       "      <th>SYSTEM</th>\n",
       "      <th>SMS/IM</th>\n",
       "      <th>PHONE</th>\n",
       "      <th>TOOL</th>\n",
       "      <th>GAME</th>\n",
       "      <th>CALENDAR/REMINDER</th>\n",
       "      <th>UNKNOWN</th>\n",
       "      <th>SOCIAL</th>\n",
       "      <th>SHOPPING</th>\n",
       "      <th>HEALTH/FITNESS</th>\n",
       "      <th>MEDIA</th>\n",
       "      <th>NEWS</th>\n",
       "      <th>NAVIGATION</th>\n",
       "      <th>EMAIL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UUID</th>\n",
       "      <th>Position</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",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">device.3952</th>\n",
       "      <th>1</th>\n",
       "      <td>0.486735</td>\n",
       "      <td>0.293878</td>\n",
       "      <td>0.128571</td>\n",
       "      <td>0.056122</td>\n",
       "      <td>0.002041</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.014286</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018367</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.869388</td>\n",
       "      <td>0.098980</td>\n",
       "      <td>0.016327</td>\n",
       "      <td>0.010204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004082</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.994898</td>\n",
       "      <td>0.003061</td>\n",
       "      <td>0.001020</td>\n",
       "      <td>0.001020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          NONE    SYSTEM    SMS/IM     PHONE      TOOL  GAME  \\\n",
       "UUID        Position                                                           \n",
       "device.3952 1         0.486735  0.293878  0.128571  0.056122  0.002041   NaN   \n",
       "            2         0.869388  0.098980  0.016327  0.010204       NaN   NaN   \n",
       "            3         0.994898  0.003061  0.001020  0.001020       NaN   NaN   \n",
       "            4         1.000000       NaN       NaN       NaN       NaN   NaN   \n",
       "            5         1.000000       NaN       NaN       NaN       NaN   NaN   \n",
       "\n",
       "                      CALENDAR/REMINDER   UNKNOWN  SOCIAL  SHOPPING  \\\n",
       "UUID        Position                                                  \n",
       "device.3952 1                       NaN  0.014286     NaN       NaN   \n",
       "            2                       NaN  0.001020     NaN       NaN   \n",
       "            3                       NaN       NaN     NaN       NaN   \n",
       "            4                       NaN       NaN     NaN       NaN   \n",
       "            5                       NaN       NaN     NaN       NaN   \n",
       "\n",
       "                      HEALTH/FITNESS     MEDIA  NEWS  NAVIGATION  EMAIL  \n",
       "UUID        Position                                                     \n",
       "device.3952 1                    NaN  0.018367   NaN         NaN    NaN  \n",
       "            2                    NaN  0.004082   NaN         NaN    NaN  \n",
       "            3                    NaN       NaN   NaN         NaN    NaN  \n",
       "            4                    NaN       NaN   NaN         NaN    NaN  \n",
       "            5                    NaN       NaN   NaN         NaN    NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for index, row in g.iterrows():\n",
    "    if index % 10000 == 0:\n",
    "        print(index)\n",
    "    \n",
    "    ranking2.loc[(row['UUID'], row['Position']), row['Category']] = row['Percentage']\n",
    "\n",
    "ranking2.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NONE</th>\n",
       "      <th>SYSTEM</th>\n",
       "      <th>SMS/IM</th>\n",
       "      <th>PHONE</th>\n",
       "      <th>TOOL</th>\n",
       "      <th>GAME</th>\n",
       "      <th>CALENDAR/REMINDER</th>\n",
       "      <th>UNKNOWN</th>\n",
       "      <th>SOCIAL</th>\n",
       "      <th>SHOPPING</th>\n",
       "      <th>HEALTH/FITNESS</th>\n",
       "      <th>MEDIA</th>\n",
       "      <th>NEWS</th>\n",
       "      <th>NAVIGATION</th>\n",
