{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "975fa498-1cba-4a76-a3ce-f3e818cf9ac6",
   "metadata": {},
   "source": [
    "# Explorative Data Analysis\n",
    "\n",
    "Lecture Data Engineering and Analytics<br>\n",
    "Eva Zangerle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "01df2e3a-ba55-4e8b-9170-ae3e9ebf993b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import stemgraphic\n",
    "from scipy.stats import probplot, shapiro, kstest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "068d0eb2-6ae3-42fb-8a73-1d05a347be72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set seaborn style\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2803cb89-5c14-4f24-9f22-016a61fdfafb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set data directory\n",
    "data_dir = \"../data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "57e96ac3-8027-4daf-bc92-ed093ae13c8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set display options for pandas dataframes\n",
    "pd.set_option(\"display.max_rows\", 200)\n",
    "pd.set_option(\"display.max_columns\", 100)\n",
    "pd.set_option(\"display.max_colwidth\", 200)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "052c3ebf-436f-449f-89a0-15d6669482d6",
   "metadata": {},
   "source": [
    "The following examples make use of the hetrec2011-movielens-2k dataset (https://grouplens.org/datasets/hetrec-2011/). This dataset is based on the [MovieLens 10m dataset](https://grouplens.org/datasets/movielens/10m/) and extends it with further metadata from imdb on movies and movie reviews from rottentomatoe. Find the dataset's readme [here](https://files.grouplens.org/datasets/hetrec2011/hetrec2011-movielens-readme.txt)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "63fa331a-c219-417f-bcb3-748a13bc3226",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 20809 entries, 1 to 65133\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   genre   20809 non-null  object\n",
      "dtypes: object(1)\n",
      "memory usage: 1.4 MB\n"
     ]
    }
   ],
   "source": [
    "# read in genre data\n",
    "genres = pd.read_csv(\n",
    "    os.path.join(data_dir, \"hetrec/movie_genres.dat\"),\n",
    "    delimiter=\"\\t\",\n",
    "    index_col=\"movieID\",\n",
    ")\n",
    "genres.info(memory_usage=\"deep\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b9412b5-f3c4-4fe4-be5b-38ca26b80f01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 855598 entries, 0 to 855597\n",
      "Data columns (total 9 columns):\n",
      " #   Column       Non-Null Count   Dtype  \n",
      "---  ------       --------------   -----  \n",
      " 0   userID       855598 non-null  int64  \n",
      " 1   movieID      855598 non-null  int64  \n",
      " 2   rating       855598 non-null  float64\n",
      " 3   date_day     855598 non-null  int64  \n",
      " 4   date_month   855598 non-null  int64  \n",
      " 5   date_year    855598 non-null  int64  \n",
      " 6   date_hour    855598 non-null  int64  \n",
      " 7   date_minute  855598 non-null  int64  \n",
      " 8   date_second  855598 non-null  int64  \n",
      "dtypes: float64(1), int64(8)\n",
      "memory usage: 58.7 MB\n"
     ]
    }
   ],
   "source": [
    "# read in rating data\n",
    "ratings = pd.read_csv(\n",
    "    os.path.join(data_dir, \"hetrec/user_ratedmovies.dat\"), delimiter=\"\\t\"\n",
    ")\n",
    "ratings.info(memory_usage=\"deep\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "b4595afa-a782-4059-a984-2054aa26e96d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10197 entries, 0 to 10196\n",
      "Data columns (total 21 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   id                      10197 non-null  int64  \n",
      " 1   title                   10197 non-null  object \n",
      " 2   imdbID                  10197 non-null  int64  \n",
      " 3   spanishTitle            10197 non-null  object \n",
      " 4   imdbPictureURL          10016 non-null  object \n",
      " 5   year                    10197 non-null  int64  \n",
      " 6   rtID                    9886 non-null   object \n",
      " 7   rtAllCriticsRating      9967 non-null   float64\n",
      " 8   rtAllCriticsNumReviews  9967 non-null   float64\n",
      " 9   rtAllCriticsNumFresh    9967 non-null   float64\n",
      " 10  rtAllCriticsNumRotten   9967 non-null   float64\n",
      " 11  rtAllCriticsScore       9967 non-null   float64\n",
      " 12  rtTopCriticsRating      9967 non-null   float64\n",
      " 13  rtTopCriticsNumReviews  9967 non-null   float64\n",
      " 14  rtTopCriticsNumFresh    9967 non-null   float64\n",
      " 15  rtTopCriticsNumRotten   9967 non-null   float64\n",
      " 16  rtTopCriticsScore       9967 non-null   float64\n",
      " 17  rtAudienceRating        9967 non-null   float64\n",
      " 18  rtAudienceNumRatings    9967 non-null   float64\n",
      " 19  rtAudienceScore         9967 non-null   float64\n",
      " 20  rtPictureURL            9967 non-null   object \n",
      "dtypes: float64(13), int64(3), object(5)\n",
      "memory usage: 6.2 MB\n"
     ]
    }
   ],
   "source": [
    "# read in movie data, prefix rt = rottenTomatoes\n",
    "# only works when specifying encoding correctly (fails due to ~n)\n",
    "movies = pd.read_csv(\n",
    "    os.path.join(data_dir, \"hetrec/movies.dat\"),\n",
    "    delimiter=\"\\t\",\n",
    "    na_values=[\"\\\\N\"],\n",
    "    encoding=\"latin1\",\n",
    ")\n",
    "movies.info(memory_usage=\"deep\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df11f9a4-dab6-456c-93d7-6eab4600500d",
   "metadata": {},
   "source": [
    "## Univariate Non-Graphical EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c85638d9-0714-454f-8804-e00cbc9b374a",
   "metadata": {},
   "source": [
    "In the following, we will perform non-graphical exploratory data analysis as a first step towards getting a deeper understanding of the characteristics of the dataset. Particularly, we will start with the genre data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d021c42-4c63-44a7-a337-2dbcd4f3b06b",
   "metadata": {},
   "source": [
    "### Basics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9f8c82dc-7300-49c0-b467-9ed94e5182f7",
   "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>genre</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movieID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Animation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Children</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Fantasy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             genre\n",
       "movieID           \n",
       "1        Adventure\n",
       "1        Animation\n",
       "1         Children\n",
       "1           Comedy\n",
       "1          Fantasy"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "20809"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# simple exploration\n",
    "genres.head()\n",
    "len(genres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9f85dc2e-572d-416c-a1f6-1f3127bf8cb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Adventure', 'Animation', 'Children', 'Comedy', 'Fantasy',\n",
       "       'Romance', 'Drama', 'Action', 'Crime', 'Thriller', 'Horror',\n",
       "       'Mystery', 'Sci-Fi', 'IMAX', 'Documentary', 'War', 'Musical',\n",
       "       'Film-Noir', 'Western', 'Short'], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# which genres are contained?\n",
    "genres[\"genre\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad0bab35-d8c3-49d8-91b9-acfbd5589b4e",
   "metadata": {},
   "source": [
    "### Tabulation for Categorical Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73879162-ec37-43b4-b23b-7f1969501620",
   "metadata": {},
   "source": [
    "In a first step, we will use tabulation to investigate the distribution of genres across movies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e03f89b3-fca8-404f-9136-7b92de976715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Drama</th>\n",
       "      <td>5076</td>\n",
       "      <td>0.243933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy</th>\n",
       "      <td>3566</td>\n",
       "      <td>0.171368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thriller</th>\n",
       "      <td>1664</td>\n",
       "      <td>0.079965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romance</th>\n",
       "      <td>1644</td>\n",
       "      <td>0.079004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action</th>\n",
       "      <td>1445</td>\n",
       "      <td>0.069441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crime</th>\n",
       "      <td>1086</td>\n",
       "      <td>0.052189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventure</th>\n",
       "      <td>1003</td>\n",
       "      <td>0.048200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Horror</th>\n",
       "      <td>978</td>\n",
       "      <td>0.046999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sci-Fi</th>\n",
       "      <td>740</td>\n",
       "      <td>0.035562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fantasy</th>\n",
       "      <td>535</td>\n",
       "      <td>0.025710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Children</th>\n",
       "      <td>519</td>\n",
       "      <td>0.024941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mystery</th>\n",
       "      <td>497</td>\n",
       "      <td>0.023884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>War</th>\n",
       "      <td>494</td>\n",
       "      <td>0.023740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Documentary</th>\n",
       "      <td>430</td>\n",
       "      <td>0.020664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Musical</th>\n",
       "      <td>421</td>\n",
       "      <td>0.020232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Animation</th>\n",
       "      <td>279</td>\n",
       "      <td>0.013408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western</th>\n",
       "      <td>261</td>\n",
       "      <td>0.012543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Film-Noir</th>\n",
       "      <td>145</td>\n",
       "      <td>0.006968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMAX</th>\n",
       "      <td>25</td>\n",
       "      <td>0.001201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Short</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count     share\n",
       "Drama         5076  0.243933\n",
       "Comedy        3566  0.171368\n",
       "Thriller      1664  0.079965\n",
       "Romance       1644  0.079004\n",
       "Action        1445  0.069441\n",
       "Crime         1086  0.052189\n",
       "Adventure     1003  0.048200\n",
       "Horror         978  0.046999\n",
       "Sci-Fi         740  0.035562\n",
       "Fantasy        535  0.025710\n",
       "Children       519  0.024941\n",
       "Mystery        497  0.023884\n",
       "War            494  0.023740\n",
       "Documentary    430  0.020664\n",
       "Musical        421  0.020232\n",
       "Animation      279  0.013408\n",
       "Western        261  0.012543\n",
       "Film-Noir      145  0.006968\n",
       "IMAX            25  0.001201\n",
       "Short            1  0.000048"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# combine counts and relative frequency in a dataframe to prettify output\n",
    "pd.DataFrame(\n",
    "    {\n",
    "        \"count\": genres[\"genre\"].value_counts(),\n",
    "        \"share\": genres[\"genre\"].value_counts(normalize=True),\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f43e3750-d441-4144-9a98-8c01cbbb2002",
   "metadata": {},
   "source": [
    "### Location"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78c558fc-d9c8-458e-9451-fd80d6b91f4a",
   "metadata": {},
   "source": [
    "In a next step, we will also include the ratings data in our evaluation and investigate the rating behavior of users for movies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f0e61052-ddd0-49bc-a709-c89fba59908f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "0    1.0\n",
       "1    4.5\n",
       "2    4.0\n",
       "3    2.0\n",
       "4    4.0\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "855593    4.0\n",
       "855594    4.0\n",
       "855595    4.5\n",
       "855596    5.0\n",
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       "Name: rating, dtype: float64"
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     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "      <th></th>\n",
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       "      <th>movieID</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>156557</th>\n",
       "      <td>13029</td>\n",
       "      <td>6281</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>2006</td>\n",
       "      <td>23</td>\n",
       "      <td>37</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3949</th>\n",
       "      <td>533</td>\n",
       "      <td>3196</td>\n",
       "      <td>4.5</td>\n",
       "      <td>22</td>\n",
       "      <td>6</td>\n",
       "      <td>2003</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24877</th>\n",
       "      <td>2471</td>\n",
       "      <td>1704</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>2008</td>\n",
       "      <td>9</td>\n",
       "      <td>40</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25245</th>\n",
       "      <td>2513</td>\n",
       "      <td>1653</td>\n",
       "      <td>4.5</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>2007</td>\n",
       "      <td>21</td>\n",
       "      <td>46</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>638844</th>\n",
       "      <td>51901</td>\n",
       "      <td>4571</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>2005</td>\n",
       "      <td>11</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209532</th>\n",
       "      <td>17999</td>\n",
       "      <td>249</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2004</td>\n",
       "      <td>19</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        userID  movieID  rating  date_day  date_month  date_year  date_hour  \\\n",
       "618259   50670      517     4.0         1           6       2001         21   \n",
       "122393   10132    60753     4.0        23           8       2008         17   \n",
       "653376   52834      147     3.0        13          12       1999         17   \n",
       "147297   12296     1094     4.0        27           5       1998         15   \n",
