3.2. Analysis_Q1_Q2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "64f96990",
   "metadata": {},
   "source": [
    "# 3. Analysis\n",
    "\n",
    "## 3.2. Q1: General patterns; Q2: Frequency of news stories about heroes of special military operation\n",
    "\n",
    "## Introduction\n",
    "\n",
    "Propaganda frequently utilizes tales of heroic figures in order to promote a favorable perception of war. This notebook examines whether the First channel's news incorporates this method of using hero stories.\n",
    "\n",
    "The notebook is comprised of two main sections:\n",
    "\n",
    "1) An examination of the overall trends and patterns present in news broadcasts, and\n",
    "\n",
    "2) An investigation to determine if hero stories are being broadcasted, and if so, with what frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "62de7117",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import copy\n",
    "from collections import Counter\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "910c9046",
   "metadata": {},
   "outputs": [],
   "source": [
    "%run \"3.0. Analysis_Functions.ipynb\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5c210e89",
   "metadata": {},
   "outputs": [],
   "source": [
    "%run \"0.1. Intro_Visualization style.ipynb\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99a4f60f",
   "metadata": {},
   "source": [
    "## Data loading and filtering relevant rows"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e3f2030",
   "metadata": {},
   "source": [
    "### Data loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "86e5effd",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = 'data/df_tokenized.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4c926eeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(file)\n",
    "df.drop(columns=['Unnamed: 0'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "de8b9879",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(359041, 18)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ce3ee58b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_in_source_file</th>\n",
       "      <th>date</th>\n",
       "      <th>tags_top</th>\n",
       "      <th>title</th>\n",
       "      <th>url</th>\n",
       "      <th>body</th>\n",
       "      <th>tags_bottom</th>\n",
       "      <th>video_duration_seconds</th>\n",
       "      <th>file_key</th>\n",
       "      <th>datetime</th>\n",
       "      <th>dat</th>\n",
       "      <th>year</th>\n",
       "      <th>year_month</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>whole newscast</th>\n",
       "      <th>body_token_final</th>\n",
       "      <th>title_token_final</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>2023-01-27 21:45:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Выпуск программы «Время» в 21:00 от 27.01.2023</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446104-vypu...</td>\n",
       "      <td>Смотрите в этом выпуске: 79 лет назад была пол...</td>\n",
       "      <td>Общество</td>\n",
       "      <td>2422.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 21:45:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>['смотреть', 'выпуск', '79', 'год', 'полностью...</td>\n",
       "      <td>['выпуск', 'программа', 'время', '21:00', '27....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>2023-01-27 21:35:00</td>\n",
       "      <td>Культура</td>\n",
       "      <td>В Москве проходит церемония вручения премии «З...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446121-v_mo...</td>\n",
       "      <td>Событие в мире отечественного кино. В Москве в...</td>\n",
       "      <td>Культура,Кино,Марина Зудина,Екатерина Климова,...</td>\n",
       "      <td>290.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 21:35:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>['событие', 'мир', 'отечественный', 'кино', 'м...</td>\n",
       "      <td>['москва', 'проходить', 'церемония', 'вручение...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>2023-01-27 21:34:00</td>\n",
       "      <td>Спорт</td>\n",
       "      <td>В Туле появился новый футбольный манеж</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446120-v_tu...</td>\n",
       "      <td>Футбольный манеж в Туле — искусственный газон ...</td>\n",
       "      <td>Спорт,Регионы,Футбол,Алексей Дюмин,Тульская об...</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 21:34:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>['футбольный', 'манеж', 'тула', 'искусственный...</td>\n",
       "      <td>['тула', 'появиться', 'новый', 'футбольный', '...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "   id_in_source_file                 date  tags_top  \\\n",
       "0                 15  2023-01-27 21:45:00  Общество   \n",
       "1                 16  2023-01-27 21:35:00  Культура   \n",
       "2                 20  2023-01-27 21:34:00     Спорт   \n",
       "\n",
       "                                               title  \\\n",
       "0     Выпуск программы «Время» в 21:00 от 27.01.2023   \n",
       "1  В Москве проходит церемония вручения премии «З...   \n",
       "2             В Туле появился новый футбольный манеж   \n",
       "\n",
       "                                                 url  \\\n",
       "0  https://www.1tv.ru/news/2023-01-27/446104-vypu...   \n",
       "1  https://www.1tv.ru/news/2023-01-27/446121-v_mo...   \n",
       "2  https://www.1tv.ru/news/2023-01-27/446120-v_tu...   \n",
       "\n",
       "                                                body  \\\n",
       "0  Смотрите в этом выпуске: 79 лет назад была пол...   \n",
       "1  Событие в мире отечественного кино. В Москве в...   \n",
       "2  Футбольный манеж в Туле — искусственный газон ...   \n",
       "\n",
       "                                         tags_bottom  video_duration_seconds  \\\n",
       "0                                           Общество                  2422.0   \n",
       "1  Культура,Кино,Марина Зудина,Екатерина Климова,...                   290.0   \n",
       "2  Спорт,Регионы,Футбол,Алексей Дюмин,Тульская об...                    48.0   \n",
       "\n",
       "  file_key             datetime         dat  year year_month  hour  weekday  \\\n",
       "0     0-15  2023-01-27 21:45:00  2023-01-27  2023    2023-01    21        4   \n",
       "1     0-15  2023-01-27 21:35:00  2023-01-27  2023    2023-01    21        4   \n",
       "2     0-15  2023-01-27 21:34:00  2023-01-27  2023    2023-01    21        4   \n",
       "\n",
       "   whole newscast                                   body_token_final  \\\n",
       "0            True  ['смотреть', 'выпуск', '79', 'год', 'полностью...   \n",
       "1           False  ['событие', 'мир', 'отечественный', 'кино', 'м...   \n",
       "2           False  ['футбольный', 'манеж', 'тула', 'искусственный...   \n",
       "\n",
       "                                   title_token_final  \n",
       "0  ['выпуск', 'программа', 'время', '21:00', '27....  \n",
       "1  ['москва', 'проходить', 'церемония', 'вручение...  \n",
       "2  ['тула', 'появиться', 'новый', 'футбольный', '...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9411850f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['video_duration_min'] = df['video_duration_seconds'] / 60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "692dee7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add column to compare news patterns before special military operation and after\n",
    "# We take one year before SMO for this comparison\n",
    "df['dat'] = pd.to_datetime(df['dat'])\n",
    "df['before_after_CMO'] = np.where(df['dat']>=pd.to_datetime('2021-01-11'),\n",
    "                                  'before CMO',\n",
    "                                  np.NaN)\n",
    "df['before_after_CMO'] = np.where((df['dat']>=pd.to_datetime('2022-02-24')),\n",
    "                                  'after CMO',\n",
    "                                  df['before_after_CMO'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8d89e069",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dataframe that contains only newscasts, not individual news stories\n",
    "newscast = df[df['whole newscast']==True]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67d58e88",
   "metadata": {},
   "source": [
    "### Filtering rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c7c69e53",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dataframe that contains only individual news stories, not newscasts\n",
    "df = df[df['whole newscast']==False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e227b02e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(350719, 20)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3c19cf44",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filtering rows that are relevant for further analysis (a year before the special military operation)\n",
    "df = df[df['dat']>= pd.to_datetime('2021-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "aa61e13e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40590, 20)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62bd670b",
   "metadata": {},
   "source": [
    "## Patterns of news releases in general"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ea844237",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>2021-01-01</th>\n",
       "      <td>23.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>32.333333</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-03</th>\n",
       "      <td>27.950000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>38.300000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>41.083333</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-06</th>\n",
       "      <td>38.816667</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-07</th>\n",
       "      <td>45.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-08</th>\n",
       "      <td>51.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-09</th>\n",
       "      <td>47.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-10</th>\n",
       "      <td>46.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-11</th>\n",
       "      <td>125.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-12</th>\n",
       "      <td>122.850000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-13</th>\n",
       "      <td>117.200000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-14</th>\n",
       "      <td>125.150000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-15</th>\n",
       "      <td>116.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-16</th>\n",
       "      <td>53.100000</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-17</th>\n",
       "      <td>81.666667</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-18</th>\n",
       "      <td>113.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-19</th>\n",
       "      <td>119.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-20</th>\n",
       "      <td>116.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-21</th>\n",
       "      <td>117.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>119.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-23</th>\n",
       "      <td>64.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-24</th>\n",
       "      <td>86.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>107.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>115.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-27</th>\n",
       "      <td>126.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-28</th>\n",
       "      <td>126.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-29</th>\n",
       "      <td>128.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-30</th>\n",
       "      <td>62.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>89.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-01</th>\n",
       "      <td>122.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-02</th>\n",
       "      <td>119.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-03</th>\n",
       "      <td>119.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-04</th>\n",
       "      <td>123.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-05</th>\n",
       "      <td>121.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-06</th>\n",
       "      <td>51.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-07</th>\n",
       "      <td>90.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-08</th>\n",
       "      <td>111.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-09</th>\n",
       "      <td>113.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-10</th>\n",
       "      <td>114.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-11</th>\n",
       "      <td>119.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-12</th>\n",
       "      <td>120.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-13</th>\n",
       "      <td>50.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-14</th>\n",
       "      <td>92.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-15</th>\n",
       "      <td>114.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-16</th>\n",
       "      <td>115.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-17</th>\n",
       "      <td>120.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-18</th>\n",
       "      <td>120.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-19</th>\n",
       "      <td>118.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-20</th>\n",
       "      <td>108.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-21</th>\n",
       "      <td>78.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-22</th>\n",
       "      <td>60.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-23</th>\n",
       "      <td>60.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-24</th>\n",
       "      <td>119.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-25</th>\n",
       "      <td>116.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-26</th>\n",
       "      <td>108.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-27</th>\n",
       "      <td>59.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-28</th>\n",
       "      <td>77.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-01</th>\n",
       "      <td>119.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-02</th>\n",
       "      <td>118.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-03</th>\n",
       "      <td>123.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-04</th>\n",
       "      <td>126.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-05</th>\n",
       "      <td>115.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-06</th>\n",
       "      <td>47.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-07</th>\n",
       "      <td>81.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-08</th>\n",
       "      <td>43.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-09</th>\n",
       "      <td>111.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-10</th>\n",
       "      <td>114.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-11</th>\n",
       "      <td>112.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-12</th>\n",
       "      <td>111.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-13</th>\n",
       "      <td>52.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-14</th>\n",
       "      <td>84.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-15</th>\n",
       "      <td>115.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-16</th>\n",
       "      <td>114.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-17</th>\n",
       "      <td>115.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-18</th>\n",
       "      <td>134.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-19</th>\n",
       "      <td>120.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-20</th>\n",
       "      <td>47.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-21</th>\n",
       "      <td>85.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-22</th>\n",
       "      <td>123.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-23</th>\n",
       "      <td>122.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-24</th>\n",
       "      <td>132.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-25</th>\n",
       "      <td>121.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-26</th>\n",
       "      <td>122.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-27</th>\n",
       "      <td>45.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-28</th>\n",
       "      <td>89.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-29</th>\n",
       "      <td>109.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-30</th>\n",
