Capstone-Project.ipynb

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    "___\n",
    "\n",
    "<a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>\n",
    "___\n",
    "<center><em>Авторские права принадлежат Pierian Data Inc.</em></center>\n",
    "<center><em>Для дополнительной информации посетите наш сайт <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>"
   ]
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   "source": [
    "# Большой проверочный проект по обработке и визуализации данных\n",
    "\n",
    "## Обзор\n",
    "\n",
    "Вы планируете посмотреть какой-то фильм. Можете ли Вы доверять онлайн-рейтингам и отзывам о фильмах? *Особенно* если та компания, которая занимается рейтингами и отзывами, *также* зарабатывает на продаже билетов на фильмы. Есть ли у таких компаний тенденция выдавать завышенные или заниженные рейтинги?\n",
    "\n",
    "### Цель проекта:\n",
    "\n",
    "**Цель проекта - выполнить шаги по мотивам статьи на сайте fivethirtyeight.com о рейтингах и посмотреть, сможем ли мы прийти к тем же выводам, которые приведены в статье. Вы будете применять Ваши навыки работы с pandas и навыки визуализации данных для того, чтобы определить, предоставляла ли компания Fandango завышенные рейтинги в 2015 году для того, чтобы продавать больше билетов.**\n",
    "\n",
    "---\n",
    "---\n",
    "\n",
    "**Выполните шаги, написанные жирным шрифтом.**\n",
    "\n",
    "---\n",
    "----\n",
    "\n",
    "## Часть 1: Исследуем данные\n",
    "\n",
    "\n",
    "**ЗАДАНИЕ (ОПЦИОНАЛЬНО): Это задание не является обязательным, но если Вы хорошо знаете английский язык, то прочтите эту статью, по мотивам которой строится наш проект: [Be Suspicious Of Online Movie Ratings, Especially Fandango’s](http://fivethirtyeight.com/features/fandango-movies-ratings/)**"
   ]
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   "source": [
    "----\n",
    "\n",
    "**ЗАДАНИЕ: Прочитайте описание двух .csv-файлов, которые мы будем далее загружать и обрабатывать:**\n",
    "\n",
    "### Данные\n",
    "\n",
    "Исходные данные для статьи [Be Suspicious Of Online Movie Ratings, Especially Fandango’s](http://fivethirtyeight.com/features/fandango-movies-ratings/) находятся в свободном доступе по следующей ссылке на github: https://github.com/fivethirtyeight/data. Это два csv-файла. В одном файле данные о рейтингах от компании Fandango, а в другом файле агрегированные данные о рейтингах от других компаний, таких как Metacritic, IMDB и Rotten Tomatoes.\n",
    "\n",
    "#### all_sites_scores.csv"
   ]
  },
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   "attachments": {},
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   "metadata": {},
   "source": [
    "-----\n",
    "\n",
    "Файл `all_sites_scores.csv` содержит все фильмы, для которых есть рейтинг Rotten Tomatoes, рейтинг RT User, оценка Metacritic, оценка Metacritic User и оценка IMDb, а также как минимум 30 отзывов от фанатов на Fandango. Данные Fandango были выгружены 24 августа 2015."
   ]
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   "source": [
    "Колонка | Определение\n",
    "--- | -----------\n",
    "FILM | Название фильма\n",
    "RottenTomatoes | Оценка \"Rotten Tomatoes Tomatometer\" для этого фильма\n",
    "RottenTomatoes_User | Оценка \"Rotten Tomatoes user\" для этого фильма\n",
    "Metacritic | Оценка \"Metacritic\" для этого фильма\n",
    "Metacritic_User | Оценка \"Metacritic user\" для этого фильма\n",
    "IMDB | Оценка \"IMDb user\" для этого фильма\n",
    "Metacritic_user_vote_count | Количество голосов за этот фильм от пользователей Metacritic\n",
    "IMDB_user_vote_count | Количество голосов за этот фильм от пользователей IMDb"
   ]
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   "source": [
    "----\n",
    "----\n",
    "\n",
    "#### fandango_scape.csv"
   ]
  },
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   "source": [
    "Фильм `fandango_scrape.csv` содержит данные о фильмах, которые авторы статьи выгрузили с Fandango.\n",
    "\n",
    "Колонка | Определение\n",
    "--- | ---------\n",
    "FILM | Название фильма\n",
    "STARS | Количество звёзд на Fandango.com\n",
    "RATING |  Рейтинг Fandango - значение, прочитанное с HTML-страницы. Это средний рейтинг фильма.\n",
    "VOTES | Количество голосов пользователей, которые написали отзыв о фильме (на момент выгрузки данных)."
   ]
  },
  {
   "attachments": {},
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   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "**ЗАДАНИЕ: Импортируйте библиотеки, которые по Вашему мнению могут Вам понадобиться:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "source": [
    "## Часть 2: Сравниваем рейтинги Fandango и другие пользовательские рейтинги\n",
    "\n",
    "Сначала давайте изучим рейтинги Fandango и посмотрим, совпадут ли результаты нашего анализа с выводами в статье.\n",
    "\n",
    "**ЗАДАНИЕ: Выполните ячейку ниже для загрузки файла fandango_scrape.csv**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "fandango = pd.read_csv(\"fandango_scrape.csv\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Изучите свойства полученного объекта DataFrame - выведите несколько первых строк, а также общую информацию.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "                          FILM  STARS  RATING  VOTES\n",
       "0  Fifty Shades of Grey (2015)    4.0     3.9  34846\n",
       "1        Jurassic World (2015)    4.5     4.5  34390\n",
       "2       American Sniper (2015)    5.0     4.8  34085\n",
       "3             Furious 7 (2015)    5.0     4.8  33538\n",
       "4            Inside Out (2015)    4.5     4.5  15749"
      ]
     },
     "execution_count": 79,
     "metadata": {},
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   "source": [
    "fandango.head()"
   ]
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   "execution_count": 80,
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 504 entries, 0 to 503\n",
      "Data columns (total 4 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   FILM    504 non-null    object \n",
      " 1   STARS   504 non-null    float64\n",
      " 2   RATING  504 non-null    float64\n",
      " 3   VOTES   504 non-null    int64  \n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 15.9+ KB\n"
     ]
    }
   ],
   "source": [
    "fandango.info()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>504.000000</td>\n",
       "      <td>504.000000</td>\n",
       "      <td>504.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.558532</td>\n",
       "      <td>3.375794</td>\n",
       "      <td>1147.863095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.563133</td>\n",
       "      <td>1.491223</td>\n",
       "      <td>3830.583136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>18.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.300000</td>\n",
       "      <td>189.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>34846.000000</td>\n",
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       "            STARS      RATING         VOTES\n",
       "count  504.000000  504.000000    504.000000\n",
       "mean     3.558532    3.375794   1147.863095\n",
       "std      1.563133    1.491223   3830.583136\n",
       "min      0.000000    0.000000      0.000000\n",
       "25%      3.500000    3.100000      3.000000\n",
       "50%      4.000000    3.800000     18.500000\n",
       "75%      4.500000    4.300000    189.750000\n",
       "max      5.000000    5.000000  34846.000000"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "fandango.describe()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Давайте изучим связь между популярностью фильма и его рейтингом. Нарисуйте график scatterplot, показывающий связь между колонками RATING и VOTES. Можете поменять стилизацию графика по Вашему вкусу.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='RATING', ylabel='VOTES'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "sns.scatterplot(data=fandango, x='RATING', y='VOTES')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Вычислите корреляцию между колонками:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Андрей\\AppData\\Local\\Temp\\ipykernel_9552\\3624955426.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  fandango.corr()\n"
     ]
    },
    {
     "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>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>STARS</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.994696</td>\n",
       "      <td>0.164218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RATING</th>\n",
       "      <td>0.994696</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.163764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOTES</th>\n",
       "      <td>0.164218</td>\n",
