Netflix Wrapped.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dataset has my viewing activity from january, 2021 till june 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import the necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import the dataset\n",
    "df=pd.read_csv('/Users/rakshakannusami/Downloads/NETFLIX WRAPPED/netflix-report/CONTENT_INTERACTION/ViewingActivity.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4453 entries, 0 to 4452\n",
      "Data columns (total 10 columns):\n",
      " #   Column                   Non-Null Count  Dtype \n",
      "---  ------                   --------------  ----- \n",
      " 0   Profile Name             4453 non-null   object\n",
      " 1   Start Time               4453 non-null   object\n",
      " 2   Duration                 4453 non-null   object\n",
      " 3   Attributes               1786 non-null   object\n",
      " 4   Title                    4453 non-null   object\n",
      " 5   Supplemental Video Type  1410 non-null   object\n",
      " 6   Device Type              4453 non-null   object\n",
      " 7   Bookmark                 4453 non-null   object\n",
      " 8   Latest Bookmark          4453 non-null   object\n",
      " 9   Country                  4453 non-null   object\n",
      "dtypes: object(10)\n",
      "memory usage: 348.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Profile Name', 'Start Time', 'Duration', 'Attributes', 'Title',\n",
       "       'Supplemental Video Type', 'Device Type', 'Bookmark', 'Latest Bookmark',\n",
       "       'Country'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_columns = ['Country', 'Bookmark', 'Latest Bookmark', 'Attributes']\n",
    "df = df.drop(columns = drop_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Supplemental Video Type</th>\n",
       "      <th>Device Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 14:35:51</td>\n",
       "      <td>00:20:06</td>\n",
       "      <td>Notting Hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DefaultWidevineAndroidPhone</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 10:13:37</td>\n",
       "      <td>00:08:35</td>\n",
       "      <td>Start-Up: Season 1: Elevator Speech (Episode 14)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 09:05:29</td>\n",
       "      <td>00:36:49</td>\n",
       "      <td>Start-Up: Season 1: Comfort Zone (Episode 13)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:59:18</td>\n",
       "      <td>00:52:07</td>\n",
       "      <td>Start-Up: Season 1: Acqhire (Episode 12)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:23:44</td>\n",
       "      <td>00:34:35</td>\n",
       "      <td>Start-Up: Season 1: Exit (Episode 11)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name           Start Time  Duration  \\\n",
       "0       Ambika  2021-06-12 14:35:51  00:20:06   \n",
       "1       Ambika  2021-06-12 10:13:37  00:08:35   \n",
       "2       Ambika  2021-06-12 09:05:29  00:36:49   \n",
       "3       Ambika  2021-06-12 07:59:18  00:52:07   \n",
       "4       Ambika  2021-06-12 07:23:44  00:34:35   \n",
       "\n",
       "                                              Title Supplemental Video Type  \\\n",
       "0                                      Notting Hill                     NaN   \n",
       "1  Start-Up: Season 1: Elevator Speech (Episode 14)                     NaN   \n",
       "2     Start-Up: Season 1: Comfort Zone (Episode 13)                     NaN   \n",
       "3          Start-Up: Season 1: Acqhire (Episode 12)                     NaN   \n",
       "4             Start-Up: Season 1: Exit (Episode 11)                     NaN   \n",
       "\n",
       "                           Device Type  \n",
       "0          DefaultWidevineAndroidPhone  \n",
       "1  Netflix Chrome MAC (Cadmium) HTML 5  \n",
       "2  Netflix Chrome MAC (Cadmium) HTML 5  \n",
       "3  Netflix Chrome MAC (Cadmium) HTML 5  \n",
       "4  Netflix Chrome MAC (Cadmium) HTML 5  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[['Date','Time']] = df['Start Time'].str.split(' ',expand = True, n=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Supplemental Video Type</th>\n",
       "      <th>Device Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 14:35:51</td>\n",
       "      <td>00:20:06</td>\n",
       "      <td>Notting Hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DefaultWidevineAndroidPhone</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>14:35:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 10:13:37</td>\n",
       "      <td>00:08:35</td>\n",
       "      <td>Start-Up: Season 1: Elevator Speech (Episode 14)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>10:13:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 09:05:29</td>\n",
       "      <td>00:36:49</td>\n",
       "      <td>Start-Up: Season 1: Comfort Zone (Episode 13)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>09:05:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:59:18</td>\n",
       "      <td>00:52:07</td>\n",
       "      <td>Start-Up: Season 1: Acqhire (Episode 12)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:59:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:23:44</td>\n",
       "      <td>00:34:35</td>\n",
       "      <td>Start-Up: Season 1: Exit (Episode 11)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:23:44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name           Start Time  Duration  \\\n",
       "0       Ambika  2021-06-12 14:35:51  00:20:06   \n",
       "1       Ambika  2021-06-12 10:13:37  00:08:35   \n",
       "2       Ambika  2021-06-12 09:05:29  00:36:49   \n",
       "3       Ambika  2021-06-12 07:59:18  00:52:07   \n",
       "4       Ambika  2021-06-12 07:23:44  00:34:35   \n",
       "\n",
       "                                              Title Supplemental Video Type  \\\n",
       "0                                      Notting Hill                     NaN   \n",
       "1  Start-Up: Season 1: Elevator Speech (Episode 14)                     NaN   \n",
       "2     Start-Up: Season 1: Comfort Zone (Episode 13)                     NaN   \n",
       "3          Start-Up: Season 1: Acqhire (Episode 12)                     NaN   \n",
       "4             Start-Up: Season 1: Exit (Episode 11)                     NaN   \n",
       "\n",
       "                           Device Type        Date      Time  \n",
       "0          DefaultWidevineAndroidPhone  2021-06-12  14:35:51  \n",