       "156557   13029     6281     5.0        27           1       2006         23   \n",
       "3949       533     3196     4.5        22           6       2003          8   \n",
       "24877     2471     1704     3.0        15           7       2008          9   \n",
       "25245     2513     1653     4.5         8           7       2007         21   \n",
       "638844   51901     4571     3.5         1          11       2005         11   \n",
       "209532   17999      249     3.0         3           6       2004         19   \n",
       "\n",
       "        date_minute  date_second  \n",
       "618259           49           46  \n",
       "122393            5           45  \n",
       "653376           40           45  \n",
       "147297           19           49  \n",
       "156557           37           41  \n",
       "3949             10           16  \n",
       "24877            40           36  \n",
       "25245            46            6  \n",
       "638844           45            7  \n",
       "209532           44           48  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at raw data\n",
    "ratings[\"rating\"].head()\n",
    "ratings[\"rating\"].tail()\n",
    "ratings.sample(n=10, random_state=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d809ecd1-c278-426c-b512-2f75c6a0871c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  rating distribution across all movies\n",
    "plt.hist(ratings[\"rating\"], bins=10)\n",
    "plt.xlabel(\"Rating\")\n",
    "plt.ylabel(\"Frequency\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d36d867a-263c-4741-8bfc-ddb4a6a7a4bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.437945156487042"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "3.5"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0    4.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inspect location\n",
    "# mean\n",
    "ratings[\"rating\"].mean()\n",
    "# median\n",
    "ratings[\"rating\"].median()\n",
    "# mode\n",
    "ratings[\"rating\"].mode()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4327620f-4705-45b1-8846-d73ceecb9008",
   "metadata": {},
   "source": [
    "The following examples showcase the role of location for a normal, hence, symmetric distribution and a highly skewed distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ac5bea93-9af4-4205-bd6c-dbc00405cbe6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a symmetricly distributed dataset\n",
    "normal_distribution = pd.Series(np.random.randn(20000) + 100)\n",
    "plt.hist(normal_distribution, bins=50)\n",
    "plt.xlabel(\"Value\")\n",
    "plt.ylabel(\"Occurrences\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "669e4fc1-3270-4912-8c53-22ef4bfe6427",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100.0036948049208"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "100.00700767844339"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# location\n",
    "normal_distribution.mean()\n",
    "normal_distribution.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "358e93e2-1060-4575-bcf3-92c8d51fc366",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "movieID\n",
       "5405       1\n",
       "795        1\n",
       "7322       1\n",
       "7295       1\n",
       "7291       1\n",
       "        ... \n",
       "5952    1528\n",
       "296     1537\n",
       "356     1568\n",
       "4993    1576\n",
       "2571    1670\n",
       "Name: rating, Length: 10109, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "movieID\n",
       "67       1\n",
       "134      1\n",
       "139      1\n",
       "143      1\n",
       "226      1\n",
       "        ..\n",
       "65006    1\n",
       "65011    1\n",
       "65088    1\n",
       "65091    1\n",
       "65130    1\n",
       "Name: rating, Length: 602, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# asymmetric, skewed distribution\n",
    "# number of ratings per movie\n",
    "rating_counts = ratings.groupby(\"movieID\")[\"rating\"].agg(\"count\")\n",
    "rating_counts.sort_values()\n",
    "rating_counts[rating_counts == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "de4ea66e-1743-45d6-886a-54e06b397c6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot number of movies with given number of ratings\n",
    "plt.plot(rating_counts.value_counts())\n",
    "plt.xlabel(\"Number of Ratings\")\n",
    "plt.ylabel(\"Number of Movies\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "54488e96-63ce-4bab-aeba-f063e437a4e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# histogram of number of movies with given number of ratings\n",
    "# (binned value counts)\n",
    "fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "axes[0].hist(rating_counts, bins=100)\n",
    "axes[0].set_ylabel(\"Number of Movies\")\n",
    "axes[0].set_xlabel(\"Number of Ratings\")\n",
    "axes[1].hist(rating_counts, log=True, bins=100)\n",
    "axes[1].set_ylabel(\"Number of Movies (log)\")\n",
    "axes[1].set_xlabel(\"Number of Ratings\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e68666c9-0fa6-493e-9f6c-b190315811b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "84.63725393213967"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "21.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "count    10109.000000\n",
       "mean        84.637254\n",
       "std        172.115584\n",
       "min          1.000000\n",
       "25%          6.000000\n",
       "50%         21.000000\n",
       "75%         75.000000\n",
       "max       1670.000000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean and median number of ratings\n",
    "rating_counts.mean()\n",
    "rating_counts.median()\n",
    "rating_counts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d7374509-6104-40fb-9463-f1ee6768c3ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# slightly different way of getting overview of ratings per movie\n",
    "# plot distribution of binned count values\n",
    "count_histogram = rating_counts.value_counts()\n",
    "fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "axes[0].scatter(count_histogram.index, count_histogram)\n",
    "axes[0].set_xlabel(\"Number of Ratings\")\n",
    "axes[0].set_ylabel(\"Number of Movies\")\n",
    "axes[1].scatter(count_histogram.index, count_histogram)\n",
    "axes[1].set_xlabel(\"Number of Ratings (log)\")\n",
    "axes[1].set_ylabel(\"Number of Movies (log)\")\n",
    "axes[1].set_xscale(\"log\")\n",
    "axes[1].set_yscale(\"log\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "eb52beb5-4f94-4cce-81e2-6e95c166de3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    855598.000000\n",
       "mean          3.437945\n",
       "std           1.002561\n",
       "min           0.500000\n",
       "25%           3.000000\n",
       "50%           3.500000\n",
       "75%           4.000000\n",
       "max           5.000000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use describe function for summary of ratings generally\n",
    "ratings[\"rating\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15364d28-75aa-4f9b-90a6-382c904b2705",
   "metadata": {},
   "source": [
    "### Spread"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd0c9b60-cc3e-4a8f-9214-78cd4f1ce7d2",
   "metadata": {},
   "source": [
    "The following examples show measure of spread for our ratings example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1d4f957e-30ed-4995-9ecb-0228ed41ddab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.002560872161038"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "1.005128302388301"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings[\"rating\"].std()\n",
    "ratings[\"rating\"].var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8776f04a-6a0f-475c-aee3-c920d59a90f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "count    855598.000000\n",
       "mean          3.437945\n",
       "std           1.002561\n",
       "min           0.500000\n",
       "25%           3.000000\n",
       "50%           3.500000\n",
       "75%           4.000000\n",
       "max           5.000000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# IQR\n",
    "ratings[\"rating\"].quantile(0.75) - ratings[\"rating\"].quantile(0.25)\n",
    "ratings[\"rating\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6db406d-d3cf-471a-a78f-bec544e99cce",
   "metadata": {},
   "source": [
    "Short detour: how does sample size impact how representative the sample is for the full population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2846ff54-b36a-4042-b553-188414fcc6a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0142448879302735"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "1.028692692692693"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sampling effect (for n=10 vs. n=1000, for instance)\n",
    "sample_ratings = ratings.sample(n=1000, random_state=5)\n",
    "sample_ratings[\"rating\"].std()\n",
    "sample_ratings[\"rating\"].var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "529f94c2-a440-4a5a-b639-dd8200a39e90",
   "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>userID</th>\n",
       "      <th>movieID</th>\n",
       "      <th>rating</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_month</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_hour</th>\n",
       "      <th>date_minute</th>\n",
       "      <th>date_second</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97121</th>\n",
       "      <td>8127</td>\n",
       "      <td>7254</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>2006</td>\n",
       "      <td>13</td>\n",
       "      <td>57</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854304</th>\n",
       "      <td>71509</td>\n",
       "      <td>3060</td>\n",
       "      <td>3.5</td>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>2004</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320729</th>\n",
       "      <td>26116</td>\n",
       "      <td>8933</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>2004</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75021</th>\n",
       "      <td>6757</td>\n",
       "      <td>2692</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772382</th>\n",
       "      <td>64621</td>\n",
       "      <td>3654</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>2001</td>\n",
       "      <td>5</td>\n",
       "      <td>39</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469043</th>\n",
       "      <td>37419</td>\n",
       "      <td>588</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>2007</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541266</th>\n",
       "      <td>43527</td>\n",
       "      <td>8873</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2006</td>\n",
       "      <td>17</td>\n",
       "      <td>33</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768444</th>\n",
       "      <td>64472</td>\n",
       "      <td>1438</td>\n",
       "      <td>2.5</td>\n",
       "      <td>27</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>22</td>\n",
       "      <td>46</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519540</th>\n",
       "      <td>41201</td>\n",
       "      <td>101</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>806968</th>\n",
       "      <td>67635</td>\n",
       "      <td>1544</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>2004</td>\n",
       "      <td>14</td>\n",
       "      <td>26</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>698 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        userID  movieID  rating  date_day  date_month  date_year  date_hour  \\\n",
       "97121     8127     7254     3.0         4          12       2006         13   \n",
       "854304   71509     3060     3.5        30           8       2004         16   \n",
       "320729   26116     8933     4.0        12          10       2004          1   \n",
       "75021     6757     2692     3.0         5           7       2002          9   \n",
       "772382   64621     3654     4.0        20          10       2001          5   \n",
       "...        ...      ...     ...       ...         ...        ...        ...   \n",
       "469043   37419      588     4.0        11           8       2007          9   \n",
       "541266   43527     8873     4.0         2           9       2006         17   \n",
       "768444   64472     1438     2.5        27           5       2003         22   \n",
       "519540   41201      101     3.5         1          11       2008          0   \n",
       "806968   67635     1544     3.0         8           4       2004         14   \n",
       "\n",
       "        date_minute  date_second  \n",
       "97121            57           17  \n",
       "854304           50           29  \n",
       "320729           14           41  \n",
       "75021            26           34  \n",
       "772382           39           11  \n",
       "...             ...          ...  \n",
       "469043           11            8  \n",
       "541266           33           58  \n",
       "768444           46           53  \n",
       "519540            0           17  \n",
       "806968           26           24  \n",
       "\n",
       "[698 rows x 9 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at all samples that have a rating within mean +/- 1 std\n",
    "sample_ratings = ratings.sample(n=1000, random_state=5)\n",
    "sample_ratings[\n",
    "    (\n",
    "        sample_ratings[\"rating\"]\n",
    "        > (sample_ratings[\"rating\"].mean() - sample_ratings[\"rating\"].std())\n",
    "    )\n",
    "    & (\n",
    "        sample_ratings[\"rating\"]\n",
    "        < (sample_ratings[\"rating\"].mean() + sample_ratings[\"rating\"].std())\n",
    "    )\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "07fa94c3-8a62-44e4-b52e-48d962972c9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "855598"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ratings)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfc7d9a3-4b1b-41c0-88cb-390e3b2b9240",
   "metadata": {},
   "source": [
    "Side note - for normal distributions:  \n",
    "68% of all observations fall within +/- 1 standard deviation  \n",
    "95% of all observations fall within +/- 2 standard deviations  \n",
    "99.7% of all observations fall within +/- 3 standard deviations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "adf25d75-1f21-4e37-9911-a82110647781",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.931491494178772, 5.4851319809639435e-21)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use shapiro-wilk test to test for normal distribution (usually quite suited\n",
