Sessionized Activities Analysis.ipynb

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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>childid</th>\n",
       "      <th>session_id</th>\n",
       "      <th>createdat</th>\n",
       "      <th>gamename</th>\n",
       "      <th>duration</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>wordtype</th>\n",
       "      <th>platform</th>\n",
       "      <th>gamescore</th>\n",
       "      <th>minutes_since_last_interval</th>\n",
       "      <th>new_event_boundary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1004</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-07 20:34:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>47</td>\n",
       "      <td>F</td>\n",
       "      <td>19</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-07 20:52:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>7</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-07 20:53:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>0</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-07 20:54:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>0</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1010</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-08 00:45:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>70</td>\n",
       "      <td>F</td>\n",
       "      <td>4</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   childid  session_id            createdat gamename  duration gender  age  \\\n",
       "0     1004           0  2016-11-07 20:34:00   Lagoon        47      F   19   \n",
       "1     1005           0  2016-11-07 20:52:00   Lagoon         7      F    7   \n",
       "2     1005           0  2016-11-07 20:53:00   Lagoon         0      F    7   \n",
       "3     1005           0  2016-11-07 20:54:00   Lagoon         0      F    7   \n",
       "4     1010           0  2016-11-08 00:45:00  Bubbles        70      F    4   \n",
       "\n",
       "  wordtype   platform  gamescore  minutes_since_last_interval  \\\n",
       "0     WORD  Not Known          1                          NaN   \n",
       "1     WORD  Not Known          1                          NaN   \n",
       "2     WORD  Not Known          1                          1.0   \n",
       "3     WORD  Not Known          1                          1.0   \n",
       "4     WORD  Not Known          1                          NaN   \n",
       "\n",
       "   new_event_boundary  \n",
       "0                   0  \n",
       "1                   0  \n",
       "2                   0  \n",
       "3                   0  \n",
       "4                   0  "
      ]
     },
     "execution_count": 11,
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   ],
   "source": [
    "import utils\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "import pprint\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import tree, model_selection\n",
    "\n",
    "\n",
    "df = pd.read_csv(\"Sessionized_SquarePanda.csv\", error_bad_lines=False)\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
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   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>session_id</th>\n",
       "      <th>createdat</th>\n",
       "      <th>gamename</th>\n",
       "      <th>duration</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>wordtype</th>\n",
       "      <th>platform</th>\n",
       "      <th>gamescore</th>\n",
       "      <th>minutes_since_last_interval</th>\n",
       "      <th>new_event_boundary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>childid</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>183</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-02 18:54:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>47</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-01-30 06:26:00</td>\n",
       "      <td>Bowling</td>\n",
       "      <td>158</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-05-29 00:08:00</td>\n",
       "      <td>Jiggity Jamble</td>\n",
       "      <td>175</td>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>WORD</td>\n",
       "      <td>iOS</td>\n",
       "      <td>1</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>4</td>\n",
       "      <td>2017-04-28 18:23:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>98</td>\n",
       "      <td>M</td>\n",
       "      <td>7</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Android</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-25 19:33:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>144</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>WORD</td>\n",
       "      <td>Not Known</td>\n",
       "      <td>1</td>\n",
       "      <td>24484.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         session_id            createdat        gamename  duration gender  \\\n",
       "childid                                                                     \n",
       "183               3  2017-01-02 18:54:00          Lagoon        47      F   \n",
       "188               2  2017-01-30 06:26:00         Bowling       158      M   \n",
       "189               2  2017-05-29 00:08:00  Jiggity Jamble       175      M   \n",
       "191               4  2017-04-28 18:23:00          Lagoon        98      M   \n",
       "193               4  2016-11-25 19:33:00         Bubbles       144      F   \n",
       "\n",
       "         age wordtype   platform  gamescore  minutes_since_last_interval  \\\n",
       "childid                                                                    \n",
       "183        5     WORD  Not Known          1                          8.0   \n",
       "188        5     WORD  Not Known          1                         22.0   \n",
       "189        6     WORD        iOS          1                         43.0   \n",
       "191        7     WORD    Android          1                          4.0   \n",
       "193        5     WORD  Not Known          1                      24484.0   \n",
       "\n",
       "         new_event_boundary  \n",
       "childid                      \n",
       "183                       0  \n",
       "188                       0  \n",
       "189                       1  \n",
       "191                       0  \n",
       "193                       1  "
      ]
     },