       "1  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  10:13:37  \n",
       "2  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  09:05:29  \n",
       "3  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:59:18  \n",
       "4  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:23:44  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[['Hour','Min','Sec']] = df['Time'].str.split(':',expand = True, n=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Supplemental Video Type</th>\n",
       "      <th>Device Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Min</th>\n",
       "      <th>Sec</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 14:35:51</td>\n",
       "      <td>00:20:06</td>\n",
       "      <td>Notting Hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DefaultWidevineAndroidPhone</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>14:35:51</td>\n",
       "      <td>14</td>\n",
       "      <td>35</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 10:13:37</td>\n",
       "      <td>00:08:35</td>\n",
       "      <td>Start-Up: Season 1: Elevator Speech (Episode 14)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>10:13:37</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 09:05:29</td>\n",
       "      <td>00:36:49</td>\n",
       "      <td>Start-Up: Season 1: Comfort Zone (Episode 13)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>09:05:29</td>\n",
       "      <td>09</td>\n",
       "      <td>05</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:59:18</td>\n",
       "      <td>00:52:07</td>\n",
       "      <td>Start-Up: Season 1: Acqhire (Episode 12)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:59:18</td>\n",
       "      <td>07</td>\n",
       "      <td>59</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:23:44</td>\n",
       "      <td>00:34:35</td>\n",
       "      <td>Start-Up: Season 1: Exit (Episode 11)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:23:44</td>\n",
       "      <td>07</td>\n",
       "      <td>23</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name           Start Time  Duration  \\\n",
       "0       Ambika  2021-06-12 14:35:51  00:20:06   \n",
       "1       Ambika  2021-06-12 10:13:37  00:08:35   \n",
       "2       Ambika  2021-06-12 09:05:29  00:36:49   \n",
       "3       Ambika  2021-06-12 07:59:18  00:52:07   \n",
       "4       Ambika  2021-06-12 07:23:44  00:34:35   \n",
       "\n",
       "                                              Title Supplemental Video Type  \\\n",
       "0                                      Notting Hill                     NaN   \n",
       "1  Start-Up: Season 1: Elevator Speech (Episode 14)                     NaN   \n",
       "2     Start-Up: Season 1: Comfort Zone (Episode 13)                     NaN   \n",
       "3          Start-Up: Season 1: Acqhire (Episode 12)                     NaN   \n",
       "4             Start-Up: Season 1: Exit (Episode 11)                     NaN   \n",
       "\n",
       "                           Device Type        Date      Time Hour Min Sec  \n",
       "0          DefaultWidevineAndroidPhone  2021-06-12  14:35:51   14  35  51  \n",
       "1  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  10:13:37   10  13  37  \n",
       "2  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  09:05:29   09  05  29  \n",
       "3  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:59:18   07  59  18  \n",
       "4  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:23:44   07  23  44  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How many people use this account?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Ambika', 'Raksha', 'Uchitha', 'Ujesha', 'Upasana'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Profile Name'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### There are 5 profiles on this account"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2448, 11)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removing rows with less than 2 minutes as duration\n",
    "df['Duration'] = pd.to_timedelta(df['Duration'])\n",
    "df = df[df['Duration'].dt.total_seconds() > 120]\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df=df.rename(columns = {'Start Time':'Date'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert Start Time to datetime. Currently it is object\n",
    "df['Start Time'] = pd.to_datetime(df['Start Time'])\n",
    "#my_data['Date'] = my_data['Date'].dt.tz_localize('GMT').dt.tz_convert('Asia/Kolkata') #Convert from UTC to IST. \n",
    "df['Year'] =df['Start Time'].dt.year\n",
    "df['Month'] = df['Start Time'].dt.month\n",
    "df['Day'] = df['Start Time'].dt.day\n",
    "df['day_of_week'] = df['Start Time'].dt.dayofweek\n",
    "df['day_name'] = df['Start Time'].dt.day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['Supplemental Video Type'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2436 entries, 0 to 4451\n",
      "Data columns (total 16 columns):\n",
      " #   Column                   Non-Null Count  Dtype          \n",
      "---  ------                   --------------  -----          \n",
      " 0   Profile Name             2436 non-null   object         \n",
      " 1   Start Time               2436 non-null   datetime64[ns] \n",
      " 2   Duration                 2436 non-null   timedelta64[ns]\n",
      " 3   Title                    2436 non-null   object         \n",
      " 4   Supplemental Video Type  0 non-null      object         \n",
      " 5   Device Type              2436 non-null   object         \n",
      " 6   Date                     2436 non-null   object         \n",
      " 7   Time                     2436 non-null   object         \n",
      " 8   Hour                     2436 non-null   object         \n",
      " 9   Min                      2436 non-null   object         \n",
      " 10  Sec                      2436 non-null   object         \n",
      " 11  Year                     2436 non-null   int64          \n",
      " 12  Month                    2436 non-null   int64          \n",
      " 13  Day                      2436 non-null   int64          \n",
      " 14  day_of_week              2436 non-null   int64          \n",
      " 15  day_name                 2436 non-null   object         \n",
      "dtypes: datetime64[ns](1), int64(4), object(10), timedelta64[ns](1)\n",