    "# for smaller samples)\n",
    "# here, non-normal distribution is already clear from the histogram\n",
    "# output of shapiro-wilk: test statistics, p-value\n",
    "# null hypothesis: distribution was drawn from normally distributed data\n",
    "statistics, p = shapiro(sample_ratings[\"rating\"])\n",
    "statistics, p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f3c51f11-48a6-48c1-bf8d-32ee288d5a3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.9092498680518208, 0.0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Kolmogorov-Smirnov test\n",
    "ks_statistic, p_value = kstest(sample_ratings[\"rating\"], \"norm\")\n",
    "ks_statistic, p_value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaddb47c-7b83-4c78-abab-139b08e07235",
   "metadata": {},
   "source": [
    "### Shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bcfc241-02f1-4437-b550-487a04add2d6",
   "metadata": {},
   "source": [
    "The following examples showcase shape measures for the given dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9470ef42-f954-461b-94ba-792a5e467d9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.7009990282814003"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.33623508094406773"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# skewness and kurtosis of ratings\n",
    "ratings[\"rating\"].skew()\n",
    "ratings[\"rating\"].kurtosis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "69654f99-9ce3-4a14-a660-46b29207eae0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(ratings[\"rating\"])\n",
    "plt.xlabel(\"Rating\")\n",
    "plt.ylabel(\"Frequency\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "467d6cd0-05b7-45c4-906e-05b9a03effa4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.981817617200359"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "19.488816492218888"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#skewness and kurtosis of rating counts\n",
    "rating_counts.skew()\n",
    "rating_counts.kurtosis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5184b3e2-5b5a-42ae-b26f-d12c3948ee52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(rating_counts);\n",
    "plt.xlabel(\"Ratings\")\n",
    "plt.ylabel(\"Movies\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e27b0c37-6758-4492-9302-8e12e925a848",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.025304929630210707"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.019646099647941728"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# in comparison: skew and kurtosis of normally distributed values\n",
    "normal_distribution.skew()\n",
    "normal_distribution.kurtosis()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d098e086-0aa1-4101-895a-b2ee7743b035",
   "metadata": {},
   "source": [
    "## Univariate Graphical EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d4f70bb-5831-41ff-b1a0-689f4365630a",
   "metadata": {},
   "source": [
    "Even though we have already seen a number of charts in the previous section (mostly to support the explanation of the non-graphical EDA elements), we now focus on graphical EDA."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "456300ca-ca59-4d93-a53d-6723797c2385",
   "metadata": {},
   "source": [
    "### Boxplots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7f7fa33-21e6-4d83-89b3-a3821b93dd87",
   "metadata": {},
   "source": [
    "The following examples showcase boxplots for different distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c3ec9178-1598-4596-83f6-3b5ffbd4b489",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# normally distributed data\n",
    "plt.boxplot(normal_distribution, showmeans=True)\n",
    "plt.title(\"Normal Distribution\")\n",
    "plt.ylabel(\"Value\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "28f0ff26-2393-445a-9ab6-0e31266bb606",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    10109.000000\n",
       "mean         3.213406\n",
       "std          0.640538\n",
       "min          0.500000\n",
       "25%          2.851293\n",
       "50%          3.312415\n",
       "75%          3.681452\n",
       "max          5.000000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# average rating per movie\n",
    "rating_mean = ratings.groupby(\"movieID\")[\"rating\"].agg(\"mean\")\n",
    "rating_mean.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "09a4a9a1-2bd6-4e86-bf31-a18b77203540",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# somewhat symmetrical distribution\n",
    "plt.boxplot(rating_mean, showmeans=True)\n",
    "plt.ylabel(\"Rating\")\n",
    "plt.title(\"Rating Distribution\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b058f5fe-146e-46e3-967f-2d88a1ec5382",
   "metadata": {},
   "source": [
    "For skewed distributions (long tails), the boxplot also (naturally) is skewed. The box (including median) and whiskers are not symmetrical. Considering value higher than Q3+1.5QR is shown as an outlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7ae77d0c-aa51-47fb-acbd-ae4015390a2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# skewed, long tail distribution example\n",
    "sns.boxplot(x=rating_counts)\n",
    "plt.xlabel(\"Rating Counts\")\n",
    "plt.title(\"Number of Ratings per Movie\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad4df579-74ec-4e6c-b45f-c186b7c09695",
   "metadata": {},
   "source": [
    "### Histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1915e91e-ee4e-41a2-8440-4c5eeba2096f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# rating distribution\n",
    "plt.hist(ratings[\"rating\"])\n",
    "plt.xlabel(\"Rating\")\n",
    "plt.ylabel(\"Frequency\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec2432fc-c23c-4170-bb93-4ccadb6123b3",
   "metadata": {},
   "source": [
    "In the following, we will investigate different numbers of bins for the same dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2b1e8ca9-e12e-4bea-a052-c69cea97a611",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n",
    "\n",
    "sns.histplot(rating_mean, ax=axes[0, 0], bins=5)\n",
    "axes[0, 0].set_title(\"5 Bins\")\n",
    "axes[0, 0].set_xlabel(\"Average Rating\")\n",
    "axes[0, 0].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.histplot(rating_mean, ax=axes[0, 1], bins=10)\n",
    "axes[0, 1].set_title(\"10 Bins\")\n",
    "axes[0, 1].set_xlabel(\"Average Rating\")\n",
    "axes[0, 1].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.histplot(rating_mean, ax=axes[1, 0], bins=50)\n",
    "axes[1, 0].set_title(\"50 Bins\")\n",
    "axes[1, 0].set_xlabel(\"Average Rating\")\n",
    "axes[1, 0].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.histplot(rating_mean, ax=axes[1, 1], bins=100)\n",
    "axes[1, 1].set_title(\"100 Bins\")\n",
    "axes[1, 1].set_xlabel(\"Average Rating\")\n",
    "axes[1, 1].set_ylabel(\"Frequency\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51955b8a-69e3-485a-80ea-79be08691708",
   "metadata": {},
   "source": [
    "### Density Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "252f9dd9-fbcb-4626-b13e-f82c7ebcc6cf",
   "metadata": {},
   "source": [
    "Closely related to histograms are density plots (Kernel Density Estimation). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "42ee6329-8408-4643-9c8b-462a855d643e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# kde plot of average rating per movie (default parameters)\n",
    "sns.displot(rating_mean, kind=\"kde\")\n",
    "plt.xlabel(\"Average Rating\")\n",
    "plt.ylabel(\"Density\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af86f09a-968a-439f-b96d-eb18548b91b9",
   "metadata": {},
   "source": [
    "In the following, we will investigate different settings for the bandwidth parameter and its impact on the smoothness of the density function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7f6b4ba5-38f5-4615-bd8d-58ca71647a9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:1699: FutureWarning: The `bw` parameter is deprecated in favor of `bw_method` and `bw_adjust`. Using 0.01 for `bw_method`, but please see the docs for the new parameters and update your code.\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:1699: FutureWarning: The `bw` parameter is deprecated in favor of `bw_method` and `bw_adjust`. Using 0.1 for `bw_method`, but please see the docs for the new parameters and update your code.\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:1699: FutureWarning: The `bw` parameter is deprecated in favor of `bw_method` and `bw_adjust`. Using 0.5 for `bw_method`, but please see the docs for the new parameters and update your code.\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:1699: FutureWarning: The `bw` parameter is deprecated in favor of `bw_method` and `bw_adjust`. Using 1.0 for `bw_method`, but please see the docs for the new parameters and update your code.\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n",
    "\n",
    "sns.distplot(rating_mean, kde_kws={\"bw\": 0.01}, ax=axes[0, 0])\n",
    "axes[0, 0].set_title(\"Bandwidth: 0.01\")\n",
    "axes[0, 0].set_xlabel(\"Average Rating\")\n",
    "axes[0, 0].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.distplot(rating_mean, kde_kws={\"bw\": 0.1}, ax=axes[0, 1])\n",
    "axes[0, 1].set_title(\"Bandwidth: 0.1\")\n",
    "axes[0, 1].set_xlabel(\"Average Rating\")\n",
    "axes[0, 1].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.distplot(rating_mean, kde_kws={\"bw\": 0.5}, ax=axes[1, 0])\n",
    "axes[1, 0].set_title(\"Bandwidth: 0.5\")\n",
    "axes[1, 0].set_xlabel(\"Average Rating\")\n",
    "axes[1, 0].set_ylabel(\"Frequency\")\n",
    "\n",
    "sns.distplot(rating_mean, kde_kws={\"bw\": 1.0}, ax=axes[1, 1])\n",
    "axes[1, 1].set_title(\"Bandwidth: 1.0\")\n",
    "axes[1, 1].set_xlabel(\"Average Rating\")\n",
    "axes[1, 1].set_ylabel(\"Frequency\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87440f18-00ed-4f47-80d2-00044e4bca1e",
   "metadata": {},
   "source": [
    "### Stem and Leaf Plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "331b02e7-6a66-416b-b3e5-52a6a1bd522e",
   "metadata": {},
   "source": [
    "Stem plots can be considered a very basic histogram, where the stem captures the first number (or, hundreds, thousands, etc) of the number and the leaf shows the remainder of the number for each value; hence, forming a basic histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "d6e3243e-f16a-4122-bc96-e215abee9085",
   "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>userID</th>\n",
       "      <th>movieID</th>\n",
       "      <th>rating</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_month</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_hour</th>\n",
       "      <th>date_minute</th>\n",
       "      <th>date_second</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>618259</th>\n",
       "      <td>50670</td>\n",
       "      <td>517</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2001</td>\n",
       "      <td>21</td>\n",
       "      <td>49</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122393</th>\n",
       "      <td>10132</td>\n",
       "      <td>60753</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23</td>\n",
       "      <td>8</td>\n",
       "      <td>2008</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653376</th>\n",
       "      <td>52834</td>\n",
       "      <td>147</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>1999</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147297</th>\n",
       "      <td>12296</td>\n",
       "      <td>1094</td>\n",
       "      <td>4.0</td>\n",
       "      <td>27</td>\n",
       "      <td>5</td>\n",
       "      <td>1998</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156557</th>\n",
       "      <td>13029</td>\n",
       "      <td>6281</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>2006</td>\n",
       "      <td>23</td>\n",
       "      <td>37</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3949</th>\n",
       "      <td>533</td>\n",
       "      <td>3196</td>\n",
       "      <td>4.5</td>\n",
       "      <td>22</td>\n",
       "      <td>6</td>\n",
       "      <td>2003</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24877</th>\n",
       "      <td>2471</td>\n",
       "      <td>1704</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>2008</td>\n",
       "      <td>9</td>\n",
       "      <td>40</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25245</th>\n",
       "      <td>2513</td>\n",
       "      <td>1653</td>\n",
       "      <td>4.5</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>2007</td>\n",
       "      <td>21</td>\n",
       "      <td>46</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>638844</th>\n",
       "      <td>51901</td>\n",
       "      <td>4571</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>2005</td>\n",
       "      <td>11</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209532</th>\n",
       "      <td>17999</td>\n",
       "      <td>249</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2004</td>\n",
       "      <td>19</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27762</th>\n",
       "      <td>2692</td>\n",
       "      <td>2329</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>2008</td>\n",
       "      <td>17</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250656</th>\n",
       "      <td>20812</td>\n",
       "      <td>6157</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2004</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50648</th>\n",
       "      <td>4869</td>\n",
       "      <td>26606</td>\n",
       "      <td>3.5</td>\n",
       "      <td>22</td>\n",
       "      <td>7</td>\n",
       "      <td>2008</td>\n",
       "      <td>8</td>\n",
       "      <td>52</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559474</th>\n",
       "      <td>44567</td>\n",
       "      <td>2924</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>2003</td>\n",
       "      <td>21</td>\n",
       "      <td>56</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>716508</th>\n",
       "      <td>59557</td>\n",
       "      <td>555</td>\n",
       "      <td>4.0</td>\n",
       "      <td>28</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>56</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>344978</th>\n",
       "      <td>28350</td>\n",
       "      <td>1271</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>595958</th>\n",
       "      <td>48370</td>\n",