     "execution_count": 12,
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   ],
   "source": [
    "df_1 = df.groupby(df['childid']).last()\n",
    "df_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#from matplotlib import pyplot as plt\n",
    "#from matplotlib import style\n",
    "#style.use('ggplot')\n",
    "#x1=df_1.index.values\n",
    "#y1=df_1['session_id']\n",
    "\n",
    "#plt.scatter(x1,y1,color='g')\n",
    "#plt.title('childid v/s sessionid')\n",
    "#plt.xlabel('Child ID')\n",
    "#plt.ylabel('No of Sessions')\n",
    "#plt.ylim(0,100)\n",
    "#plt.figure(figsize=(200,150))\n",
    "#plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
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   "outputs": [
    {
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0ILgZp6r3k6wbc8OL44m632kF4fVSeskS/5fVBmdTUr/w5oQJ1rfzqQ+wtMJd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\nCSGkIlDQCSGkIlDQCSGkIvw/4bgKeNjNizoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f131aa471d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_1=df.groupby(['childid'])['session_id'].mean()\n",
    "df_1.plot.line(x='childid',y='session_id')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average number of sessions per user is 10.2765"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.3605808012906699"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['childid','session_id'])['session_id'].count().mean()\n",
    "#df.groupby(['childid'])['session_id'].count().plot(x=df.childid,y=df.session_id.count(),kind='bar')\n",
    "\n",
    "\n",
    "#df_1.plot(x=df_1.index,y=df_1['session_id'])\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average number of activities per session is 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets find how many unique games a child plays per session"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets make a groupby object for each childid and a particular sessionid and find all unique games for that session for that child"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4484538854530788"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['childid','session_id'])['gamename'].nunique().mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# To confirm our values let's check manually as below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>childid</th>\n",
       "      <th>session_id</th>\n",
       "      <th>createdat</th>\n",
       "      <th>gamename</th>\n",
       "      <th>minutes_since_last_interval</th>\n",
       "      <th>new_event_boundary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25559</th>\n",
       "      <td>183</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-10 14:46:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25560</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-11 02:26:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>700.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25561</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-11 02:27:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25562</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-11 02:33:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25563</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-11 02:35:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25564</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-11-11 02:38:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25565</th>\n",
       "      <td>183</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-11-11 14:20:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>702.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25566</th>\n",
       "      <td>183</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-11-11 14:29:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25567</th>\n",
       "      <td>183</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-11-11 14:50:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25568</th>\n",
       "      <td>183</td>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-02 18:46:00</td>\n",
       "      <td>Bubbles</td>\n",
       "      <td>75116.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25569</th>\n",
       "      <td>183</td>\n",
       "      <td>3</td>\n",
       "      <td>2017-01-02 18:54:00</td>\n",
       "      <td>Lagoon</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       childid  session_id            createdat gamename  \\\n",
       "25559      183           0  2016-11-10 14:46:00   Lagoon   \n",
       "25560      183           1  2016-11-11 02:26:00  Bubbles   \n",
       "25561      183           1  2016-11-11 02:27:00  Bubbles   \n",
       "25562      183           1  2016-11-11 02:33:00  Bubbles   \n",
       "25563      183           1  2016-11-11 02:35:00  Bubbles   \n",
       "25564      183           1  2016-11-11 02:38:00  Bubbles   \n",
       "25565      183           2  2016-11-11 14:20:00  Bubbles   \n",
       "25566      183           2  2016-11-11 14:29:00  Bubbles   \n",
       "25567      183           2  2016-11-11 14:50:00   Lagoon   \n",
       "25568      183           3  2017-01-02 18:46:00  Bubbles   \n",
       "25569      183           3  2017-01-02 18:54:00   Lagoon   \n",
       "\n",
       "       minutes_since_last_interval  new_event_boundary  \n",
       "25559                          NaN                   0  \n",
       "25560                        700.0                   1  \n",
       "25561                          1.0                   0  \n",
       "25562                          6.0                   0  \n",
       "25563                          2.0                   0  \n",
       "25564                          3.0                   0  \n",
       "25565                        702.0                   1  \n",
       "25566                          9.0                   0  \n",
       "25567                         21.0                   0  \n",
       "25568                      75116.0                   1  \n",
       "25569                          8.0                   0  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['childid'] == 183]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For childid 183 the no of unique games per session perfectly matches our results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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