      "memory usage: 323.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[['TV Show', 'Season', 'Episode']] = df['Title'].str.split(':', expand = True, n = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Content Type'] = df['Season'].apply(lambda x : 'Movie' if x == None else 'Series')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns = ['Supplemental Video Type'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
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       "      <th>Title</th>\n",
       "      <th>Device Type</th>\n",
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       "      <th>Time</th>\n",
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       "      <th>Min</th>\n",
       "      <th>Sec</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_name</th>\n",
       "      <th>TV Show</th>\n",
       "      <th>Season</th>\n",
       "      <th>Episode</th>\n",
       "      <th>Content Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 14:35:51</td>\n",
       "      <td>00:20:06</td>\n",
       "      <td>Notting Hill</td>\n",
       "      <td>DefaultWidevineAndroidPhone</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>14:35:51</td>\n",
       "      <td>14</td>\n",
       "      <td>35</td>\n",
       "      <td>51</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Notting Hill</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 10:13:37</td>\n",
       "      <td>00:08:35</td>\n",
       "      <td>Start-Up: Season 1: Elevator Speech (Episode 14)</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>10:13:37</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>37</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Start-Up</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Elevator Speech (Episode 14)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 09:05:29</td>\n",
       "      <td>00:36:49</td>\n",
       "      <td>Start-Up: Season 1: Comfort Zone (Episode 13)</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>09:05:29</td>\n",
       "      <td>09</td>\n",
       "      <td>05</td>\n",
       "      <td>29</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Start-Up</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Comfort Zone (Episode 13)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:59:18</td>\n",
       "      <td>00:52:07</td>\n",
       "      <td>Start-Up: Season 1: Acqhire (Episode 12)</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:59:18</td>\n",
       "      <td>07</td>\n",
       "      <td>59</td>\n",
       "      <td>18</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Start-Up</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Acqhire (Episode 12)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-06-12 07:23:44</td>\n",
       "      <td>00:34:35</td>\n",
       "      <td>Start-Up: Season 1: Exit (Episode 11)</td>\n",
       "      <td>Netflix Chrome MAC (Cadmium) HTML 5</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>07:23:44</td>\n",
       "      <td>07</td>\n",
       "      <td>23</td>\n",
       "      <td>44</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Start-Up</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Exit (Episode 11)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name          Start Time Duration  \\\n",
       "0       Ambika 2021-06-12 14:35:51 00:20:06   \n",
       "1       Ambika 2021-06-12 10:13:37 00:08:35   \n",
       "2       Ambika 2021-06-12 09:05:29 00:36:49   \n",
       "3       Ambika 2021-06-12 07:59:18 00:52:07   \n",
       "4       Ambika 2021-06-12 07:23:44 00:34:35   \n",
       "\n",
       "                                              Title  \\\n",
       "0                                      Notting Hill   \n",
       "1  Start-Up: Season 1: Elevator Speech (Episode 14)   \n",
       "2     Start-Up: Season 1: Comfort Zone (Episode 13)   \n",
       "3          Start-Up: Season 1: Acqhire (Episode 12)   \n",
       "4             Start-Up: Season 1: Exit (Episode 11)   \n",
       "\n",
       "                           Device Type        Date      Time Hour Min Sec  \\\n",
       "0          DefaultWidevineAndroidPhone  2021-06-12  14:35:51   14  35  51   \n",
       "1  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  10:13:37   10  13  37   \n",
       "2  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  09:05:29   09  05  29   \n",
       "3  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:59:18   07  59  18   \n",
       "4  Netflix Chrome MAC (Cadmium) HTML 5  2021-06-12  07:23:44   07  23  44   \n",
       "\n",
       "   Year  Month  Day  day_of_week  day_name       TV Show     Season  \\\n",
       "0  2021      6   12            5  Saturday  Notting Hill       None   \n",
       "1  2021      6   12            5  Saturday      Start-Up   Season 1   \n",
       "2  2021      6   12            5  Saturday      Start-Up   Season 1   \n",
       "3  2021      6   12            5  Saturday      Start-Up   Season 1   \n",
       "4  2021      6   12            5  Saturday      Start-Up   Season 1   \n",
       "\n",
       "                         Episode Content Type  \n",
       "0                           None        Movie  \n",
       "1   Elevator Speech (Episode 14)       Series  \n",
       "2      Comfort Zone (Episode 13)       Series  \n",
       "3           Acqhire (Episode 12)       Series  \n",
       "4              Exit (Episode 11)       Series  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['DefaultWidevineAndroidPhone',\n",
       "       'Netflix Chrome MAC (Cadmium) HTML 5', 'Chrome PC (Cadmium)',\n",
       "       'Netflix Windows App - Cadmium Windows Mobile',\n",
       "       'Android DefaultWidevineL3Phone Android Phone',\n",
       "       'Samsung 2014 MStar DTV'], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Device Type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['Device Type'].str.contains('Chrome'), 'Device Type'] = 'Laptop'\n",
    "df.loc[df['Device Type'].str.contains('Mobile'), 'Device Type'] = 'Mobile'\n",
    "df.loc[df['Device Type'].str.contains('Phone'), 'Device Type'] = 'Mobile'\n",
    "df.loc[df['Device Type'].str.contains('TV'), 'Device Type'] = 'TV'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Mobile', 'Laptop', 'TV'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Device Type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>3899</th>\n",
       "      <td>Upasana</td>\n",
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       "      <td>01:10:10</td>\n",
       "      <td>Search WWW: Season 1: Episode 1</td>\n",
       "      <td>TV</td>\n",
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       "      <td>07:10:43</td>\n",