       "      <td>0.163764</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           STARS    RATING     VOTES\n",
       "STARS   1.000000  0.994696  0.164218\n",
       "RATING  0.994696  1.000000  0.163764\n",
       "VOTES   0.164218  0.163764  1.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango.corr()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Сделаем предположение, что каждая строка в колонке FILM содержит значение в следующем формате:**\n",
    "\n",
    "    Название Фильма (Год)\n",
    "    \n",
    "**Создайте новую колонку, в ней возьмите из строки FILM только год, и назовите эту новую колонку YEAR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango['YEAR'] = fandango['FILM'].apply(lambda x: x[-5:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  STARS  RATING  VOTES  YEAR\n",
       "0  Fifty Shades of Grey (2015)    4.0     3.9  34846  2015\n",
       "1        Jurassic World (2015)    4.5     4.5  34390  2015\n",
       "2       American Sniper (2015)    5.0     4.8  34085  2015\n",
       "3             Furious 7 (2015)    5.0     4.8  33538  2015\n",
       "4            Inside Out (2015)    4.5     4.5  15749  2015"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Сколько фильмов содержится в наборе данных Fandango, в разбивке по годам?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2015    478\n",
       "2014     23\n",
       "2016      1\n",
       "1964      1\n",
       "2012      1\n",
       "Name: YEAR, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango['YEAR'].value_counts()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Визуализируйте количество фильмов в год с помощью графика:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='YEAR', ylabel='Count'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "sns.histplot(data=fandango, x='YEAR')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Какие 10 фильмов получили наибольшее количество голосов (votes)?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Hobbit: The Battle of the Five Armies (2014)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>15337</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kingsman: The Secret Service (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>15205</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Minions (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14998</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>14846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Into the Woods (2014)</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13055</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               FILM  STARS  RATING  VOTES  \\\n",
       "0                       Fifty Shades of Grey (2015)    4.0     3.9  34846   \n",
       "1                             Jurassic World (2015)    4.5     4.5  34390   \n",
       "2                            American Sniper (2015)    5.0     4.8  34085   \n",
       "3                                  Furious 7 (2015)    5.0     4.8  33538   \n",
       "4                                 Inside Out (2015)    4.5     4.5  15749   \n",
       "5  The Hobbit: The Battle of the Five Armies (2014)    4.5     4.3  15337   \n",
       "6               Kingsman: The Secret Service (2015)    4.5     4.2  15205   \n",
       "7                                    Minions (2015)    4.0     4.0  14998   \n",
       "8                    Avengers: Age of Ultron (2015)    5.0     4.5  14846   \n",
       "9                             Into the Woods (2014)    3.5     3.4  13055   \n",
       "\n",
       "   YEAR  \n",
       "0  2015  \n",
       "1  2015  \n",
       "2  2015  \n",
       "3  2015  \n",
       "4  2015  \n",
       "5  2014  \n",
       "6  2015  \n",
       "7  2015  \n",
       "8  2015  \n",
       "9  2014  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango.nlargest(n=10, columns='VOTES')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Сколько фильмов имеет нулевое количество голосов (votes)?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "69"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "len(fandango[fandango['VOTES'] == 0])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Создайте DataFrame только с теми фильмами, которые имеют голоса (votes) - то есть, удалите те фильмы, у которых нет ни одного голоса.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango = fandango[fandango['VOTES'] != 0]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "**Из-за особенностей отображения рейтингов в виде звёзд на страницах HTML, истинные рейтинги пользователей могут немного отличаться от рейтингов, которые показываются пользователю. Давайте визуализируем эту разницу распределений.**\n",
    "\n",
    "**ЗАДАНИЕ: Создайте график KDE plot (или несколько таких графиков), который отображает распределение отображаемых рейтингов (STARS) и истинных рейтингов на основе голосов пользователей (RATING). Обрежьте диапазон KDE в пределах 0-5.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x23919735b90>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.xlim(0, 5)\n",
    "sns.kdeplot(data=fandango, x='RATING', fill=True, label='True Rating')\n",
    "sns.kdeplot(data=fandango, x='STARS', fill=True, label='Stars Displayed')\n",
    "plt.legend(loc=(1.01, 0.5))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Теперь давайте посчитаем эту разницу в численном виде; Создайте новую колонку, в которой сохраните разницу между колонками STARS и RATING с помощью обычного вычитания STARS-RATING, а также выполните округление до одной десятичной цифры после запятой.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango['STARS_DIFF'] = round(fandango['STARS']-fandango['RATING'], 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STARS_DIFF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>That Sugar Film (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>The Intern (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>The Park Bench (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>The Wanted 18 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>Z For Zachariah (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF\n",
       "0    Fifty Shades of Grey (2015)    4.0     3.9  34846  2015         0.1\n",
       "1          Jurassic World (2015)    4.5     4.5  34390  2015         0.0\n",
       "2         American Sniper (2015)    5.0     4.8  34085  2015         0.2\n",
       "3               Furious 7 (2015)    5.0     4.8  33538  2015         0.2\n",
       "4              Inside Out (2015)    4.5     4.5  15749  2015         0.0\n",
       "..                           ...    ...     ...    ...   ...         ...\n",
       "430       That Sugar Film (2015)    5.0     5.0      1  2015         0.0\n",
       "431            The Intern (2015)    5.0     5.0      1  2015         0.0\n",
       "432        The Park Bench (2015)    5.0     5.0      1  2015         0.0\n",
       "433         The Wanted 18 (2015)    5.0     5.0      1  2015         0.0\n",
       "434       Z For Zachariah (2015)    5.0     5.0      1  2015         0.0\n",
       "\n",
       "[435 rows x 6 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Нарисуйте график count plot для отображения того, сколько раз встречается то или иное значение разницы между STAR и RATING:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='STARS_DIFF', ylabel='count'>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "sns.countplot(data=fandango, x='STARS_DIFF')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: На этом графике мы видим, что один из фильмов имеет разницу в 1 звезду между отображаемым рейтингом и истинным рейтингом! Найдите этот фильм.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STARS_DIFF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>Turbo Kid (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF\n",
       "381  Turbo Kid (2015)    5.0     4.0      2  2015         1.0"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "fandango[fandango['STARS_DIFF'] == 1]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Часть 3: Сравнение рейтингов Fandango с рейтингами других компаний\n",
    "\n",
    "Давайте посмотрим, как рейтинги Fandango соотносятся с рейтингами других компаний.\n",
    "\n",
    "**ЗАДАНИЕ: Выполните ячейку ниже, чтобы загрузить файл \"all_sites_scores.csv\"**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sites = pd.read_csv(\"all_sites_scores.csv\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Изучите общие свойства полученного объекта DataFrame.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "0  Avengers: Age of Ultron (2015)              74                   86   \n",
       "1               Cinderella (2015)              85                   80   \n",
       "2                  Ant-Man (2015)              80                   90   \n",
       "3          Do You Believe? (2015)              18                   84   \n",