       "      <td>114.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-31</th>\n",
       "      <td>120.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-01</th>\n",
       "      <td>117.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-02</th>\n",
       "      <td>119.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-03</th>\n",
       "      <td>47.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-04</th>\n",
       "      <td>81.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-05</th>\n",
       "      <td>113.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-06</th>\n",
       "      <td>111.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-07</th>\n",
       "      <td>101.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-08</th>\n",
       "      <td>121.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-09</th>\n",
       "      <td>119.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-10</th>\n",
       "      <td>54.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-11</th>\n",
       "      <td>76.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-12</th>\n",
       "      <td>119.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-13</th>\n",
       "      <td>114.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-14</th>\n",
       "      <td>120.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-15</th>\n",
       "      <td>124.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-16</th>\n",
       "      <td>118.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-17</th>\n",
       "      <td>57.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-18</th>\n",
       "      <td>109.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-19</th>\n",
       "      <td>126.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-20</th>\n",
       "      <td>122.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-21</th>\n",
       "      <td>182.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-22</th>\n",
       "      <td>131.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-23</th>\n",
       "      <td>114.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-24</th>\n",
       "      <td>47.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-25</th>\n",
       "      <td>99.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-26</th>\n",
       "      <td>114.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-27</th>\n",
       "      <td>122.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-28</th>\n",
       "      <td>119.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-29</th>\n",
       "      <td>118.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-30</th>\n",
       "      <td>114.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-01</th>\n",
       "      <td>83.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-02</th>\n",
       "      <td>75.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-03</th>\n",
       "      <td>44.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-04</th>\n",
       "      <td>46.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-05</th>\n",
       "      <td>48.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-06</th>\n",
       "      <td>58.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-07</th>\n",
       "      <td>68.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-08</th>\n",
       "      <td>44.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-09</th>\n",
       "      <td>163.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-10</th>\n",
       "      <td>55.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-11</th>\n",
       "      <td>114.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-12</th>\n",
       "      <td>124.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-13</th>\n",
       "      <td>125.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-14</th>\n",
       "      <td>115.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-15</th>\n",
       "      <td>51.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-16</th>\n",
       "      <td>99.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-17</th>\n",
       "      <td>117.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-18</th>\n",
       "      <td>147.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-19</th>\n",
       "      <td>119.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-20</th>\n",
       "      <td>147.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-21</th>\n",
       "      <td>138.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-22</th>\n",
       "      <td>50.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-23</th>\n",
       "      <td>107.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-24</th>\n",
       "      <td>120.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-25</th>\n",
       "      <td>116.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>114.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-27</th>\n",
       "      <td>120.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-28</th>\n",
       "      <td>114.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-29</th>\n",
       "      <td>49.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-30</th>\n",
       "      <td>87.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-31</th>\n",
       "      <td>109.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-01</th>\n",
       "      <td>124.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-02</th>\n",
       "      <td>119.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-03</th>\n",
       "      <td>111.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-04</th>\n",
       "      <td>153.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-05</th>\n",
       "      <td>59.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-06</th>\n",
       "      <td>117.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-07</th>\n",
       "      <td>116.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-08</th>\n",
       "      <td>117.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-09</th>\n",
       "      <td>130.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-10</th>\n",
       "      <td>131.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-11</th>\n",
       "      <td>117.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-12</th>\n",
       "      <td>64.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-13</th>\n",
       "      <td>75.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-14</th>\n",
       "      <td>67.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-15</th>\n",
       "      <td>127.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-16</th>\n",
       "      <td>201.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-17</th>\n",
       "      <td>133.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-18</th>\n",
       "      <td>128.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-19</th>\n",
       "      <td>75.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-20</th>\n",
       "      <td>109.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-21</th>\n",
       "      <td>127.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-22</th>\n",
       "      <td>138.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-23</th>\n",
       "      <td>125.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-24</th>\n",
       "      <td>121.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-25</th>\n",
       "      <td>113.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-26</th>\n",
       "      <td>71.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-27</th>\n",
       "      <td>73.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-28</th>\n",
       "      <td>122.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-29</th>\n",
       "      <td>112.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>223.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-01</th>\n",
       "      <td>133.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-02</th>\n",
       "      <td>115.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-03</th>\n",
       "      <td>49.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-04</th>\n",
       "      <td>99.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-05</th>\n",
       "      <td>133.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-06</th>\n",
       "      <td>122.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-07</th>\n",
       "      <td>130.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-08</th>\n",
       "      <td>130.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-09</th>\n",
       "      <td>116.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-10</th>\n",
       "      <td>55.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-11</th>\n",
       "      <td>78.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-12</th>\n",
       "      <td>118.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-13</th>\n",
       "      <td>128.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-14</th>\n",
       "      <td>129.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-15</th>\n",
       "      <td>128.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-16</th>\n",
       "      <td>123.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-17</th>\n",
       "      <td>57.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-18</th>\n",
       "      <td>96.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-19</th>\n",
       "      <td>126.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-20</th>\n",
       "      <td>128.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-21</th>\n",
       "      <td>132.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-22</th>\n",
       "      <td>140.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-23</th>\n",
       "      <td>124.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-24</th>\n",
       "      <td>57.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-25</th>\n",
       "      <td>143.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>125.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>125.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>104.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>102.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>125.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-31</th>\n",
       "      <td>49.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-01</th>\n",
       "      <td>110.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-02</th>\n",
       "      <td>138.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-03</th>\n",
       "      <td>147.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-04</th>\n",
       "      <td>127.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-05</th>\n",
       "      <td>151.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-06</th>\n",
       "      <td>141.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-07</th>\n",
       "      <td>51.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-08</th>\n",
       "      <td>97.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-09</th>\n",
       "      <td>125.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-10</th>\n",
       "      <td>119.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-11</th>\n",
       "      <td>121.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-12</th>\n",
       "      <td>119.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-13</th>\n",
       "      <td>112.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-14</th>\n",
       "      <td>61.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-15</th>\n",
       "      <td>85.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-16</th>\n",
       "      <td>116.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-17</th>\n",
       "      <td>116.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-18</th>\n",
       "      <td>117.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-19</th>\n",
       "      <td>121.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-20</th>\n",
       "      <td>126.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-21</th>\n",
       "      <td>44.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-22</th>\n",
       "      <td>102.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-23</th>\n",
       "      <td>126.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-24</th>\n",
       "      <td>128.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-25</th>\n",
       "      <td>118.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-26</th>\n",
       "      <td>126.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-27</th>\n",
       "      <td>111.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-28</th>\n",
       "      <td>56.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-29</th>\n",
       "      <td>103.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-30</th>\n",
       "      <td>120.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>121.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-01</th>\n",
       "      <td>121.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-02</th>\n",
       "      <td>130.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-03</th>\n",
       "      <td>129.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-04</th>\n",
       "      <td>62.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-05</th>\n",
       "      <td>83.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-06</th>\n",
       "      <td>113.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-07</th>\n",
       "      <td>114.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-08</th>\n",
       "      <td>125.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-09</th>\n",
       "      <td>126.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-10</th>\n",
       "      <td>125.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-11</th>\n",
       "      <td>67.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-12</th>\n",
       "      <td>89.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-13</th>\n",
       "      <td>119.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-14</th>\n",
       "      <td>124.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-15</th>\n",
       "      <td>126.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-16</th>\n",
       "      <td>130.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-17</th>\n",
       "      <td>122.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-18</th>\n",
       "      <td>62.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-19</th>\n",
       "      <td>81.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-20</th>\n",
       "      <td>120.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-21</th>\n",
       "      <td>115.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-22</th>\n",
       "      <td>112.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-23</th>\n",
       "      <td>121.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-24</th>\n",
       "      <td>120.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-25</th>\n",
       "      <td>61.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-26</th>\n",
       "      <td>83.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27</th>\n",
       "      <td>118.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-28</th>\n",
       "      <td>120.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-29</th>\n",
       "      <td>112.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>116.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-01</th>\n",
       "      <td>110.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-02</th>\n",
       "      <td>61.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-03</th>\n",
       "      <td>79.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-04</th>\n",
       "      <td>127.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-05</th>\n",
       "      <td>184.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-06</th>\n",
       "      <td>129.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-07</th>\n",
       "      <td>118.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-08</th>\n",
       "      <td>112.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-09</th>\n",
       "      <td>51.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-10</th>\n",
       "      <td>82.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-11</th>\n",
       "      <td>108.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-12</th>\n",
       "      <td>124.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-13</th>\n",
       "      <td>127.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-14</th>\n",