       "      <td>07</td>\n",
       "      <td>10</td>\n",
       "      <td>43</td>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>Search WWW</td>\n",
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       "      <td>Episode 1</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>Uchitha</td>\n",
       "      <td>2021-06-10 07:46:09</td>\n",
       "      <td>00:06:05</td>\n",
       "      <td>Some Assembly Required: Season 1: Lobster Trap...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-10</td>\n",
       "      <td>07:46:09</td>\n",
       "      <td>07</td>\n",
       "      <td>46</td>\n",
       "      <td>09</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>Some Assembly Required</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Lobster Trap (Episode 10)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2283</th>\n",
       "      <td>Uchitha</td>\n",
       "      <td>2021-01-22 15:20:16</td>\n",
       "      <td>00:20:44</td>\n",
       "      <td>Hunter X Hunter (2011): Season 1: Departure x ...</td>\n",
       "      <td>TV</td>\n",
       "      <td>2021-01-22</td>\n",
       "      <td>15:20:16</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>Friday</td>\n",
       "      <td>Hunter X Hunter (2011)</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Departure x and x Friends (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2635</th>\n",
       "      <td>Ujesha</td>\n",
       "      <td>2021-05-16 09:44:56</td>\n",
       "      <td>00:21:32</td>\n",
       "      <td>CAROLE &amp; TUESDAY: Part 1: True Colors (Episode 1)</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-05-16</td>\n",
       "      <td>09:44:56</td>\n",
       "      <td>09</td>\n",
       "      <td>44</td>\n",
       "      <td>56</td>\n",
       "      <td>2021</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>CAROLE &amp; TUESDAY</td>\n",
       "      <td>Part 1</td>\n",
       "      <td>True Colors (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3397</th>\n",
       "      <td>Upasana</td>\n",
       "      <td>2021-04-11 19:01:10</td>\n",
       "      <td>00:23:09</td>\n",
       "      <td>The Bold Type: Season 1: The Breast Issue (Epi...</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>2021-04-11</td>\n",
       "      <td>19:01:10</td>\n",
       "      <td>19</td>\n",
       "      <td>01</td>\n",
       "      <td>10</td>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Bold Type</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>The Breast Issue (Episode 6)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4195</th>\n",
       "      <td>Upasana</td>\n",
       "      <td>2021-01-18 18:16:05</td>\n",
       "      <td>00:40:14</td>\n",
       "      <td>Tribhanga - Tedhi Medhi Crazy</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-01-18</td>\n",
       "      <td>18:16:05</td>\n",
       "      <td>18</td>\n",
       "      <td>16</td>\n",
       "      <td>05</td>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>Monday</td>\n",
       "      <td>Tribhanga - Tedhi Medhi Crazy</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-01 08:00:04</td>\n",
       "      <td>00:21:32</td>\n",
       "      <td>The Good Place: Season 2: Team Cockroach (Epis...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>08:00:04</td>\n",
       "      <td>08</td>\n",
       "      <td>00</td>\n",
       "      <td>04</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 2</td>\n",
       "      <td>Team Cockroach (Episode 3)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4399</th>\n",
       "      <td>Upasana</td>\n",
       "      <td>2021-01-03 19:46:59</td>\n",
       "      <td>00:02:56</td>\n",
       "      <td>What's Wrong with Secretary Kim: Season 1: Epi...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-01-03</td>\n",
       "      <td>19:46:59</td>\n",
       "      <td>19</td>\n",
       "      <td>46</td>\n",
       "      <td>59</td>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>What's Wrong with Secretary Kim</td>\n",
       "      <td>Season 1</td>\n",
       "      <td>Episode 14</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2184</th>\n",
       "      <td>Uchitha</td>\n",
       "      <td>2021-02-24 15:36:25</td>\n",
       "      <td>00:21:02</td>\n",
       "      <td>Cardcaptor Sakura: Cardcaptor Sakura: Clow Car...</td>\n",
       "      <td>TV</td>\n",
       "      <td>2021-02-24</td>\n",
       "      <td>15:36:25</td>\n",
       "      <td>15</td>\n",
       "      <td>36</td>\n",
       "      <td>25</td>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>Cardcaptor Sakura</td>\n",
       "      <td>Cardcaptor Sakura</td>\n",
       "      <td>Clow Card: Sakura and Tomoyo and The Big Hous...</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Ambika</td>\n",
       "      <td>2021-04-15 06:27:52</td>\n",
       "      <td>00:08:35</td>\n",
       "      <td>Schitt's Creek: Season 3: Murder Mystery (Epis...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-04-15</td>\n",
       "      <td>06:27:52</td>\n",
       "      <td>06</td>\n",
       "      <td>27</td>\n",
       "      <td>52</td>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>Schitt's Creek</td>\n",
       "      <td>Season 3</td>\n",
       "      <td>Murder Mystery (Episode 6)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Profile Name          Start Time Duration  \\\n",
       "3899      Upasana 2021-02-13 07:10:43 01:10:10   \n",
       "2006      Uchitha 2021-06-10 07:46:09 00:06:05   \n",
       "2283      Uchitha 2021-01-22 15:20:16 00:20:44   \n",
       "2635       Ujesha 2021-05-16 09:44:56 00:21:32   \n",
       "3397      Upasana 2021-04-11 19:01:10 00:23:09   \n",
       "4195      Upasana 2021-01-18 18:16:05 00:40:14   \n",
       "1272       Raksha 2021-06-01 08:00:04 00:21:32   \n",
       "4399      Upasana 2021-01-03 19:46:59 00:02:56   \n",
       "2184      Uchitha 2021-02-24 15:36:25 00:21:02   \n",
       "499        Ambika 2021-04-15 06:27:52 00:08:35   \n",
       "\n",
       "                                                  Title Device Type  \\\n",
       "3899                    Search WWW: Season 1: Episode 1          TV   \n",
       "2006  Some Assembly Required: Season 1: Lobster Trap...      Laptop   \n",
       "2283  Hunter X Hunter (2011): Season 1: Departure x ...          TV   \n",
       "2635  CAROLE & TUESDAY: Part 1: True Colors (Episode 1)      Laptop   \n",