       "      <td>7361</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>2006</td>\n",
       "      <td>22</td>\n",
       "      <td>57</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117450</th>\n",
       "      <td>9470</td>\n",
       "      <td>4973</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2005</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459586</th>\n",
       "      <td>36495</td>\n",
       "      <td>377</td>\n",
       "      <td>4.0</td>\n",
       "      <td>29</td>\n",
       "      <td>9</td>\n",
       "      <td>1998</td>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204257</th>\n",
       "      <td>17755</td>\n",
       "      <td>1682</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>2005</td>\n",
       "      <td>23</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        userID  movieID  rating  date_day  date_month  date_year  date_hour  \\\n",
       "618259   50670      517     4.0         1           6       2001         21   \n",
       "122393   10132    60753     4.0        23           8       2008         17   \n",
       "653376   52834      147     3.0        13          12       1999         17   \n",
       "147297   12296     1094     4.0        27           5       1998         15   \n",
       "156557   13029     6281     5.0        27           1       2006         23   \n",
       "3949       533     3196     4.5        22           6       2003          8   \n",
       "24877     2471     1704     3.0        15           7       2008          9   \n",
       "25245     2513     1653     4.5         8           7       2007         21   \n",
       "638844   51901     4571     3.5         1          11       2005         11   \n",
       "209532   17999      249     3.0         3           6       2004         19   \n",
       "27762     2692     2329     4.5        15           7       2008         17   \n",
       "250656   20812     6157     3.5         5           3       2004          2   \n",
       "50648     4869    26606     3.5        22           7       2008          8   \n",
       "559474   44567     2924     4.0        17          12       2003         21   \n",
       "716508   59557      555     4.0        28          12       2008          4   \n",
       "344978   28350     1271     3.0         9           2       2000          2   \n",
       "595958   48370     7361     5.0        19           4       2006         22   \n",
       "117450    9470     4973     5.0         1           4       2005          0   \n",
       "459586   36495      377     4.0        29           9       1998         18   \n",
       "204257   17755     1682     4.0        13           4       2005         23   \n",
       "\n",
       "        date_minute  date_second  \n",
       "618259           49           46  \n",
       "122393            5           45  \n",
       "653376           40           45  \n",
       "147297           19           49  \n",
       "156557           37           41  \n",
       "3949             10           16  \n",
       "24877            40           36  \n",
       "25245            46            6  \n",
       "638844           45            7  \n",
       "209532           44           48  \n",
       "27762             8            6  \n",
       "250656            6           10  \n",
       "50648            52           20  \n",
       "559474           56           50  \n",
       "716508           56           57  \n",
       "344978           10           50  \n",
       "595958           57           45  \n",
       "117450           34           20  \n",
       "459586           11           37  \n",
       "204257           51           41  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x144 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stem_ratings = ratings.sample(n=20, random_state=3)\n",
    "stem_ratings\n",
    "fig, ax = stemgraphic.stem_graphic(stem_ratings[\"rating\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f73538c7-f51c-41bf-a4df-7b99364db92c",
   "metadata": {},
   "source": [
    "### Violin plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "944622e7-18ad-4f16-8ccd-5cc71d4abd1c",
   "metadata": {},
   "source": [
    "Violin plots combine boxplots and density plots. The shape of the box describes the density function, the thin bar in the box describes [Q1-1.5 IQR, Q3+1.5 IQR] (essentially the whiskers), the thick bar describes the box (IQR) and the white dot describes the median of the distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "7d77bb8a-3b39-4d45-ac73-07761b2ac142",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# violin and kde for rating counts \n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
    "\n",
    "sns.violinplot(x=normal_distribution,ax=axes[0],linewidth=3);\n",
    "axes[0].set_xlabel(\"Values\");\n",
    "axes[0].set_title(\"Violin Plot: Normal Distribution\");\n",
    "\n",
    "sns.distplot(normal_distribution, ax=axes[1]);\n",
    "axes[1].set_title(\"KDE: Normal Distribution\");\n",
    "axes[1].set_xlabel(\"Values\");\n",
    "axes[1].set_ylabel(\"Density\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "eb7d1d0d-7086-48dd-b385-8b9b0624dc37",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# violin and kde for rating counts \n",
    "fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "\n",
    "sns.violinplot(x=rating_counts,ax=axes[0]);\n",
    "axes[0].set_xlabel(\"Violin Plot: Rating Counts\");\n",
    "axes[0].set_title(\"Number of Ratings per Movie\");\n",
    "\n",
    "sns.distplot(rating_counts, ax=axes[1]);\n",
    "axes[1].set_title(\"KDE: Rating Counts\");\n",
    "axes[1].set_xlabel(\"Average Rating\");\n",
    "axes[1].set_ylabel(\"Density\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "82000fc4-8b2f-44d7-bfe7-90f99ef250ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eva/.local/share/virtualenvs/data-engineering-analytics-notebooks-Qx0adyYX/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(x=rating_counts);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb7f4e2d-10e0-4ecc-9794-68867ae34cde",
   "metadata": {},
   "source": [
    "### Quantile-Normal Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c16549d-12d1-4df0-97d0-1004db2f0a70",
   "metadata": {},
   "source": [
    "Quantile-quantile plots aim to compare two distributions by comparing their quantiles (i.e., we plot their quantiles against each other). Often, one of the distributions is a normal distributions to check whether the other distribution is also normally distributed. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6ed9764-2964-4e29-a796-cc29c0f19ad2",
   "metadata": {},
   "source": [
    "The `probplot` function (from `scipy.stats`) generates a probability plot of sample data against the quantiles of a specified theoretical distribution (the normal distribution by default)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "e9d2dc5e-f712-47ff-a85c-4c15b56424db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# no distribution given -> use normal distribution with same mean and\n",
    "fig, axes = plt.subplots(2, 2, figsize=(12, 15))\n",
    "probplot(normal_distribution, plot=axes[0, 0])\n",
    "axes[0, 0].set_title(\"Q-N Plot of Normal Distribution\")\n",
    "axes[0, 1].hist(normal_distribution)\n",
    "axes[0, 1].set_title(\"Normal Distribution (Histogram)\")\n",
    "\n",
    "probplot(rating_counts, plot=axes[1, 0])\n",
    "axes[1, 0].set_title(\"Q-N Plot of Rating Counts\")\n",
    "axes[1, 1].hist(rating_counts)\n",
    "axes[1, 1].set_title(\"Rating Count (Histogram)\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3aae66f8-d198-461f-8f92-2f7543b8c0fd",
   "metadata": {},
   "source": [
    "In the case of rating counts, we clearly see that (i) the distribution is not normally distributed, (ii) and that the distribution is heavy tailed."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4519a466-6dfd-418e-b3d0-7060cc0d7c94",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Multivariate Non-Graphical EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b435213f-6a3a-4f6a-989f-46e9d52119e9",
   "metadata": {},
   "source": [
    "### Cross-Tabulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "0b6363a1-4de9-413a-9514-76ffd6955911",
   "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>userID</th>\n",
       "      <th>movieID</th>\n",
       "      <th>rating</th>\n",
       "      <th>date_day</th>\n",
       "      <th>date_month</th>\n",
       "      <th>date_year</th>\n",
       "      <th>date_hour</th>\n",
       "      <th>date_minute</th>\n",
       "      <th>date_second</th>\n",
       "      <th>genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>29</td>\n",
       "      <td>10</td>\n",
       "      <td>2006</td>\n",
       "      <td>23</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>75</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>29</td>\n",
       "      <td>10</td>\n",
       "      <td>2006</td>\n",
       "      <td>23</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "      <td>Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>783</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>2006</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>55</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>783</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>2006</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>55</td>\n",
       "      <td>Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>788</td>\n",
       "      <td>3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>31</td>\n",
       "      <td>8</td>\n",
       "      <td>2007</td>\n",
       "      <td>14</td>\n",
       "      <td>49</td>\n",
       "      <td>41</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userID  movieID  rating  date_day  date_month  date_year  date_hour  \\\n",
       "0      75        3     1.0        29          10       2006         23   \n",
       "1      75        3     1.0        29          10       2006         23   \n",
       "2     783        3     2.0         2          11       2006         18   \n",
       "3     783        3     2.0         2          11       2006         18   \n",
       "4     788        3     3.5        31           8       2007         14   \n",
       "\n",
       "   date_minute  date_second    genre  \n",
       "0           17           16   Comedy  \n",
       "1           17           16  Romance  \n",
       "2           33           55   Comedy  \n",
       "3           33           55  Romance  \n",
       "4           49           41   Comedy  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data preparation\n",
    "# merge ratings and genre data frames\n",
    "genre_ratings = pd.merge(ratings, genres, on=\"movieID\")\n",
    "genre_ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "b2f8d199-d8f2-4a5c-a31d-2cd3101eb248",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute ratings per genre and year\n",
    "genre_year_rating_counts = pd.DataFrame(\n",
    "    genre_ratings.groupby([\"genre\", \"date_year\"])[\"rating\"].agg(\"count\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3e2066a2-cccf-48f3-ad86-83868de1a96b",
   "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></th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre</th>\n",
       "      <th>date_year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Action</th>\n",
       "      <th>1997</th>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>3206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>7349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>6872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Western</th>\n",
       "      <th>2006</th>\n",
       "      <td>3357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>2723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>2424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <th></th>\n",
       "      <td>2240215</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>248 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    rating\n",
       "genre   date_year         \n",
       "Action  1997           200\n",
       "        1998           540\n",
       "        1999          3206\n",
       "        2000          7349\n",
       "        2001          6872\n",
       "...                    ...\n",
       "Western 2006          3357\n",
       "        2007          2723\n",
       "        2008          2424\n",
       "        2009            64\n",
       "All                2240215\n",
       "\n",
       "[248 rows x 1 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# alternative\n",
    "genre_ratings.pivot_table(\n",
    "    [\"rating\"], index=[\"genre\", \"date_year\"], aggfunc=\"count\", margins=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "225c3257-170d-4399-82bc-a3767e352ca0",
   "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>date_year</th>\n",
       "      <th>1997</th>\n",
       "      <th>1998</th>\n",
       "      <th>1999</th>\n",
       "      <th>2000</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Action</th>\n",
       "      <td>200</td>\n",
       "      <td>540</td>\n",
       "      <td>3206</td>\n",
       "      <td>7349</td>\n",
       "      <td>6872</td>\n",
       "      <td>8069</td>\n",
       "      <td>12868</td>\n",
       "      <td>22478</td>\n",
       "      <td>37289</td>\n",
       "      <td>53049</td>\n",
       "      <td>46625</td>\n",
       "      <td>42087</td>\n",
       "      <td>961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventure</th>\n",
       "      <td>141</td>\n",
       "      <td>437</td>\n",
       "      <td>2390</td>\n",
       "      <td>5689</td>\n",
       "      <td>4906</td>\n",
       "      <td>5792</td>\n",
       "      <td>9746</td>\n",
       "      <td>16581</td>\n",
       "      <td>27022</td>\n",
       "      <td>40023</td>\n",
       "      <td>34476</td>\n",
       "      <td>31521</td>\n",
       "      <td>702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Animation</th>\n",
       "      <td>31</td>\n",
       "      <td>93</td>\n",
       "      <td>587</td>\n",
       "      <td>1312</td>\n",
       "      <td>1067</td>\n",
       "      <td>1505</td>\n",
       "      <td>2549</td>\n",
       "      <td>3871</td>\n",
       "      <td>6726</td>\n",
       "      <td>10872</td>\n",
       "      <td>8839</td>\n",
       "      <td>8704</td>\n",
       "      <td>195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Children</th>\n",
       "      <td>56</td>\n",