       "4   Hot Tub Time Machine 2 (2015)              14                   28   \n",
       "\n",
       "   Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "0          66              7.1   7.8                        1330   \n",
       "1          67              7.5   7.1                         249   \n",
       "2          64              8.1   7.8                         627   \n",
       "3          22              4.7   5.4                          31   \n",
       "4          29              3.4   5.1                          88   \n",
       "\n",
       "   IMDB_user_vote_count  \n",
       "0                271107  \n",
       "1                 65709  \n",
       "2                103660  \n",
       "3                  3136  \n",
       "4                 19560  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 8 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      "dtypes: float64(2), int64(5), object(1)\n",
      "memory usage: 9.3+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>60.849315</td>\n",
       "      <td>63.876712</td>\n",
       "      <td>58.808219</td>\n",
       "      <td>6.519178</td>\n",
       "      <td>6.736986</td>\n",
       "      <td>185.705479</td>\n",
       "      <td>42846.205479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>30.168799</td>\n",
       "      <td>20.024430</td>\n",
       "      <td>19.517389</td>\n",
       "      <td>1.510712</td>\n",
       "      <td>0.958736</td>\n",
       "      <td>316.606515</td>\n",
       "      <td>67406.509171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>243.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>31.250000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>43.500000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>33.250000</td>\n",
       "      <td>5627.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63.500000</td>\n",
       "      <td>66.500000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>6.850000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>72.500000</td>\n",
       "      <td>19103.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>168.500000</td>\n",
       "      <td>45185.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>2375.000000</td>\n",
       "      <td>334164.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       RottenTomatoes  RottenTomatoes_User  Metacritic  Metacritic_User  \\\n",
       "count      146.000000           146.000000  146.000000       146.000000   \n",
       "mean        60.849315            63.876712   58.808219         6.519178   \n",
       "std         30.168799            20.024430   19.517389         1.510712   \n",
       "min          5.000000            20.000000   13.000000         2.400000   \n",
       "25%         31.250000            50.000000   43.500000         5.700000   \n",
       "50%         63.500000            66.500000   59.000000         6.850000   \n",
       "75%         89.000000            81.000000   75.000000         7.500000   \n",
       "max        100.000000            94.000000   94.000000         9.600000   \n",
       "\n",
       "             IMDB  Metacritic_user_vote_count  IMDB_user_vote_count  \n",
       "count  146.000000                  146.000000            146.000000  \n",
       "mean     6.736986                  185.705479          42846.205479  \n",
       "std      0.958736                  316.606515          67406.509171  \n",
       "min      4.000000                    4.000000            243.000000  \n",
       "25%      6.300000                   33.250000           5627.000000  \n",
       "50%      6.900000                   72.500000          19103.000000  \n",
       "75%      7.400000                  168.500000          45185.750000  \n",
       "max      8.600000                 2375.000000         334164.000000  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.describe()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Рейтинги от Rotten Tomatoes\n",
    "\n",
    "Начнём с рейтингов Rotten Tomatoes. Здесь два набора рейтингов - рейтинги, опубликованные официальными критиками, и пользовательские рейтинги. \n",
    "\n",
    "**ЗАДАНИЕ: Нарисуйте график scatterplot, изображающий для Rotten Tomatoes связь между рейтингами от критиков и пользовательскими рейтингами.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='RottenTomatoes', ylabel='RottenTomatoes_User'>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "plt.xlim(0, 100)\n",
    "plt.ylim(0, 100)\n",
    "sns.scatterplot(data=all_sites, x='RottenTomatoes', y='RottenTomatoes_User', s=50)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Давайте изучим численную разницу между этими двумя рейтингами. Мы посчитаем эту разницу с помощью формулы RottenTomatoes-RottenTomatoes_User. Полученные значения Rotten_Diff - это рейтинг критиков минус рейтинг пользователей. Близкие к нулю значения говорят о том, что критики и пользователи согласны друг с другом. Большие положительные значения - когда критики оценили фильм намного выше, чем пользователи. А большие отрицательные значения - наоборот, пользователи оценили фильм намного выше, чем критики.\n",
    "\n",
    "**ЗАДАНИЕ: Создайте новую колонку, в которой сохраните разницу между рейтингом от критиков и пользовательским рейтингом для Rotten Tomatoes. Используйте формулу RottenTomatoes-RottenTomatoes_User.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "all_sites['Rotten_Diff'] = all_sites['RottenTomatoes']-all_sites['RottenTomatoes_User']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "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>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "      <td>-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "      <td>-14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "0  Avengers: Age of Ultron (2015)              74                   86   \n",
       "1               Cinderella (2015)              85                   80   \n",
       "2                  Ant-Man (2015)              80                   90   \n",
       "3          Do You Believe? (2015)              18                   84   \n",
       "4   Hot Tub Time Machine 2 (2015)              14                   28   \n",
       "\n",
       "   Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "0          66              7.1   7.8                        1330   \n",
       "1          67              7.5   7.1                         249   \n",
       "2          64              8.1   7.8                         627   \n",
       "3          22              4.7   5.4                          31   \n",
       "4          29              3.4   5.1                          88   \n",
       "\n",
       "   IMDB_user_vote_count  Rotten_Diff  \n",
       "0                271107          -12  \n",
       "1                 65709            5  \n",
       "2                103660          -10  \n",
       "3                  3136          -66  \n",
       "4                 19560          -14  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь давайте посчитаем среднее значение полученной разницы по всему набору данных. Поскольку разница может быть как положительной, так и отрицательной, то давайте сначала возьмём абсолютные величины всех значений, и только после этого посчитаем среднее значение. Таким образом мы получим среднее значение абсолютной разницы между рейтингами от критиков и пользовательскими рейтингами."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Вычислите среднюю абсолютную разницу между рейтингами от критиков и пользовательскими рейтингами для Rotten Tomatoes, согласно описанию выше.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.095890410958905"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "abs(all_sites['Rotten_Diff'].values).mean()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Нарисуйте график распределения разницы между рейтингами от критиков и пользовательскими рейтингами для Rotten Tomatoes. На этом графике будут отрицательные значения. Для отображения этого распределения можете использовать как KDE, так и гистограммы.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Rotten_Diff', ylabel='Count'>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "sns.histplot(data=all_sites, x='Rotten_Diff', kde=True, bins=24)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Далее нарисуйте график распределения *абсолютных значений* разницы между рейтингами от критиков и пользовательскими рейтингами для Rotten Tomatoes.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sites['abs_Rotten_Diff'] = abs(all_sites['Rotten_Diff'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='abs_Rotten_Diff', ylabel='Count'>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "sns.histplot(data=all_sites, x='abs_Rotten_Diff', kde=True, bins=20)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Давайте выясним, какие фильмы наиболее отличаются по рейтингам. Сначала выведите 5 фильмов с наибольшей по модулю *отрицательной* разницей рейтингов. Поскольку мы вычисляли разницу рейтингов по формуле Critics Rating - Users Rating, большие по модулю отрицательные значения говорят о том, что пользователи в среднем оценили эти фильмы намного выше, чем критики.**"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Какие 5 фильмов в среднем были выше всего оценены пользователями, по сравнению с оценками от критиков:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "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>FILM</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Little Boy (2015)</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>The Longest Ride (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>The Wedding Ringer (2015)</td>\n",