       "      <th>EMAIL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Position</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>1</th>\n",
       "      <td>0.219647</td>\n",
       "      <td>0.131091</td>\n",
       "      <td>0.198862</td>\n",
       "      <td>0.050646</td>\n",
       "      <td>0.088665</td>\n",
       "      <td>0.013044</td>\n",
       "      <td>0.011950</td>\n",
       "      <td>0.065951</td>\n",
       "      <td>0.101947</td>\n",
       "      <td>0.008317</td>\n",
       "      <td>0.009639</td>\n",
       "      <td>0.066117</td>\n",
       "      <td>0.011021</td>\n",
       "      <td>0.006028</td>\n",
       "      <td>0.017074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.439091</td>\n",
       "      <td>0.118725</td>\n",
       "      <td>0.074548</td>\n",
       "      <td>0.029987</td>\n",
       "      <td>0.079525</td>\n",
       "      <td>0.013048</td>\n",
       "      <td>0.008810</td>\n",
       "      <td>0.059537</td>\n",
       "      <td>0.086108</td>\n",
       "      <td>0.008151</td>\n",
       "      <td>0.007674</td>\n",
       "      <td>0.038558</td>\n",
       "      <td>0.010336</td>\n",
       "      <td>0.007306</td>\n",
       "      <td>0.018597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.604845</td>\n",
       "      <td>0.088448</td>\n",
       "      <td>0.034488</td>\n",
       "      <td>0.016724</td>\n",
       "      <td>0.062258</td>\n",
       "      <td>0.010494</td>\n",
       "      <td>0.005811</td>\n",
       "      <td>0.046075</td>\n",
       "      <td>0.059070</td>\n",
       "      <td>0.006655</td>\n",
       "      <td>0.005428</td>\n",
       "      <td>0.029922</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.006808</td>\n",
       "      <td>0.014675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.717566</td>\n",
       "      <td>0.062133</td>\n",
       "      <td>0.020257</td>\n",
       "      <td>0.010081</td>\n",
       "      <td>0.046794</td>\n",
       "      <td>0.007954</td>\n",
       "      <td>0.003824</td>\n",
       "      <td>0.034265</td>\n",
       "      <td>0.041315</td>\n",
       "      <td>0.005117</td>\n",
       "      <td>0.003978</td>\n",
       "      <td>0.023454</td>\n",
       "      <td>0.006465</td>\n",
       "      <td>0.005907</td>\n",
       "      <td>0.010889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.791614</td>\n",
       "      <td>0.044342</td>\n",
       "      <td>0.013179</td>\n",
       "      <td>0.006334</td>\n",
       "      <td>0.035445</td>\n",
       "      <td>0.006068</td>\n",
       "      <td>0.002528</td>\n",
       "      <td>0.026287</td>\n",
       "      <td>0.031041</td>\n",
       "      <td>0.003848</td>\n",
       "      <td>0.002951</td>\n",
       "      <td>0.018821</td>\n",
       "      <td>0.004823</td>\n",
       "      <td>0.004841</td>\n",
       "      <td>0.007879</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              NONE    SYSTEM    SMS/IM     PHONE      TOOL      GAME  \\\n",
       "Position                                                               \n",
       "1         0.219647  0.131091  0.198862  0.050646  0.088665  0.013044   \n",
       "2         0.439091  0.118725  0.074548  0.029987  0.079525  0.013048   \n",
       "3         0.604845  0.088448  0.034488  0.016724  0.062258  0.010494   \n",
       "4         0.717566  0.062133  0.020257  0.010081  0.046794  0.007954   \n",
       "5         0.791614  0.044342  0.013179  0.006334  0.035445  0.006068   \n",
       "\n",
       "          CALENDAR/REMINDER   UNKNOWN    SOCIAL  SHOPPING  HEALTH/FITNESS  \\\n",
       "Position                                                                    \n",
       "1                  0.011950  0.065951  0.101947  0.008317        0.009639   \n",
       "2                  0.008810  0.059537  0.086108  0.008151        0.007674   \n",
       "3                  0.005811  0.046075  0.059070  0.006655        0.005428   \n",
       "4                  0.003824  0.034265  0.041315  0.005117        0.003978   \n",