       "      <td>128.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-15</th>\n",
       "      <td>117.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-16</th>\n",
       "      <td>54.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-17</th>\n",
       "      <td>159.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-18</th>\n",
       "      <td>112.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-19</th>\n",
       "      <td>121.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-20</th>\n",
       "      <td>119.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-21</th>\n",
       "      <td>143.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-22</th>\n",
       "      <td>117.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-23</th>\n",
       "      <td>53.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-24</th>\n",
       "      <td>107.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-25</th>\n",
       "      <td>118.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-26</th>\n",
       "      <td>117.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-27</th>\n",
       "      <td>116.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-28</th>\n",
       "      <td>119.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-29</th>\n",
       "      <td>117.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-30</th>\n",
       "      <td>57.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-31</th>\n",
       "      <td>96.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-01</th>\n",
       "      <td>110.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-02</th>\n",
       "      <td>120.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-03</th>\n",
       "      <td>112.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-04</th>\n",
       "      <td>55.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-05</th>\n",
       "      <td>52.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-06</th>\n",
       "      <td>48.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-07</th>\n",
       "      <td>52.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-08</th>\n",
       "      <td>113.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-09</th>\n",
       "      <td>109.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-10</th>\n",
       "      <td>126.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-11</th>\n",
       "      <td>123.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-12</th>\n",
       "      <td>114.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-13</th>\n",
       "      <td>59.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-14</th>\n",
       "      <td>82.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-15</th>\n",
       "      <td>110.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-16</th>\n",
       "      <td>114.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-17</th>\n",
       "      <td>112.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-18</th>\n",
       "      <td>119.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-19</th>\n",
       "      <td>126.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-20</th>\n",
       "      <td>59.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-21</th>\n",
       "      <td>89.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-22</th>\n",
       "      <td>116.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-23</th>\n",
       "      <td>116.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24</th>\n",
       "      <td>125.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-25</th>\n",
       "      <td>125.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26</th>\n",
       "      <td>120.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-27</th>\n",
       "      <td>51.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-28</th>\n",
       "      <td>95.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29</th>\n",
       "      <td>112.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-30</th>\n",
       "      <td>115.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-01</th>\n",
       "      <td>122.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-02</th>\n",
       "      <td>123.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-03</th>\n",
       "      <td>118.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-04</th>\n",
       "      <td>59.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-05</th>\n",
       "      <td>107.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-06</th>\n",
       "      <td>117.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-07</th>\n",
       "      <td>122.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-08</th>\n",
       "      <td>130.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-09</th>\n",
       "      <td>125.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-10</th>\n",
       "      <td>121.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-11</th>\n",
       "      <td>45.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-12</th>\n",
       "      <td>100.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-13</th>\n",
       "      <td>109.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-14</th>\n",
       "      <td>110.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-15</th>\n",
       "      <td>110.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-16</th>\n",
       "      <td>108.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-17</th>\n",
       "      <td>126.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-18</th>\n",
       "      <td>47.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-19</th>\n",
       "      <td>98.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-20</th>\n",
       "      <td>118.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-21</th>\n",
       "      <td>131.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-22</th>\n",
       "      <td>127.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-23</th>\n",
       "      <td>189.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-24</th>\n",
       "      <td>114.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-25</th>\n",
       "      <td>51.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-26</th>\n",
       "      <td>142.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-27</th>\n",
       "      <td>115.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-28</th>\n",
       "      <td>114.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-29</th>\n",
       "      <td>121.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-30</th>\n",
       "      <td>115.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>39.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>12.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-02</th>\n",
       "      <td>36.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-03</th>\n",
       "      <td>38.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>40.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>43.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>40.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>49.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-08</th>\n",
       "      <td>42.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-09</th>\n",
       "      <td>55.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>115.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>120.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-12</th>\n",
       "      <td>127.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>120.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>123.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-15</th>\n",
       "      <td>51.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-16</th>\n",
       "      <td>89.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-17</th>\n",
       "      <td>115.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-18</th>\n",
       "      <td>124.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-19</th>\n",
       "      <td>116.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-20</th>\n",
       "      <td>123.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-21</th>\n",
       "      <td>118.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-22</th>\n",
       "      <td>47.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-23</th>\n",
       "      <td>101.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-24</th>\n",
       "      <td>114.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-25</th>\n",
       "      <td>131.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-26</th>\n",
       "      <td>121.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-27</th>\n",
       "      <td>126.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-28</th>\n",
       "      <td>111.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-29</th>\n",
       "      <td>47.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-30</th>\n",
       "      <td>97.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-31</th>\n",
       "      <td>116.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-01</th>\n",
       "      <td>132.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-02</th>\n",
       "      <td>122.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-03</th>\n",
       "      <td>126.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-04</th>\n",
       "      <td>109.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-05</th>\n",
       "      <td>48.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-06</th>\n",
       "      <td>102.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-07</th>\n",
       "      <td>109.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-08</th>\n",
       "      <td>121.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-09</th>\n",
       "      <td>119.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-10</th>\n",
       "      <td>121.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-11</th>\n",
       "      <td>99.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-12</th>\n",
       "      <td>49.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-13</th>\n",
       "      <td>110.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-14</th>\n",
       "      <td>111.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-15</th>\n",
       "      <td>133.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-16</th>\n",
       "      <td>114.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-17</th>\n",
       "      <td>126.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-18</th>\n",
       "      <td>118.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-19</th>\n",
       "      <td>80.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-20</th>\n",
       "      <td>102.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-21</th>\n",
       "      <td>259.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-22</th>\n",
       "      <td>152.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-23</th>\n",
       "      <td>68.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-24</th>\n",
       "      <td>354.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-25</th>\n",
       "      <td>263.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-26</th>\n",
       "      <td>142.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-27</th>\n",
       "      <td>217.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-28</th>\n",
       "      <td>234.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-01</th>\n",
       "      <td>207.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-02</th>\n",
       "      <td>171.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-03</th>\n",
       "      <td>229.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-04</th>\n",
       "      <td>210.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-05</th>\n",
       "      <td>171.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-06</th>\n",
       "      <td>203.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-07</th>\n",
       "      <td>109.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-08</th>\n",
       "      <td>109.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-09</th>\n",
       "      <td>215.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-10</th>\n",
       "      <td>246.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-11</th>\n",
       "      <td>219.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-12</th>\n",
       "      <td>103.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-13</th>\n",
       "      <td>169.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14</th>\n",
       "      <td>205.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-15</th>\n",
       "      <td>200.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-16</th>\n",
       "      <td>236.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-17</th>\n",
       "      <td>210.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-18</th>\n",
       "      <td>219.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-19</th>\n",
       "      <td>118.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-20</th>\n",
       "      <td>185.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-21</th>\n",
       "      <td>197.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-22</th>\n",
       "      <td>195.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-23</th>\n",
       "      <td>212.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-24</th>\n",
       "      <td>210.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>192.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-26</th>\n",
       "      <td>113.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-27</th>\n",
       "      <td>192.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-28</th>\n",
       "      <td>180.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>193.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-30</th>\n",
       "      <td>201.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-31</th>\n",
       "      <td>195.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
       "      <td>200.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-02</th>\n",
       "      <td>118.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-03</th>\n",
       "      <td>166.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-04</th>\n",
       "      <td>189.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-05</th>\n",
       "      <td>181.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-06</th>\n",
       "      <td>203.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-07</th>\n",
       "      <td>195.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-08</th>\n",
       "      <td>183.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-09</th>\n",
       "      <td>97.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-10</th>\n",
       "      <td>185.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-11</th>\n",
       "      <td>152.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-12</th>\n",
       "      <td>170.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-13</th>\n",
       "      <td>143.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-14</th>\n",
       "      <td>152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-15</th>\n",
       "      <td>144.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-16</th>\n",
       "      <td>96.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-17</th>\n",
       "      <td>187.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-18</th>\n",
       "      <td>144.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-19</th>\n",
       "      <td>128.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-20</th>\n",
       "      <td>144.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-21</th>\n",
       "      <td>158.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-22</th>\n",
       "      <td>146.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-23</th>\n",
       "      <td>96.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-24</th>\n",
       "      <td>170.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-25</th>\n",
       "      <td>140.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-26</th>\n",
       "      <td>141.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-27</th>\n",
       "      <td>152.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>135.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-29</th>\n",
       "      <td>144.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-30</th>\n",
       "      <td>96.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-01</th>\n",