       "3397  The Bold Type: Season 1: The Breast Issue (Epi...      Mobile   \n",
       "4195                      Tribhanga - Tedhi Medhi Crazy      Laptop   \n",
       "1272  The Good Place: Season 2: Team Cockroach (Epis...      Laptop   \n",
       "4399  What's Wrong with Secretary Kim: Season 1: Epi...      Laptop   \n",
       "2184  Cardcaptor Sakura: Cardcaptor Sakura: Clow Car...          TV   \n",
       "499   Schitt's Creek: Season 3: Murder Mystery (Epis...      Laptop   \n",
       "\n",
       "            Date      Time Hour Min Sec  Year  Month  Day  day_of_week  \\\n",
       "3899  2021-02-13  07:10:43   07  10  43  2021      2   13            5   \n",
       "2006  2021-06-10  07:46:09   07  46  09  2021      6   10            3   \n",
       "2283  2021-01-22  15:20:16   15  20  16  2021      1   22            4   \n",
       "2635  2021-05-16  09:44:56   09  44  56  2021      5   16            6   \n",
       "3397  2021-04-11  19:01:10   19  01  10  2021      4   11            6   \n",
       "4195  2021-01-18  18:16:05   18  16  05  2021      1   18            0   \n",
       "1272  2021-06-01  08:00:04   08  00  04  2021      6    1            1   \n",
       "4399  2021-01-03  19:46:59   19  46  59  2021      1    3            6   \n",
       "2184  2021-02-24  15:36:25   15  36  25  2021      2   24            2   \n",
       "499   2021-04-15  06:27:52   06  27  52  2021      4   15            3   \n",
       "\n",
       "       day_name                          TV Show              Season  \\\n",
       "3899   Saturday                       Search WWW            Season 1   \n",
       "2006   Thursday           Some Assembly Required            Season 1   \n",
       "2283     Friday           Hunter X Hunter (2011)            Season 1   \n",
       "2635     Sunday                 CAROLE & TUESDAY              Part 1   \n",
       "3397     Sunday                    The Bold Type            Season 1   \n",
       "4195     Monday    Tribhanga - Tedhi Medhi Crazy                None   \n",
       "1272    Tuesday                   The Good Place            Season 2   \n",
       "4399     Sunday  What's Wrong with Secretary Kim            Season 1   \n",
       "2184  Wednesday                Cardcaptor Sakura   Cardcaptor Sakura   \n",
       "499    Thursday                   Schitt's Creek            Season 3   \n",
       "\n",
       "                                                Episode Content Type  \n",
       "3899                                          Episode 1       Series  \n",
       "2006                          Lobster Trap (Episode 10)       Series  \n",
       "2283              Departure x and x Friends (Episode 1)       Series  \n",
       "2635                            True Colors (Episode 1)       Series  \n",
       "3397                       The Breast Issue (Episode 6)       Series  \n",
       "4195                                               None        Movie  \n",
       "1272                         Team Cockroach (Episode 3)       Series  \n",
       "4399                                         Episode 14       Series  \n",
       "2184   Clow Card: Sakura and Tomoyo and The Big Hous...       Series  \n",
       "499                          Murder Mystery (Episode 6)       Series  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Upasana    836\n",
       "Ambika     770\n",
       "Raksha     389\n",
       "Uchitha    343\n",
       "Ujesha      98\n",
       "Name: Profile Name, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Profile Name'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "watch_time_days = df.groupby(by=['Profile Name'])['Duration'].sum().dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "watch_time_days.plot(kind='bar')\n",
    "ax.set_ylabel('Total time of Netflix sessions (in days)')\n",
    "ax.set_xlabel('User')\n",
    "ax.set_title('Time (in days) spent watching Netflix content per user')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['Profile Name']=='Raksha']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 389 entries, 1219 to 1972\n",
      "Data columns (total 19 columns):\n",
      " #   Column        Non-Null Count  Dtype          \n",
      "---  ------        --------------  -----          \n",
      " 0   Profile Name  389 non-null    object         \n",
      " 1   Start Time    389 non-null    datetime64[ns] \n",
      " 2   Duration      389 non-null    timedelta64[ns]\n",
      " 3   Title         389 non-null    object         \n",
      " 4   Device Type   389 non-null    object         \n",
      " 5   Date          389 non-null    object         \n",
      " 6   Time          389 non-null    object         \n",
      " 7   Hour          389 non-null    object         \n",
      " 8   Min           389 non-null    object         \n",
      " 9   Sec           389 non-null    object         \n",
      " 10  Year          389 non-null    int64          \n",
      " 11  Month         389 non-null    int64          \n",
      " 12  Day           389 non-null    int64          \n",
      " 13  day_of_week   389 non-null    int64          \n",
      " 14  day_name      389 non-null    object         \n",
      " 15  TV Show       389 non-null    object         \n",
      " 16  Season        351 non-null    object         \n",
      " 17  Episode       345 non-null    object         \n",
      " 18  Content Type  389 non-null    object         \n",
      "dtypes: datetime64[ns](1), int64(4), object(13), timedelta64[ns](1)\n",
      "memory usage: 60.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Device Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Min</th>\n",
       "      <th>Sec</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_name</th>\n",
       "      <th>TV Show</th>\n",
       "      <th>Season</th>\n",
       "      <th>Episode</th>\n",
       "      <th>Content Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1219</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-12 06:31:39</td>\n",
       "      <td>01:00:58</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>06:31:39</td>\n",
       "      <td>06</td>\n",
       "      <td>31</td>\n",
       "      <td>39</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1220</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-11 17:39:06</td>\n",
       "      <td>00:56:05</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-11</td>\n",
       "      <td>17:39:06</td>\n",
       "      <td>17</td>\n",
       "      <td>39</td>\n",