       "      <td>-39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  Rotten_Diff\n",
       "3       Do You Believe? (2015)          -66\n",
       "85           Little Boy (2015)          -61\n",
       "105    Hitman: Agent 47 (2015)          -42\n",
       "134    The Longest Ride (2015)          -42\n",
       "125  The Wedding Ringer (2015)          -39"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "all_sites.nsmallest(n=5, columns='Rotten_Diff')[['FILM', 'Rotten_Diff']]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Далее наоборот - отобразите 5 фильмов, которые в среднем были выше всего оценены критиками, по сравнению с оценками от пользователей.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>FILM</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Mr. Turner (2014)</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>It Follows (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>While We're Young (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Welcome to Me (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>I'll See You In My Dreams (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 FILM  Rotten_Diff\n",
       "69                  Mr. Turner (2014)           42\n",
       "112                 It Follows (2015)           31\n",
       "115          While We're Young (2015)           31\n",
       "37               Welcome to Me (2015)           24\n",
       "40   I'll See You In My Dreams (2015)           24"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "all_sites.nlargest(n=5, columns='Rotten_Diff')[['FILM', 'Rotten_Diff']]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Рейтинги от MetaCritic\n",
    "\n",
    "Далее давайте быстро взглянем на рейтинги от MetaCritic. Они тоже отображают два типа рейтингов - как свои официальные рейтинги, так и пользовательские рейтинги."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Нарисуйте график scatterplot для сравнения рейтингов Metacritic и Metacritic User.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Metacritic', ylabel='Metacritic_User'>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "plt.xlim(0, 100)\n",
    "plt.ylim(0, 10)\n",
    "sns.scatterplot(data=all_sites, x='Metacritic', y='Metacritic_User', s=50)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Рейтинги от IMDB\n",
    "\n",
    "И наконец, посмотрим на рейтинги от IMDB. Обратите внимание, что Metacritic и IMDB показывают количество голосов. Посмотрим на наиболее популярные фильмы.\n",
    "\n",
    "**ЗАДАНИЕ: Нарисуйте график scatterplot для изображения связи между количеством голосов на MetaCritic и количеством голосов на IMDB.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Metacritic_user_vote_count', ylabel='IMDB_user_vote_count'>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "sns.scatterplot(data=all_sites, x='Metacritic_user_vote_count', y='IMDB_user_vote_count', s=50)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Здесь мы видим два \"выброса\" - точки, очень сильно отличающиеся от всех других точек. Один фильм получил наибольшее количество голосов на IMDB, но только 500 голосов на Metacritic. Что это за фильм?**\n",
    "\n",
    "**ЗАДАНИЕ: Какой фильм получил наибольшее количество голосов на IMDB?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "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>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "      <th>abs_Rotten_Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>The Imitation Game (2014)</td>\n",
       "      <td>90</td>\n",
       "      <td>92</td>\n",
       "      <td>73</td>\n",
       "      <td>8.2</td>\n",
       "      <td>8.1</td>\n",
       "      <td>566</td>\n",
       "      <td>334164</td>\n",
       "      <td>-2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "14  The Imitation Game (2014)              90                   92   \n",
       "\n",
       "    Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "14          73              8.2   8.1                         566   \n",
       "\n",
       "    IMDB_user_vote_count  Rotten_Diff  abs_Rotten_Diff  \n",
       "14                334164           -2                2  "
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "all_sites[(all_sites['Metacritic_user_vote_count'] > 500) & (all_sites['IMDB_user_vote_count'] > 320000)]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Какой фильм получил наибольшее количество голосов на Metacritic?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "      <th>abs_Rotten_Diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Mad Max: Fury Road (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>88</td>\n",
       "      <td>89</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2375</td>\n",
       "      <td>292023</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "88  Mad Max: Fury Road (2015)              97                   88   \n",
       "\n",
       "    Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "88          89              8.7   8.3                        2375   \n",
       "\n",
       "    IMDB_user_vote_count  Rotten_Diff  abs_Rotten_Diff  \n",
       "88                292023            9                9  "
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "all_sites.nlargest(1, columns='Metacritic_user_vote_count')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Сравнение рейтингов Fandango с рейтингами других компаний\n",
    "\n",
    "Давайте наконец выясним, являлись ли рейтинги Fandango искусственно завышенными, чтобы продавать больше билетов."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Объедините таблицу fandango с таблицей all_sites. Не каждый фильм в таблице Fandango найдётся в таблице all_sites, потому что некоторые фильмы Fandango имеют очень мало отзывов или вообще не имеют отзывов. Но мы хотим сравнивать только те фильмы, которые есть в обеих таблицах. Поэтому сделайте объединение \"*inner* merge\" двух наборов данных, сопоставляя строки по колонке FILM.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "df = fandango.merge(how='inner', right=all_sites, on='FILM')\n",
    "df = df.drop(['abs_Rotten_Diff'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 145 entries, 0 to 144\n",
      "Data columns (total 14 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        145 non-null    object \n",
      " 1   STARS                       145 non-null    float64\n",
      " 2   RATING                      145 non-null    float64\n",
      " 3   VOTES                       145 non-null    int64  \n",
      " 4   YEAR                        145 non-null    object \n",
      " 5   STARS_DIFF                  145 non-null    float64\n",
      " 6   RottenTomatoes              145 non-null    int64  \n",
      " 7   RottenTomatoes_User         145 non-null    int64  \n",
      " 8   Metacritic                  145 non-null    int64  \n",
      " 9   Metacritic_User             145 non-null    float64\n",
      " 10  IMDB                        145 non-null    float64\n",
      " 11  Metacritic_user_vote_count  145 non-null    int64  \n",
      " 12  IMDB_user_vote_count        145 non-null    int64  \n",
      " 13  Rotten_Diff                 145 non-null    int64  \n",
      "dtypes: float64(5), int64(7), object(2)\n",
      "memory usage: 17.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>145.000000</td>\n",
       "      <td>145.000000</td>\n",
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       "      <td>145.000000</td>\n",
       "      <td>145.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.086207</td>\n",
       "      <td>3.841379</td>\n",
       "      <td>3817.696552</td>\n",
       "      <td>0.244828</td>\n",
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       "      <td>42572.186207</td>\n",
       "      <td>-3.062069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.541169</td>\n",
       "      <td>0.502437</td>\n",
       "      <td>6368.668671</td>\n",
       "      <td>0.152721</td>\n",
       "      <td>30.161098</td>\n",