       "5                  0.002528  0.026287  0.031041  0.003848        0.002951   \n",
       "\n",
       "             MEDIA      NEWS  NAVIGATION     EMAIL  \n",
       "Position                                            \n",
       "1         0.066117  0.011021    0.006028  0.017074  \n",
       "2         0.038558  0.010336    0.007306  0.018597  \n",
       "3         0.029922  0.008299    0.006808  0.014675  \n",
       "4         0.023454  0.006465    0.005907  0.010889  \n",
       "5         0.018821  0.004823    0.004841  0.007879  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking2 = ranking2.fillna(0)\n",
    "ranking2 = ranking2.groupby('Position').mean()\n",
    "ranking2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Position\n",
       "1    1.0\n",
       "2    1.0\n",
       "3    1.0\n",
       "4    1.0\n",
       "5    1.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking2.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "ranking2 = ranking2[[\n",
    "    'PHONE',\n",
    "    'SMS/IM', 'SOCIAL',\n",
    "    'EMAIL', 'CALENDAR/REMINDER',\n",
    "    'SYSTEM', 'TOOL',\n",
    "    \n",
    "    'NAVIGATION', 'MEDIA', 'SHOPPING', 'GAME', 'NEWS', 'HEALTH/FITNESS', # 'WEATHER',\n",
    "    'UNKNOWN', 'NONE'\n",
    "]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8824"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(category_mapping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set(category_mapping.values()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot category ranking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ranking_plot = ranking2.copy()\n",
    "\n",
    "# Remove capslock from column names\n",
    "ranking_plot.columns = pd.Series(ranking_plot.columns).apply(str.title).tolist()\n",
    "\n",
    "# Sort by column name\n",
    "ranking_plot = ranking_plot.reindex(sorted(ranking_plot.columns[:-2]) + list(ranking_plot.columns[-2:]), axis=1)\n",
    "\n",
    "# Rename specific columns\n",
    "ranking_plot = ranking_plot.rename(columns={\n",
    "    'Shopping': 'Shopping &\\nFinance',\n",
    "    'Calendar/Reminder': 'Calendar &\\nReminder',\n",
    "    'Health/Fitness': 'Health &\\nFitness',\n",
    "    'Sms/Im': 'SMS & IM',\n",
    "    'Unknown': 'Uncategorized',\n",
    "    'Social': 'Social &\\nDating',\n",
    "    'None': 'No notification\\nshown',\n",
    "    'News': 'News &\\nWeather'\n",
    "})\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "im = ax.imshow(np.log(ranking_plot.values), cmap='GnBu') # , vmax=1\n",
    "\n",
    "# Ticks\n",
    "ax.set_xticks(range(len(ranking_plot.columns)))\n",
    "ax.set_yticks(range(len(ranking_plot.index)))\n",
    "\n",
    "# Tick labels\n",
    "ax.set_xticklabels(ranking_plot.columns)\n",
    "ax.set_yticklabels(range(1, 6))\n",
    "\n",
    "# Rotate labels\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha='right', rotation_mode='anchor')\n",
    "\n",
    "# Labels\n",
    "ax.set_xlabel('', fontsize=10)\n",
    "ax.set_ylabel('Position', fontsize=10)\n",
    "ax.tick_params(labelsize=10)\n",
    "\n",
    "# Values\n",
    "for i in range(len(ranking_plot.index)):\n",
    "    for j in range(len(ranking_plot.columns)):\n",
    "        value = ranking_plot.values[i, j]\n",
    "        color = 'k' #if value < 0.2 else 'w'\n",
    "        text = str(np.round(value * 100, 1)) + '%'\n",
    "        ax.text(j, i, text, ha='center', va='center', color=color, fontsize=10)\n",
    "\n",
    "ax.set_yticks([x + 0.5 for x in range(0, 5)], minor=True)\n",
    "ax.grid(which='minor', color='k', linestyle='-', linewidth=1)\n",
    "ax.tick_params(which='minor', bottom=False, left=False)\n",
    "    \n",
    "plt.savefig('figures/category_positions.png', bbox_inches='tight', pad_inches=0, dpi=300)\n",
    "plt.savefig('figures/category_positions.pdf', bbox_inches='tight', pad_inches=0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Position 1\n",
      "-----------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NONE                 0.219647\n",