       "      <td>167.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-02</th>\n",
       "      <td>105.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-03</th>\n",
       "      <td>99.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-04</th>\n",
       "      <td>144.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-05</th>\n",
       "      <td>140.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-06</th>\n",
       "      <td>136.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-07</th>\n",
       "      <td>100.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-08</th>\n",
       "      <td>172.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-09</th>\n",
       "      <td>388.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-10</th>\n",
       "      <td>102.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-11</th>\n",
       "      <td>129.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-12</th>\n",
       "      <td>158.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-13</th>\n",
       "      <td>150.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-14</th>\n",
       "      <td>91.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-15</th>\n",
       "      <td>182.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-16</th>\n",
       "      <td>141.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-17</th>\n",
       "      <td>128.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-18</th>\n",
       "      <td>130.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-19</th>\n",
       "      <td>161.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-20</th>\n",
       "      <td>153.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-21</th>\n",
       "      <td>100.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-22</th>\n",
       "      <td>173.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-23</th>\n",
       "      <td>120.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-24</th>\n",
       "      <td>152.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-25</th>\n",
       "      <td>143.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-26</th>\n",
       "      <td>154.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-27</th>\n",
       "      <td>156.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-28</th>\n",
       "      <td>92.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-29</th>\n",
       "      <td>198.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-30</th>\n",
       "      <td>135.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-31</th>\n",
       "      <td>155.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>141.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-02</th>\n",
       "      <td>153.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-03</th>\n",
       "      <td>159.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-04</th>\n",
       "      <td>92.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-05</th>\n",
       "      <td>172.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-06</th>\n",
       "      <td>142.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-07</th>\n",
       "      <td>157.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-08</th>\n",
       "      <td>140.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-09</th>\n",
       "      <td>161.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-10</th>\n",
       "      <td>167.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-11</th>\n",
       "      <td>91.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-12</th>\n",
       "      <td>104.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-13</th>\n",
       "      <td>173.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-14</th>\n",
       "      <td>133.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-15</th>\n",
       "      <td>139.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-16</th>\n",
       "      <td>154.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-17</th>\n",
       "      <td>192.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-18</th>\n",
       "      <td>94.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-19</th>\n",
       "      <td>173.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-20</th>\n",
       "      <td>135.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-21</th>\n",
       "      <td>126.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-22</th>\n",
       "      <td>144.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-23</th>\n",
       "      <td>151.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-24</th>\n",
       "      <td>131.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-25</th>\n",
       "      <td>90.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-26</th>\n",
       "      <td>170.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-27</th>\n",
       "      <td>125.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-28</th>\n",
       "      <td>137.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-29</th>\n",
       "      <td>142.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-30</th>\n",
       "      <td>154.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-01</th>\n",
       "      <td>159.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-02</th>\n",
       "      <td>90.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-03</th>\n",
       "      <td>175.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-04</th>\n",
       "      <td>135.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-05</th>\n",
       "      <td>140.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-06</th>\n",
       "      <td>144.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-07</th>\n",
       "      <td>169.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-08</th>\n",
       "      <td>173.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-09</th>\n",
       "      <td>90.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-10</th>\n",
       "      <td>176.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-11</th>\n",
       "      <td>150.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-12</th>\n",
       "      <td>123.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-13</th>\n",
       "      <td>135.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-14</th>\n",
       "      <td>132.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-15</th>\n",
       "      <td>151.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-16</th>\n",
       "      <td>93.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-17</th>\n",
       "      <td>169.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-18</th>\n",
       "      <td>155.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-19</th>\n",
       "      <td>145.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-20</th>\n",
       "      <td>153.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-21</th>\n",
       "      <td>142.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-22</th>\n",
       "      <td>154.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-23</th>\n",
       "      <td>92.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-24</th>\n",
       "      <td>170.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-25</th>\n",
       "      <td>164.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-26</th>\n",
       "      <td>149.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-27</th>\n",
       "      <td>152.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-28</th>\n",
       "      <td>129.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-29</th>\n",
       "      <td>168.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-30</th>\n",
       "      <td>103.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-31</th>\n",
       "      <td>206.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-01</th>\n",
       "      <td>125.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-02</th>\n",
       "      <td>136.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-03</th>\n",
       "      <td>135.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-04</th>\n",
       "      <td>145.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-05</th>\n",
       "      <td>159.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-06</th>\n",
       "      <td>83.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-07</th>\n",
       "      <td>159.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-08</th>\n",
       "      <td>137.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-09</th>\n",
       "      <td>146.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-10</th>\n",
       "      <td>137.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-11</th>\n",
       "      <td>131.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-12</th>\n",
       "      <td>162.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-13</th>\n",
       "      <td>79.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-14</th>\n",
       "      <td>140.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-15</th>\n",
       "      <td>142.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-16</th>\n",
       "      <td>145.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-17</th>\n",
       "      <td>135.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-18</th>\n",
       "      <td>143.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-19</th>\n",
       "      <td>140.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-20</th>\n",
       "      <td>80.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-21</th>\n",
       "      <td>148.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-22</th>\n",
       "      <td>133.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-23</th>\n",
       "      <td>137.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-24</th>\n",
       "      <td>153.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-25</th>\n",
       "      <td>149.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-26</th>\n",
       "      <td>141.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-27</th>\n",
       "      <td>85.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-28</th>\n",
       "      <td>158.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-29</th>\n",
       "      <td>141.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-30</th>\n",
       "      <td>128.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-31</th>\n",
       "      <td>150.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-01</th>\n",
       "      <td>161.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-02</th>\n",
       "      <td>136.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-03</th>\n",
       "      <td>86.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-04</th>\n",
       "      <td>141.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-05</th>\n",
       "      <td>166.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-06</th>\n",
       "      <td>165.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-07</th>\n",
       "      <td>198.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-08</th>\n",
       "      <td>143.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-09</th>\n",
       "      <td>151.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-10</th>\n",
       "      <td>85.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-11</th>\n",
       "      <td>172.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-12</th>\n",
       "      <td>143.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-13</th>\n",
       "      <td>125.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-14</th>\n",
       "      <td>134.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-15</th>\n",
       "      <td>144.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-16</th>\n",
       "      <td>178.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-17</th>\n",
       "      <td>81.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-18</th>\n",
       "      <td>134.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-19</th>\n",
       "      <td>139.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-20</th>\n",
       "      <td>151.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-21</th>\n",
       "      <td>203.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-22</th>\n",
       "      <td>151.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-23</th>\n",
       "      <td>153.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-24</th>\n",
       "      <td>82.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-25</th>\n",
       "      <td>150.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-26</th>\n",
       "      <td>139.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-27</th>\n",
       "      <td>164.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-28</th>\n",
       "      <td>148.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-29</th>\n",
       "      <td>134.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-30</th>\n",
       "      <td>160.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-01</th>\n",
       "      <td>82.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-02</th>\n",
       "      <td>161.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-03</th>\n",
       "      <td>147.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-04</th>\n",
       "      <td>140.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-05</th>\n",
       "      <td>145.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-06</th>\n",
       "      <td>145.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-07</th>\n",
       "      <td>118.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-08</th>\n",
       "      <td>96.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-09</th>\n",
       "      <td>147.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-10</th>\n",
       "      <td>137.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-11</th>\n",
       "      <td>145.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-12</th>\n",
       "      <td>156.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-13</th>\n",
       "      <td>153.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-14</th>\n",
       "      <td>125.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-15</th>\n",
       "      <td>76.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-16</th>\n",
       "      <td>139.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-17</th>\n",
       "      <td>115.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-18</th>\n",
       "      <td>146.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-19</th>\n",
       "      <td>116.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-20</th>\n",
       "      <td>129.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-21</th>\n",
       "      <td>143.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-22</th>\n",
       "      <td>76.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-23</th>\n",
       "      <td>137.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-24</th>\n",
       "      <td>132.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-25</th>\n",
       "      <td>121.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-26</th>\n",
       "      <td>129.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-27</th>\n",
       "      <td>112.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-28</th>\n",
       "      <td>138.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-29</th>\n",
       "      <td>82.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-30</th>\n",
       "      <td>141.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-31</th>\n",
       "      <td>131.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-01</th>\n",
       "      <td>133.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-02</th>\n",
       "      <td>123.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-03</th>\n",
       "      <td>125.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-04</th>\n",
       "      <td>90.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-05</th>\n",
       "      <td>79.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-06</th>\n",
       "      <td>123.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-07</th>\n",
       "      <td>133.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-08</th>\n",
       "      <td>123.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-09</th>\n",
       "      <td>143.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-10</th>\n",
       "      <td>120.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-11</th>\n",