       "      <td>218</td>\n",
       "      <td>936</td>\n",
       "      <td>2411</td>\n",
       "      <td>1809</td>\n",
       "      <td>2470</td>\n",
       "      <td>4264</td>\n",
       "      <td>6150</td>\n",
       "      <td>10073</td>\n",
       "      <td>15200</td>\n",
       "      <td>11619</td>\n",
       "      <td>10798</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy</th>\n",
       "      <td>247</td>\n",
       "      <td>767</td>\n",
       "      <td>4512</td>\n",
       "      <td>12458</td>\n",
       "      <td>10428</td>\n",
       "      <td>13223</td>\n",
       "      <td>23018</td>\n",
       "      <td>33914</td>\n",
       "      <td>49961</td>\n",
       "      <td>72448</td>\n",
       "      <td>58235</td>\n",
       "      <td>52867</td>\n",
       "      <td>1271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crime</th>\n",
       "      <td>98</td>\n",
       "      <td>292</td>\n",
       "      <td>1742</td>\n",
       "      <td>3913</td>\n",
       "      <td>3676</td>\n",
       "      <td>4361</td>\n",
       "      <td>7784</td>\n",
       "      <td>12173</td>\n",
       "      <td>19416</td>\n",
       "      <td>29321</td>\n",
       "      <td>25559</td>\n",
       "      <td>23919</td>\n",
       "      <td>513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Documentary</th>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>124</td>\n",
       "      <td>291</td>\n",
       "      <td>185</td>\n",
       "      <td>290</td>\n",
       "      <td>679</td>\n",
       "      <td>1368</td>\n",
       "      <td>2016</td>\n",
       "      <td>3080</td>\n",
       "      <td>2633</td>\n",
       "      <td>2287</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama</th>\n",
       "      <td>328</td>\n",
       "      <td>971</td>\n",
       "      <td>5945</td>\n",
       "      <td>14897</td>\n",
       "      <td>11706</td>\n",
       "      <td>14168</td>\n",
       "      <td>24326</td>\n",
       "      <td>36247</td>\n",
       "      <td>55398</td>\n",
       "      <td>80793</td>\n",
       "      <td>72064</td>\n",
       "      <td>65850</td>\n",
       "      <td>1338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fantasy</th>\n",
       "      <td>46</td>\n",
       "      <td>182</td>\n",
       "      <td>1165</td>\n",
       "      <td>2780</td>\n",
       "      <td>2240</td>\n",
       "      <td>3001</td>\n",
       "      <td>5081</td>\n",
       "      <td>8456</td>\n",
       "      <td>13801</td>\n",
       "      <td>21843</td>\n",
       "      <td>20140</td>\n",
       "      <td>17313</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Film-Noir</th>\n",
       "      <td>8</td>\n",
       "      <td>28</td>\n",
       "      <td>225</td>\n",
       "      <td>473</td>\n",
       "      <td>321</td>\n",
       "      <td>415</td>\n",
       "      <td>665</td>\n",
       "      <td>981</td>\n",
       "      <td>1846</td>\n",
       "      <td>2811</td>\n",
       "      <td>2405</td>\n",
       "      <td>1909</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Horror</th>\n",
       "      <td>54</td>\n",
       "      <td>136</td>\n",
       "      <td>1133</td>\n",
       "      <td>2562</td>\n",
       "      <td>2347</td>\n",
       "      <td>2559</td>\n",
       "      <td>3854</td>\n",
       "      <td>6619</td>\n",
       "      <td>11215</td>\n",
       "      <td>15359</td>\n",
       "      <td>13158</td>\n",
       "      <td>11094</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMAX</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>56</td>\n",
       "      <td>85</td>\n",
       "      <td>123</td>\n",
       "      <td>322</td>\n",
       "      <td>796</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Musical</th>\n",
       "      <td>31</td>\n",
       "      <td>125</td>\n",
       "      <td>651</td>\n",
       "      <td>1586</td>\n",
       "      <td>1111</td>\n",
       "      <td>1367</td>\n",
       "      <td>2488</td>\n",
       "      <td>3684</td>\n",
       "      <td>5304</td>\n",
       "      <td>8163</td>\n",
       "      <td>6270</td>\n",
       "      <td>5767</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mystery</th>\n",
       "      <td>35</td>\n",
       "      <td>134</td>\n",
       "      <td>867</td>\n",
       "      <td>2053</td>\n",
       "      <td>1674</td>\n",
       "      <td>2308</td>\n",
       "      <td>3491</td>\n",
       "      <td>5533</td>\n",
       "      <td>8987</td>\n",
       "      <td>13108</td>\n",
       "      <td>11645</td>\n",
       "      <td>10103</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romance</th>\n",
       "      <td>139</td>\n",
       "      <td>467</td>\n",
       "      <td>2523</td>\n",
       "      <td>6034</td>\n",
       "      <td>4636</td>\n",
       "      <td>6021</td>\n",
       "      <td>9802</td>\n",
       "      <td>15132</td>\n",
       "      <td>22690</td>\n",
       "      <td>33372</td>\n",
       "      <td>26982</td>\n",
       "      <td>24840</td>\n",
       "      <td>608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sci-Fi</th>\n",
       "      <td>93</td>\n",
       "      <td>338</td>\n",
       "      <td>1931</td>\n",
       "      <td>4287</td>\n",
       "      <td>3560</td>\n",
       "      <td>4412</td>\n",
       "      <td>7081</td>\n",
       "      <td>11722</td>\n",
       "      <td>18997</td>\n",
       "      <td>26180</td>\n",
       "      <td>23587</td>\n",
       "      <td>21660</td>\n",
       "      <td>426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Short</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thriller</th>\n",
       "      <td>189</td>\n",
       "      <td>543</td>\n",
       "      <td>3137</td>\n",
       "      <td>7318</td>\n",
       "      <td>6641</td>\n",
       "      <td>7943</td>\n",
       "      <td>12489</td>\n",
       "      <td>20561</td>\n",
       "      <td>33417</td>\n",
       "      <td>49014</td>\n",
       "      <td>45362</td>\n",
       "      <td>39937</td>\n",
       "      <td>898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>War</th>\n",
       "      <td>56</td>\n",
       "      <td>145</td>\n",
       "      <td>741</td>\n",
       "      <td>1631</td>\n",
       "      <td>1448</td>\n",
       "      <td>1518</td>\n",
       "      <td>2583</td>\n",
       "      <td>4101</td>\n",
       "      <td>6704</td>\n",
       "      <td>9620</td>\n",
       "      <td>8952</td>\n",
       "      <td>7939</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western</th>\n",
       "      <td>13</td>\n",
       "      <td>46</td>\n",
       "      <td>268</td>\n",
       "      <td>732</td>\n",
       "      <td>634</td>\n",
       "      <td>535</td>\n",
       "      <td>1012</td>\n",
       "      <td>1580</td>\n",
       "      <td>2263</td>\n",
       "      <td>3357</td>\n",
       "      <td>2723</td>\n",
       "      <td>2424</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "date_year    1997  1998  1999   2000   2001   2002   2003   2004   2005  \\\n",
       "genre                                                                     \n",
       "Action        200   540  3206   7349   6872   8069  12868  22478  37289   \n",
       "Adventure     141   437  2390   5689   4906   5792   9746  16581  27022   \n",
       "Animation      31    93   587   1312   1067   1505   2549   3871   6726   \n",
       "Children       56   218   936   2411   1809   2470   4264   6150  10073   \n",
       "Comedy        247   767  4512  12458  10428  13223  23018  33914  49961   \n",
       "Crime          98   292  1742   3913   3676   4361   7784  12173  19416   \n",
       "Documentary     3    18   124    291    185    290    679   1368   2016   \n",
       "Drama         328   971  5945  14897  11706  14168  24326  36247  55398   \n",
       "Fantasy        46   182  1165   2780   2240   3001   5081   8456  13801   \n",
       "Film-Noir       8    28   225    473    321    415    665    981   1846   \n",
       "Horror         54   136  1133   2562   2347   2559   3854   6619  11215   \n",
       "IMAX            0     0     7     21     21     22     24     56     85   \n",
       "Musical        31   125   651   1586   1111   1367   2488   3684   5304   \n",
       "Mystery        35   134   867   2053   1674   2308   3491   5533   8987   \n",
       "Romance       139   467  2523   6034   4636   6021   9802  15132  22690   \n",
       "Sci-Fi         93   338  1931   4287   3560   4412   7081  11722  18997   \n",
       "Short           0     0     0      0      0      0      0      1      0   \n",
       "Thriller      189   543  3137   7318   6641   7943  12489  20561  33417   \n",
       "War            56   145   741   1631   1448   1518   2583   4101   6704   \n",
       "Western        13    46   268    732    634    535   1012   1580   2263   \n",
       "\n",
       "date_year     2006   2007   2008  2009  \n",
       "genre                                   \n",
       "Action       53049  46625  42087   961  \n",
       "Adventure    40023  34476  31521   702  \n",
       "Animation    10872   8839   8704   195  \n",
       "Children     15200  11619  10798   281  \n",
       "Comedy       72448  58235  52867  1271  \n",
       "Crime        29321  25559  23919   513  \n",
       "Documentary   3080   2633   2287    24  \n",
       "Drama        80793  72064  65850  1338  \n",
       "Fantasy      21843  20140  17313   374  \n",
       "Film-Noir     2811   2405   1909    17  \n",
       "Horror       15359  13158  11094   265  \n",
       "IMAX           123    322    796    18  \n",
       "Musical       8163   6270   5767   111  \n",
       "Mystery      13108  11645  10103   217  \n",
       "Romance      33372  26982  24840   608  \n",
       "Sci-Fi       26180  23587  21660   426  \n",
       "Short            0      0      1     0  \n",
       "Thriller     49014  45362  39937   898  \n",
       "War           9620   8952   7939   166  \n",
       "Western       3357   2723   2424    64  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# another, visually cleaner alternative\n",
    "pd.crosstab(genre_ratings.genre, genre_ratings.date_year)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86d7c8ec-eb63-4d26-b428-4dc226a44dae",
   "metadata": {},
   "source": [
    "### Univariate Statistics per Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "676a8f16-c06a-4e7a-b480-54cad0c4d12f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Action</th>\n",
       "      <td>241593.0</td>\n",
       "      <td>3.338652</td>\n",
       "      <td>1.018203</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventure</th>\n",
       "      <td>179426.0</td>\n",
       "      <td>3.401007</td>\n",
       "      <td>1.004163</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Animation</th>\n",
       "      <td>46351.0</td>\n",
       "      <td>3.526450</td>\n",
       "      <td>0.963297</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Children</th>\n",
       "      <td>66285.0</td>\n",
       "      <td>3.310410</td>\n",
       "      <td>1.045600</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy</th>\n",
       "      <td>333349.0</td>\n",
       "      <td>3.346851</td>\n",
       "      <td>1.018833</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crime</th>\n",
       "      <td>132767.0</td>\n",
       "      <td>3.601392</td>\n",
       "      <td>0.949798</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Documentary</th>\n",
       "      <td>12998.0</td>\n",
       "      <td>3.706840</td>\n",
       "      <td>0.933780</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama</th>\n",
       "      <td>384031.0</td>\n",
       "      <td>3.608434</td>\n",
       "      <td>0.926720</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fantasy</th>\n",
       "      <td>96422.0</td>\n",
       "      <td>3.435113</td>\n",
       "      <td>1.008190</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Film-Noir</th>\n",
       "      <td>12104.0</td>\n",
       "      <td>3.925190</td>\n",
       "      <td>0.822689</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Horror</th>\n",
       "      <td>70355.0</td>\n",
       "      <td>3.203411</td>\n",
       "      <td>1.082659</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMAX</th>\n",
       "      <td>1495.0</td>\n",
       "      <td>3.757191</td>\n",
       "      <td>0.916661</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Musical</th>\n",
       "      <td>36658.0</td>\n",
       "      <td>3.470157</td>\n",
       "      <td>1.009008</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mystery</th>\n",
       "      <td>60155.0</td>\n",
       "      <td>3.608121</td>\n",
       "      <td>0.941557</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romance</th>\n",
       "      <td>153246.0</td>\n",
       "      <td>3.466619</td>\n",
       "      <td>0.977567</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sci-Fi</th>\n",
       "      <td>124274.0</td>\n",
       "      <td>3.325116</td>\n",
       "      <td>1.034849</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Short</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.75</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.25</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thriller</th>\n",
       "      <td>227449.0</td>\n",
       "      <td>3.431804</td>\n",
       "      <td>0.981452</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>War</th>\n",
       "      <td>45604.0</td>\n",
       "      <td>3.663933</td>\n",
       "      <td>0.941441</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western</th>\n",
       "      <td>15651.0</td>\n",
       "      <td>3.537538</td>\n",
       "      <td>0.962432</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count      mean       std  min   25%  50%   75%  max\n",
       "genre                                                               \n",
       "Action       241593.0  3.338652  1.018203  0.5  3.00  3.5  4.00  5.0\n",
       "Adventure    179426.0  3.401007  1.004163  0.5  3.00  3.5  4.00  5.0\n",
       "Animation     46351.0  3.526450  0.963297  0.5  3.00  3.5  4.00  5.0\n",
       "Children      66285.0  3.310410  1.045600  0.5  3.00  3.5  4.00  5.0\n",
       "Comedy       333349.0  3.346851  1.018833  0.5  3.00  3.5  4.00  5.0\n",
       "Crime        132767.0  3.601392  0.949798  0.5  3.00  4.0  4.00  5.0\n",
       "Documentary   12998.0  3.706840  0.933780  0.5  3.50  4.0  4.50  5.0\n",