       "SMS/IM               0.198862\n",
       "SYSTEM               0.131091\n",
       "SOCIAL               0.101947\n",
       "TOOL                 0.088665\n",
       "MEDIA                0.066117\n",
       "UNKNOWN              0.065951\n",
       "PHONE                0.050646\n",
       "EMAIL                0.017074\n",
       "GAME                 0.013044\n",
       "CALENDAR/REMINDER    0.011950\n",
       "NEWS                 0.011021\n",
       "HEALTH/FITNESS       0.009639\n",
       "SHOPPING             0.008317\n",
       "NAVIGATION           0.006028\n",
       "Name: 1, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Position 2\n",
      "-----------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NONE                 0.439091\n",
       "SYSTEM               0.118725\n",
       "SOCIAL               0.086108\n",
       "TOOL                 0.079525\n",
       "SMS/IM               0.074548\n",
       "UNKNOWN              0.059537\n",
       "MEDIA                0.038558\n",
       "PHONE                0.029987\n",
       "EMAIL                0.018597\n",
       "GAME                 0.013048\n",
       "NEWS                 0.010336\n",
       "CALENDAR/REMINDER    0.008810\n",
       "SHOPPING             0.008151\n",
       "HEALTH/FITNESS       0.007674\n",
       "NAVIGATION           0.007306\n",
       "Name: 2, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Position 3\n",
      "-----------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NONE                 0.604845\n",
       "SYSTEM               0.088448\n",
       "TOOL                 0.062258\n",
       "SOCIAL               0.059070\n",
       "UNKNOWN              0.046075\n",
       "SMS/IM               0.034488\n",
       "MEDIA                0.029922\n",
       "PHONE                0.016724\n",
       "EMAIL                0.014675\n",
       "GAME                 0.010494\n",
       "NEWS                 0.008299\n",
       "NAVIGATION           0.006808\n",
       "SHOPPING             0.006655\n",
       "CALENDAR/REMINDER    0.005811\n",
       "HEALTH/FITNESS       0.005428\n",
       "Name: 3, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Position 4\n",
      "-----------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NONE                 0.717566\n",
       "SYSTEM               0.062133\n",
       "TOOL                 0.046794\n",
       "SOCIAL               0.041315\n",
       "UNKNOWN              0.034265\n",
       "MEDIA                0.023454\n",
       "SMS/IM               0.020257\n",
       "EMAIL                0.010889\n",
       "PHONE                0.010081\n",
       "GAME                 0.007954\n",
       "NEWS                 0.006465\n",
       "NAVIGATION           0.005907\n",
       "SHOPPING             0.005117\n",
       "HEALTH/FITNESS       0.003978\n",
       "CALENDAR/REMINDER    0.003824\n",
       "Name: 4, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Position 5\n",
      "-----------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NONE                 0.791614\n",
       "SYSTEM               0.044342\n",
       "TOOL                 0.035445\n",
       "SOCIAL               0.031041\n",
       "UNKNOWN              0.026287\n",
       "MEDIA                0.018821\n",
       "SMS/IM               0.013179\n",
       "EMAIL                0.007879\n",
       "PHONE                0.006334\n",
       "GAME                 0.006068\n",
       "NAVIGATION           0.004841\n",
       "NEWS                 0.004823\n",
       "SHOPPING             0.003848\n",
       "HEALTH/FITNESS       0.002951\n",
       "CALENDAR/REMINDER    0.002528\n",
       "Name: 5, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 5):\n",
    "    print('Position %s\\n-----------------------------' % (i + 1))\n",
    "    display(ranking2.iloc[i].T.sort_values(ascending=False))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1: ['SMS/IM', 'SYSTEM', 'SOCIAL', 'TOOL', 'MEDIA']\n",
      "2: ['SYSTEM', 'SOCIAL', 'TOOL', 'SMS/IM', 'UNKNOWN']\n",