       "      <td>129.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-12</th>\n",
       "      <td>74.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-13</th>\n",
       "      <td>126.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-14</th>\n",
       "      <td>115.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-15</th>\n",
       "      <td>137.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-16</th>\n",
       "      <td>157.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-17</th>\n",
       "      <td>143.066667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-18</th>\n",
       "      <td>130.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-19</th>\n",
       "      <td>82.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-20</th>\n",
       "      <td>126.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-21</th>\n",
       "      <td>125.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-22</th>\n",
       "      <td>133.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-23</th>\n",
       "      <td>136.483333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-24</th>\n",
       "      <td>130.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-25</th>\n",
       "      <td>130.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-26</th>\n",
       "      <td>77.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-27</th>\n",
       "      <td>139.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>124.683333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-29</th>\n",
       "      <td>116.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-30</th>\n",
       "      <td>145.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-01</th>\n",
       "      <td>144.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-02</th>\n",
       "      <td>157.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-03</th>\n",
       "      <td>86.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-04</th>\n",
       "      <td>135.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-05</th>\n",
       "      <td>139.516667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-06</th>\n",
       "      <td>124.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-07</th>\n",
       "      <td>141.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-08</th>\n",
       "      <td>126.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-09</th>\n",
       "      <td>146.116667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-10</th>\n",
       "      <td>76.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-11</th>\n",
       "      <td>136.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-12</th>\n",
       "      <td>116.716667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-13</th>\n",
       "      <td>114.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-14</th>\n",
       "      <td>112.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-15</th>\n",
       "      <td>145.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-16</th>\n",
       "      <td>129.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-17</th>\n",
       "      <td>79.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-18</th>\n",
       "      <td>125.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-19</th>\n",
       "      <td>125.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-20</th>\n",
       "      <td>126.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-21</th>\n",
       "      <td>131.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-22</th>\n",
       "      <td>151.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-23</th>\n",
       "      <td>132.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-24</th>\n",
       "      <td>74.216667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-25</th>\n",
       "      <td>134.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-26</th>\n",
       "      <td>117.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27</th>\n",
       "      <td>130.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28</th>\n",
       "      <td>126.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29</th>\n",
       "      <td>138.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30</th>\n",
       "      <td>140.233333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>70.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01</th>\n",
       "      <td>72.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-02</th>\n",
       "      <td>79.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>69.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>69.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>70.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>68.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-07</th>\n",
       "      <td>71.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-08</th>\n",
       "      <td>53.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>114.783333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-10</th>\n",
       "      <td>101.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-11</th>\n",
       "      <td>127.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-12</th>\n",
       "      <td>136.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-13</th>\n",
       "      <td>136.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-14</th>\n",
       "      <td>75.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-15</th>\n",
       "      <td>171.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-16</th>\n",
       "      <td>118.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-17</th>\n",
       "      <td>132.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-18</th>\n",
       "      <td>142.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-19</th>\n",
       "      <td>124.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-20</th>\n",
       "      <td>141.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-21</th>\n",
       "      <td>78.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-22</th>\n",
       "      <td>180.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-23</th>\n",
       "      <td>124.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-24</th>\n",
       "      <td>138.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-25</th>\n",
       "      <td>161.383333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-26</th>\n",
       "      <td>126.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-27</th>\n",
       "      <td>137.466667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            video_duration_min\n",
       "dat                           \n",
       "2021-01-01           23.750000\n",
       "2021-01-02           32.333333\n",
       "2021-01-03           27.950000\n",
       "2021-01-04           38.300000\n",
       "2021-01-05           41.083333\n",
       "2021-01-06           38.816667\n",
       "2021-01-07           45.466667\n",
       "2021-01-08           51.100000\n",
       "2021-01-09           47.100000\n",
       "2021-01-10           46.666667\n",
       "2021-01-11          125.200000\n",
       "2021-01-12          122.850000\n",
       "2021-01-13          117.200000\n",
       "2021-01-14          125.150000\n",
       "2021-01-15          116.233333\n",
       "2021-01-16           53.100000\n",
       "2021-01-17           81.666667\n",
       "2021-01-18          113.816667\n",
       "2021-01-19          119.083333\n",
       "2021-01-20          116.933333\n",
       "2021-01-21          117.300000\n",
       "2021-01-22          119.166667\n",
       "2021-01-23           64.516667\n",
       "2021-01-24           86.100000\n",
       "2021-01-25          107.183333\n",
       "2021-01-26          115.850000\n",
       "2021-01-27          126.416667\n",
       "2021-01-28          126.700000\n",
       "2021-01-29          128.850000\n",
       "2021-01-30           62.983333\n",
       "2021-01-31           89.066667\n",
       "2021-02-01          122.500000\n",
       "2021-02-02          119.150000\n",
       "2021-02-03          119.883333\n",
       "2021-02-04          123.833333\n",
       "2021-02-05          121.050000\n",
       "2021-02-06           51.050000\n",
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       "2022-04-27          152.866667\n",
       "2022-04-28          135.483333\n",
       "2022-04-29          144.466667\n",
       "2022-04-30           96.550000\n",
       "2022-05-01          167.783333\n",
       "2022-05-02          105.366667\n",
       "2022-05-03           99.966667\n",
       "2022-05-04          144.000000\n",
       "2022-05-05          140.083333\n",
       "2022-05-06          136.800000\n",
       "2022-05-07          100.900000\n",
       "2022-05-08          172.266667\n",
       "2022-05-09          388.633333\n",
       "2022-05-10          102.666667\n",
       "2022-05-11          129.383333\n",
       "2022-05-12          158.016667\n",
       "2022-05-13          150.533333\n",
       "2022-05-14           91.466667\n",
       "2022-05-15          182.200000\n",
       "2022-05-16          141.266667\n",
       "2022-05-17          128.116667\n",
       "2022-05-18          130.066667\n",
       "2022-05-19          161.900000\n",
       "2022-05-20          153.900000\n",
       "2022-05-21          100.300000\n",
       "2022-05-22          173.216667\n",
       "2022-05-23          120.483333\n",
       "2022-05-24          152.133333\n",
       "2022-05-25          143.083333\n",
       "2022-05-26          154.550000\n",
       "2022-05-27          156.250000\n",
       "2022-05-28           92.833333\n",
       "2022-05-29          198.833333\n",
       "2022-05-30          135.750000\n",
       "2022-05-31          155.966667\n",
       "2022-06-01          141.733333\n",
       "2022-06-02          153.550000\n",
       "2022-06-03          159.150000\n",
       "2022-06-04           92.600000\n",
       "2022-06-05          172.216667\n",
       "2022-06-06          142.000000\n",
       "2022-06-07          157.750000\n",
       "2022-06-08          140.866667\n",
       "2022-06-09          161.150000\n",
       "2022-06-10          167.883333\n",
       "2022-06-11           91.566667\n",
       "2022-06-12          104.366667\n",
       "2022-06-13          173.500000\n",
       "2022-06-14          133.133333\n",
       "2022-06-15          139.683333\n",
       "2022-06-16          154.433333\n",
       "2022-06-17          192.266667\n",
       "2022-06-18           94.916667\n",
       "2022-06-19          173.450000\n",
       "2022-06-20          135.616667\n",
       "2022-06-21          126.916667\n",
       "2022-06-22          144.150000\n",
       "2022-06-23          151.850000\n",
       "2022-06-24          131.166667\n",
       "2022-06-25           90.300000\n",
       "2022-06-26          170.316667\n",
       "2022-06-27          125.200000\n",
       "2022-06-28          137.266667\n",
       "2022-06-29          142.333333\n",
       "2022-06-30          154.300000\n",
       "2022-07-01          159.066667\n",
       "2022-07-02           90.616667\n",
       "2022-07-03          175.033333\n",
       "2022-07-04          135.250000\n",
       "2022-07-05          140.266667\n",
       "2022-07-06          144.116667\n",
       "2022-07-07          169.983333\n",
       "2022-07-08          173.500000\n",
       "2022-07-09           90.150000\n",
       "2022-07-10          176.916667\n",
       "2022-07-11          150.233333\n",
       "2022-07-12          123.733333\n",
       "2022-07-13          135.683333\n",
       "2022-07-14          132.866667\n",
       "2022-07-15          151.800000\n",
       "2022-07-16           93.400000\n",
       "2022-07-17          169.233333\n",
       "2022-07-18          155.433333\n",
       "2022-07-19          145.316667\n",
       "2022-07-20          153.616667\n",
       "2022-07-21          142.150000\n",
       "2022-07-22          154.483333\n",
       "2022-07-23           92.050000\n",
       "2022-07-24          170.783333\n",
       "2022-07-25          164.266667\n",
       "2022-07-26          149.316667\n",
       "2022-07-27          152.066667\n",
       "2022-07-28          129.650000\n",
       "2022-07-29          168.983333\n",
       "2022-07-30          103.766667\n",
       "2022-07-31          206.766667\n",
       "2022-08-01          125.283333\n",
       "2022-08-02          136.766667\n",
       "2022-08-03          135.316667\n",
       "2022-08-04          145.566667\n",
       "2022-08-05          159.716667\n",
       "2022-08-06           83.083333\n",
       "2022-08-07          159.466667\n",
       "2022-08-08          137.000000\n",
       "2022-08-09          146.916667\n",
       "2022-08-10          137.533333\n",
       "2022-08-11          131.916667\n",
       "2022-08-12          162.333333\n",
       "2022-08-13           79.716667\n",
       "2022-08-14          140.200000\n",
       "2022-08-15          142.250000\n",
       "2022-08-16          145.633333\n",
       "2022-08-17          135.566667\n",
       "2022-08-18          143.183333\n",
       "2022-08-19          140.200000\n",
       "2022-08-20           80.633333\n",
       "2022-08-21          148.283333\n",
       "2022-08-22          133.583333\n",
       "2022-08-23          137.016667\n",
       "2022-08-24          153.433333\n",
       "2022-08-25          149.383333\n",
       "2022-08-26          141.583333\n",
       "2022-08-27           85.650000\n",
       "2022-08-28          158.416667\n",
       "2022-08-29          141.450000\n",
       "2022-08-30          128.566667\n",
       "2022-08-31          150.783333\n",
       "2022-09-01          161.366667\n",
       "2022-09-02          136.150000\n",
       "2022-09-03           86.066667\n",
       "2022-09-04          141.983333\n",
       "2022-09-05          166.083333\n",
       "2022-09-06          165.383333\n",
       "2022-09-07          198.516667\n",
       "2022-09-08          143.450000\n",
       "2022-09-09          151.983333\n",
       "2022-09-10           85.350000\n",
       "2022-09-11          172.350000\n",
       "2022-09-12          143.800000\n",
       "2022-09-13          125.500000\n",
       "2022-09-14          134.200000\n",
       "2022-09-15          144.866667\n",
       "2022-09-16          178.933333\n",
       "2022-09-17           81.666667\n",
       "2022-09-18          134.333333\n",
       "2022-09-19          139.966667\n",
       "2022-09-20          151.250000\n",
       "2022-09-21          203.383333\n",
       "2022-09-22          151.683333\n",
       "2022-09-23          153.833333\n",
       "2022-09-24           82.700000\n",
       "2022-09-25          150.250000\n",
       "2022-09-26          139.866667\n",
       "2022-09-27          164.150000\n",
       "2022-09-28          148.466667\n",
       "2022-09-29          134.350000\n",
       "2022-09-30          160.633333\n",
       "2022-10-01           82.550000\n",
       "2022-10-02          161.083333\n",
       "2022-10-03          147.116667\n",
       "2022-10-04          140.083333\n",
       "2022-10-05          145.816667\n",
       "2022-10-06          145.333333\n",
       "2022-10-07          118.866667\n",
       "2022-10-08           96.866667\n",
       "2022-10-09          147.583333\n",
       "2022-10-10          137.333333\n",
       "2022-10-11          145.066667\n",
       "2022-10-12          156.050000\n",
       "2022-10-13          153.116667\n",
       "2022-10-14          125.966667\n",
       "2022-10-15           76.333333\n",
       "2022-10-16          139.816667\n",
       "2022-10-17          115.783333\n",
       "2022-10-18          146.166667\n",
       "2022-10-19          116.050000\n",
       "2022-10-20          129.150000\n",
       "2022-10-21          143.700000\n",
       "2022-10-22           76.216667\n",
       "2022-10-23          137.383333\n",
       "2022-10-24          132.816667\n",
       "2022-10-25          121.533333\n",
       "2022-10-26          129.166667\n",
       "2022-10-27          112.250000\n",
       "2022-10-28          138.883333\n",
       "2022-10-29           82.466667\n",
       "2022-10-30          141.300000\n",
       "2022-10-31          131.616667\n",
       "2022-11-01          133.933333\n",
       "2022-11-02          123.766667\n",
       "2022-11-03          125.200000\n",
       "2022-11-04           90.116667\n",
       "2022-11-05           79.800000\n",
       "2022-11-06          123.916667\n",
       "2022-11-07          133.666667\n",
       "2022-11-08          123.333333\n",
       "2022-11-09          143.883333\n",
       "2022-11-10          120.200000\n",
       "2022-11-11          129.050000\n",
       "2022-11-12           74.500000\n",
       "2022-11-13          126.516667\n",
       "2022-11-14          115.616667\n",