       "Drama        384031.0  3.608434  0.926720  0.5  3.00  4.0  4.00  5.0\n",
       "Fantasy       96422.0  3.435113  1.008190  0.5  3.00  3.5  4.00  5.0\n",
       "Film-Noir     12104.0  3.925190  0.822689  0.5  3.50  4.0  4.50  5.0\n",
       "Horror        70355.0  3.203411  1.082659  0.5  2.50  3.5  4.00  5.0\n",
       "IMAX           1495.0  3.757191  0.916661  0.5  3.00  4.0  4.50  5.0\n",
       "Musical       36658.0  3.470157  1.009008  0.5  3.00  3.5  4.00  5.0\n",
       "Mystery       60155.0  3.608121  0.941557  0.5  3.00  4.0  4.00  5.0\n",
       "Romance      153246.0  3.466619  0.977567  0.5  3.00  3.5  4.00  5.0\n",
       "Sci-Fi       124274.0  3.325116  1.034849  0.5  3.00  3.5  4.00  5.0\n",
       "Short             2.0  4.000000  0.707107  3.5  3.75  4.0  4.25  4.5\n",
       "Thriller     227449.0  3.431804  0.981452  0.5  3.00  3.5  4.00  5.0\n",
       "War           45604.0  3.663933  0.941441  0.5  3.00  4.0  4.50  5.0\n",
       "Western       15651.0  3.537538  0.962432  0.5  3.00  3.5  4.00  5.0"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rating behavior per genre\n",
    "genre_ratings.groupby(\"genre\")[\"rating\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee056b97-c9f1-488f-8010-c8fdc625772a",
   "metadata": {},
   "source": [
    "### Correlation and Covariance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "70a5c18f-e736-45fb-900f-52e1f52d4366",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.150556177288637"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.4935367209137638"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# covariance\n",
    "movies[\"rtAllCriticsRating\"].cov(movies[\"rtTopCriticsRating\"])\n",
    "movies[\"rtAllCriticsRating\"].cov(movies[\"rtAudienceRating\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e1fd5e8c-8cf1-431a-b279-e8ea0153a8a8",
   "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>rtAllCriticsRating</th>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>rtAllCriticsRating</th>\n",
       "      <td>6.749855</td>\n",
       "      <td>2.405259</td>\n",
       "      <td>3.461344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <td>2.405259</td>\n",
       "      <td>2.379055</td>\n",
       "      <td>2.565817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "      <td>3.461344</td>\n",
       "      <td>2.565817</td>\n",
       "      <td>9.857172</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    rtAllCriticsRating  rtAudienceRating  rtTopCriticsRating\n",
       "rtAllCriticsRating            6.749855          2.405259            3.461344\n",
       "rtAudienceRating              2.405259          2.379055            2.565817\n",
       "rtTopCriticsRating            3.461344          2.565817            9.857172"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# covariance pairwise between multiple variables\n",
    "movies[[\"rtAllCriticsRating\", \"rtAudienceRating\", \"rtTopCriticsRating\"]].cov()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "bc9a0ce1-7237-4938-9839-7b30905e0597",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7183644677215845"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# correlation coefficient\n",
    "movies[\"rtAudienceRating\"].corr(movies[\"rtAllCriticsRating\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b0d8b4a-d4ac-4af0-9681-899822d3824c",
   "metadata": {},
   "source": [
    "We can also look into the pairwise correlation between multiple variables, displayed as a correlation matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "32ff236f-75a7-4b72-98ce-60cd26a9f72c",
   "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>rtAllCriticsRating</th>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>rtAllCriticsRating</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.600223</td>\n",
       "      <td>0.424347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <td>0.600223</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.529843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "      <td>0.424347</td>\n",
       "      <td>0.529843</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    rtAllCriticsRating  rtAudienceRating  rtTopCriticsRating\n",
       "rtAllCriticsRating            1.000000          0.600223            0.424347\n",
       "rtAudienceRating              0.600223          1.000000            0.529843\n",
       "rtTopCriticsRating            0.424347          0.529843            1.000000"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# correlation coefficient pairwise between multiple variables\n",
    "movies[[\"rtAllCriticsRating\", \"rtAudienceRating\", \"rtTopCriticsRating\"]].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c0ab0b65-7846-48da-8db2-c2e8247e8637",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3n+IaNGhA8+bNOXPmDAALFy6kf//+BAUFMXXqVAzD4IsvviA9PZ2xY8cSGhpKXl4eQ4cO5ccffwSgXbt2zJs3j5CQEAYNGsTZs2cBOHHiBIMGDSI4OJh58+bRrl07Z067iMhtY7dbnH5UB6dnVsePH2fIkCF89dVX1K5dm4SEBObOnQtcXbp7+umn8fT0pEGDBqSnp5fbV35+PlOnTmXRokVs2LDBkSB+LyYmhhdffJH169ezYMECpkyZ4th29OhRli1bxieffMIHH3xAYWEhhw4dIjY2lhUrVvDZZ58xefLkCvu55tSpU+Tn5+Pt7Q3ACy+8wPr160lMTCQvL48dO3YQEBCAj48P7777LgkJCXh4eJTo47fffqNNmzZ89tlndOzYkXXr1jnGHzZsGJ9//jmNGzd28oyLiNw+Zp9ZOV1g8cADD9C2bdvrbktKSmLYsGHA1WW1pKQkfHx8yuzrl19+oWnTpjz88MMAhISEOP5hL+7bb78tcT3oypUr5OTkANC1a1fc3d1p2LAhDRs25Ny5c+zatYuAgAAaNmwIQP369SvsZ/PmzXz33XccPXqUqVOnUrNmTeDqrHDp0qXk5eVx8eJFWrRogZ+fX7nnqEaNGnTr1g0AHx8fvvnmGwD279/PBx98AEBwcDDvvPNOuf2IiNxuZi+wcDpZ1a5d+7qvX7x4kV27dnHw4EEsFgs2mw2LxUJkZCSurq7Y7f+54VR+fn6lgrPb7axbt86RQIpzd3d3/L+rqytFRUU31E9gYCBRUVH8+OOPhIeH4+fnx7333sv06dNZv349TZo0YcGCBU7FXqNGDSyWqz9wFxcXbDabM4cpIlLtzF66fkPVgG5ubhQWFgKwdetWQkND2bFjB9u3byclJYWmTZuyd+9eHnzwQY4cOUJBQQGXLl0iNTUVgEceeYTMzExOnDgBUGZRxt/+9jdWrVrleH7gwIFy4+rcuTNffPEFFy5cAK4mUmf78fX1JSQkhJUrVzoSU4MGDcjJyWHr1q2OdnXq1HHMypzVpk0btm3bBpR9rCIi1cmoxKMiO3fupFevXvTo0eO61d0zZ84kNDSU0NBQevXqRceOHSvs84Y+ZzVo0CBCQkJo1aoVp0+fZsSIESW29+zZk8TERKZPn05AQABBQUE0bdqUVq1aAVCzZk2io6OJiIigVq1adOjQ4boJYPLkyURHRxMcHIzNZqNjx46O4ovradGiBaNGjWLo0KG4uLjQqlUrZs2a5XQ/I0aMoF+/fowcOZKBAwcSFBTEfffdh6+vr6NN3759mTZtGh4eHsTHxzt1viZNmsS4ceOIjY3l6aefpm7duk7tJyJyu9jsNzR3Kd2PzUZ0dDRxcXFYrVYGDBiAn59fiarpSZMmOf5/1apV/N///V+F/VoMo7qq5v84cnNz8fDwwGKxkJSURGJi4nXL/4ub+PCQ2xTdH1v03hnVHcJdr3e7V6s7hLvetpNf3HQf/2w8wOm2T2d9Wua2H374gYULF7Js2TIAFi9eDFCiMry45557jtGjR/PUU0+VO6buYHEb/PTTT0RHR2MYBvfeey8zZ86s7pBEREowcP6aVXx8fImVpbCwMMLCwgDIzs4uUfVstVpJS0u7bj+ZmZlkZGTQuXPnCsdUsroNOnbsyGeffVbdYYiIlMleiTW24snpZiQlJdGrVy9cXV0rbFs1i5QiInJHs2Nx+lEeq9VKVlaW43l2djZWq/W6bTdv3kzv3r2dik/JSkREMLA4/SiPr68vx44d4+TJkxQUFJCUlHTdz6geOXKES5cuOX1HHy0DiogItkpcsyqPm5sbUVFRDB8+HJvNRv/+/WnRogXz58/Hx8cHf39/4OqsKjAw0PHZ1Ar7rZLoRETkjmavuInTunbtSteuXUu8NmbMmBLPR48eXak+laxERKRKk9WtoGQlIiKVKl2vDkpWIiJCNX3zh9OUrEREpMKS9OqmZCUiIpj9OyKUrEREBLuTJeTVRclKRESc+uqP6qRkJSIiKl0XERHzUzWgiIiYXlXdbulWUbISERHNrERExPx0zUpERExP1YAiImJ6WgYUERHT0zKgiIiYnk0zKxERMTvNrERExPSUrERExPRUDSgiIqanakARETE9LQOKiIjp6csXRUTE9LQMKCIipqdlQBERMT1VA8oNmXMqpbpD+EPY1+7V6g7hrpf0w4fVHYI4wW7ydKVkJSIiKrAQERHzM/s1K5fqDkBERKqf3eL8oyI7d+6kV69e9OjRgyVLlly3zebNmwkMDKR37968+eabFfapmZWIiFTZNSubzUZ0dDRxcXFYrVYGDBiAn58fXl5ejjbHjh1jyZIlrFmzhnr16nHu3LkK+9XMSkREMCrxKE9aWhrNmzenWbNmuLu707t3b5KTk0u0WbduHc8//zz16tUD4E9/+lOF8WlmJSIilbpmFR8fT3x8vON5WFgYYWFhAGRnZ9O4cWPHNqvVSlpaWon9jx07BsBzzz2H3W7ntddeo0uXLuWOqWQlIiLYKrEMWDw53dBYNhvHjx9n1apVZGVl8cILL/D5559z7733lrmPlgFFRAR7JR7lsVqtZGVlOZ5nZ2djtVpLtfHz86NGjRo0a9aMhx9+2DHbKouSlYiIYMdw+lEeX19fjh07xsmTJykoKCApKQk/P78Sbbp3786ePXsAOH/+PMeOHaNZs2bl9qtlQBERqbL7V7i5uREVFcXw4cOx2Wz079+fFi1aMH/+fHx8fPD39+fpp5/mm2++ITAwEFdXVyIjI2nQoEG5/VoMwzD3PTb+oNzcH6zuEP4Q/Ky+1R3CXU+3W7r1atz3yE33Mebh55xuO//Y2pser7I0sxIRkUoVWFQHJSsREdGNbEVExPzMnaqUrEREBM2sRETkDmD2u64rWYmICIZmViIiYnaqBhQREdPTMqCIiJie3eT3h1CyEhERky8CKlmJiAgqXRcRkTuAqgFFRMT0ipSsRETE7DSzEhER01PpuoiImJ7Zv9pQyUpERFQNKCIi5qfbLYmIiOlpZiUiIqZ3112zWrRoEaNGjeLChQu89NJLAJw9exYXFxcaNmwIwCeffIK7u7vTfW7atImlS5disVhwdXUlODiY8PDwUu3WrFlDrVq16NOnDxs2bOCpp57CarUCMHnyZF5++WW8vLycHjcjI4PAwEA8PT0pLCzEx8eHmJgYatSoUeY+u3fvpkaNGrRv375UTCIid6q7qhrQMAxiY2MZNWoUDRo0ICEhAYAFCxZQu3bt6yaYiqSkpLBixQqWLVuG1WqloKCATZs2lWpXVFTE4MGDHc83btxIixYtHMkqJiam0mMDPPTQQyQkJGCz2Xj55ZfZsmULISEhZbbfs2cPtWvXdiSr4jGJiNyp7vjPWWVkZBAeHk6bNm34/vvvycvLIzQ0FC8vL+bOnVuqfWpqKrNnz8Zms+Hj48P06dNxd3fHz8+PgIAA/vnPf1KzZk3mzp1L8+bNWbJkCZGRkY6k4+7uzqBBgwAYOnQoLVu2ZN++fQQFBZGTk0Pt2rV58MEHSU9PZ+zYsXh4eBAfH8+IESOIjIzE19eXnTt3Mm/ePGw2Gw0aNGDFihXs2bPHkdAsFgsfffRRibhdXV1p3bo12dnZAGzfvp3Y2FgKCwupX78+7777Lnl5eaxduxYXFxc+++wzpk6dSmpqqiNRDx06lNatW7N7924uX75MTEwMHTt2JDc3lwkTJnDo0CE8PT05ffo0UVFR+Pr63txPT0SkitwV16yOHz/O7Nmzeeedd2jXrp1jRvV7+fn5TJgwgeXLl+Pp6UlkZCQff/yxY7nwnnvu4fPPP2fTpk3MnDmTxYsXc+jQIXx8fMocu7CwkA0bNgBXZ3AAAQEBrF692pGcijt//jxTp07lo48+olmzZly8eBGAf/zjH0RFRdGhQwdycnKoWbNmqdj/9a9/MXnyZAA6dOjAunXrsFgsfPLJJyxdupQJEybw3HPPlZhFpqamlujHZrPx6aefkpKSwsKFC1m+fDkff/wx9erVY/PmzRw8eFBLhiJiOjbD3AuBLs40euCBB2jbtm2F7Y4ePUrTpk3x9PQEoG/fvuzdu9exPSgoCIDevXuzf/9+pwIMDAx0qt01+/fvp2PHjjRr1gyA+vXrA9C+fXtmzZrFypUruXz5Mm5uV/P0iRMnCA0N5a9//Sv3338/LVu2BCArK4vw8HCCg4NZunQphw4dcmr8Hj16APDnP/+ZzMxMAPbt2+c4jsceewxvb+9KHZOIyK1mVOK/6uBUsqpdu/YtC8DLy4v09PQyt9eqVatKxomIiGDGjBnk5eUxePBgjhw5AvznmtWXX35Jeno6ycnJAMyYMYPnn3+ezz//nOjoaAoKCpwa51phiYuLCzabrUpiFxG51eyG4fSjOjiVrIpzc3OjsLDwuts8PT3JzMzk+PHjACQkJPDEE084tm/ZsgWAzZs3065dOwBGjhzJnDlzOHPmDAAFBQV88sknFcZRp04dcnJySr3etm1b9u7dy8mTJwEcy4AnTpzA29ubiIgIfH19OXr0aIn9GjZsyNixY1myZAkAly9fdlxHK17wUda45Wnfvr3j2A8fPszBgwcrtb+IyK1mVOJRHSpduj5o0CBCQkJo1apVqQKLmjVr8vbbbzNmzBhHgUXxarl///vfBAcH4+7uznvvvQdA165dOXv2LC+//DKGYWCxWOjfv3+FcfTt25dp06Y5CiyuadiwIdHR0YwePRq73c6f/vQn4uLiWLFiBbt378ZisdCiRQu6dOnC6dOnS/TZvXt3FixYwN69e3nttdcYM2YM9erVo1OnTmRkZADQrVs3Xn/9dZKTk5k6dapT52zIkCFMmDCBwMBAHnnkEby8vLjnnnuc2ldE5HYwe4GFxbhNnwTz8/Pj008/dXwW64/EZrNRVFREzZo1OXHiBC+99BJffPFFuZ9Fc3N/8DZG+MflZ1VF5q2W9MOH1R3CXa/GfY/cdB9PPtjN6bapmTtuerzK0h0sboPc3FyGDRtGUVERhmEwbdq0Sn1oWkTkVqvKasCdO3cSExOD3W5n4MCBRERElNi+YcMG3nnnHcellhdeeIGBAweW2+dtS1bbt2+/XUOZTt26dR3l9yIiZlRVVX42m43o6Gji4uKwWq0MGDAAPz+/UncXCgwMJCoqyul+K11gISIidx/DMJx+lCctLY3mzZvTrFkz3N3d6d27t6PK+mZoGVBERCpVYBEfH1+isC0sLIywsDAAsrOzady4sWOb1WolLS2tVB/btm3ju+++w9PTk4kTJ9KkSZNyx1SyEhGRSt11vXhyuhHdunUjKCgId3d31q5dy/jx41m5cmW5+2gZUEREsGF3+lEeq9VKVlaW43l2drajkOKaBg0aOIrMBg4cyE8//VRhfEpWIiJSZXew8PX15dixY5w8eZKCggKSkpLw8/Mr0ab4Z1y3b9/Oo48+WmF8WgYUEZEqqwZ0c3MjKiqK4cOHY7PZ6N+/Py1atGD+/Pn4+Pjg7+/PqlWr2L59O66urtSrV4+33367wn5v24eCpXL0oeDbQx8KvvX0oeBbryo+FPz4/X9xuu2B03tuerzK0sxKRETu/C9fFBGRu1913U3dWUpWIiJi+i9fVLISEREtA4qIiPkZmlmJiIjZmf37rJSsRESkUrdbqg5KViIiopmViIiYn82ua1YiImJyqgYUERHT0zUrERExPV2zEhER09PMSkRETE8FFiIiYnpaBhQREdPTMqCIiJieviJERERMT5+zEhER09PMSkRETM+urwgRERGzU4GFiIiYnpKViIiYnrlTFVgMs6dTERH5w3Op7gBEREQqomQlIiKmp2QlIiKmp2QlIiKmp2QlIiKmp2QlIiKmp2QlIiKmp2R1h1q0aFGp17766iu8vb05cuSI47WMjAyCgoIA2L17NyNHjnRsS0lJoV+/fgQGBtKnTx9mzZp13bGSk5NZsmSJY4zDhw87ts2fP59vv/220vE//vjjhIaGEhQUxKhRo7h06VK57Q8cOEBKSsp1Y7oVnD2/zip+7m917MVt2LCBzp07ExoaSkBAAMuXL3dqn+zsbMfzyZMnl/iZV4Vr5/fChQuEhoYSGhrKU089xdNPP+14XlBQUKk+N23aRFBQEMHBwfTp04dly5Zdt92aNWvYtGkTUDXHmpGRQevWrQkNDSUwMJDIyEgKCwvL3Wf37t18//33141JymDIHcdutxutW7cu9fqYMWOMwYMHG/Pnz3e8dvLkSaN3796GYRjGrl27jIiICMMwDOPnn382/P39jcOHDxuGYRhFRUXG6tWrS/VZWFhY4vn48eONLVu23PQxtG3b1vH/kZGRxocfflhu+/Xr1xvTp0+/6XGdUZnz66zi5/52Kn7ezp8/b/zlL38xTp06Ve4+L7zwgpGWlnbLYirr/L7//vvG0qVLb6jPr7/+2ujTp4+RlZVlGIZh5OfnG/Hx8aXa/f73uSqOtfjfWFFRkTF06FAjISGh3H1u5lj/qHS7pTtERkYG4eHhtGnThu+//568vDxCQ0Px8vJi7ty55OTksG/fPlauXMmoUaN4/fXXy+1v6dKljBo1ikcffRQAV1dXhgwZAsCECRNwd3fnwIEDtG/fHm9vb9LT0wkKCmL79u3s2bOH2NhYFixYwIcffsgzzzxDQEAAaWlpzJw5k99++w13d3eWL1/Or7/+ysSJEyksLMRut7NgwQIefvjhErG0bduWn3/+GYC0tDRiYmLIz8/Hw8ODmTNn0rRpU95//33y8vLYt28fI0eOJC8vj/T0dKKiopgwYQJ169YlPT2dM2fOMG7cOAICArDb7URHR7Nr1y6aNGmCm5sb/fv3JyAgoMrO7+7du/nHP/7B4sWLAYiOjsbHx4d+/fqxc+dOZs6cSa1atejQoYNjrA0bNjhiP3/+PNOmTePUqVMATJo0iQ4dOrBgwQJOnTpFRkYGp06d4sUXX2TYsGHA1RnEsmXLsFgseHt7M2fOnDL7Ka5BgwY0b96cM2fO0KRJExYuXMiOHTvIz8+nXbt2REdHs3XrVtLT0xk7diweHh7Ex8czYsQIIiMj8fX1pV27dgwbNowdO3bg4eHBhx9+yH333ceJEycYO3Ysubm5+Pn5sXLlSn744Qenz+/vpaamMnv2bGw2Gz4+PkyfPh13d3f8/PwICAjgn//8JzVr1mTu3Lk0b96cJUuWEBkZidVqBcDd3Z1BgwYBMHToUFq2bMm+ffsICgoiJyeH2rVr8+CDD5Z7rDt37mTevHnYbDYaNGjAihUr2LNnDzExMQBYLBY++uijEnG7urrSunVrx2xt+/btxMbGUlhYSP369Xn33XfJy8tj7dq1uLi48NlnnzF16lRSU1OpXbs24eHhDB06lNatW7N7924uX75MTEwMHTt2JDc3lwkTJnDo0CE8PT05ffo0UVFR+Pr6ljp/d6XqzpbinJMnTxre3t7GDz/8YBhGyZmJYRhGQkKCMXHiRMMwDCMsLMz48ccfHftdb2bVp08f48CBA9cda/z48UZERIRRVFRkGEbJd+e/n1lde56fn2/4+fkZ//rXvwzDMIzLly8bhYWFRnR0tONdZn5+vpGbm1si/qKiImP06NFGSkpKif0MwzC++eYb47XXXisVw/ViGj16tGGz2YxDhw4Z3bt3NwzDMLZs2WIMHz7csNlsxunTp42OHTuWOSu80fP7+xnT9OnTjfXr1xt5eXlGly5djKNHjxp2u914/fXXHe2Kx/73v//d+O677wzDMIzMzEwjICDAMIyr77zDwsKM/Px849y5c8Zf/vIXo6CgwDh48KDRs2dP49y5c4ZhGMaFCxfK7af4WJmZmUZISIiRl5dXYl/DMIyxY8caycnJhmGUnm0Uf/7YY4852s2ePdv44IMPDMMwjIiICOPzzz83DMMwPv7441Lnr6Lze+2Yly5d6jh3v/zyi2EYhjFu3DgjLi7OMAzD6Natm2MWvnHjRsc5feKJJ4xLly6V6vNa/NOmTSs1TnnHeu7cOaNLly7GiRMnSpyrkSNHGnv37jUMwzCuXLliFBYWlvgby8vLM1544QXH39bFixcNu91uGIZhrFu3znj77bdLxXC9mK61+/rrr40XX3zRMAzDWLp0qTF16lTDMK6ujDz++OO3dAZsNppZ3UEeeOAB2rZte91tSUlJjnfegYGBJCUl4ePjc8NjBQQE4Orq6nT7o0eP0qhRI1q3bg1A3bp1gauzpkWLFpGVlUXPnj0ds6pr76yzs7N59NFHeeqppwC4fPky48eP5/jx41gslgrX/q/p3r07Li4ueHl5cfbsWQD27dtHQEAALi4uNGrUiE6dOpXbR1We319++YWmTZs6jjckJIR169aVavftt9+WuEZy5coVcnJyAOjatSvu7u40bNiQhg0bcu7cOXbt2kVAQAANGzYEoH79+hX2s3nzZr777juOHj3K1KlTqVmzJnB1Vrh06VLy8vK4ePEiLVq0wM/Pr9xzVKNGDbp16waAj48P33zzDQD79+/ngw8+ACA4OJh33nmn1L7lnd/ijh49StOmTfH09ASgb9++rF69mpdeegnAcQ22d+/evP322xX2B1d/ZpWxf/9+OnbsSLNmzYD/nOf27dsza9YsgoOD6dmzJ3Xq1AHgxIkThIaGkpGRwTPPPEPLli0ByMrK4o033uDMmTMUFBTQtGlTp8bv0aMHAH/+85/JzMwErv4+X/sdfOyxx/D29q7UMd3plKzuILVr177u6xcvXmTXrl0cPHgQi8WCzWbDYrEQGRlZZl9eXl6kp6c7/qh+r1atWlUSc3BwMG3atOHrr78mIiKC6dOn8+STT+Lh4UFCQgK5ubmEh4ezevVqhg0bxvz58+nUqRMffPABGRkZjj/Oiri7u990rDdyfl1dXbHb//Oldfn5+ZUa0263s27dOkcCKa74Mbm6ulJUVHRD/QQGBhIVFcWPP/5IeHg4fn5+3HvvvUyfPp3169fTpEkTFixY4FTsNWrUwGKxAODi4oLNZnPmMIGyz29VuPb7/OSTT153e1X9PkdERNC1a1dSUlIYPHgwS5cupWbNmjz00EMkJCRw/vx5Bg8eTHJyMv7+/syYMYOXXnoJf39/du/ezcKFC50a59rPvrLn+G6masA7lJubm2PWsXXrVkJDQ9mxYwfbt28nJSWFpk2bsnfv3jL3Dw8PZ/HixRw9ehS4+o/dmjVrKhy3Tp06jnfsxXl6enLmzBnS0tKAq+/si4qKOHnyJM2aNWPYsGH4+/s7rk1dU6tWLaZMmUJcXBxFRUVcvnzZcd1h48aNFY5bnvbt27Nt2zbsdjtnz55lz549Tu/r7Pl98MEHOXLkCAUFBVy6dInU1FQAHnnkETIzMzlx4gRwdWZ2PX/7299YtWqV4/mBAwfKjatz58588cUXXLhwAbiaSJ3tx9fXl5CQEFauXOlITA0aNCAnJ4etW7c62t3IuW7Tpg3btm0Dyj7W4oqf39/z9PQkMzOT48ePA5CQkMATTzzh2L5lyxbg6oyxXbt2AIwcOZI5c+Zw5swZAAoKCvjkk08qjKOsY23bti179+7l5MmTwH/O84kTJ/D29iYiIgJfX1/H3881DRs2ZOzYsY5qz+K/z8Wr/W709/nasR8+fJiDBw9Wav87nZLVHWrQoEGEhITw5ptvkpiYSPfu3Uts79mzJ4mJiWXu37JlSyZNmsSbb77Js88+S1BQkOMPszyBgYEsW7aMPn36OP4hhqvvBOfNm8eMGTMICQnhlVdeIT8/ny1bthAUFERoaCgHDx6kT58+pfps1aoV3t7eJCYmMnz4cN577z369OlTYibRqVMnDh8+TGhoKJs3b3biDEGvXr2wWq0EBgYybtw4WrVqxT333OPUvs6e3yZNmhAQEEBQUBD//d//TatWrQCoWbMm0dHRRERE0LdvX8ey3e9NnjyZ9PR0goODCQwMrPANQ4sWLRg1ahRDhw4lJCTE8XEDZ/sZMWIEGzZswMXFhYEDBxIUFER4eHiJi/R9+/Zl2rRphIaGkpeX59T5mjRpEnFxcQQHB3P8+HHHMnBZip/f36tZsyZvv/02Y8aMITg4GIvFwuDBgx3b//3vfxMcHMzKlSuZOHEicHXJ9Pnnn+fll1+md+/e9OvXjytXrlQYd1nH2rBhQ6Kjoxk9ejQhISG88cYbAKxYscJRHu/m5kaXLl1K9dm9e3dyc3PZu3cvr732GmPGjKFfv36OpUSAbt268eWXXxIaGlrum8rihgwZwoULFwgMDOR///d/8fLycvr3+W6g77OSu1pOTg516tThwoULDBw4kDVr1tCoUaPqDuuuk5ubi4eHBxaLhaSkJBITE4mNja3ycfz8/Pj000/LTP53M5vNRlFRETVr1uTEiRO89NJLfPHFF1WyBH4n0DUruatd+8BxYWEhr776qhLVLfLTTz8RHR2NYRjce++9zJw5s7pDuuvk5uYybNgwioqKMAyDadOm/WESFWhmJSIidwBdsxIREdNTshIREdNTshIREdNTshIREdNTshIREdP7f15326Eb/VklAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize correlation matrix as heatmap\n",