      "3: ['SYSTEM', 'TOOL', 'SOCIAL', 'UNKNOWN', 'SMS/IM']\n",
      "4: ['SYSTEM', 'TOOL', 'SOCIAL', 'UNKNOWN', 'MEDIA']\n",
      "5: ['SYSTEM', 'TOOL', 'SOCIAL', 'UNKNOWN', 'MEDIA']\n"
     ]
    }
   ],
   "source": [
    "test = ranking2.copy()\n",
    "del test['NONE']\n",
    "\n",
    "for index in test.index:\n",
    "    print('%s: %s' % (index, test.loc[index].T.sort_values(ascending=False).index.tolist()[:5]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Category counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UNKNOWN              7915\n",
       "TOOL                  190\n",
       "MEDIA                 150\n",
       "SHOPPING              127\n",
       "GAME                  111\n",
       "SYSTEM                 94\n",
       "NEWS                   48\n",
       "SMS/IM                 45\n",
       "SOCIAL                 40\n",
       "HEALTH/FITNESS         24\n",
       "NAVIGATION             24\n",
       "CALENDAR/REMINDER      23\n",
       "PHONE                  18\n",
       "EMAIL                  14\n",
       "NONE                    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_counts = pd.Series(list(category_mapping.values())).value_counts()\n",
    "category_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7915</td>\n",
       "      <td>UNKNOWN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>190</td>\n",
       "      <td>TOOL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>150</td>\n",
       "      <td>MEDIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>127</td>\n",
       "      <td>SHOPPING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>111</td>\n",
       "      <td>GAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>94</td>\n",
       "      <td>SYSTEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>48</td>\n",
       "      <td>NEWS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>45</td>\n",
       "      <td>SMS/IM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>40</td>\n",
       "      <td>SOCIAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24</td>\n",
       "      <td>HEALTH/FITNESS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>24</td>\n",
       "      <td>NAVIGATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23</td>\n",
       "      <td>CALENDAR/REMINDER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>18</td>\n",
       "      <td>PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>EMAIL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Count           Category\n",
       "0    7915            UNKNOWN\n",
       "1     190               TOOL\n",
       "2     150              MEDIA\n",
       "3     127           SHOPPING\n",
       "4     111               GAME\n",
       "5      94             SYSTEM\n",
       "6      48               NEWS\n",
       "7      45             SMS/IM\n",
       "8      40             SOCIAL\n",
       "9      24     HEALTH/FITNESS\n",
       "10     24         NAVIGATION\n",
       "11     23  CALENDAR/REMINDER\n",
       "12     18              PHONE\n",
       "13     14              EMAIL"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_counts_2 = category_counts[(category_counts.index != 'NONE')] # & (category_counts.index != 'UNKNOWN')\n",
    "category_counts_2 = pd.DataFrame(category_counts_2)\n",
    "\n",
    "category_counts_2['Category'] = category_counts_2.index\n",
    "category_counts_2 = category_counts_2.rename(columns={\n",
    "    0: 'Count'\n",
    "})\n",
    "category_counts_2 = category_counts_2.reset_index(drop=True)\n",
    "\n",
    "category_counts_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(category_counts_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>23</td>\n",
       "      <td>Calendar &amp; Reminder</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Email</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>111</td>\n",
       "      <td>Game</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24</td>\n",
       "      <td>Health &amp; Fitness</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>150</td>\n",