       "      <td>06</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Friday</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1222</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-08 16:08:11</td>\n",
       "      <td>00:10:08</td>\n",
       "      <td>The Good Place: Season 3: Everything is Bonzer...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-08</td>\n",
       "      <td>16:08:11</td>\n",
       "      <td>16</td>\n",
       "      <td>08</td>\n",
       "      <td>11</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 3</td>\n",
       "      <td>Everything is Bonzer (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1223</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-07 09:16:47</td>\n",
       "      <td>00:11:43</td>\n",
       "      <td>The Good Place: Season 3: Everything is Bonzer...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-07</td>\n",
       "      <td>09:16:47</td>\n",
       "      <td>09</td>\n",
       "      <td>16</td>\n",
       "      <td>47</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>Monday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 3</td>\n",
       "      <td>Everything is Bonzer (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1226</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 18:33:18</td>\n",
       "      <td>00:08:15</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>18:33:18</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>18</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Profile Name          Start Time Duration  \\\n",
       "1219       Raksha 2021-06-12 06:31:39 01:00:58   \n",
       "1220       Raksha 2021-06-11 17:39:06 00:56:05   \n",
       "1222       Raksha 2021-06-08 16:08:11 00:10:08   \n",
       "1223       Raksha 2021-06-07 09:16:47 00:11:43   \n",
       "1226       Raksha 2021-06-06 18:33:18 00:08:15   \n",
       "\n",
       "                                                  Title Device Type  \\\n",
       "1219                                         The Intern      Laptop   \n",
       "1220                                         The Intern      Laptop   \n",
       "1222  The Good Place: Season 3: Everything is Bonzer...      Laptop   \n",
       "1223  The Good Place: Season 3: Everything is Bonzer...      Laptop   \n",
       "1226                              The Edge of Seventeen      Laptop   \n",
       "\n",
       "            Date      Time Hour Min Sec  Year  Month  Day  day_of_week  \\\n",
       "1219  2021-06-12  06:31:39   06  31  39  2021      6   12            5   \n",
       "1220  2021-06-11  17:39:06   17  39  06  2021      6   11            4   \n",
       "1222  2021-06-08  16:08:11   16  08  11  2021      6    8            1   \n",
       "1223  2021-06-07  09:16:47   09  16  47  2021      6    7            0   \n",
       "1226  2021-06-06  18:33:18   18  33  18  2021      6    6            6   \n",
       "\n",
       "      day_name                TV Show     Season  \\\n",
       "1219  Saturday             The Intern       None   \n",
       "1220    Friday             The Intern       None   \n",
       "1222   Tuesday         The Good Place   Season 3   \n",
       "1223    Monday         The Good Place   Season 3   \n",
       "1226    Sunday  The Edge of Seventeen       None   \n",
       "\n",
       "                                Episode Content Type  \n",
       "1219                               None        Movie  \n",
       "1220                               None        Movie  \n",
       "1222   Everything is Bonzer (Episode 1)       Series  \n",
       "1223   Everything is Bonzer (Episode 1)       Series  \n",
       "1226                               None        Movie  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "The Bold Type             68\n",
       "Good Girls                55\n",
       "The Good Place            39\n",
       "Trinkets                  27\n",
       "Behind Her Eyes           22\n",
       "Teenage Bounty Hunters    20\n",
       "The Queen's Gambit        15\n",
       "Ginny & Georgia           14\n",
       "Girlboss                  14\n",
       "DASH & LILY               10\n",
       "Name: TV Show, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['TV Show'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Frequency')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.set_context(\"poster\")\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.subplot(2,1,1)\n",
    "ax = sns.barplot(x=df[\"day_name\"].value_counts().index, y=df[\"day_name\"].value_counts(), palette=\"viridis\",alpha=0.7)\n",
    "plt.title(\"Viewing activity on different days of the week\")\n",
    "plt.xlabel(\"Day of the Week\")\n",
    "plt.ylabel(\"Frequency\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rakshakannusami/opt/anaconda3/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Viewing activity of different content type')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Which is more watched? movie or series?\n",
    "sns.countplot(df['Content Type'])\n",
    "sns.set_context(\"talk\")\n",
    "plt.title(\"Viewing activity of different content type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rakshakannusami/opt/anaconda3/lib/python3.7/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Day of the month - Monthly viewing distribution\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.subplot(2,1,1)\n",
    "plt.title(\"viewing activity on different days of the month\")\n",
    "ax = sns.distplot(df['Day'],bins=31,color=\"red\",hist=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rakshakannusami/opt/anaconda3/lib/python3.7/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Hour of the day viewing distribution\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.subplot(2,1,1)\n",
    "plt.xticks(range(1, 25))\n",
    "plt.title(\"When do I start watching Netflix during the day?\")\n",
    "ax = sns.distplot(df['Hour'],bins=31,color=\"red\",hist=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'What do I watch? Movies or Series?')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_freq = df.groupby('Content Type')['day_of_week'].value_counts().sort_values(ascending=False).reset_index(name='Count')\n",
    "#show_freq\n",
    "plt.figure(figsize=(15,8))\n",
    "plt.subplot(2,1,1)\n",
    "ax = sns.barplot(x=show_freq[\"day_of_week\"], y=show_freq[\"Count\"], hue=show_freq[\"Content Type\"], palette=\"viridis\",alpha=0.7)\n",
    "plt.title(\"What do I watch? Movies or Series?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Device Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Min</th>\n",