    "sns.heatmap(\n",
    "    movies[\n",
    "        [\"rtAllCriticsRating\", \"rtAudienceRating\", \"rtTopCriticsRating\"]\n",
    "    ].corr()\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f08e7f6-974a-4630-9bd9-290c83a543c0",
   "metadata": {},
   "source": [
    "## Multivariate Graphical EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d1fe203-cb95-4544-83b1-aa3e083af95e",
   "metadata": {},
   "source": [
    "### Univariate Graph per Category"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2130477d-1397-4eb5-8ac2-b50e42a95c2d",
   "metadata": {},
   "source": [
    "Performing multivariate, graphical EDA often simply means that we look at univariate distributions for multiple categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "fb3f9f00-f58d-4a14-8523-e7400a5de832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# boxplot with rating distribution per genre\n",
    "ax = sns.boxplot(x=\"genre\", y=\"rating\", data=genre_ratings)\n",
    "locs, labels = plt.xticks()\n",
    "plt.setp(labels, rotation=60)\n",
    "ax.set_xticklabels(labels, fontsize=10, rotation=30, ha=\"right\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48f4acaf-b07f-4225-8b8a-70b0db19df08",
   "metadata": {},
   "source": [
    "### Scatterplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "7f7545e9-34b3-459a-b7ff-78c29d9d1c6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>imdbID</th>\n",
       "      <th>spanishTitle</th>\n",
       "      <th>imdbPictureURL</th>\n",
       "      <th>year</th>\n",
       "      <th>rtID</th>\n",
       "      <th>rtAllCriticsRating</th>\n",
       "      <th>rtAllCriticsNumReviews</th>\n",
       "      <th>rtAllCriticsNumFresh</th>\n",
       "      <th>rtAllCriticsNumRotten</th>\n",
       "      <th>rtAllCriticsScore</th>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "      <th>rtTopCriticsNumReviews</th>\n",
       "      <th>rtTopCriticsNumFresh</th>\n",
       "      <th>rtTopCriticsNumRotten</th>\n",
       "      <th>rtTopCriticsScore</th>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <th>rtAudienceNumRatings</th>\n",
       "      <th>rtAudienceScore</th>\n",
       "      <th>rtPictureURL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy story</td>\n",
       "      <td>114709</td>\n",
       "      <td>Toy story (juguetes)</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTMwNDU0NTY2Nl5BMl5BanBnXkFtZTcwOTUxOTM5Mw@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>toy_story</td>\n",
       "      <td>9.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>102338.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/93/63/10936393_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji</td>\n",
       "      <td>113497</td>\n",
       "      <td>Jumanji</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMzM5NjE1OTMxNV5BMl5BanBnXkFtZTcwNDY2MzEzMQ@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>1068044-jumanji</td>\n",
       "      <td>5.6</td>\n",
       "      <td>28.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>44587.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>http://content8.flixster.com/movie/56/79/73/5679734_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpy Old Men</td>\n",
       "      <td>107050</td>\n",
       "      <td>Dos viejos gruñones</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTI5MTgyMzE0OF5BMl5BanBnXkFtZTYwNzAyNjg5._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1993</td>\n",
       "      <td>grumpy_old_men</td>\n",
       "      <td>5.9</td>\n",
       "      <td>36.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>10489.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>http://content6.flixster.com/movie/25/60/256020_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale</td>\n",
       "      <td>114885</td>\n",
       "      <td>Esperando un respiro</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTczMTMyMTgyM15BMl5BanBnXkFtZTcwOTc4OTQyMQ@@._V1._SY314_CR4,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>waiting_to_exhale</td>\n",
       "      <td>5.6</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>5666.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>http://content9.flixster.com/movie/10/94/17/10941715_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II</td>\n",
       "      <td>113041</td>\n",
       "      <td>Vuelve el padre de la novia (Ahora también abuelo)</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTg1NDc2MjExOF5BMl5BanBnXkFtZTcwNjU1NDAzMQ@@._V1._SY314_CR5,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>father_of_the_bride_part_ii</td>\n",
       "      <td>5.3</td>\n",
       "      <td>19.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13761.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>http://content8.flixster.com/movie/25/54/255426_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10192</th>\n",
       "      <td>65088</td>\n",
       "      <td>Bedtime Stories</td>\n",
       "      <td>960731</td>\n",
       "      <td>Más allá de los sueños</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5Njk5MTUxNF5BMl5BanBnXkFtZTcwMDI3MTg5MQ@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>bedtime_stories</td>\n",
       "      <td>4.4</td>\n",
       "      <td>104.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>108877.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/94/33/10943312_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10193</th>\n",
       "      <td>65091</td>\n",
       "      <td>Manhattan Melodrama</td>\n",
       "      <td>25464</td>\n",
       "      <td>El enemigo público número 1</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTUyODE3Nzc4Nl5BMl5BanBnXkFtZTcwMTAwMTQyMQ@@._V1._SX77_SY140_.jpg</td>\n",
       "      <td>1934</td>\n",
       "      <td>manhattan_melodrama</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>344.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>http://content9.flixster.com/movie/66/44/64/6644647_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10194</th>\n",
       "      <td>65126</td>\n",
       "      <td>Choke</td>\n",
       "      <td>1024715</td>\n",
       "      <td>Choke</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTMxMDI4MTE0Ml5BMl5BanBnXkFtZTcwNTg0NDI3MQ@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>choke</td>\n",
       "      <td>5.6</td>\n",
       "      <td>135.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>26.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>13893.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/85/09/10850932_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10195</th>\n",
       "      <td>65130</td>\n",
       "      <td>Revolutionary Road</td>\n",
       "      <td>959337</td>\n",
       "      <td>Revolutionary Road</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTI2MzY2MDY1N15BMl5BanBnXkFtZTcwMTI1MDk5Mg@@._V1._SY314_CR4,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>revolutionary_road</td>\n",
       "      <td>6.7</td>\n",
       "      <td>194.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>36.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>46044.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>http://content8.flixster.com/movie/10/88/40/10884042_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10196</th>\n",
       "      <td>65133</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>212579</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1999</td>\n",
       "      <td>blackadder-back-forth</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/34/10/69/3410693_det.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10197 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                        title   imdbID  \\\n",
       "0          1                    Toy story   114709   \n",
       "1          2                      Jumanji   113497   \n",
       "2          3               Grumpy Old Men   107050   \n",
       "3          4            Waiting to Exhale   114885   \n",
       "4          5  Father of the Bride Part II   113041   \n",
       "...      ...                          ...      ...   \n",
       "10192  65088              Bedtime Stories   960731   \n",
       "10193  65091          Manhattan Melodrama    25464   \n",
       "10194  65126                        Choke  1024715   \n",
       "10195  65130           Revolutionary Road   959337   \n",
       "10196  65133      Blackadder Back & Forth   212579   \n",
       "\n",
       "                                             spanishTitle  \\\n",
       "0                                    Toy story (juguetes)   \n",
       "1                                                 Jumanji   \n",
       "2                                     Dos viejos gruñones   \n",
       "3                                    Esperando un respiro   \n",
       "4      Vuelve el padre de la novia (Ahora también abuelo)   \n",
       "...                                                   ...   \n",
       "10192                              Más allá de los sueños   \n",
       "10193                         El enemigo público número 1   \n",
       "10194                                               Choke   \n",
       "10195                                  Revolutionary Road   \n",
       "10196                             Blackadder Back & Forth   \n",
       "\n",
       "                                                                                                         imdbPictureURL  \\\n",
       "0      http://ia.media-imdb.com/images/M/MV5BMTMwNDU0NTY2Nl5BMl5BanBnXkFtZTcwOTUxOTM5Mw@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "1      http://ia.media-imdb.com/images/M/MV5BMzM5NjE1OTMxNV5BMl5BanBnXkFtZTcwNDY2MzEzMQ@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "2          http://ia.media-imdb.com/images/M/MV5BMTI5MTgyMzE0OF5BMl5BanBnXkFtZTYwNzAyNjg5._V1._SX214_CR0,0,214,314_.jpg   \n",
       "3      http://ia.media-imdb.com/images/M/MV5BMTczMTMyMTgyM15BMl5BanBnXkFtZTcwOTc4OTQyMQ@@._V1._SY314_CR4,0,214,314_.jpg   \n",
       "4      http://ia.media-imdb.com/images/M/MV5BMTg1NDc2MjExOF5BMl5BanBnXkFtZTcwNjU1NDAzMQ@@._V1._SY314_CR5,0,214,314_.jpg   \n",
       "...                                                                                                                 ...   \n",
       "10192  http://ia.media-imdb.com/images/M/MV5BMjA5Njk5MTUxNF5BMl5BanBnXkFtZTcwMDI3MTg5MQ@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "10193           http://ia.media-imdb.com/images/M/MV5BMTUyODE3Nzc4Nl5BMl5BanBnXkFtZTcwMTAwMTQyMQ@@._V1._SX77_SY140_.jpg   \n",
       "10194  http://ia.media-imdb.com/images/M/MV5BMTMxMDI4MTE0Ml5BMl5BanBnXkFtZTcwNTg0NDI3MQ@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "10195  http://ia.media-imdb.com/images/M/MV5BMTI2MzY2MDY1N15BMl5BanBnXkFtZTcwMTI1MDk5Mg@@._V1._SY314_CR4,0,214,314_.jpg   \n",
       "10196  http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "\n",
       "       year                         rtID  rtAllCriticsRating  \\\n",
       "0      1995                    toy_story                 9.0   \n",
       "1      1995              1068044-jumanji                 5.6   \n",
       "2      1993               grumpy_old_men                 5.9   \n",
       "3      1995            waiting_to_exhale                 5.6   \n",
       "4      1995  father_of_the_bride_part_ii                 5.3   \n",
       "...     ...                          ...                 ...   \n",
       "10192  2008              bedtime_stories                 4.4   \n",
       "10193  1934          manhattan_melodrama                 7.0   \n",
       "10194  2008                        choke                 5.6   \n",
       "10195  2008           revolutionary_road                 6.7   \n",
       "10196  1999        blackadder-back-forth                 0.0   \n",
       "\n",
       "       rtAllCriticsNumReviews  rtAllCriticsNumFresh  rtAllCriticsNumRotten  \\\n",
       "0                        73.0                  73.0                    0.0   \n",
       "1                        28.0                  13.0                   15.0   \n",
       "2                        36.0                  24.0                   12.0   \n",
       "3                        25.0                  14.0                   11.0   \n",
       "4                        19.0                   9.0                   10.0   \n",
       "...                       ...                   ...                    ...   \n",
       "10192                   104.0                  26.0                   78.0   \n",
       "10193                    12.0                  10.0                    2.0   \n",
       "10194                   135.0                  73.0                   62.0   \n",
       "10195                   194.0                 133.0                   61.0   \n",
       "10196                     0.0                   0.0                    0.0   \n",
       "\n",
       "       rtAllCriticsScore  rtTopCriticsRating  rtTopCriticsNumReviews  \\\n",
       "0                  100.0                 8.5                    17.0   \n",
       "1                   46.0                 5.8                     5.0   \n",
       "2                   66.0                 7.0                     6.0   \n",
       "3                   56.0                 5.5                    11.0   \n",
       "4                   47.0                 5.4                     5.0   \n",
       "...                  ...                 ...                     ...   \n",
       "10192               25.0                 4.7                    26.0   \n",
       "10193               83.0                 0.0                     4.0   \n",
       "10194               54.0                 4.9                    26.0   \n",
       "10195               68.0                 6.9                    36.0   \n",