       "      <td>Media</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>24</td>\n",
       "      <td>Navigation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>48</td>\n",
       "      <td>News</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>18</td>\n",
       "      <td>Phone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>127</td>\n",
       "      <td>Shopping &amp; Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>45</td>\n",
       "      <td>SMS &amp; IM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>40</td>\n",
       "      <td>Social &amp; Dating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>94</td>\n",
       "      <td>System</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>190</td>\n",
       "      <td>Tool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7915</td>\n",
       "      <td>Uncategorized</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Count             Category\n",
       "11     23  Calendar & Reminder\n",
       "13     14                Email\n",
       "4     111                 Game\n",
       "9      24     Health & Fitness\n",
       "2     150                Media\n",
       "10     24           Navigation\n",
       "6      48                 News\n",
       "12     18                Phone\n",
       "3     127   Shopping & Finance\n",
       "7      45             SMS & IM\n",
       "8      40      Social & Dating\n",
       "5      94               System\n",
       "1     190                 Tool\n",
       "0    7915        Uncategorized"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_counts_2.Category = category_counts_2.Category.apply(str.title)\n",
    "category_counts_2 = category_counts_2.sort_values('Category', ascending=True)\n",
    "\n",
    "category_counts_2.Category = category_counts_2.Category.replace({\n",
    "    'Shopping': 'Shopping & Finance',\n",
    "    'Calendar/Reminder': 'Calendar & Reminder',\n",
    "    'Health/Fitness': 'Health & Fitness',\n",
    "    'Sms/Im': 'SMS & IM',\n",
    "    'Unknown': 'Uncategorized',\n",
    "    'Social': 'Social & Dating',\n",
    "    'None': 'No notification shown'\n",
    "})\n",
    "\n",
    "category_counts_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lr}\n",
      "\\toprule\n",
      "            Category &  Count \\\\\n",
      "\\midrule\n",
      " Calendar \\& Reminder &     23 \\\\\n",
      "               Email &     14 \\\\\n",
      "                Game &    111 \\\\\n",
      "    Health \\& Fitness &     24 \\\\\n",
      "               Media &    150 \\\\\n",
      "          Navigation &     24 \\\\\n",
      "                News &     48 \\\\\n",
      "               Phone &     18 \\\\\n",
      "  Shopping \\& Finance &    127 \\\\\n",
      "            SMS \\& IM &     45 \\\\\n",
      "     Social \\& Dating &     40 \\\\\n",
      "              System &     94 \\\\\n",
      "                Tool &    190 \\\\\n",
      "       Uncategorized &   7915 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(category_counts_2[['Category', 'Count']].to_latex(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = category_counts_2.plot(\n",
    "    kind='bar',\n",
    "    x='Category',\n",
    "    y='Count',\n",
    "    ylim=(0, 200),\n",
    "    figsize=(10, 4),\n",
    "    legend=False,\n",
    "    grid=True\n",
    ")\n",
    "\n",
    "# Grid\n",
    "ax.set_axisbelow(True)\n",
    "ax.xaxis.grid(alpha=0.2, linestyle='dashed')\n",
    "ax.yaxis.grid(alpha=0.2, linestyle='dashed')\n",
    "\n",
    "# Tweak font sizes\n",
    "ax.set_xlabel('', fontsize=10)\n",
    "ax.set_ylabel('# Apps', fontsize=10)\n",
    "ax.tick_params(labelsize=10)\n",
    "\n",
    "\n",
    "# Rotate labels\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha='right', rotation_mode='anchor')\n",
    "\n",
    "#plt.savefig('figures/category_counts.png', bbox_inches='tight', pad_inches=0, dpi=300)\n",
    "#plt.savefig('figures/category_counts.pdf', bbox_inches='tight', pad_inches=0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}