       "      <td>19.974749</td>\n",
       "      <td>19.538183</td>\n",
       "      <td>1.510883</td>\n",
       "      <td>0.957944</td>\n",
       "      <td>317.361740</td>\n",
       "      <td>67558.506121</td>\n",
       "      <td>19.218488</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.700000</td>\n",
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       "      <td>5.000000</td>\n",
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       "      <td>13.000000</td>\n",
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       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>-66.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>218.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>5626.000000</td>\n",
       "      <td>-14.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.900000</td>\n",
       "      <td>1430.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>6.800000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>18986.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.200000</td>\n",
       "      <td>4279.000000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>44711.000000</td>\n",
       "      <td>11.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.800000</td>\n",
       "      <td>34846.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>2375.000000</td>\n",
       "      <td>334164.000000</td>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "            STARS      RATING         VOTES  STARS_DIFF  RottenTomatoes  \\\n",
       "count  145.000000  145.000000    145.000000  145.000000      145.000000   \n",
       "mean     4.086207    3.841379   3817.696552    0.244828       60.634483   \n",
       "std      0.541169    0.502437   6368.668671    0.152721       30.161098   \n",
       "min      3.000000    2.700000     35.000000    0.000000        5.000000   \n",
       "25%      3.500000    3.500000    218.000000    0.100000       31.000000   \n",
       "50%      4.000000    3.900000   1430.000000    0.200000       63.000000   \n",
       "75%      4.500000    4.200000   4279.000000    0.400000       89.000000   \n",
       "max      5.000000    4.800000  34846.000000    0.500000      100.000000   \n",
       "\n",
       "       RottenTomatoes_User  Metacritic  Metacritic_User        IMDB  \\\n",
       "count           145.000000  145.000000       145.000000  145.000000   \n",
       "mean             63.696552   58.696552         6.508966    6.729655   \n",
       "std              19.974749   19.538183         1.510883    0.957944   \n",
       "min              20.000000   13.000000         2.400000    4.000000   \n",
       "25%              50.000000   43.000000         5.700000    6.300000   \n",
       "50%              66.000000   59.000000         6.800000    6.900000   \n",
       "75%              81.000000   75.000000         7.500000    7.400000   \n",
       "max              94.000000   94.000000         9.600000    8.600000   \n",
       "\n",
       "       Metacritic_user_vote_count  IMDB_user_vote_count  Rotten_Diff  \n",
       "count                  145.000000            145.000000   145.000000  \n",
       "mean                   184.489655          42572.186207    -3.062069  \n",
       "std                    317.361740          67558.506121    19.218488  \n",
       "min                      4.000000            243.000000   -66.000000  \n",
       "25%                     33.000000           5626.000000   -14.000000  \n",
       "50%                     72.000000          18986.000000     0.000000  \n",
       "75%                    167.000000          44711.000000    11.000000  \n",
       "max                   2375.000000         334164.000000    42.000000  "
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Нормализация колонок до диапазона 0-5 в соответствии с колонками STARS и RATINGS от Fandango\n",
    "\n",
    "Обратите внимание, что компании Rotten Tomatoes, Metacritic и IMDB используют другую шкалу измерения рейтингов, чем шкала от 0 до 5 звезд в Fandango. Чтобы выполнить сравнения, нам нужно *нормализовать* эти значения, чтобы они попадали с диапазон от 0 до 5 звёзд.\n",
    "\n",
    "**ЗАДАНИЕ: Добавьте дополнительные колонки в all_sites, и запишите в них нормализованные значения рейтингов от 0 до 5. Это можно сделать разными способами.**\n",
    "\n",
    "В качестве подсказки, можете прочитать вот эту статью: https://stackoverflow.com/questions/26414913/normalize-columns-of-pandas-data-frame\n",
    "\n",
    "\n",
    "Ещё одна подсказка - простой способ конвертации рейтингов:\n",
    "* 100/20 = 5 \n",
    "* 10/2 = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STARS_DIFF</th>\n",
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       "      <th>Metacritic</th>\n",
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       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Paul Blart: Mall Cop 2 (2015)</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3054</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>36</td>\n",
       "      <td>13</td>\n",
       "      <td>2.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>211</td>\n",
       "      <td>15004</td>\n",
       "      <td>-31</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF  \\\n",
       "49  Paul Blart: Mall Cop 2 (2015)    3.5     3.5   3054  2015         0.0   \n",
       "\n",
       "    RottenTomatoes  RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "49               5                   36          13              2.4   4.3   \n",
       "\n",
       "    Metacritic_user_vote_count  IMDB_user_vote_count  Rotten_Diff  \n",
       "49                         211                 15004          -31  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_df = (df[['RottenTomatoes', 'RottenTomatoes_User', 'Metacritic', 'Metacritic_User', 'IMDB']]) / 20 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_df[['Metacritic_User', 'IMDB']] = norm_df[['Metacritic_User', 'IMDB']] * 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_df = round(norm_df, 1)\n",
    "norm_df.columns = ['RottenTomatoes_Norm', 'RottenTomatoes_User_Norm', 'Metacritic_Norm', 'Metacritic_User_Norm', 'IMDB_Norm']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat([df, norm_df], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>Rotten_Diff</th>\n",
       "      <th>RottenTomatoes_Norm</th>\n",
       "      <th>RottenTomatoes_User_Norm</th>\n",
       "      <th>Metacritic_Norm</th>\n",
       "      <th>Metacritic_User_Norm</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.1</td>\n",
       "      <td>25</td>\n",
       "      <td>42</td>\n",
       "      <td>46</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>778</td>\n",
       "      <td>179506</td>\n",
       "      <td>-17</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71</td>\n",
       "      <td>81</td>\n",
       "      <td>59</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>1281</td>\n",
       "      <td>241807</td>\n",
       "      <td>-10</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "      <td>72</td>\n",
       "      <td>85</td>\n",
       "      <td>72</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7.4</td>\n",
       "      <td>850</td>\n",
       "      <td>251856</td>\n",
       "      <td>-13</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "      <td>81</td>\n",
       "      <td>84</td>\n",
       "      <td>67</td>\n",
       "      <td>6.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>764</td>\n",
       "      <td>207211</td>\n",
       "      <td>-3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98</td>\n",
       "      <td>90</td>\n",
       "      <td>94</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>807</td>\n",
       "      <td>96252</td>\n",
       "      <td>8</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF  \\\n",
       "0  Fifty Shades of Grey (2015)    4.0     3.9  34846  2015         0.1   \n",
       "1        Jurassic World (2015)    4.5     4.5  34390  2015         0.0   \n",
       "2       American Sniper (2015)    5.0     4.8  34085  2015         0.2   \n",
       "3             Furious 7 (2015)    5.0     4.8  33538  2015         0.2   \n",
       "4            Inside Out (2015)    4.5     4.5  15749  2015         0.0   \n",
       "\n",
       "   RottenTomatoes  RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0              25                   42          46              3.2   4.2   \n",
       "1              71                   81          59              7.0   7.3   \n",
       "2              72                   85          72              6.6   7.4   \n",
       "3              81                   84          67              6.8   7.4   \n",
       "4              98                   90          94              8.9   8.6   \n",
       "\n",
       "   Metacritic_user_vote_count  IMDB_user_vote_count  Rotten_Diff  \\\n",