       "      <th>Sec</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_name</th>\n",
       "      <th>TV Show</th>\n",
       "      <th>Season</th>\n",
       "      <th>Episode</th>\n",
       "      <th>Content Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-08 16:08:11</td>\n",
       "      <td>00:10:08</td>\n",
       "      <td>The Good Place: Season 3: Everything is Bonzer...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-08</td>\n",
       "      <td>16:08:11</td>\n",
       "      <td>16</td>\n",
       "      <td>08</td>\n",
       "      <td>11</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 3</td>\n",
       "      <td>Everything is Bonzer (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-07 09:16:47</td>\n",
       "      <td>00:11:43</td>\n",
       "      <td>The Good Place: Season 3: Everything is Bonzer...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-07</td>\n",
       "      <td>09:16:47</td>\n",
       "      <td>09</td>\n",
       "      <td>16</td>\n",
       "      <td>47</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>Monday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 3</td>\n",
       "      <td>Everything is Bonzer (Episode 1)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 08:23:26</td>\n",
       "      <td>00:21:28</td>\n",
       "      <td>The Good Place: Season 2: Somewhere Else (Epis...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>08:23:26</td>\n",
       "      <td>08</td>\n",
       "      <td>23</td>\n",
       "      <td>26</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 2</td>\n",
       "      <td>Somewhere Else (Episode 12)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 08:17:46</td>\n",
       "      <td>00:05:39</td>\n",
       "      <td>The Good Place: Season 2: The Burrito (Episode...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>08:17:46</td>\n",
       "      <td>08</td>\n",
       "      <td>17</td>\n",
       "      <td>46</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 2</td>\n",
       "      <td>The Burrito (Episode 11)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-05 19:30:55</td>\n",
       "      <td>00:16:33</td>\n",
       "      <td>The Good Place: Season 2: The Burrito (Episode...</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-05</td>\n",
       "      <td>19:30:55</td>\n",
       "      <td>19</td>\n",
       "      <td>30</td>\n",
       "      <td>55</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>The Good Place</td>\n",
       "      <td>Season 2</td>\n",
       "      <td>The Burrito (Episode 11)</td>\n",
       "      <td>Series</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name          Start Time Duration  \\\n",
       "0       Raksha 2021-06-08 16:08:11 00:10:08   \n",
       "1       Raksha 2021-06-07 09:16:47 00:11:43   \n",
       "2       Raksha 2021-06-06 08:23:26 00:21:28   \n",
       "3       Raksha 2021-06-06 08:17:46 00:05:39   \n",
       "4       Raksha 2021-06-05 19:30:55 00:16:33   \n",
       "\n",
       "                                               Title Device Type        Date  \\\n",
       "0  The Good Place: Season 3: Everything is Bonzer...      Laptop  2021-06-08   \n",
       "1  The Good Place: Season 3: Everything is Bonzer...      Laptop  2021-06-07   \n",
       "2  The Good Place: Season 2: Somewhere Else (Epis...      Laptop  2021-06-06   \n",
       "3  The Good Place: Season 2: The Burrito (Episode...      Laptop  2021-06-06   \n",
       "4  The Good Place: Season 2: The Burrito (Episode...      Laptop  2021-06-05   \n",
       "\n",
       "       Time Hour Min Sec  Year  Month  Day  day_of_week  day_name  \\\n",
       "0  16:08:11   16  08  11  2021      6    8            1   Tuesday   \n",
       "1  09:16:47   09  16  47  2021      6    7            0    Monday   \n",
       "2  08:23:26   08  23  26  2021      6    6            6    Sunday   \n",
       "3  08:17:46   08  17  46  2021      6    6            6    Sunday   \n",
       "4  19:30:55   19  30  55  2021      6    5            5  Saturday   \n",
       "\n",
       "          TV Show     Season                            Episode Content Type  \n",
       "0  The Good Place   Season 3   Everything is Bonzer (Episode 1)       Series  \n",
       "1  The Good Place   Season 3   Everything is Bonzer (Episode 1)       Series  \n",
       "2  The Good Place   Season 2        Somewhere Else (Episode 12)       Series  \n",
       "3  The Good Place   Season 2           The Burrito (Episode 11)       Series  \n",
       "4  The Good Place   Season 2           The Burrito (Episode 11)       Series  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tvshow = df.loc[df['Content Type'] == 'Series']\n",
    "df_tvshow.index = pd.RangeIndex(len(df_tvshow.index)) \n",
    "df_tvshow.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>Profile Name</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Title</th>\n",
       "      <th>Device Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Min</th>\n",
       "      <th>Sec</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_name</th>\n",
       "      <th>TV Show</th>\n",
       "      <th>Season</th>\n",
       "      <th>Episode</th>\n",
       "      <th>Content Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-12 06:31:39</td>\n",
       "      <td>01:00:58</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-12</td>\n",
       "      <td>06:31:39</td>\n",
       "      <td>06</td>\n",
       "      <td>31</td>\n",
       "      <td>39</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-11 17:39:06</td>\n",
       "      <td>00:56:05</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-11</td>\n",
       "      <td>17:39:06</td>\n",
       "      <td>17</td>\n",
       "      <td>39</td>\n",
       "      <td>06</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Friday</td>\n",
       "      <td>The Intern</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 18:33:18</td>\n",
       "      <td>00:08:15</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>18:33:18</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>18</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 18:14:54</td>\n",
       "      <td>00:15:58</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>18:14:54</td>\n",
       "      <td>18</td>\n",
       "      <td>14</td>\n",
       "      <td>54</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Raksha</td>\n",