       "2022-11-15          137.183333\n",
       "2022-11-16          157.016667\n",
       "2022-11-17          143.066667\n",
       "2022-11-18          130.616667\n",
       "2022-11-19           82.783333\n",
       "2022-11-20          126.316667\n",
       "2022-11-21          125.566667\n",
       "2022-11-22          133.316667\n",
       "2022-11-23          136.483333\n",
       "2022-11-24          130.633333\n",
       "2022-11-25          130.200000\n",
       "2022-11-26           77.250000\n",
       "2022-11-27          139.116667\n",
       "2022-11-28          124.683333\n",
       "2022-11-29          116.250000\n",
       "2022-11-30          145.916667\n",
       "2022-12-01          144.233333\n",
       "2022-12-02          157.016667\n",
       "2022-12-03           86.016667\n",
       "2022-12-04          135.183333\n",
       "2022-12-05          139.516667\n",
       "2022-12-06          124.183333\n",
       "2022-12-07          141.050000\n",
       "2022-12-08          126.916667\n",
       "2022-12-09          146.116667\n",
       "2022-12-10           76.183333\n",
       "2022-12-11          136.033333\n",
       "2022-12-12          116.716667\n",
       "2022-12-13          114.033333\n",
       "2022-12-14          112.783333\n",
       "2022-12-15          145.916667\n",
       "2022-12-16          129.200000\n",
       "2022-12-17           79.183333\n",
       "2022-12-18          125.500000\n",
       "2022-12-19          125.416667\n",
       "2022-12-20          126.433333\n",
       "2022-12-21          131.550000\n",
       "2022-12-22          151.783333\n",
       "2022-12-23          132.733333\n",
       "2022-12-24           74.216667\n",
       "2022-12-25          134.283333\n",
       "2022-12-26          117.916667\n",
       "2022-12-27          130.183333\n",
       "2022-12-28          126.750000\n",
       "2022-12-29          138.000000\n",
       "2022-12-30          140.233333\n",
       "2022-12-31           70.250000\n",
       "2023-01-01           72.466667\n",
       "2023-01-02           79.200000\n",
       "2023-01-03           69.366667\n",
       "2023-01-04           69.000000\n",
       "2023-01-05           70.083333\n",
       "2023-01-06           68.016667\n",
       "2023-01-07           71.000000\n",
       "2023-01-08           53.300000\n",
       "2023-01-09          114.783333\n",
       "2023-01-10          101.900000\n",
       "2023-01-11          127.616667\n",
       "2023-01-12          136.766667\n",
       "2023-01-13          136.000000\n",
       "2023-01-14           75.366667\n",
       "2023-01-15          171.083333\n",
       "2023-01-16          118.316667\n",
       "2023-01-17          132.600000\n",
       "2023-01-18          142.450000\n",
       "2023-01-19          124.500000\n",
       "2023-01-20          141.250000\n",
       "2023-01-21           78.533333\n",
       "2023-01-22          180.466667\n",
       "2023-01-23          124.466667\n",
       "2023-01-24          138.500000\n",
       "2023-01-25          161.383333\n",
       "2023-01-26          126.366667\n",
       "2023-01-27          137.466667"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate total new duration per day\n",
    "news_duration = df.groupby('dat')[['video_duration_min']].sum()\n",
    "pd.set_option('display.max_rows', None)\n",
    "news_duration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "11de51d2",
   "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>video_duration_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>757.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>121.140555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>40.189596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>12.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>104.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>121.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>140.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>388.633333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       video_duration_min\n",
       "count          757.000000\n",
       "mean           121.140555\n",
       "std             40.189596\n",
       "min             12.950000\n",
       "25%            104.366667\n",
       "50%            121.833333\n",
       "75%            140.200000\n",
       "max            388.633333"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "news_duration.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "82dc0b16",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate an exponential moving average\n",
    "news_duration['EMA'] = news_duration['video_duration_min'].ewm(alpha=0.15).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "db57c94b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw timeseries of daily news duration\n",
    "\n",
    "plt.figure(figsize=(8, 3))\n",
    "plt.plot(news_duration.index, news_duration['video_duration_min'], \n",
    "         c=color_1, label='total duration')\n",
    "plt.plot(news_duration.index, news_duration['EMA'], \n",
    "         c=color_2, label='exponential moving average')\n",
    "\n",
    "# Label start of special military operation\n",
    "plt.annotate('2022-02-24,\\n start of the special\\nmilitary operation', \n",
    "             xy=(0.55, 0.84), xycoords='axes fraction', weight='bold',\n",
    "             xytext=(0.43, 0.6), textcoords='axes fraction',\n",
    "             fontsize=8, color=color_4, horizontalalignment='center',\n",
    "             arrowprops=dict(arrowstyle='->, head_width=0.2', \n",
    "                             color=color_4, linewidth=0.8))\n",
    "\n",
    "# Label Victory day\n",
    "plt.annotate('2022-05-09,\\n Victory day (over\\nNazi Germany)', \n",
    "             xy=(0.65, 0.92), xycoords='axes fraction', weight='bold',\n",
    "             xytext=(0.8, 0.8), textcoords='axes fraction',\n",
    "             fontsize=8, color=color_4, horizontalalignment='center',\n",
    "             arrowprops=dict(arrowstyle='->, head_width=0.2', \n",
    "                             color=color_4, linewidth=0.8))\n",
    "\n",
    "plt.title('Daily Total Duration of News Releases, mins')\n",
    "plt.xticks(rotation=30, size=9)\n",
    "plt.yticks(size=10)\n",
    "plt.legend(frameon=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c88763f",
   "metadata": {},
   "source": [
    "### Cyclicity\n",
    "Based on the picture, it appears that the duration of daily news follows a cyclical pattern, which could differ by the day of the week. To better understand this cyclicity, creating boxplots for each day of the week would be useful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a343a809",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_boxplot(df, plot_dim, fig_size):\n",
    "    \"\"\"\n",
    "    Plot boxplots of duration for days of week\n",
    "    Args: df - dataframe; For its columns, a probability density will be drawn;\n",
    "          plot_dim - tuple, dimension of the plot\n",
    "          fig_size - tuple, figure size\n",
    "    \"\"\"\n",
    "    \n",
    "    plt.figure(figsize=fig_size)\n",
    "    plots_quantity = plot_dim[0] * plot_dim[1]\n",
    "    \n",
    "    # Add a day of week\n",
    "    df['day_of_week'] = df.index.dayofweek\n",
    "    \n",
    "    dic = {0: 'Monday', 1: 'Tuesday', 2: 'Wednesday',\n",
    "           3: 'Thursday', 4: 'Friday', 5: 'Saturday',\n",
    "           6: 'Sunday'}\n",
    "    \n",
    "    data = []\n",
    "    \n",
    "    for plot_indx in range(plots_quantity):\n",
    "        data.append(df.loc[df['day_of_week']==plot_indx, 'video_duration_min'])\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=fig_size)\n",
    "    \n",
    "    ax.set_title('Total Duration of News Releases by Day of Week, minutes', size=11)\n",
    "       \n",
    "    ax.boxplot(data, boxprops=dict(color=color_1), \n",
    "               capprops=dict(color=color_1), \n",
    "               whiskerprops=dict(color=color_1),\n",
    "               flierprops=dict(color=color_1, markeredgecolor=color_1))   \n",
    "    plt.xticks([1, 2, 3, 4, 5, 6, 7], dic.values())\n",
    "    plt.xticks(rotation=30, size=9)\n",
    "    plt.yticks(size=10)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ba2daeb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x250 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplot(news_duration, (1,7), (8,2.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f4366542",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x250 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Total duration of news releases by day of week before CMO\n",
    "duration_before_CMO = df[df['before_after_CMO']=='before CMO'].groupby('dat')[['video_duration_min']].sum()\n",
    "plot_boxplot(duration_before_CMO, (1,7), (8,2.5))\n",
    "plt.title('Total Duration of News Releases by Day of Week, before CMO, min');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2495a3a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x250 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Total duration of news releases by day of week after CMO\n",
    "duration_after_CMO = df[df['before_after_CMO']=='after CMO'].groupby('dat')[['video_duration_min']].sum()\n",
    "plot_boxplot(duration_after_CMO, (1,7), (8,2.5))\n",
    "plt.title('Total Duration of News Releases by Day of Week, after CMO, min');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47ab614e",
   "metadata": {},
   "source": [
    "### Comparison of news duration before and after commencement of special military operation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "809e2cac",
   "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>video_duration_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>409.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>105.941361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>31.038865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>12.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>89.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>115.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>122.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>259.816667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       video_duration_min\n",
       "count          409.000000\n",
       "mean           105.941361\n",
       "std             31.038865\n",
       "min             12.950000\n",
       "25%             89.416667\n",
       "50%            115.850000\n",
       "75%            122.816667\n",
       "max            259.816667"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration_before_CMO[['video_duration_min']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "94ed4e22",
   "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>video_duration_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>141.955079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>39.256238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>53.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>125.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>140.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>157.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>388.633333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       video_duration_min\n",
       "count          338.000000\n",
       "mean           141.955079\n",
       "std             39.256238\n",
       "min             53.300000\n",
       "25%            125.200000\n",
       "50%            140.416667\n",
       "75%            157.950000\n",
       "max            388.633333"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration_after_CMO[['video_duration_min']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82904c04",
   "metadata": {},
   "source": [
    "The tables above reveal that the median daily news duration is higher by 25 minutes following the initiation of the special military operation compared to prior to it. It is interesting to compare the distribution of daily news duration before and after the start of the special operation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2d974f69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ridgeline plot\n",
    "fig, ax = plt.subplots(2, 1, figsize=(8,3), sharex=True)\n",
    "duration_before_CMO['video_duration_min'].hist(ax=ax[0], density = True, bins='auto', \n",
    "                        color = color_1, histtype=\"bar\")\n",
    "duration_after_CMO['video_duration_min'].hist(ax=ax[1], density = True, bins='auto', \n",
    "                         color = color_1, histtype=\"bar\")\n",
    "ax[0].grid(False)\n",
    "ax[1].grid(False)\n",
    "plt.suptitle('Distributions of total daily news duration prior to and following SMO', fontsize=13, weight='bold')\n",
    "ax[0].set_ylabel('Before special\\nmilitary operation', rotation=0, fontsize=11,\n",
    "                 labelpad=55, va='center', weight='bold')\n",
    "ax[1].set_ylabel('After special\\nmilitary operation', rotation=0, fontsize=11,\n",
    "                 labelpad=55, va='center', weight='bold')\n",
    "plt.xlabel('Total daily news duration, minutes')\n",
    "# Remove ticks\n",
    "ax[0].set_yticks([], [])\n",
    "ax[1].set_yticks([], []);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490ce57b",
   "metadata": {},
   "source": [
    "### Newscasts analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e96be75d",
   "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>id_in_source_file</th>\n",
       "      <th>date</th>\n",
       "      <th>tags_top</th>\n",
       "      <th>title</th>\n",
       "      <th>url</th>\n",
       "      <th>body</th>\n",
       "      <th>tags_bottom</th>\n",
       "      <th>video_duration_seconds</th>\n",
       "      <th>file_key</th>\n",
       "      <th>datetime</th>\n",
       "      <th>dat</th>\n",
       "      <th>year</th>\n",
       "      <th>year_month</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>whole newscast</th>\n",
       "      <th>body_token_final</th>\n",
       "      <th>title_token_final</th>\n",
       "      <th>video_duration_min</th>\n",
       "      <th>before_after_CMO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>2023-01-27 21:45:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Выпуск программы «Время» в 21:00 от 27.01.2023</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446104-vypu...</td>\n",
       "      <td>Смотрите в этом выпуске: 79 лет назад была пол...</td>\n",
       "      <td>Общество</td>\n",
       "      <td>2422.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 21:45:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>['смотреть', 'выпуск', '79', 'год', 'полностью...</td>\n",
       "      <td>['выпуск', 'программа', 'время', '21:00', '27....</td>\n",
       "      <td>40.366667</td>\n",
       "      <td>after CMO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>35</td>\n",
       "      <td>2023-01-27 18:45:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Выпуск новостей в 18:00 от 27.01.2023</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446090-vypu...</td>\n",
       "      <td>Смотрите в этом выпуске: сегодня 79 лет со дня...</td>\n",
       "      <td>Общество</td>\n",
       "      <td>2391.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 18:45:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>['смотреть', 'выпуск', 'сегодня', '79', 'год',...</td>\n",
       "      <td>['выпуск', 'новость', '18:00', '27.01.2023']</td>\n",
       "      <td>39.850000</td>\n",
       "      <td>after CMO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>51</td>\n",
       "      <td>2023-01-27 15:15:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Выпуск новостей в 15:00 от 27.01.2023</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446082-vypu...</td>\n",
       "      <td>Смотрите в этом выпуске: память, которая навсе...</td>\n",
       "      <td>Общество</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 15:15:00</td>\n",
       "      <td>2023-01-27</td>\n",
       "      <td>2023</td>\n",
       "      <td>2023-01</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>['смотреть', 'выпуск', 'память', 'навсегда', '...</td>\n",
       "      <td>['выпуск', 'новость', '15:00', '27.01.2023']</td>\n",
       "      <td>16.766667</td>\n",
       "      <td>after CMO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id_in_source_file                 date  tags_top  \\\n",
       "0                  15  2023-01-27 21:45:00  Общество   \n",
       "16                 35  2023-01-27 18:45:00  Общество   \n",
       "30                 51  2023-01-27 15:15:00  Общество   \n",
       "\n",
       "                                             title  \\\n",
       "0   Выпуск программы «Время» в 21:00 от 27.01.2023   \n",
       "16           Выпуск новостей в 18:00 от 27.01.2023   \n",