       "0                         778                179506          -17   \n",
       "1                        1281                241807          -10   \n",
       "2                         850                251856          -13   \n",
       "3                         764                207211           -3   \n",
       "4                         807                 96252            8   \n",
       "\n",
       "   RottenTomatoes_Norm  RottenTomatoes_User_Norm  Metacritic_Norm  \\\n",
       "0                  1.2                       2.1              2.3   \n",
       "1                  3.6                       4.0              3.0   \n",
       "2                  3.6                       4.2              3.6   \n",
       "3                  4.0                       4.2              3.4   \n",
       "4                  4.9                       4.5              4.7   \n",
       "\n",
       "   Metacritic_User_Norm  IMDB_Norm  \n",
       "0                   1.6        2.1  \n",
       "1                   3.5        3.6  \n",
       "2                   3.3        3.7  \n",
       "3                   3.4        3.7  \n",
       "4                   4.4        4.3  "
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Далее создайте DataFrame с названием norm_scores, в котором оставьте только нормализованные рейтинги. Также оставьте колонки STARS и RATING из исходной таблицы fandango.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_scores = pd.concat([df[['STARS', 'RATING']], norm_df], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "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>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>RottenTomatoes_Norm</th>\n",
       "      <th>RottenTomatoes_User_Norm</th>\n",
       "      <th>Metacritic_Norm</th>\n",
       "      <th>Metacritic_User_Norm</th>\n",
       "      <th>IMDB_Norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   STARS  RATING  RottenTomatoes_Norm  RottenTomatoes_User_Norm  \\\n",
       "0    4.0     3.9                  1.2                       2.1   \n",
       "1    4.5     4.5                  3.6                       4.0   \n",
       "2    5.0     4.8                  3.6                       4.2   \n",
       "3    5.0     4.8                  4.0                       4.2   \n",
       "4    4.5     4.5                  4.9                       4.5   \n",
       "\n",
       "   Metacritic_Norm  Metacritic_User_Norm  IMDB_Norm  \n",
       "0              2.3                   1.6        2.1  \n",
       "1              3.0                   3.5        3.6  \n",
       "2              3.6                   3.3        3.7  \n",
       "3              3.4                   3.4        3.7  \n",
       "4              4.7                   4.4        4.3  "
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Сравнение распределений рейтингов от разных компаний\n",
    "\n",
    "\n",
    "А теперь момент истины! Действильно ли Fandango показывал неоправданно высокие рейтинги? Мы уже знаем, что отображаемые значения RATING были выше значений STARS. Но являются ли сами рейтинги в среднем более высокими, чем у других компаний?\n",
    "\n",
    "\n",
    "**ЗАДАНИЕ: Нарисуйте график, сравнивающий распределения нормализованных рейтингов от всех компаний. Это можно сделать разными способами, но попробуйте использовать Seaborn KDEplot (посмотрите документацию). Не беспокойтесь, если Ваш график будет выглядеть немного иначе нашего примера. Главное, чтобы были видны отличия между отдельными распределениями.**\n",
    "\n",
    "p.s. если Вам нужно переместить легенду на графике seaborn kdeplot, то это можно сделать вот так: https://github.com/mwaskom/seaborn/issues/2280"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Density'>"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "plt.xlim(-1, 5)\n",
    "\n",
    "sns.kdeplot(data=norm_scores, fill=True, legend=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Мы сразу видим, что рейтинги Fandango очень сдвинуты справо. Интересно также, что рейтинги RT от критиков имеют очень пологое распределение. Давайте сравним только эти два распределения.** \n",
    "\n",
    "**ЗАДАНИЕ: Нарисуйте график KDE plot, сравнивающий распределение рейтингов Rotten Tomatoes от критиков и распределение рейтингов STARS от Fandango.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='STARS', ylabel='Density'>"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "plt.xlim(0, 5)\n",
    "sns.kdeplot(data=norm_scores, x='STARS', fill=True)\n",
    "sns.kdeplot(data=norm_scores, x='RottenTomatoes_Norm', fill=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ОПЦИОНАЛЬНОЕ ЗАДАНИЕ: Нарисуйте график histplot, сравнивающий все нормализованные рейтинги.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Count'>"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WltavX6+uXbs6MTMAAAAAAIArm1MfGcvOztaePXts36ekpCgpKUnBwcGKiIjQuHHj9OKLL6pZs2aKiorSc889p/r16+v22293XtIAAAAAAABXOKcWhDZu3KiePXvavh8/frwkafjw4YqLi9NTTz2lnJwc/e1vf1NGRoauueYaLV++XF5eXs5KGQCAGm/dunXat2+fXTF8fHzUqFEju3PJz8+3e+7AkJAQRURE2J2LJO3es0cn80oM7Ws5ZN+YXgopKSlKTEw0vK8krfojUXtTjxiKse3AXknSqawspaamGopRvr+jOGJMUDNYLBa5+hm7bi0Wi4OzAYAzObUg1KNHD5WWlp5zvclk0rRp0zRt2rTLmBUAADiXdevWqXu3bjr3b++LY5LsjlEWx6RSOyP5+PgoOTnZrqLQH3/8IUla+dNPcvVLMhSjOPuELVaHDh0M5+IIuXm5kqTnnntOzz33nOE4Jkk/Jm20O5+NGzdq0w7jBbPysT1ltRqOkZGdLZMcMyYZp/NB9VRevFy6dKlc/YINxSi/Zu0phALAhVS7LmMAAODS2bdvn0olPdauq6LDwg3F+OPgPr27baMG3niDbr2hh+Fc1m3arHkff6rHH3he7Vp3NBRj/8G9mvzGeFksFrsKQocOHZIkNW8Yq8jG7Y3lsm+TEjcvt8VypoKiAknS2EF/08AbbjMU4/FZT2vTzj80rkOQ2tStZSjGf3cc1fL9VrVs4Kfrru1sKIYkbUzcpJWbpbzCfMMxrPl5KpX08n1Xq093Y9fb92sT9PSHvyknL8dwHqj6MjIyJEk92zdWdItmhmLs2LlbX23+XywAuBQoCAEAgEqLDgtX16atDO2bl5cnSaoTHKQWjaMM53DgcNljSA3rNVJ0E2O5OFotvyCF1zVWKDt5dL9jk3GAhnXqq10zY2Pr7+MnSYqt7aeeEfUNxVh7KEuSVT6erqpXO8BQDEkK8PYwvO9fNQ4NUIfmDQztu3vPboflgaovyM/L8HWb7scUGQAuvSrbZQwAAAAAAACXBgUhAAAAAACAGoaCEAAAAAAAQA3DHEIAAACo0kqKS5R96pTh/QsKyibJPnA0TT9u+t1QjF2HzZKkU1mnDHd+OpVV9hqyrdlKO37UUIzy/e3NJSenek5snZFx0q7OXMdOt3tPTk42HCMlJcXwvrg4FotFrn7GzrPl9DkGQEEIAAAAVVRpaakkyZqTrY2JCYbjpKaXfQD8fVeyft9l/IO+JG3YuFGHdiYay+NUiSRp064/dPR4tuEcDh/fZ3cu29OLJUklpSWG86hKrFarJOmnn1YqecNqw3HKz9GwYcPszqmwsMjuGKiovNi3dOlSufoFG4pRnH2iQiygJqMgBAAAgCrNy8NT0VHGO9KlWsqKL4Nahah/qxaGYvyQvE//3Zyq8Dr1NaxXT0MxFv/8s6R9iqxbTzd1vMZQDElavjFbm/dLTRtEasg13Q3FmLV8lbRjv3S66Halyy/IlyS1i4hQn9gIw3G+326WEvdq1LXXaeDVVxuK8X+//qq4tb+ouJiCkKNlZGRIkpp1bq56scbey6nbd2rT5uW2WEBNRkEIAAAAVZrJxUU+3sbbcLu6mCRJDQL81KVxpKEYyWkWSany9PBQWO26hmJ4eXie/q+7avvXMhRDkrzcPSRJ3h5eduTibfj4VZm/l6dCA4yPrb9X2TlqGBioNuHhhmLUCzR+fFwcnwBv1QoxNs6ZAdXz2geMYFJpAAAAAACAGoaCEAAAAAAAQA1DQQgAAAAAAKCGYQ4hAABwRTt5MsNwtxhHtx+25mXreJaxmNY8412n/urIcYutTboR6SdPOCyXqqSgOF8Z2SeN7Xt60uLqJreoSJbTHboqy1pU6NBc7GkZn33qlENzOZyRoT8OHjS0b1pmpsPySElJUWKisU5y5UJCQhQRYXyibQDVFwUhAABwRSpvM71y5U9KXL/ZUIxM63FJ9rcfLu9Ws23/Zu2wGPsQWd4K2Z7ONxaLRSZJc75ZajhGOZOkk6eM51KVlJzupHUs85h+3BxvKMbhE2Vt2guLqkfnqMzcsmLOnoxMpWzfYShG8eniWn6+fcUyR7SM35Jedn6KiortyiWvsGxc3lnzs95Z87NdsYrsuFbKW9Y/99xzeu655+zKw9vHWzuSd1AUAnAGCkIAAOCKlF9QIElq37ytrm1znaEYm3YnaG3yN3a3Hy7/QFu3cZgatmhpKMahnduUvfl/sYw4deqUSiWNjW2tDg2Mf/hbf2Cv5uzaoZw847lUJeWd1f1q+yn2amPt683rzdKO4yopKXFgZs6Te7rg0Laup9o1Ndap7PddVm2QfYUPyTEt4+f9ulvacUjFJfYVhIpOn9/OPZuqa7doQzFWx2/V5t/2q9iOa6W8Zf21Q65Vt4HdDMdJS0nTomcWyWKxUBACcAYKQgAA4Irm5+1ruPV2rdQAh+bi4eUhv1r+hvd1lIa+vooOqm14/4PH7LtjqqpydXeVr7+PoX3dPKrnn82+Hq4K9TN27fm6O3Y6Untaxvt6uDs0l4AgbzWMMPYe8nVgW/NadWopIoZCDoBLg0mlAQAAAAAAahgKQgAAAAAAADUMBSEAAAAAAIAapno+DI0rktlstrv9L201cTlxzZ4d43KmdevWad++fXbFaNy4sbp27eqgjOxnzjypwKNHDO17yMGdq9JOHNaug8mG9j18uiOYva2djx07JknKL8xXZo6xltP5hdWzrTmqtuKSEuUUGmsfX+TgCbaPnjyp5P0phvY94eC280dTT2rLpl2G9j1+7KRDcwGAS4WCEKoEs9ms6Jho5Vpz7YpDW01cLmazWTExMXZ1A5IkHx8fJScnV5trlnE507p169S9WzeV2hnHJGntr786vShUXuybsW6FtG6FXbGyc+y7Tk7l5MgkKe6HOYr7YY7hOCY5prWzJGXlnFR+6h5D++bnlH2ITE9PtzsP4ELKO4NlFeQr+ZixIn7m6Xbz5S3SjbKcPv7OYxZl5Z0wFOPAybLuYtl2/i2ZllH2c2XLukPasu6QXbFy8+zLBQAuNQpCqBIsFotyrbka/tJwhUWFGYpBW01cThaLRVarVVPHv6HI8CaGYuw/uFeT3xhfra5ZxuVM+/btU6mkx9p1VXRYuKEYO9IOalZS2V1Gzi4InTr9r/DX9o9Ri6iGhmIk7z2gtct3KS/fvjticvPyVSppVHQXXR1lrNX7bynbNHvHet3UvavuvrW/4Vxenv2e9hw8pFruXmoYYKwz0aFjmTouKTPT2B1GQGUUl5YVUDx93FSvvrFue6knMiRJRcX2FYSyc7IlSUF1vBXbLMhQjAPFxyVlK9/g3U7lsvKKVCpp5DV+ats02FCML34/ppXbc+0ulAHApUZBCFVKWFQYrTVxRYkMb6LoJq2cnUaVw7icKTosXF2b2jMm6xyWiyME1vZRvQbGPrgdPnnMobk08AlQdLCxf0w4mF72yFhwrQC1aBxlOAdvLy9JkruLi3w9jLXwdndhakdcfiaTSR4exj4SmFxMDs3Fw8NNQUH+hvZ193BsIbV+kLtiw40Vyn7ZziNjAK4M/OUBAAAAAABQw1AQAgAAAAAAqGF4ZAzARakqnaMckYejcgFQfZzIzNLOfca6G0lSbl6eA7Ox36GcHO04edzw/kfsnBge57f/aIp+2bbG8P4Hju53XDKSSgx2C7N3snwAgHNREAJwQWazWTHR0bLm2tctw8fbW8k7jHeBc1QHK6l6dbECYFxGQa5Mkn5Yu04/rLV/nqbiIse24a6sjIwMmSS9tX2LtH2LXbFMkrKs2Q7JC2WOZZVdb+t3rdP6XfZfbzn5xn8vFxeXXaslpaWyGixolpyOUWTnRM4AAOegIATggiwWi6y5uZpz3/1qHmZs4tZdaWl69MMP7Ooc5YgOVlL162IFwLicosKyLnA9GqhPF2OdyiTp39/8pi+2Zqm42Ln3TFitVpVKer5rHXVtWMdwnLXmdL24/rjy8qvWnU9Xuqz8suttdPtAXV2/ruE43+