       "      <td>2021-06-06 16:42:36</td>\n",
       "      <td>00:35:40</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>Laptop</td>\n",
       "      <td>2021-06-06</td>\n",
       "      <td>16:42:36</td>\n",
       "      <td>16</td>\n",
       "      <td>42</td>\n",
       "      <td>36</td>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>The Edge of Seventeen</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Movie</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Profile Name          Start Time Duration                  Title  \\\n",
       "0       Raksha 2021-06-12 06:31:39 01:00:58             The Intern   \n",
       "1       Raksha 2021-06-11 17:39:06 00:56:05             The Intern   \n",
       "2       Raksha 2021-06-06 18:33:18 00:08:15  The Edge of Seventeen   \n",
       "3       Raksha 2021-06-06 18:14:54 00:15:58  The Edge of Seventeen   \n",
       "4       Raksha 2021-06-06 16:42:36 00:35:40  The Edge of Seventeen   \n",
       "\n",
       "  Device Type        Date      Time Hour Min Sec  Year  Month  Day  \\\n",
       "0      Laptop  2021-06-12  06:31:39   06  31  39  2021      6   12   \n",
       "1      Laptop  2021-06-11  17:39:06   17  39  06  2021      6   11   \n",
       "2      Laptop  2021-06-06  18:33:18   18  33  18  2021      6    6   \n",
       "3      Laptop  2021-06-06  18:14:54   18  14  54  2021      6    6   \n",
       "4      Laptop  2021-06-06  16:42:36   16  42  36  2021      6    6   \n",
       "\n",
       "   day_of_week  day_name                TV Show Season Episode Content Type  \n",
       "0            5  Saturday             The Intern   None    None        Movie  \n",
       "1            4    Friday             The Intern   None    None        Movie  \n",
       "2            6    Sunday  The Edge of Seventeen   None    None        Movie  \n",
       "3            6    Sunday  The Edge of Seventeen   None    None        Movie  \n",
       "4            6    Sunday  The Edge of Seventeen   None    None        Movie  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_movie = df.loc[df['Content Type'] == 'Movie']\n",
    "df_movie.index = pd.RangeIndex(len(df_movie.index)) \n",
    "df_movie.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TV Show\n",
       "The Bold Type            1 days 07:05:48\n",
       "Good Girls               0 days 23:25:22\n",
       "The Good Place           0 days 09:28:20\n",
       "Ginny & Georgia          0 days 08:29:59\n",
       "Trinkets                 0 days 08:11:02\n",
       "Teenage Bounty Hunters   0 days 07:42:47\n",
       "The Queen's Gambit       0 days 06:16:11\n",
       "Behind Her Eyes          0 days 04:27:03\n",
       "Girlboss                 0 days 03:52:38\n",
       "DASH & LILY              0 days 03:00:44\n",
       "Name: Duration, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "times_each_show = df_tvshow.groupby('TV Show').Duration.sum().sort_values(ascending = False)[:10]\n",
    "times_each_show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TV Show\n",
       "The Bold Type             31.0\n",
       "Good Girls                23.0\n",
       "The Good Place             9.0\n",
       "Ginny & Georgia            8.0\n",
       "Trinkets                   8.0\n",
       "Teenage Bounty Hunters     7.0\n",
       "The Queen's Gambit         6.0\n",
       "Behind Her Eyes            4.0\n",
       "Girlboss                   3.0\n",
       "DASH & LILY                3.0\n",
       "Name: Duration, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_hour = times_each_show.astype('timedelta64[h]')\n",
    "show_hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The Bold Type',\n",
       " 'Good Girls',\n",
       " 'The Good Place',\n",
       " 'Ginny & Georgia',\n",
       " 'Trinkets',\n",
       " 'Teenage Bounty Hunters',\n",
       " \"The Queen's Gambit\",\n",
       " 'Behind Her Eyes',\n",
       " 'Girlboss',\n",
       " 'DASH & LILY']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_show_grouped = df_tvshow.groupby(['TV Show'])['Duration'].sum().reset_index(name='Total Time').sort_values(['Total Time'], ascending=False)\n",
    "xaxis_show = df_show_grouped['TV Show'][:10].tolist() # getting first ten rows as list instead of pd.dataframe\n",
    "xaxis_show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,7))\n",
    "plt.subplot()\n",
    "ax = sns.barplot(x = xaxis_show, \n",
    "                 y = show_hour,\n",
    "                 palette=\"gnuplot\")\n",
    "for i, val in enumerate(show_hour):\n",
    "    plt.text(i, val, int(val), horizontalalignment='center', verticalalignment='bottom', fontdict={'fontweight':500, 'size':12})\n",
    "\n",
    "plt.title(\"Ten Most Watched Shows by Hour\", fontsize=22)\n",
    "plt.xlabel(\"Show Name\", fontsize=18)\n",
    "plt.ylabel(\"Hours\", fontsize=18)\n",
    "plt.style.use('fivethirtyeight')\n",
    "plt.box(False)\n",
    "loc, labels = plt.xticks()\n",
    "ax.set_xticklabels(labels, rotation=40)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preparing the data for x axis\n",
    "df_movie_grouped = df_movie.groupby(['TV Show'])['Duration'].sum().reset_index(name='Total Time').sort_values(['Total Time'], ascending=False)\n",
    "xaxis_movie = df_movie_grouped['TV Show'][:10].tolist() # getting list outcome instead of pd.dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preparing the data for y axis\n",
    "times_each_movie = df_movie.groupby('TV Show').Duration.sum().sort_values(ascending = False)[:10]\n",
    "movie_hour = times_each_movie.astype('timedelta64[h]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,7))\n",
    "plt.subplot()\n",
    "ax = sns.barplot(x = xaxis_movie, \n",
    "                 y = movie_hour,\n",
    "                 palette=\"gnuplot\")\n",
    "for i, val in enumerate(movie_hour):\n",
    "    plt.text(i, val, int(val), horizontalalignment='center', verticalalignment='bottom', fontdict={'fontweight':500, 'size':12})\n",
    "\n",
    "plt.title(\"Ten Most Watched Movies by Hour\", fontsize=22)\n",
    "plt.xlabel(\"Movie Name\", fontsize=18)\n",
    "plt.ylabel(\"Hours\", fontsize=18)\n",
    "plt.style.use('fivethirtyeight')\n",
    "plt.box(False)\n",
    "loc, labels = plt.xticks()\n",
    "ax.set_xticklabels(labels, rotation=45)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.4 64-bit ('base': conda)",
   "language": "python",
   "name": "python37464bitbaseconda3d22a4fc3b90432aba33d81c1563341c"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}