       "30           Выпуск новостей в 15:00 от 27.01.2023   \n",
       "\n",
       "                                                  url  \\\n",
       "0   https://www.1tv.ru/news/2023-01-27/446104-vypu...   \n",
       "16  https://www.1tv.ru/news/2023-01-27/446090-vypu...   \n",
       "30  https://www.1tv.ru/news/2023-01-27/446082-vypu...   \n",
       "\n",
       "                                                 body tags_bottom  \\\n",
       "0   Смотрите в этом выпуске: 79 лет назад была пол...    Общество   \n",
       "16  Смотрите в этом выпуске: сегодня 79 лет со дня...    Общество   \n",
       "30  Смотрите в этом выпуске: память, которая навсе...    Общество   \n",
       "\n",
       "    video_duration_seconds file_key             datetime        dat  year  \\\n",
       "0                   2422.0     0-15  2023-01-27 21:45:00 2023-01-27  2023   \n",
       "16                  2391.0     0-15  2023-01-27 18:45:00 2023-01-27  2023   \n",
       "30                  1006.0     0-15  2023-01-27 15:15:00 2023-01-27  2023   \n",
       "\n",
       "   year_month  hour  weekday  whole newscast  \\\n",
       "0     2023-01    21        4            True   \n",
       "16    2023-01    18        4            True   \n",
       "30    2023-01    15        4            True   \n",
       "\n",
       "                                     body_token_final  \\\n",
       "0   ['смотреть', 'выпуск', '79', 'год', 'полностью...   \n",
       "16  ['смотреть', 'выпуск', 'сегодня', '79', 'год',...   \n",
       "30  ['смотреть', 'выпуск', 'память', 'навсегда', '...   \n",
       "\n",
       "                                    title_token_final  video_duration_min  \\\n",
       "0   ['выпуск', 'программа', 'время', '21:00', '27....           40.366667   \n",
       "16       ['выпуск', 'новость', '18:00', '27.01.2023']           39.850000   \n",
       "30       ['выпуск', 'новость', '15:00', '27.01.2023']           16.766667   \n",
       "\n",
       "   before_after_CMO  \n",
       "0         after CMO  \n",
       "16        after CMO  \n",
       "30        after CMO  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dataframe that contains only newscasts, not individual news stories\n",
    "pd.reset_option('display.max_rows')\n",
    "newscast.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1d6c07e8",
   "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>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>409.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.977995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.433837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            title\n",
       "count  409.000000\n",
       "mean     4.977995\n",
       "std      1.433837\n",
       "min      1.000000\n",
       "25%      3.000000\n",
       "50%      6.000000\n",
       "75%      6.000000\n",
       "max      8.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Newscasts before special military operation\n",
    "newscast_before = newscast[newscast['before_after_CMO']=='before CMO']\n",
    "newscast_before_count = newscast_before.groupby(['dat'])[['title']].count()\n",
    "newscast_before_count.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "223de12a",
   "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>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.710059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.181379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>14.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            title\n",
       "count  338.000000\n",
       "mean     6.710059\n",
       "std      2.181379\n",
       "min      3.000000\n",
       "25%      5.000000\n",
       "50%      7.000000\n",
       "75%      7.000000\n",
       "max     14.000000"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Newscasts after special military operation\n",
    "newscast_after = newscast[newscast['before_after_CMO']=='after CMO']\n",
    "newscast_after_count = newscast_after.groupby(['dat'])[['title']].count()\n",
    "newscast_after_count.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9159cbcf",
   "metadata": {},
   "source": [
    "Based on the tables above, we can observe that the median number of newscasts before the special military operation was 6, while after the operation, it is 7. This suggests that, on average, the number of newscasts increased by 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "26fd5ccc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hour\n",
       "7     270\n",
       "8       3\n",
       "9     273\n",
       "10    132\n",
       "11      2\n",
       "12    394\n",
       "13      4\n",
       "14      1\n",
       "15    273\n",
       "16      1\n",
       "18    270\n",
       "19      6\n",
       "21    338\n",
       "22     69\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newscast_before.groupby('hour')['title'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ed77ba0",
   "metadata": {},
   "source": [
    "The primary times for news broadcasting before the special military operation were 7am, 9am, 12pm, 3pm, 6pm, and 9pm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9c030c2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hour\n",
       "7      72\n",
       "9     229\n",
       "10    114\n",
       "11     34\n",
       "12    338\n",
       "13    225\n",
       "14    232\n",
       "15    280\n",
       "16     14\n",
       "17     32\n",
       "18    315\n",
       "19     16\n",
       "20     30\n",
       "21    208\n",
       "22    100\n",
       "23     29\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newscast_after.groupby('hour')['title'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca51d808",
   "metadata": {},
   "source": [
    "Following the special military operation, the primary times for news broadcasting are 9am, 12pm, 1pm, 2pm, 3pm, 6pm, and 9pm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2a06d254",
   "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>video_duration_min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hour</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>25.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15.308333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>39.425000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>34.741667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      video_duration_min\n",
       "hour                    \n",
       "7               5.950000\n",
       "9              25.050000\n",
       "12             15.308333\n",
       "15             15.016667\n",
       "18             39.425000\n",
       "21             34.741667"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "before_prime_time = [7, 9, 12, 15, 18, 21]\n",
    "newscast_before_h = newscast_before.groupby(['dat', 'hour'])[['video_duration_min']].sum()\n",
    "newscast_before_h.reset_index(inplace=True)\n",
    "newscast_before_h[newscast_before_h['hour'].isin(before_prime_time)].groupby('hour').median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "312cd005",
   "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>video_duration_min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hour</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>21.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>15.533333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15.775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>24.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>44.416667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      video_duration_min\n",
       "hour                    \n",
       "9              21.750000\n",
       "12             15.533333\n",
       "13             15.533333\n",
       "14             15.250000\n",
       "15             15.775000\n",
       "18             24.200000\n",
       "21             44.416667"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "after_prime_time = [9, 12, 13, 14, 15, 18, 21]\n",
    "newscast_after_h = newscast_after.groupby(['dat', 'hour'])[['video_duration_min']].sum()\n",
    "newscast_after_h.reset_index(inplace=True)\n",
    "newscast_after_h[newscast_after_h['hour'].isin(after_prime_time)].groupby('hour').median()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48660643",
   "metadata": {},
   "source": [
    "It appears that the First channel implemented the following changes after the start of the special military operation: 1) added one newscast, 2) extended the 9pm newscast, which is accessible to working citizens, and 3) shortened the 6pm newscast, which is not accessible to working citizens (as the workday in Russia typically ends at 6pm)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb169642",
   "metadata": {},
   "source": [
    "## Frequency of news stories about heroes of special military operation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a53f7224",
   "metadata": {},
   "source": [
    "### Marking the rows of interest with the tag 'Special military operation' and phrases about bravery and heroism"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fa06deca",
   "metadata": {},
   "outputs": [],
   "source": [
    " words_to_find = [\n",
    "     'героизм', 'геройств', 'героич', \n",
    "     'герой', 'героя', 'герою', 'герои', 'героев', 'героем', 'героям',\n",
    "     'доблест', 'самопожертвован', 'самоотвержен',\n",
    "     'храбр', 'неустрашим', \n",
    "     'мужеств', 'отваг', 'отваж',\n",
    "     'смелост', 'смелы', 'смело', 'смелая', 'смельчак',\n",
    "     'подвиг', 'наград', 'орден']\n",
    "    \n",
    "token_dict = {'body_token_final':  words_to_find,\n",
    "              'title_token_final':  words_to_find}                  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "f261ac2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find news stories about heroes and heroism\n",
    "df = find_tokens(df, token_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8bcea71e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find news about Special Military Operation\n",
    "df['SMO'] = df['tags_bottom'].str.contains('Специальная военная операция|Вооруженные силы')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "90b5e5d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find news about heroes of Special Military Operation\n",
    "df['heroes_of_SMO'] = df['SMO'] * df['contain_token']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "60694767",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_SMO = df[(df['SMO']==1)&(df['dat']>=pd.to_datetime('2022-02-24'))]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdea803f",
   "metadata": {},
   "source": [
    "### What is the frequency of news coverage on the First channel regarding heroes of special military operations?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1d069bb7",
   "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>id_in_source_file</th>\n",
       "      <th>date</th>\n",
       "      <th>tags_top</th>\n",
       "      <th>title</th>\n",
       "      <th>url</th>\n",
       "      <th>body</th>\n",
       "      <th>tags_bottom</th>\n",
       "      <th>video_duration_seconds</th>\n",
       "      <th>file_key</th>\n",
       "      <th>datetime</th>\n",
       "      <th>...</th>\n",
       "      <th>whole newscast</th>\n",
       "      <th>body_token_final</th>\n",
       "      <th>title_token_final</th>\n",
       "      <th>video_duration_min</th>\n",
       "      <th>before_after_CMO</th>\n",
       "      <th>body_token_final_contain</th>\n",
       "      <th>title_token_final_contain</th>\n",
       "      <th>contain_token</th>\n",
       "      <th>SMO</th>\n",
       "      <th>heroes_of_SMO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>40</td>\n",
       "      <td>2023-01-27 21:19:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Минобороны РФ сообщило новые имена героев — уч...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446114-mino...</td>\n",
       "      <td>И еще о стойкости наших героев. Ефрейтор Матве...</td>\n",
       "      <td>Общество,Вооруженные силы</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 21:19:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['стойкость', 'герой', 'ефрейтор', 'матвей', '...</td>\n",
       "      <td>['минобороны', 'рф', 'сообщить', 'новый', 'имя...</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>28</td>\n",
       "      <td>2023-01-27 18:20:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>Российские военные действуют доблестно и отваж...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-27/446095-ross...</td>\n",
       "      <td>Ефрейтор Матвей Орлов, командир боевой машины,...</td>\n",
       "      <td>Общество,Вооруженные силы</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-27 18:20:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['ефрейтор', 'матвей', 'орлов', 'командир', 'б...</td>\n",
       "      <td>['российский', 'военный', 'действовать', 'добл...</td>\n",
       "      <td>0.566667</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>95</td>\n",
       "      <td>2023-01-26 21:13:00</td>\n",
       "      <td>Общество</td>\n",
       "      <td>О новых подвигах участников спецоперации расск...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-26/446049-o_no...</td>\n",
       "      <td>И еще о наших защитниках.Группа гвардии старше...</td>\n",
       "      <td>Общество,Вооруженные силы</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-26 21:13:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['защитниках', 'группа', 'гвардия', 'старший',...</td>\n",
       "      <td>['новый', 'подвиг', 'участник', 'спецоперация'...</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>132</td>\n",
       "      <td>2023-01-26 12:04:00</td>\n",
       "      <td>В мире</td>\n",
       "      <td>Российские военные в зоне спецоперации действу...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-26/445993-ross...</td>\n",
       "      <td>Группа гвардии старшего лейтенанта Амира Шахба...</td>\n",
       "      <td>В мире,Специальная военная операция на Украине</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-26 12:04:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['группа', 'гвардия', 'старший', 'лейтенант', ...</td>\n",
       "      <td>['российский', 'военный', 'зона', 'спецопераци...</td>\n",
       "      <td>0.633333</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>159</td>\n",
       "      <td>2023-01-25 21:38:00</td>\n",
       "      <td>Политика,Общество</td>\n",
       "      <td>Глава Подмосковья встретился со школьниками, к...</td>\n",
       "      <td>https://www.1tv.ru/news/2023-01-25/445973-glav...</td>\n",
       "      <td>Поддержка семей военнослужащих. Социальные про...</td>\n",
       "      <td>Политика,Общество,Регионы,Специальная военная ...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0-15</td>\n",
       "      <td>2023-01-25 21:38:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['поддержка', 'семья', 'военнослужащий', 'соци...</td>\n",
       "      <td>['глава', 'подмосковье', 'встретиться', 'школь...</td>\n",
       "      <td>1.166667</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23245</th>\n",
       "      <td>7887</td>\n",
       "      <td>2022-02-26 12:00:00</td>\n",
       "      <td>В мире</td>\n",
       "      <td>Более 80 украинских военнослужащих, сложивших ...</td>\n",
       "      <td>https://www.1tv.ru/news/2022-02-26/421880-bole...</td>\n",
       "      <td>82 украинских военнослужащих, добровольно слож...</td>\n",
       "      <td>В мире,Конфликты,Специальная военная операция ...</td>\n",
       "      <td>225.0</td>\n",
       "      <td>15-30</td>\n",
       "      <td>2022-02-26 12:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['82', 'украинских', 'военнослужащий', 'добров...</td>\n",
       "      <td>['80', 'украинских', 'военнослужащий', 'сложив...</td>\n",
       "      <td>3.750000</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23252</th>\n",
       "      <td>7880</td>\n",
       "      <td>2022-02-26 10:02:00</td>\n",
       "      <td>В мире</td>\n",
       "      <td>В Севастополь с острова Змеиный доставили укра...</td>\n",
       "      <td>https://www.1tv.ru/news/2022-02-26/421873-v_se...</td>\n",
       "      <td>В числе украинских военнослужащих те самые пог...</td>\n",
       "      <td>В мире,Конфликты,Специальная военная операция ...</td>\n",
       "      <td>182.0</td>\n",
       "      <td>15-30</td>\n",
       "      <td>2022-02-26 10:02:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['число', 'украинских', 'военнослужащий', 'сам...</td>\n",
       "      <td>['севастополь', 'остров', 'змеиный', 'доставит...</td>\n",
       "      <td>3.033333</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23282</th>\n",
       "      <td>7909</td>\n",
       "      <td>2022-02-25 21:03:00</td>\n",