1L10fJmSq0oxBTUlpWzHExmeTt4WUohoupbPaJYoN3GAEAnIuCEICL1jwsTG3CjbXNdiQ6WAFwtAaBHmodbqzFtCSF+FatP6kia3modR1fw/sfynB3YDb4qyaBXureIMTw/snHMhyXjExycXE1uisA4ArGpNIAAAAAAAA1DAUhAAAAAACAGoaCEAAAAAAAQA1TtR54x2VXVVqJVyW0Nb+0kpOT7d53/8G9duVQvr8jcrFYLEr1STUUwxHXWbmq9l625xzZe36rqry8PGWfOmV4X0lKSUlRYmKiXXlUpZ9N2VarUlONvX8kKSen6rVGLywsVk52vqF9C/KLHZdHcbGsBcbykKSi05MEnzh1Ukm7txqKccqBHcpKS0uUn19gPMDp11NSUqy8QmMTZReXlp2fgqICpR0/aihGUZFju3HZk0txcdHp/ytVaal9k6FbrVb9seUPw/tnn6Kb3bkcOXBEiWuM/9y3HHTc3xoAqh8KQjWY2WxWdEy0cq32tRL39vHWjmTjrcSrEkeNiVS9xsUR0rOyJEnDhg2zO9bkN8bbHUNyTC5Lly5VLZ/ahvbNtB6XJLs+EEtl121MdLSsufZdtz7e3kreYd81m5qaKpPsP0cm2T8uVUV5oS4lJUUuFmMfevZklo3Fc889p+eee86ufHx8fJScnOzUn02lpz+cb9+2Tf/+t/EPK/uOlr2HyrslOVN2flkOGces2px70FCM4uyygmGewRbgknTqdNHxZPYp7T5sPM6Bk/kySfp+40p9v3Gl4TiSlF9sR6HrdJ2iqKhIqWlHDIcpKCorfuQW5mlf2j5DMXJOn5f0kxbFffsfQzEsGY4p+hWefg/Zk8vJU6cLQqVScYnBvE4XkjJOZmjp0s+NxZB07FhxeSo47ZS17HpL/CZRid/Y9w8BJkmbN29Whw4dHJAZgOqEglANZrFYlGvN1fCXhissylgr8bSUNC16ZlG1ad/tiDGRqt+4OEJWbtm/5A94coCi20cbivHb8t+0+oPV6nJ3d7Vs29ZwLts2b9b6JWt1z20Pq0/PWwzF+H7l11r85TxFN2mszi07Goqxfe92rU3+RhkZGYb2L2exWGTNzdWc++5X8zBj1+2utDQ9+uEHdl+zGRkZKpU0seuNahPexFCMPw7u1Yx1K+wel6qi/AN6neAgtQiPMhQjfXdZjAG979Ggm+8ynMv+g3s1+Y3xTv/ZVFpS9rEvsl6EhvcfbDjOguVfaM+xE3bf3eAIeUVlH9Bb1HNX86ZBhmLs2ZutDZulggLjd8KUF5NqeddSVKjx32Nrjh1QqXL19671dH/vGw3FePOr7/RJ0jEV2VGwKz+zbq6uCgsONRzHxaWsqOrj6qbmgXUMxdjlli4pVwE+PrrlKmM/983xCZIybYUUo4pOj0wjX18Nad3SUIwtRxIllf1DgqvJ6CwSZW3GvD091MuO38spa7ZIylYpJSGbvMKygt3AzgG6oXNdw3G2p2RqznfHdPjwYUelBqAaoSAEhUWFKSKGosWfMSaXTkh4iOGx3bFphyQpoG6AwqLqG87hYGqKJCk0pJ7h9vVJWxIkSb5e3goJCjQUw8/Xx9B+59I8LExtwsMdGtOoiFpBiqlr7BxlZJ1wcDZVg7ubm3y8vQzt6+ZW1hI6JCjU8DVbFXl5eiks2PgHHS9PTwdm4xg+HibV9jP251Wql+OmdnRzdZW3h7HrTZJcT7chbxDgofaNjBWW6vh5GD7+mUzycHO3Y+8yLiaTfAzGcTkdxc3FRbX9axmK4ebq2Ok7vVzcVNfX31guLv/rGW8y2dc/3t3FVeEhxguQbq7GH+Gu7sICPdQuKtjw/rnZdjxqCaDaY1JpAAAAAACAGoaCEAAAAAAAQA1DQQgAAAAAAKCGYQ4hoAqraq3ELRaLUt2M/djIOJnhkBwkKceaI8tJY212y/d3lB0HtkmuxtoI7z9yQJL9rcSTk8vmXrDn/Nh7nVVFjnj/SFJ+fr487Zir5sgR452R/spyMl079hprAS6VTSrtKEXFxSow2Aa8vCtYljVHuw6bDeeQmeO49/KpHKv2mo11B5OkwkLHtRM/fPiwXnzxRUP7bt++3WF5SI5psZ5XVKTjeVZjxzfa/aqGKCkpVk6usfeBIydjLy4t1fFTmcb3/1MnupISg5OQV4HJ5f+qqLBQ6enphvYtnyC+pLhEBQX5xnOwp8vfX6SlpNm9b/nfLEalpKTYtT+AiigIAVWU2WxWdEy0cq32tRL39vHWjmT7W4lLZS3W6xgsOOzKL/vDxppj7EOBJOXllsVI3rNFeyw7DMcpzCj7kJKVnWE4xpH0sg+OP2z4Rj9s+MZwHMkxrcQl+87PsdMtmatLq3ez2ayY6GhZc+17/0hlk9E64mNGfqHxiT0zT38Y+OLHxfrix8V252LPeS7v/paddUpHUo0VuzJOlHVN+31Xsn7fZf9kshkFxturn8zNliQdPX5Cq9ZvNBwnN/9/LbyNyi8s+yB85MgRu38m5J1+TxtV/tnaES3WU3Iy9dWBU4ZiHMkrfx1V78O+U50+QbkF+UravcVQiIIiRxQxy/LIycvT17+vNRzlVO7ptvMlpYa77JWczqXEjq52jlJUVJZLXm6ukncY+xmXnVX2nsnNy7XrZ3b2qbKfj/Z07kxNTZVJ0qJnFhmOIZX9Ph02bJhdMco5sggP1GQUhIAqymKxKNeaq+EvDVdYlLHOHWkpaVr0zCKHtBKXpA4tY9QhvKGhGF8l79CKP7Yo345/5So4/YG6eXBdtY9pbDjOth0pWqOTys0zXizIPJUhSWpzfbiiGhrrkrTvULq2rD6k66/qqweG/sNwLl/88F8t/e4jtW7RXlc3NdZ+OPHgHv13zfJq0+rdYrHImpur58f8Q5ENjHekW7dps+Z9/KlevvU2XRUdbSjGRyt/0sKNG1VcbPwDuvX0vq1v66DOXa82HCdl1x6tXPiDXefZai0r6np7+RhuA75jd9kdJ417NlT3zu0N5/Jb4h/a/eMBWe34YJtTVPYzqalvgK4JN97WfPPhfZLs+5f4ouKyD5H9m/vr1o7G3svfJu3QV8kZKjR6l8Vp5eWXYD8/3XKVsXOU8uPvkrIVVMdHbaNDDMXYlJUq7bc69G6WauH0cHi4u6tZA2O/391275RkZ+Hw9H+D3d01sEkTw3EOn9grqUgmyXA3OVN5L7kqcK0Ul5b9LHDzdlNog0BDMQ4ey5Akubi6KsSeboxHj0nKsv3sNiIjI0OlkibeF6vYaGM/JxMTD2jmZ/t0/f3X6+q+xn+P/fr5r1rzyZoKd5UBMI6CEFDFhUWFGW7T7mj+vr6qbbDFuo+3t8Py8HHzUB2DbXYlydfdeOvivwoN8VOLSGMFu+zTdyYEBgTb1Ur81+DVkiRfH3/DfzT6nzD+CF5VFtmgvlo0jjK8/4HDZXfANA4JUZvwcEMx4v2NX6t/5Rfip7Ao4wWujKwTDsvF1cUkD4PvpfL23V5BXgoNr204B58U423V/8rP3UP1axlv7ezuut9huYQFeOq62OaG9t2UYpaU4bBc3F3dDLdYdzWVta5383CRn5+xc+XoNu3VjavJJB8PY4+02ttq/s/cXUwK8TL+e97d5X/n2cXF2Dl33KtxHDcXk/x8jF37rq5lr8hFJrkbLJJJxsfzbCLCfBUdFWho36Pmsr8zAkMD7fq7dtsv2wzvC+BM/JYFAAAAAACoYSgIAQAAAAAA1DAUhAAAAAAAAGoY5hBCtWNPO0t7W2E6Mt6fW4m7pxp7dtzRrcRP5eTouMH28Y7o9uRoJzIshlt4l08q7QgHU1O0fNUXhvfflVJ2reTnFyj7lLFOPuXtbdeuNd4l5s/77zmWJg83Y/Mm7DlW1po2JSVFiYmJhmKUv3+WfPWtgmsFGIohSftPzyH069atOplx0lCMnQfLOtIVFxcr32ib9tOTZ+bl58py0vh8T6dyjLeFvhROHcvRzh0HDO+feays3faOjKNatjPBUAzz6TEpLS1VUZEdk5Q6cB7bouJinTxl7HorOj0BeV6J8VbvkpRvxyTol0JJaamsdjQlcP40wxXlFdt5fk5PWlxsx7g4cqLuwpJSWexo1GDvJOh/VlxSouxsY78LJanYnp8DVdiuXbv00UcfGdrX3r8NAFRdFIRQbWRZsiQ5pp1ldnZ2lcll6dKlcg80VhAqb69ubyvx8sJS4rZkHdy521CM8rbzefnG20M7Sm5O2Yfy5T9/ruU/f25XrPwS4384Zp1uBZu4bZ0St62zKw9J2r5/j7xPGSs47Mksu0bmzp2ruXPn2p3LGwk/S/rZrhjPPfec3a23f1hr/7hK0qwNv0sb7IuRmpVh+L14LKfsw83+w3t0+HvjBZTynwmOLhZXVnZugUySDq5J1cE19v18MklaefSAVh41Pi6SdKow364PkSUl9n+4Lv98np17SivW/2AoRsapsp9J+3Oy9NUB4/8osd9aXnBwfgtvSSosKtKuw2bD+xcVVY329cWnT3KKnecn9XSbdmtBgXYbHJciO35/lSu/Zk8UFurzvcb+PijbvywXe6628jObl5urhARjBWJJyrF146pqZURjCgvKrv34+HjFx8fbFcueTmUAqiYKQqg2rKfKfkkNeHKAotsbaw+97Zdt+nrO17a7JZyZy2/Lf9PqD1arXUSEOrQy1iVp1+4j+mrV73a3Ej91+q6T5hHR6tTQWLv3vN1bpD1bVFhgvD20oxTkl/3hGXtLG13d/RpDMVZ++4NS1uxRkR3/qpl3Oo8W19ZXq2aRhuNs23NAO34+LJOHm+GOWod3ZkiSrmndS9d1uM5wLktXfaodB7aqc89INYuoZyjGrgOHtXGVWddf1VcPDP2HoRhvvT9DidvWqeU19dUwNMhQDEnavjtVB/84oZhuddTaYDe5LfvTlPzrMRXLpDCDXeBKD5R1a2oREKx2LY11n5KknbsPaaVO2t7TzpKfX6RSSSN7+KlNZKDhOCs2WfTt5jwN6+KjNpHGzvPPO07o6825KiwtlZ+3r+FcHNGwqfzDtVeQl1peY+w87/5pl6RsBYR4qW2M8VbVBxOPSjtOqcSBd24YUX50L1c3xQQZ70h35MjpDntO/oxferpwGFTHR22jQwzH2b8xXVK23Nw8FBVq7Pey2+5k2d12/vR4+tRyV/v2xn5GStLedWmSilRix11LpadPrqeHl12dOz3TtkgqcPq14ijFRWXvooZdG+mqHl0Nxdi8MkF7f9utwkJj/+gEoOqiIIRqJyQ8xHA7y7SUtCqTy45NOyRJfl6eCq1lrOVvuneGof3OxdfLR0EBxj50eXs4rj20o/jW9jXcwtu7lvH2un8VHOyj2KYNDe+fdvKYJMnV5CIfb4OtnV3KCg51g0LVIaad4Vx+2vCjJKlWkLcaNjTWwjv9VNkHt8CAYMN/1Pv7lr1n6tUJUJumxtvbHjmaqYM6Ib9ATzWNCjUUIyWz7NEfk8kkD3cPQzFcTlcbvN3cVMfXeBv7w57Gjn+p1A9yU+twP8P7J+0uu1Ya1HZXu6aBhmLsOJpl+3/X0+8DZzO5uco3wFhxysXtdKt3d1fDrd4lyc2taoxFOVeT5ONm/M9WR7ZYdwQ3Dxe7zo+rR9nrMZlMhn+/OnJIXN1M8vP3tGt/R3ExucrHjuKui0vVulYcJaB2gKLbGvudat66X5LxO8AAVF1MKg0AAAAAAFDDUBACAAAAAACoYXhkzAnMZrPdE3qGhIQoIsL4YxCOZm93Lkd01LJ3npzqzN7uEJs3b5YkHc45pV0njhmKcTS3rBuQ1Wo1PLGuoyczzCvIM9yxqcCBz9GXlpaqwGD3Kel/k9la8nMNn5+00+fHUUpVqqJiYxOWls8hse/ALi1ZtshQjMOp9k0w/FclpaWy5hvs5HP6/BwvyNOuDGPnJ6Ow7NglxcXKzjZ+ruy5zv6quKRUBYVG5wQrtf2nsIp09qpKSkuLlWM1dp5LSh3bISm/qFD70g4b2regyPlzxl0K1sIC/bHf2OMzeQ6eg6WgpMRwt7JiB3YZq0rv5bziIpktxrsxFhQ5rsNeqaRigx37Sh38A66gsMDw3zx5+WXXWGFhoU4ZnHy/oNB4l0AAlw4FocvMbDYrOiZauVb7WnB7+3hrR/IOpxeFHNlNS7Kvo1buwbIxtebQAaFcxsmybmmO6hz1zvYN0nb7Wi1t375du48Y+0O6/ByX2Nn1pvB0Z5VDqfu17HtjH3RyLWW52NW29/S+BYUFOpJ6xHCYU5llHxy/Sk3RV6kpxvORZM2zrzBUfm6KioqUbXDi4ozMsvfwlt0btWX3RrvyybXzA2np6SltC4oKtfvwQUMxTp3uJvd1+gF9nW5focpaUCiLxVhRSfpfUfXgQWOvRfrfJPO5eValnUg3FKO8WFhcUqwTpzIN51JSzSpC5a+mqLhI+9OMvZfL287b21K8/MNoTl6+1mzbbChGbsHpAoEjCw9OVN6pLC+/QJsMdtTKL++mZWdXutKisv3T83MNdyvLOP167MmkfN8SlTr9vVxyevLk9Dyrvt233XAcy+mGDw5oHKiS0lKdMti5tqS47PXYWxgq/0eWdMsRLft+iaEY2QfLXsOxYxYlJBg7z4cPlxWE8nKd320WwP9QELrMLBaLcq25Gv7ScIVFGevGkJaSpkXPLJLFYnF6QcgR3bSk/3XUimnaWq06tjMUY/PqjVqf8KvyC/gXiHK5OWVj0aJ/S7Vs29pwnN9XrdOhdQfU5vpwtWvSyFCMhD/2aNvGNNWr21DX9OxpKMbqr37UTm1XqZ0FoeLTf+VF+QfqqpbGrttVxzdrh07Z/aFLKpvINiTIeCes0uJDkqRW1zZQh2bGuoxt32fWxlVm5dv5L3jlH3JcXVwNd2wqOP0hslm3UMVEGvsZt2nbPh3cfNxW/DOq/Px6unkpKszY2O47/WGt5TX11bFJpKEYv2zepX1JFslkUpCfHZNKu5UV8U+cOGE4RnkXRk93d9X2NzbhffkEv64urgr0M37tu8ixd7Y5W/lPE0+Ti5rVMtZRa4vJeHH5z4pPF0PrenrqpgbhhmIcOrFfUlF1qQfp9Odz+db2VLNmxq7b3XkW2dtNS5LKm7/51/ZU21hjE97/fvyQpGKH3IniIhenv5f/PCatousYjrP399Mdz+wZl9O7miTDE1ybXBwzs0f5+W3g468eLdsairHy8GbtlFU+3l5q0djY7+XME0ckWR16hzUA+1EQcpKwqDDD3aeqInu6aUn/66jl6+OrkCBjbXJ9vI13qqnuatevbbizhCTt2LJNkuQX6KmwesY+APqklHUf8XT3MnyOPT2MdzA5G3s6Nnk6sAOPi4tJ7nZ0z3FR2Ydr30APw+fn4AlHd4EzydXV2BiVFwuCg33VuomxD6L7Dh6R8XtgzpKTi4vhTj7lHWt8ankoNMzY+fHee/rOSZPkabBTmSS5OrB7jslk/Lq1dTcymeTuasefIlWsc5SjuJhc5Otu7Oedi8mx00N6uripvsEP+h4ujnwXVh0e7q6qGxRgaF93t5MOzcWebnKurg68VqrQe9nN3VW1AnwM7+/qwN/vJpnkarCw4+ifbp5urnb8zVN2bl1dXOTjZbCbaRXrXAigDJNKAwAAAAAA1DBXREFo9uzZioyMlJeXl7p06aLff//d2SkBAAAAAABcsap8Qejjjz/W+PHjNXnyZCUmJqpt27bq06ePjh413j0AAAAAAACgJqvycwi98cYbevjhhzVy5EhJ0rvvvqtvvvlGCxYs0MSJE8/YPj8/X/l/ag2cmVk2E35WVtblSfgCsk93Gvi/1/5PngHG5gfIzyp7fffcc498fY1NVCdJOTk5dudyKrWs28zX73+tlUtXGs4l41CGJCnxhw3au9FY546TaWWTpP788c9KWplkKIajXo8j4pSPye+rdmrvpkOGYhxNL7vuk3/eqrTtxicaPXqorAC7e0u6Th401i0j/WjZmOxbv1tLUuIMxTh2qKy70o5NR2RJMd7NJDWtbN9dm9N00vyLwRgZkqQ9244q87CxznbleezddlRZh413HnREnBMZZa9h064NmvxequFcDpxu9779j1SlHjA2V0Zq+unXs/2oTh35zVCMI2llx96XfEynjtgxtqdzSUk+pmyDcapKDEnKyCqbEHrFihXq2LGjoRh79+6VJG3dfESHUoxNTn30UNnPpt93W5V63NjPN0nafqTs9SSk5OpYtrE42w6VxfjliFXpVmPdmiRp18myiVJTjxxVqcHW78ePWiSVva4la4y9HkeMieSYcUk6Vhbj931WpZ0ylsue1LLr/dDRo1pVbLyhwLFjZWO79XC+U8fWUefHEXH2HSu7ZtOOHFOSwWYNjrhmy/eXqtjY7svVsWxj82DtPfq/nweJMja2x9LLxnbboTx99NN+QzEk6UB62e93867j+izL2N88Rw6V/U79fVumzMeM/TxISy97L29asUkHdhrvuHky5fTv9w2blX7Q2N+2uaevW6vVWmU+IwL2KL+OjTS7MZU6okXOJVJQUCAfHx99+umnuv32223Lhw8froyMDH3xxRdn7DNlyhRNnTr1MmYJAAAAAADgPHv37lXjxo0rtU+VvkPIYrGouLhYoaEV22mGhoZqx44dZ91n0qRJGj9+vO37jIwMNWrUSGazWbVqGevuAlQlWVlZCg8P18GDBxUQYKzLCVCVcE2jOuF6RnXDNY3qhmsa1U1mZqYiIiIUHBxc6X2rdEHICE9PT3l6nvn4U61atXjDo1oJCAjgmka1wjWN6oTrGdUN1zSqG65pVDcuLpWfIrpKTyodEhIiV1dXpaenV1ienp6usLAwJ2UFAAAAAABwZavSBSEPDw917NhR8fHxtmUlJSWKj49X165dnZgZAAAAAADAlavKPzI2fvx4DR8+XJ06ddJVV12lmTNnKicnx9Z17EI8PT01efLksz5GBlyJuKZR3XBNozrhekZ1wzWN6oZrGtWNPdd0le4yVu6dd97Rv/71L6Wlpaldu3aaNWuWunTp4uy0AAAAAAAArkhXREEIAAAAAAAAjlOl5xACAAAAAACA41EQAgAAAAAAqGEoCAEAAAAAANQwFIQAAAAAAABqmGpdEJo9e7YiIyPl5eWlLl266Pfff3d2SoBhP//8s2699VbVr19fJpNJy5Ytc3ZKgGHTp09X586d5e/vr7p16+r222/Xzp07nZ0WYNjcuXPVpk0bBQQEKCAgQF27dtV3333n7LQAh5kxY4ZMJpPGjRvn7FQAQ6ZMmSKTyVThKzo62tlpAYYdPnxYw4YNU+3ateXt7a3WrVtr48aNlYpRbQtCH3/8scaPH6/JkycrMTFRbdu2VZ8+fXT06FFnpwYYkpOTo7Zt22r27NnOTgWw2+rVqzVq1Cj99ttvWrFihQoLC3XTTTcpJyfH2akBhjRs2FAzZsxQQkKCNm7cqF69emnAgAHatm2bs1MD7LZhwwa99957atOmjbNTAezSsmVLpaam2r5++eUXZ6cEGHLy5El1795d7u7u+u6777R9+3a9/vrrCgoKqlScatt2vkuXLurcubPeeecdSVJJSYnCw8M1ZswYTZw40cnZAfYxmUz6/PPPdfvttzs7FcAhjh07prp162r16tW67rrrnJ0O4BDBwcH617/+pQcffNDZqQCGZWdnq0OHDpozZ45efPFFtWvXTjNnznR2WkClTZkyRcuWLVNSUpKzUwHsNnHiRK1du1Zr1qyxK061vEOooKBACQkJ6t27t22Zi4uLevfurXXr1jkxMwDA2WRmZkoq+wANXOmKi4u1ZMkS5eTkqGvXrs5OB7DLqFGjdPPNN1f4uxq4Uu3evVv169dX48aNde+998psNjs7JcCQL7/8Up06ddKQIUNUt25dtW/fXvPmzat0nGpZELJYLCouLlZoaGiF5aGhoUpLS3NSVgCAsykpKdG4cePUvXt3tWrVytnpAIZt2bJFfn5+8vT01N///nd9/vnnio2NdXZagGFLlixRYmKipk+f7uxUALt16dJFcXFxWr58uebOnauUlBRde+21OnXqlLNTAypt3759mjt3rpo1a6bvv/9e//jHP/TYY49p0aJFlYrjdonyAwDgoowaNUpbt27lOX5c8Vq0aKGkpCRlZmbq008/1fDhw7V69WqKQrgiHTx4UGPHjtWKFSvk5eXl7HQAu/Xr18/2/23atFGXLl3UqFEj/fe//+XRXlxxSkpK1KlTJ7388suSpPbt22vr1q169913NXz48IuOUy3vEAoJCZGrq6vS09MrLE9PT1dYWJiTsgIA/NXo0aP19ddfa+XKlWrYsKGz0wHs4uHhoaZNm6pjx46aPn262rZtq7feesvZaQGGJCQk6OjRo+rQoYPc3Nzk5uam1atXa9asWXJz+/927hgktTAM4/hzMYQIUQoHFw8uQYsIWkM1FNHg0FqIkDbnkrS4FDQ0uwUuNblKWw5KY4TDgaaiaBGLoikbGvTcTYi4w7F771ee/w/OcN7h45mfj+8dU6/XMx0R+JJQKKTp6Wnd3t6ajgK4FolEPl04zczMuH4GOZKFkN/vVzKZVKPRGMz6/b4ajQZv+QHgG3AcR4VCQbVaTc1mU7FYzHQk4K/r9/t6f383HQMYysrKiq6urmTb9uBLpVLKZrOybVs+n890ROBLut2u7u7uFIlETEcBXFtYWND19fWH2c3NjSzLcnXOyD4ZKxaLyuVySqVSmpubU7lc1tvbm7a2tkxHA4bS7XY/3GDc39/Ltm1NTk4qGo0aTAa4t729rWq1qtPTUwUCgcF+t2AwqPHxccPpAPdKpZLS6bSi0aheX19VrVZ1fn6uer1uOhowlEAg8Gmv28TEhKamptj3hh9pd3dXa2trsixLnU5H+/v78vl8ymQypqMBru3s7Gh+fl6Hh4daX1/X5eWlKpWKKpWKq3NGthDa2NjQ8/Oz9vb29Pj4qEQiobOzs0+LpoGfotVqaXl5efBfLBYlSblcTicnJ4ZSAcM5OjqSJC0tLX2YHx8fK5/P//9AwBc9PT1pc3NTDw8PCgaDisfjqtfrWl1dNR0NACCp3W4rk8no5eVF4XBYi4uLuri4UDgcNh0NcG12dla1Wk2lUkkHBweKxWIql8vKZrOuzvnlOI7zjzICAAAAAADgGxrJHUIAAAAAAAD4MwohAAAAAAAAj6EQAgAAAAAA8BgKIQAAAAAAAI+hEAIAAAAAAPAYCiEAAAAAAACPoRACAAAAAADwGAohAAAAAAAAj6EQAgAAAAAA8BgKIQAAAAAAAI+hEAIAAAAAAPCY388OmF320JWxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "plt.xlim(0, 6)\n",
    "sns.histplot(data=norm_scores, bins=50)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Как различные компании оценивают фильмы с наименьшими рейтингами?\n",
    "\n",
    "**ЗАДАНИЕ: Нарисуйте график clustermap для всех нормализованных рейтингов. Обратите внимание на отличия в рейтингах между разными компаниями. Фильмы с высокими рейтингами должны попадать в одни кластеры, а фильмы с низкими рейтингами в другие кластеры. Замечание: для этого графика clustermap вовсе необязательно указывать колонку FILM в качестве индекса, так что при желании можете удалить эту колонку перед построением графика clustermap.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x23925be9a10>"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "sns.clustermap(data=norm_scores)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ЗАДАНИЕ: Мы видели, что рейтинги Fandango явно выше рейтингов других компаний, особенно если смотреть на округлённые вверх значения рейтингов. Давайте посмотрим на 10 фильмов с наихудшими рейтингами по версии Rotten Tomatoes Critic - какие это 10 фильмов? Какие нормализованные рейтинги дали этим фильмам другие компании? Возможно Вам понадобится колонка FILM, так что если вы удаляли её, то верните эту колонку обратно.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "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>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>RottenTomatoes_Norm</th>\n",
       "      <th>RottenTomatoes_User_Norm</th>\n",
       "      <th>Metacritic_Norm</th>\n",
       "      <th>Metacritic_User_Norm</th>\n",
       "      <th>IMDB_Norm</th>\n",
       "      <th>FILM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>Paul Blart: Mall Cop 2 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Taken 3 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Fantastic Four (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.4</td>\n",
       "      <td>Hot Pursuit (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>The Boy Next Door (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Seventh Son (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Mortdecai (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Sinister 2 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>Unfinished Business (2015)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    STARS  RATING  RottenTomatoes_Norm  RottenTomatoes_User_Norm  \\\n",
       "49    3.5     3.5                  0.2                       1.8   \n",
       "25    4.5     4.1                  0.4                       2.3   \n",
       "28    3.0     2.7                  0.4                       1.0   \n",
       "54    4.0     3.7                  0.4                       1.8   \n",
       "84    4.0     3.9                  0.4                       2.4   \n",
       "50    4.0     3.6                  0.5                       1.8   \n",
       "77    3.5     3.2                  0.6                       1.8   \n",
       "78    3.5     3.2                  0.6                       1.5   \n",
       "83    3.5     3.3                  0.6                       1.7   \n",
       "87    3.5     3.2                  0.6                       1.4   \n",
       "\n",
       "    Metacritic_Norm  Metacritic_User_Norm  IMDB_Norm  \\\n",
       "49              0.6                   1.2        2.2   \n",
       "25              1.3                   2.3        3.0   \n",
       "28              1.4                   1.2        2.0   \n",
       "54              1.6                   1.8        2.4   \n",
       "84              1.4                   1.6        3.0   \n",
       "50              1.5                   2.8        2.3   \n",
       "77              1.5                   2.0        2.8   \n",
       "78              1.4                   1.6        2.8   \n",
       "83              1.6                   2.5        2.8   \n",
       "87              1.6                   1.9        2.7   \n",
       "\n",
       "                             FILM  \n",
       "49  Paul Blart: Mall Cop 2 (2015)  \n",
       "25                 Taken 3 (2015)  \n",
       "28          Fantastic Four (2015)  \n",
       "54             Hot Pursuit (2015)  \n",
       "84        Hitman: Agent 47 (2015)  \n",
       "50       The Boy Next Door (2015)  \n",
       "77             Seventh Son (2015)  \n",
       "78               Mortdecai (2015)  \n",
       "83              Sinister 2 (2015)  \n",
       "87     Unfinished Business (2015)  "
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "norm_scores['FILM'] = df['FILM']\n",
    "norm_scores.nsmallest(n=10, columns='RottenTomatoes_Norm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_for_final = norm_scores.nsmallest(n=10, columns='RottenTomatoes_Norm')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ФИНАЛЬНОЕ ЗАДАНИЕ: визуализируйте распределение рейтингов от всех компаний для 10 фильмов с наихудшими рейтингами.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Density'>"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# НАПИШИТЕ ВАШ КОД В ЭТОЙ ЯЧЕЙКЕ!\n",
    "plt.figure(figsize=(14, 5))\n",
    "sns.kdeplot(data=df_for_final, fill=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "----\n",
    "\n",
    "<img src=\"https://upload.wikimedia.org/wikipedia/en/6/6f/Taken_3_poster.jpg\">\n",
    "  \n",
    "**Выводы: вот это да! Fandango показывал 3-4 звезды для фильмов, которые явно были неудачными!**  \n",
    "    \n",
    "**Больше всего отличается фильм [Taken 3!](https://www.youtube.com/watch?v=tJrfImRCHJ0) - Fandango дал ему рейтинг 4.5 звёзд, хотя этот фильм получил [средний рейтинг 1.86](https://en.wikipedia.org/wiki/Taken_3#Critical_response) от других компаний!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STARS                     4.5\n",
       "RATING                    4.1\n",
       "RT_Norm                   0.4\n",
       "RTU_Norm                  2.3\n",
       "Meta_Norm                 1.3\n",
       "Meta_U_Norm               2.3\n",
       "IMDB_Norm                   3\n",
       "FILM           Taken 3 (2015)\n",
       "Name: 25, dtype: object"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_films.iloc[25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.3"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.4+2.3+1.3+2.3+3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.86"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "9.3/5"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}