       "      <td>Политика,В мире</td>\n",
       "      <td>Взять власть в свои руки призвал украинских во...</td>\n",
       "      <td>https://www.1tv.ru/news/2022-02-25/421838-vzya...</td>\n",
       "      <td>Бандеровцы и неонацисты действуют террористиче...</td>\n",
       "      <td>Политика,В мире,Специальная военная операция н...</td>\n",
       "      <td>170.0</td>\n",
       "      <td>15-30</td>\n",
       "      <td>2022-02-25 21:03:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['бандеровец', 'неонацист', 'действовать', 'те...</td>\n",
       "      <td>['взять', 'власть', 'рука', 'призвать', 'украи...</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23288</th>\n",
       "      <td>14632</td>\n",
       "      <td>2022-02-25 19:56:00</td>\n",
       "      <td>Политика,В мире</td>\n",
       "      <td>Президент сделал заявление по поводу спецопера...</td>\n",
       "      <td>https://www.1tv.ru/news/2022-02-25/421832-prez...</td>\n",
       "      <td>Бандеровцы и неонацисты прячут тяжелое вооруже...</td>\n",
       "      <td>В мире,Конфликты,Специальная военная операция ...</td>\n",
       "      <td>176.0</td>\n",
       "      <td>15-30</td>\n",
       "      <td>2022-02-25 19:56:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['бандеровец', 'неонацист', 'прятать', 'тяжёлы...</td>\n",
       "      <td>['президент', 'сделать', 'заявление', 'повод',...</td>\n",
       "      <td>2.933333</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23307</th>\n",
       "      <td>7940</td>\n",
       "      <td>2022-02-25 18:03:00</td>\n",
       "      <td>Политика,В мире</td>\n",
       "      <td>Владимир Путин сделал заявление по ситуации во...</td>\n",
       "      <td>https://www.1tv.ru/news/2022-02-25/421813-vlad...</td>\n",
       "      <td>Вначале заявление Владимира Путина по ситуации...</td>\n",
       "      <td>Политика,В мире,Специальная военная операция н...</td>\n",
       "      <td>154.0</td>\n",
       "      <td>15-30</td>\n",
       "      <td>2022-02-25 18:03:00</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>['заявление', 'владимир', 'путин', 'ситуация',...</td>\n",
       "      <td>['владимир', 'путин', 'сделать', 'заявление', ...</td>\n",
       "      <td>2.566667</td>\n",
       "      <td>after CMO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1549 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id_in_source_file                 date           tags_top  \\\n",
       "11                    40  2023-01-27 21:19:00           Общество   \n",
       "24                    28  2023-01-27 18:20:00           Общество   \n",
       "76                    95  2023-01-26 21:13:00           Общество   \n",
       "116                  132  2023-01-26 12:04:00             В мире   \n",
       "137                  159  2023-01-25 21:38:00  Политика,Общество   \n",
       "...                  ...                  ...                ...   \n",
       "23245               7887  2022-02-26 12:00:00             В мире   \n",
       "23252               7880  2022-02-26 10:02:00             В мире   \n",
       "23282               7909  2022-02-25 21:03:00    Политика,В мире   \n",
       "23288              14632  2022-02-25 19:56:00    Политика,В мире   \n",
       "23307               7940  2022-02-25 18:03:00    Политика,В мире   \n",
       "\n",
       "                                                   title  \\\n",
       "11     Минобороны РФ сообщило новые имена героев — уч...   \n",
       "24     Российские военные действуют доблестно и отваж...   \n",
       "76     О новых подвигах участников спецоперации расск...   \n",
       "116    Российские военные в зоне спецоперации действу...   \n",
       "137    Глава Подмосковья встретился со школьниками, к...   \n",
       "...                                                  ...   \n",
       "23245  Более 80 украинских военнослужащих, сложивших ...   \n",
       "23252  В Севастополь с острова Змеиный доставили укра...   \n",
       "23282  Взять власть в свои руки призвал украинских во...   \n",
       "23288  Президент сделал заявление по поводу спецопера...   \n",
       "23307  Владимир Путин сделал заявление по ситуации во...   \n",
       "\n",
       "                                                     url  \\\n",
       "11     https://www.1tv.ru/news/2023-01-27/446114-mino...   \n",
       "24     https://www.1tv.ru/news/2023-01-27/446095-ross...   \n",
       "76     https://www.1tv.ru/news/2023-01-26/446049-o_no...   \n",
       "116    https://www.1tv.ru/news/2023-01-26/445993-ross...   \n",
       "137    https://www.1tv.ru/news/2023-01-25/445973-glav...   \n",
       "...                                                  ...   \n",
       "23245  https://www.1tv.ru/news/2022-02-26/421880-bole...   \n",
       "23252  https://www.1tv.ru/news/2022-02-26/421873-v_se...   \n",
       "23282  https://www.1tv.ru/news/2022-02-25/421838-vzya...   \n",
       "23288  https://www.1tv.ru/news/2022-02-25/421832-prez...   \n",
       "23307  https://www.1tv.ru/news/2022-02-25/421813-vlad...   \n",
       "\n",
       "                                                    body  \\\n",
       "11     И еще о стойкости наших героев. Ефрейтор Матве...   \n",
       "24     Ефрейтор Матвей Орлов, командир боевой машины,...   \n",
       "76     И еще о наших защитниках.Группа гвардии старше...   \n",
       "116    Группа гвардии старшего лейтенанта Амира Шахба...   \n",
       "137    Поддержка семей военнослужащих. Социальные про...   \n",
       "...                                                  ...   \n",
       "23245  82 украинских военнослужащих, добровольно слож...   \n",
       "23252  В числе украинских военнослужащих те самые пог...   \n",
       "23282  Бандеровцы и неонацисты действуют террористиче...   \n",
       "23288  Бандеровцы и неонацисты прячут тяжелое вооруже...   \n",
       "23307  Вначале заявление Владимира Путина по ситуации...   \n",
       "\n",
       "                                             tags_bottom  \\\n",
       "11                             Общество,Вооруженные силы   \n",
       "24                             Общество,Вооруженные силы   \n",
       "76                             Общество,Вооруженные силы   \n",
       "116       В мире,Специальная военная операция на Украине   \n",
       "137    Политика,Общество,Регионы,Специальная военная ...   \n",
       "...                                                  ...   \n",
       "23245  В мире,Конфликты,Специальная военная операция ...   \n",
       "23252  В мире,Конфликты,Специальная военная операция ...   \n",
       "23282  Политика,В мире,Специальная военная операция н...   \n",
       "23288  В мире,Конфликты,Специальная военная операция ...   \n",
       "23307  Политика,В мире,Специальная военная операция н...   \n",
       "\n",
       "       video_duration_seconds file_key             datetime  ...  \\\n",
       "11                       25.0     0-15  2023-01-27 21:19:00  ...   \n",
       "24                       34.0     0-15  2023-01-27 18:20:00  ...   \n",
       "76                       27.0     0-15  2023-01-26 21:13:00  ...   \n",
       "116                      38.0     0-15  2023-01-26 12:04:00  ...   \n",
       "137                      70.0     0-15  2023-01-25 21:38:00  ...   \n",
       "...                       ...      ...                  ...  ...   \n",
       "23245                   225.0    15-30  2022-02-26 12:00:00  ...   \n",
       "23252                   182.0    15-30  2022-02-26 10:02:00  ...   \n",
       "23282                   170.0    15-30  2022-02-25 21:03:00  ...   \n",
       "23288                   176.0    15-30  2022-02-25 19:56:00  ...   \n",
       "23307                   154.0    15-30  2022-02-25 18:03:00  ...   \n",
       "\n",
       "      whole newscast                                   body_token_final  \\\n",
       "11             False  ['стойкость', 'герой', 'ефрейтор', 'матвей', '...   \n",
       "24             False  ['ефрейтор', 'матвей', 'орлов', 'командир', 'б...   \n",
       "76             False  ['защитниках', 'группа', 'гвардия', 'старший',...   \n",
       "116            False  ['группа', 'гвардия', 'старший', 'лейтенант', ...   \n",
       "137            False  ['поддержка', 'семья', 'военнослужащий', 'соци...   \n",
       "...              ...                                                ...   \n",
       "23245          False  ['82', 'украинских', 'военнослужащий', 'добров...   \n",
       "23252          False  ['число', 'украинских', 'военнослужащий', 'сам...   \n",
       "23282          False  ['бандеровец', 'неонацист', 'действовать', 'те...   \n",
       "23288          False  ['бандеровец', 'неонацист', 'прятать', 'тяжёлы...   \n",
       "23307          False  ['заявление', 'владимир', 'путин', 'ситуация',...   \n",
       "\n",
       "                                       title_token_final  video_duration_min  \\\n",
       "11     ['минобороны', 'рф', 'сообщить', 'новый', 'имя...            0.416667   \n",
       "24     ['российский', 'военный', 'действовать', 'добл...            0.566667   \n",
       "76     ['новый', 'подвиг', 'участник', 'спецоперация'...            0.450000   \n",
       "116    ['российский', 'военный', 'зона', 'спецопераци...            0.633333   \n",
       "137    ['глава', 'подмосковье', 'встретиться', 'школь...            1.166667   \n",
       "...                                                  ...                 ...   \n",
       "23245  ['80', 'украинских', 'военнослужащий', 'сложив...            3.750000   \n",
       "23252  ['севастополь', 'остров', 'змеиный', 'доставит...            3.033333   \n",
       "23282  ['взять', 'власть', 'рука', 'призвать', 'украи...            2.833333   \n",
       "23288  ['президент', 'сделать', 'заявление', 'повод',...            2.933333   \n",
       "23307  ['владимир', 'путин', 'сделать', 'заявление', ...            2.566667   \n",
       "\n",
       "       before_after_CMO  body_token_final_contain title_token_final_contain  \\\n",
       "11            after CMO                         1                         1   \n",
       "24            after CMO                         0                         1   \n",
       "76            after CMO                         0                         1   \n",
       "116           after CMO                         0                         1   \n",
       "137           after CMO                         1                         0   \n",
       "...                 ...                       ...                       ...   \n",
       "23245         after CMO                         1                         0   \n",
       "23252         after CMO                         1                         0   \n",
       "23282         after CMO                         1                         0   \n",
       "23288         after CMO                         1                         0   \n",
       "23307         after CMO                         1                         0   \n",
       "\n",
       "      contain_token   SMO heroes_of_SMO  \n",
       "11                1  True             1  \n",
       "24                1  True             1  \n",
       "76                1  True             1  \n",
       "116               1  True             1  \n",
       "137               1  True             1  \n",
       "...             ...   ...           ...  \n",
       "23245             1  True             1  \n",
       "23252             1  True             1  \n",
       "23282             1  True             1  \n",
       "23288             1  True             1  \n",
       "23307             1  True             1  \n",
       "\n",
       "[1549 rows x 25 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SMO[df_SMO['heroes_of_SMO']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "da80bbf9",
   "metadata": {},
   "outputs": [
    {
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       "<p>338 rows × 1 columns</p>\n",
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      ],
      "text/plain": [
       "            heroes_of_SMO\n",
       "dat                      \n",
       "2022-02-24              0\n",
       "2022-02-25              3\n",
       "2022-02-26              6\n",
       "2022-02-27              8\n",
       "2022-02-28              4\n",
       "...                   ...\n",
       "2023-01-23              5\n",
       "2023-01-24              4\n",
       "2023-01-25              5\n",
       "2023-01-26              2\n",
       "2023-01-27              2\n",
       "\n",
       "[338 rows x 1 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of news stories per day about heroes of SMO\n",
    "heroes_number = df_SMO.groupby('dat')[['heroes_of_SMO']].sum()\n",
    "heroes_number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9d88f664",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2022-11-20</th>\n",
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      "text/plain": [
       "            heroes_of_SMO\n",
       "dat                      \n",
       "2022-02-24              0\n",
       "2022-10-27              0\n",
       "2022-11-06              0\n",
       "2022-11-20              0\n",
       "2023-01-01              0"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of days without mentioning heroes\n",
    "heroes_number[heroes_number['heroes_of_SMO']==0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc410cce",
   "metadata": {},
   "source": [
    "After the special military operation began, the First Channel started airing news stories about the heroes of the operation on a daily basis. There were only five days of the operation when no such stories were aired."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "472452f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2.901028</td>\n",
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       "      <th>min</th>\n",
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       "      <th>25%</th>\n",
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      "text/plain": [
       "       heroes_of_SMO\n",
       "count     338.000000\n",
       "mean        4.582840\n",
       "std         2.901028\n",
       "min         0.000000\n",
       "25%         2.000000\n",
       "50%         4.000000\n",
       "75%         6.000000\n",
       "max        17.000000"
      ]
     },
     "execution_count": 41,
     "metadata": {},
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    }
   ],
   "source": [
    "heroes_number.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb590770",
   "metadata": {},
   "source": [
    "The First Channel typically broadcasts an average of 4 stories about the heroes of the special military operation. Approximately 50% of the time, the number of stories broadcasted falls within the range of 2 to 6 per day."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4f548ca",
   "metadata": {},
   "source": [
    "### What is the daily duration of news coverage on the First channel regarding heroes of special military operations?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3a699c73",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>video_duration_min</th>\n",
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       "      <td>333.000000</td>\n",
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       "      <td>9.464665</td>\n",
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       "      <th>std</th>\n",
       "      <td>9.876329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.450000</td>\n",
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       "      <th>25%</th>\n",
       "      <td>2.166667</td>\n",
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       "      <th>50%</th>\n",
       "      <td>6.050000</td>\n",
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       "      <th>75%</th>\n",
       "      <td>13.100000</td>\n",
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      "text/plain": [
       "       video_duration_min\n",
       "count          333.000000\n",
       "mean             9.464665\n",
       "std              9.876329\n",
       "min              0.450000\n",
       "25%              2.166667\n",
       "50%              6.050000\n",
       "75%             13.100000\n",
       "max             62.483333"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heroes_duration = df_SMO[df_SMO['heroes_of_SMO']==1].groupby('dat')[['video_duration_min']].sum()\n",
    "heroes_duration.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bec57a52",
   "metadata": {},
   "source": [
    "On average, the First Channel broadcasts 6 minutes of coverage about the heroes of the special military operation. Approximately 50% of the time, the duration of the stories falls within the range of 2 to 13 minutes per day."
   ]
  }
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