       "10196                0.0                 0.0                     0.0   \n",
       "\n",
       "       rtTopCriticsNumFresh  rtTopCriticsNumRotten  rtTopCriticsScore  \\\n",
       "0                      17.0                    0.0              100.0   \n",
       "1                       2.0                    3.0               40.0   \n",
       "2                       5.0                    1.0               83.0   \n",
       "3                       5.0                    6.0               45.0   \n",
       "4                       1.0                    4.0               20.0   \n",
       "...                     ...                    ...                ...   \n",
       "10192                   6.0                   20.0               23.0   \n",
       "10193                   2.0                    2.0               50.0   \n",
       "10194                   8.0                   18.0               30.0   \n",
       "10195                  25.0                   11.0               69.0   \n",
       "10196                   0.0                    0.0                0.0   \n",
       "\n",
       "       rtAudienceRating  rtAudienceNumRatings  rtAudienceScore  \\\n",
       "0                   3.7              102338.0             81.0   \n",
       "1                   3.2               44587.0             61.0   \n",
       "2                   3.2               10489.0             66.0   \n",
       "3                   3.3                5666.0             79.0   \n",
       "4                   3.0               13761.0             64.0   \n",
       "...                 ...                   ...              ...   \n",
       "10192               3.5              108877.0             63.0   \n",
       "10193               3.7                 344.0             71.0   \n",
       "10194               3.3               13893.0             55.0   \n",
       "10195               3.5               46044.0             70.0   \n",
       "10196               0.0                   0.0              0.0   \n",
       "\n",
       "                                                       rtPictureURL  \n",
       "0      http://content7.flixster.com/movie/10/93/63/10936393_det.jpg  \n",
       "1       http://content8.flixster.com/movie/56/79/73/5679734_det.jpg  \n",
       "2           http://content6.flixster.com/movie/25/60/256020_det.jpg  \n",
       "3      http://content9.flixster.com/movie/10/94/17/10941715_det.jpg  \n",
       "4           http://content8.flixster.com/movie/25/54/255426_det.jpg  \n",
       "...                                                             ...  \n",
       "10192  http://content6.flixster.com/movie/10/94/33/10943312_det.jpg  \n",
       "10193   http://content9.flixster.com/movie/66/44/64/6644647_det.jpg  \n",
       "10194  http://content6.flixster.com/movie/10/85/09/10850932_det.jpg  \n",
       "10195  http://content8.flixster.com/movie/10/88/40/10884042_det.jpg  \n",
       "10196   http://content7.flixster.com/movie/34/10/69/3410693_det.jpg  \n",
       "\n",
       "[10197 rows x 21 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at dataframe again\n",
    "movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "634bbb0c-ecc0-4aff-b385-b55b8fb9feef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oPiTJKHPjZ+P5ebsUzfc3jesW8uzSsX2BaMY8AelnYcy/cIwPt/yM2sYQ0WZSPgHJZzBhWGec26soY86CTpNEOKqgzld6vtQuWp7BV7tO4LxehdRz5PoMpPkEkUgEarUmzfch7YuzWWoL8xlkQS6bQWvFe5/pONs3gxZfx6Y3gEA0DqNGlcanC/taOncU0b9014yhLfIZcP1m48CNWmWLeP6lc0chnkxi8UuZue4lc0bi6be3p83rll8Ngkatyshpkzh4Lh5f2NfYii4AQBx/0fXD8cLKnWltbr5qkOj44PIioi13zRyGPYcbiBw894u/ZycrjhM4+5uvGoQkgEcFeQ5cmx5lFiQSwKrPUm9owuMqpQInGwLQazXQ61R44z+70yKmaD6PxbNHosEbwrpNBzD90nPwxn93Y8qFfaFQpN4eX1v/Awb2KUaJw4hadzDt7WfSuN7Y8M0Ror8pVzCfgQBMwrp9oMXXsYlP793NkdoMpXy6oC+af6mlPgOu30wcuMcfRqnN2iKe3+UJIZFMZm3T4CXPK5FIhW1mG0f4ORSOE/sSnS/pq66RPL7HHxEd715qIdvvC/PnSDl4zi+zcMZQImf/w6F6lBQYiW3mT63A8nd2ZDw+dUI5AIg2AuFakO+jIP7yj29TcwxEsO9oIx57YxvunDkUjb4wdh92Y/dhN6ZOKBf5M/j1U9D9Ta2FVt8MnnnmGSxfvhxr165FeXl5XsZgZS/bB3Li80m+BRl9WU0t5Go1QI0rDH84hodvGY2PtvyMT749wbdHElR9G6NeA5c/AqdFC7tFx8fwG3TqrHy43aJDNJbg2wCg8uykvpRKBfXvQzjOOd0KcO8Nw1FTH4Bep8J1V/QHkk2/wNEcN+8LRkXaRDazFgqFAuFoDI/PvwDRWAKuxhAcVj2UKgUaPCE8MKcS4WgCXn+Uyq/rtc1KorRzSHMscxpxfp9CeAMRkc0GnQrJJGDUq3HvDSNSGkfeMIoL9IBCAY8/ggdvGon6xiDiCQUMehUxl4KmJ2Q1avm3DI1KiVmXnwOVUgm1SgmbWeyzyHqN2+g51ao00Q8//IC//vWvOHjwIF544YWcNoOcfAYaYMdPBJ9BPwfQgYqdne00kWyfAeW8Cyo6w+XyUc+hccBZuVrK/cXFjXN8cJFNn+YzSPMBlDv4vuTy4SaDJi1uXm6s++adx+EPRjP6MrLF02ebV6b2Ul8CSQNIakt9Y4CYm1Dj8kKv07ZITyiTThJNT4jG7XM+GofNSFwvjUrJ25XtGp8OLasz3mcQiUQwc+ZM/OUvf8GsWbPyuhnUeMJEHnLJnJEosepytv1sxVm/GQCyNFpovP1Tf/gfaBXJtL7qPGHsP9bI/5qm5QbQkOn+MmiUUCoVqPeGU/aaNXA1RlDvDePQCU/aL/glc0YS+fAiuwFuXwhqVSqCpaY+wPP0NF+ElGcn+Qxm/KI/Dld5qfo+e4+6s2rw0MaX+hlI55A0i8qcRiyYNhj1ntQbhNsTgEqtFukBHa5y4/IxveAJRGA1avHeFwcxbkhXvLruB369Sp1GYj5ELrZwxxev+Ipve7jaK1o/Ls+gc5EZeq0K731xEL+8sA8efDl9bG5NOJ0jtzeMIrsBKmWKIrSbtOL7pYV+AiHOeJ/BU089hV/+8pfo0qVLi9rnMqndxxqpPOqA3oUtGv9sRVGRpa1NOGUUZfm+en8t8XrXe4MY2FvcughAYH8t3vrwJ/4Yx9U+Mm80endzZLUn4/3V5FTtKRzTAWz+/oRoTL4NhQ8XcstTJ5Q3c++Z4vElPDuJsw9F4hn1fXgbM/gvaONL/QxEfwlBs6jKFcCJOr+Iy184Y6jIli0/nsSWH0+K2o0Y0Em0XlqNkjhmLrZwx7nP0pwF4f8XzhiKxSu2AgDGDemacU2qXAEkkkmMOb8zSOhJPNpytOTvvlU2g+3bt2PXrl244447WtxHLm8GNG2iAov+7P+lnAPOqjeDXPX1BTBSuHaHxdCs3CnwJRh1aqK+TSAYw4GjDbAa1fD46bbkdH81zctqlBfrzr0ZdC0x81r/wtyA7qUWmI0aIuev16pw0ZBOmDCiBxr9YfzxuuGobwyiwRfhOXOTXo3z+xai3u3H2MFd4fFHUGDRobreD7222TdQ4jQSx+DGp/HeXK0Co558TaxGbVq+Rf/udnQqNGHhjKFw2PTweIOAQokFU89Hod0IbyCCpTePRjwWR11jGGajBq7GIIx6NR66aSTP+TtsemrdANL11qiVRH+L1agVzUk6R+6z3axrvtcoNQiE5yugwKYdx+C06VFk0+UtzP2MpoleeuklvPbaa9BqU4tcXV0Np9OJRx99FBdccIGsPpjPIHecNZsBhc+XzaMSYv1vvmogxlV0wVe7qmTlFgj53akTyonf8bb0ssm7vwTzIun7ZNPUF3LYx2v9PO9M09rx+IKwmg1pY0h57mz1CDLlFmzeeRyD+jhhNurT2gs5+GzceKZcDFqehNRGuf4H4RrT+hL6W4Q+gw+3/Izdh91EvwznI+L8FyVOS0Y/jlSbKF95T2f0ZiDF+PHj8+4zeG39DymVxUgceq0K6zYdwKwrzmM+gzMQuerrk9ove+ObNH78jhnDsOi5L9L6penATBqXis6RE+v/zw170zjsX1/ST2SjcF4PzBmJtz7YgyvH9kYimYRKocSqz/ZhcHkJ7ws4p3sBlr2+LW3s+2dXIhZLEPX9hedJ/Q/ccSk3fir1CBZMq0CBRY/l7zT7I3SaVNRMn652EW/Ox/B3suJngr/kvhsroVIqiDbT6h5kspE2L9pcpH0pFOCjiTgfzYxf9Mfhai+vvxSJJ1Bg0UGvV6Gq1s/XLejVuaA590KwJp2LzDAZNHj67e1pkUkP3DQSxZbT/zw6430GrYl6T6gprvcb0fEGb6hDbQZnC+Tq69M2A7cvQuTH6xrJtXdpOjCZ4ualsf4kDvsXo3uKbBTOy+OP8Pek0B8wuF8Jb/v8ayqIY7u9YVn6/DRNnDRu/BTqEYQi9ByGhTOGEv0ft/9mCNFfUlMfgF6rIo5Dq3uQ0UbKvOrc2fuqawyJ8gy4uZF0jv743BcAgPnXVOCx11PPmF5dCohrsmR2Jb9e0vHrPaG8bAYtRZtsBhs2bMhr/05bs5aJxx+B1azFe58fRIGFaROdiaDlAKTFXlP8CqYmDl36y6vQRq4DTMst4DTlhfwyx7WXOIw8h0+rUatQKlDni0CpTP2ydNr0Kd2dc0qhVil5Pt5q0ok0fLicAZNeQ+S2VSolBvcrwvf7TmL3YTc/XpqPhObLMJOPZ1pvq1FLjNMn1Q3g4+slHPywc4r4yl8kXaZCux5aDTlun5YnwWkFbdp+DAVmsa5TjzIL0WdA0kOSzleY10DSOeLvQ4sO99wwAhqVAv5QDPffWIlEPIlwLE70P9hNWhgo/hPHGaaV1i7lKJjPIIWzhSaS5TMgaAtJY/bf+aiZk10wtQKjB3XC5p0nZOUWkGLoaRx+RT8HvttL9jkIOWhhfLkcbl6OVj8tz2DulIFQII4kVFnj7LPF9ktzJmh6PLR6CDSfgzR/gLZGNP+HdC1IfgW5uQEk/4XQLuF6cz4DoT9BTr+8r0vZulppZ5XPoCVgeQa546zZDIC0fAJp7DVNW0jK5ftDUb5NUWFzHeBsuQXceHqdOifdn0xaM0B2/8PiOSPxwAr5Wv2Lrh8OAETdn/nTBkOnASJRoNEfEfH0wvwFvS7lQ+N/QUtyEDh9H2GsPSlOf8mckYjE4nwNA+l3pL/B+2dX4vv9LtF6lTmNuPmqQahrDPH+vRmXn4s33vsRV47tDbVKSczRyOYLEP6f0/0R5m+UOIxQq5QwGdVo8IRRYNHD1RjAkRq/SOdIaNfAPsVZ/Sr3/nYELHq1OGdAoDLrsOpRbD/zoonarc+AxkN2pM3grIJUnx+AWafmv5PjV/CHouhWaOLbCPt1+yLE3AJeB6ZpvL0nPFm5eSFnnklrhv+c4TtRnoEMLr+uMQQkQdbn94Tw+BspDlsUpw9x/gIAXitHiMPVXr5PYaw9rQbBiTo/tGpybD/tb9DtDaf5D6pcAfxwqF60jm5vmPex3H4t2edA82tI6wYIdX+E10uoRzR/agUee/0LSCG1a2Df4qzj+4NRdC4wiKPf4kCxRdfsI8jTRnAqaJebQaY48A6BXGsAn+I4bl8qxltYb/d0jynbryCwS1gHOJZI4oYrz0UsnkA4moDVqEGpw4RgOI6GYBTJRBJ1jSGRbk9JgVHUBkhx0DazmPMX2jVxTHeMGtQFDd4QHDY91nzW/Eufi8GHIolHfzcGO/fWwCGovdGjzCLqi1SbuNCmRzyRFJ3HcfO+YBSP/m4M1EoFAuFYRr+IsKYxV5NXWMNYo1LyPhK9Np3XL3Ma0anQhGgsQfSxaNTKND0jrgZyJl8Ad57d3HwdaPUIaLkbmXIDpH4C7pokkUzza3B5HUK7pH4V0vgGvRq1vnBecwnygXZJE3Von8Gp1vRtwTgZa/+erjHl5iKAbBct7l3Kh1eeW4zKAZ0y+gxofLo0l0DIzZP8Adw9SdImoo29ZdcJHDjhyVjfNxuf3buTlZ+jdF7dSm3E+QqP0+YlR1vJ4wsiCWXGugFy8i8y6QTR6gZI/QSk/INMNR+EvgXa+FLfS1vUUMm7z+DLL78kHtdqtSgtLUXnzuQ069MFlmcgD61Vy0E4Do3rPu31I7L4FaS1hoV2ya3Ju3DGUP7/mdpwtWsXTKuA2xtCod0Iq0mbxpOXOY2Y8Yv+sJl0eOhv6do1NG2ic3s68PCr6bWJOT6cO29Q30Le5yC1kdPt6dnJijp3AMUFRngCUZQ5TcQYflps/6Lrh+Pg8UYkAXQpNsOk1/AaQHLWWOjzuO+3lThc3YhCuxHxRAJ2cypnIVvdAGHOApJAg6cps7qpznHnIjOsJi1fN0AY619WaEJtQ/P8TXo1Gn1hdCmxEPWEFl0/HL5glOgnueeGEQiEYmnj20w6kX6UsM50a4eP5t1ncM899+DkyVRctd1uh9vtBgA4nU7U1dWhX79+eOKJJ9CjR4+cDM8HOnKeQWvVcpCjw3/a60dk8StktEtmTV6Rjk2GNtxnqVaN9PwqVwCHq73oWpwk9pVJqz8TH86d17XETLVRGOe/Ys0P/Pe3XzuE6gshHa9rDOH/muoGLJwxFNWuQE5rLPKR+EK8LfOnViAY8pPrBkiuC60eAYeFM4aizh0k+kIWzhgqmr/wOG2+NfUB4nfeQIT3ywgh1Y/izj/TcgkyQfZmcPXVV8Pr9eK2226DXq9HKBTC8uXLYTabcd111+FPf/oTHnjgAbz66qv5tFcWaDWQO4LP4FRr+rZ0nLzVj5DkFsQTSb4msE6tbNYMItQaBsR8PmldCm163HvDCFS5/PAGoigs0GedV6FNz/Pp5/Zw8Dr4Dsp9hyRgNZP5ZYekBjLny9BolUSe/ryeDsy/pgIFVi10WjWUCgXRz2DUq3H3dcPQ6A1Do1Ji6S2jcKzGh3pPOKf6AM1rlKptoFYpUVggzuvItsZCnt1m0vJ2mfRq2Ci1fwsEfhlRnQbKcYtRC5VKvBZCH80j80ajriGAY7UB/rrQ9ISEOQek65XNryOcL59LkGMt77aAbJpo5MiR+Pzzz6FWN+8f0WgUY8eOxVdffYVAIIALL7wQW7duzYuhzGcgE23gMyDx4TnVEZYxBomDzhSrLq23K9dnkI3nl3LCh4434IOvj2WsIZApN4CmwSMnN0Cq9S+XW+/f3U6sZ0DzM2TKMzAbNbJ9BnK1iTLVY5bbl5xrV+PyoqjALNtnIM0xoa13ms8g0Up/k03Iu89g/Pjx+Mtf/oLBgwfzx3bs2IHf//73+OSTTxAKhTB27NgzYjPo8HkGhBrA+Ywm8oXjeIigI3+qPgM5mkWZ4vmldYCF/DIXt07S7efi3gFk1bS5/8ZK3PPC5oyx9UvmjESDNwynTYtEQoEGb0ikaUPj2bnY+K4lqT9oEoctrE9MqzNAiofv392O6ZeeA08gwuskCWsC9+xkzbhG3NgGrRor1nyftsYlDmOqcptWBW8gStQmWjCtgs9ryJSzIayzID3O1W/g6jFzn8/r5aBqK3H+nntuGIGqOh9sZh38oRjvS7Bb9IjFE9j47VGMG9JV5HecO3kgrCYNXJ4IgtE4Hv5bul9n0Q3DodOo+FyC1q7JnnefwYIFC/Db3/4W48ePR1lZGaqrq/HJJ5/gvvvuA5ByMF922WW5W54HdPg8A0IN4HyOky8/hZzcgkzx/Jk0dDLp9nNx79I6uqQx3b4w/5l239V7Ug+wu57ZDCBd04Y2hpAnp3HYwvrEUyeUE88hxcPvPuzGD4fqAUAURy/0WWSrbXC42ouSAiNxjYXx/NKcB972ptoK2XI2RHUWJMelPD2v8+Qg6zwJ/T3eQATPr/weUiycMRSHq71E/SnunnaatdS6Fv5gFF0dRj6K6GypyS57M5g8eTIGDBiA999/HydPnkSPHj3w9ttvo0+fPgCAiy66CBdddFHeDM0FHdlnkBNOE49pt+iIWlAkPSHRGBStIYdNj1AkDoWKzIen8bMKMr9rMmhEseNce7VKKcoToPH8tBrGwnh8lUqJP/1uDNRqJfyBKJVnbvRHcMtVA2Ezp/weXK0Bm4z8iUKbPq32Ljd+gTV7XgRNm6h7qQUKydrlskbdSy1pdZulPL3LHaDmCRSYdXytAZL/gbNFr1UR/QRpekKCudCunai2slVPzLewm3VQlIGoc2Q3aQEl4PKk6kDQfC/Sv4/W8OOdKlieQTtGRjmK0+lbyLDeuw9SxkD2msTZ4u4z8btSTpnGh9Pq4H645WfEEkmiVhCJQ6fFrWfqKxfdHOEchWuRLc4/Wzy+UFuIxvlnWqPaxhDRllzm2BL/g1AniOQ7kuMziEQi0Gq1xHyLPYfdaffUzVcNxPl9HfhuX8pnkCl3hFbXol34DNxuN/72t79h9+7dCATEoWD/+Mc/crO2BWA+g9yRaTM4nTxmpvUmHV82bzQAEMenxZef28tB5Gc53vhwlRtTLuoLjz/C184V/ooUagAJ2993YyXR37Fkzkh4AhG4PSHYzDpE4wnoNWoolQqoVQpq7VySZlAmPl+YD9C1xAy3N4TiAiNC0biIyweaawVH4wl+LeTG+XP+hx6drIjHE3jjP7vTVEf79yggzuv+GyuJtYWlOQ8D+ziJcfvSOR6t8aVdn/tvrEQsnuDXL9N6cX6GGb/oj2qXH2qVEqVOEyxGLTZs/TlVwS0QQbHDiHgsCbcvBLNBi5MNfpxsCPHX5dZrKqg1k2l1oh+4aSSvXQUI34RSiq6kuhYAZNXyPl3Iu8/g9ttvRyQSwS9+8QsYDIYWGdla6PA+Axk4nTxmpvWmjYGkvLj/bHH3Qt74F6N7IhZPyKo1zB2vcZG5+AZvCMkkeE5ZpGlDqTvgCZDrKmSqGyzMB5h/TQUfD0/iz6tcAd7/wPclM85fmHNwtMYniu0Xfke8Xr5wRt9Jc84D+RpJ50i6PtX1AZHmEs3/IdRPEuZ43P6bIXA1BvHRtuP4aNtxUbuFM4bi/pfSk2Zp88pUJ1p6r+872ojH3tjWpG20DUB6XQsA6TkyZyAfI3sz2L59O7766iu+dOWZjA6vTZQJTb9QpFo9QMtzAzKtN5GTNWkBSXw810avVYnamIxqNHrDKLCSeVcu5v+zb47CpNcgEkuI5kWrd5utVm+BRS/S3elRZuE/FxaQfVIOwnw/++YokVvnfk2b9GosvXkU4vEEguE4aJpHQIrDdlj1iMTiou9on7n/i/R0TFqc37dQpJnEf0fR2rFTcgG4nAebRQuTQY1EnDy+kKen1RYodRgRiydE/g+Sn0BYz0BYcxmKJAosqTom3cvsabWOifc6ZV6cvcRrLCM34UzzBciFbJro17/+NZYtW4Zu3brl2yYimM8gd6TRRFn0hFqcG0BZb5K+/twpA1FRntJrIfkMhHHzQq63tsFHrTEr5IrlxLpnq9XLaQDFE0k+N0DID48eWEKsD0zS4G9pPL7ULyHMDaD5UuTWHab5WGi+Abl1AzJp/XC1AuTmLGSyX5jjIbSLlotBG5M0r0z5D1KfAWmO+fQFyEXefQZPPfUU1q9fj6uuugqFhYWi766++urcrG0BcvUZCOPLOY5wwbTBHYomkm4G+dIT8gSjWPfFQVw0rDvcvjDsZh0+2XYYFw3rTuRkeb0WgtaQPxwn6+DfWIln3t1BjEfPVR9HyoFzv9K7lphFfDQAok6RUL9IaiONWwey+w+ENt41cxiqXL4mDZ8kCiw6ooYR52cotBsBBVBd5+d/AXPaPGaDNk03h9NMktb3LXEYEIkm0OBN+UrqGwNQKlV8LgMUwHk9HXhh5U6intDqz/bzHLpSAT5u/xChtkLXEjPMBg3fVyYtKGE+ArdGUp+UXP0p7vg9N4xAMpFAOJaANxCFzaQV1Tag+bu4PAOXJwSnVQ+9TgVXYyjvvgC5yLvPYNu2bSgpKcEXX4g1vxUKRatsBrmg3kOOL+/oPoN86Qm5fREiVzv4nFIq71ps0RG1ho7V+am8NTUePUd9HJoe0PypFfw9E4rExX4NQb80/j8bt56NDxdr+IR5/8HCGUMz2iw879V1P0IKkm4Op5kkre97+1Ob+M/3PL+Zby/8e5p/TQVVT4jj0G//zRA89o9v+b4y1Vbg+8qQz0DT/RGdL1N/ijvuC0b4fA8h7p41DOFwLOPfh9OshdPcTAeZpHU0zkLI3gxef/31fNpxWsHyDMiQxjvLin1uiql2eUJw2vRwWrXw+JprGIQicQQEekD7jjbyPK7ZSIlBB+DyR0R9cbpDNB5XqptDOifTd0Ku2WrSEu8Pp7XZ/1Bo08MXjBI5fFoMu92io/oMQuE4r+9f4jRSbbzuiv58reEH5lRCqVTB4w/zukfSX+OiuHlbbro5pPq+3Hwz3Su0+ReYdc1rbNTy41uMGrovQ5H92tHqEdDi90l8Pum4WVLnWXgfaNTp2lBZ/QHSvxWL9tTkWFoZGWmiZDIJhSL115JI0GelVCpPv2USMJ9B7sjVZ5DGdyqB7w4086NCTpYW007ToZfGZNP4XVLtXKmmvnTsbHZJ49NJ8eVSPlpY+1ZqF8lnINVConHrmWow03IsaH0JaytItZHk6ObQ+pp+STkMWgW/RtK+SNpGpPrEDpsx41w27zyO47V+2bkB2eoR5OIzoOkctVhPSPK3cko+uFNEXnwGQ4YMwbffpl71zjnnHH5j4MBtFrt3726h2fLB8gxyBzHPQMDTOyw6JBJJauyzyxfBvS9+SeRkM9UHJnHb0hj0TPzuuk0H0mpRDOxTLNLq0aqVONkQgF6rQanTiDf+8yOfLUrSIBJGpNDyH4ScPadhw323eM5ILG/yQ53Xy0HMJ7j5qkE51+Tt0cnK6/YINYBo67N49khUufz8uky/9Bz8cLA+VQN56mC8/l6qjodBp8ay17altb9r1jAEwzFs/PYoLh/TS1Tf98qxvXndHqmuk82kQaHdiEgsDqVCge17qnkfESlvQJq/IXxL4fwXv7umAo2+MLbvqcbYwV2RBPAiYV1n/KI/6j0hlDlMCEZj0KiUvC/CYdXBG4iiwRtGqcOIf2/cz0cTSesZFNqNAEC8J4TXnveb5ZAbIP1b4fpdOneUiE5qDeTFZ7B+/Xr+88cff9xy61oZLM8gAwg8PS322ZWJk5UZh02NQc/A75JqUQzsW0ysYzt1Qjm0GiVVx54U0067P4R8NKdhw/2/QeCHmu+oIPqkWlKTVxR3L2N9XZ6gSM+/rjHE29Hgba7jQfNL7DncwK9d9052kc9gQmVctEbZNIf69ypCTX2AqCck1VISXbumPmvqA/xcHHYTVedI6NsQjn/7b4Zg4fLP+fPmX1NB1BMS1jO4cyb5nhDpTXF+sxxyA9L+VsBdr1CrbwYtRcbNoKysjP/83//+FzfeeGPaOa+++ipuuOGG02/ZKYDlGbQABL5T6nvhYu1JOjLc/2l679I4f1p7vVaFX1/SB4P6lqDeE4LTrkcikYDLHeZ18NUqFW6afB6cNiMi0TgK7QYRV282auBqDFLHpOn5C/noToUmLJwxFEUFBkRjCbi9YSydOwpVLj8158FqJPsiMtXklWoOZePPHRa9qCavVGuHVk9ZOrawvi8Xj6/XqnjOX1qbga8ZHYmJaiPT7KTlEwh1nbjxvt93kpiLQWpTZDdg1uXnQKVUQqtWiXxVVF+GRU/UXBLeE8Ra2jmA9sxxWs+eZ47s0FIhZSTEiBEj8PXXX592w6RgPoPckVGbSAga31nuIK6jVNNGjs9AytUW2fRpvDOtJkA2nSFh3WI5nDAp/4GklUOaYyYOmubvkPofaHORUwNZyvNz+jzSXIxM/Hs2LSdazoT0nB8P1mLHfldOa5Qpz4B2T8nVbyLlBnB1C/Q6rSyfQYvzBNq7zwBorn18yy234IUXXoDw9GPHjuG5557DJ5980kKz5YPlGeQOuZsBje+U6rBwx5fOHQV/KAqHVYdQJIG6xpTeC6ejw0UNmYxqPPJqOod+16xh0GlUfN6A9Bpl4/Ol+vy0uH9hmz9ePxwKAO99cRC/HNdHlLMQikT5+riFNn3WuHch519kN8DtC0GtUqJnJxuxbvGCaRUIheNo9IehQFPkStN8b/nV+Th20guH1QB/KAq7WYtkEognk/D6wyhxmOD2heGw6PHMuzvSookW3TAc/kAMqz7bh8kX9hHlRfA6/xL+HSDXRsi0xrRzfjhUz/toOhWZRXULhL/mA+EoypoquJHuCanOkdC3cOvUCqLmkai28o2VaPSF4Q+E0LXUjnpPCA6rHsFQGMFIkjjf+26shFmnItbSbhGEb9fWVORdW0QT5S3P4J577gEAhMNhLFq0iD+uUChQVFSEe++9twXm5hcszyA30PhOGrfuD0XRrSmu2qwFAsEolryyhT9HGGtO461p/LAcPl/KzdPi/oVtfjxUz3PN44Z0peYscDH1AGRp/Uh1+0nnH65ObchSbh0AvIEIXlq9K+34whlD8cy7O8l2Cfr2BaK8o1tav5nGv/PzyLBe2fwf4WiqVrBwTrf/Zgg1nyDbGkl1joS+Bbc3c/4G56Pg/A8cjcatC81/EovFYbWnaBxpLe0WIQFx/sFZFFYKyNgMNmzYAAC488478dhjj+XdoNMBp01P1NfvkD4DaT0Boxoef3OeQDgah1KpIOvgU2rimvQaHKn1w2HTIxFPpOkcGXQqJJOAhsLPntfTAa2WrM9P074X6esYtVh600go1So0eEIZfQAkrlmtUvLx5VaTThRrLuXas9kiJ+6di6cn+RMsRq1ojYadU4SJY3vDF4zigZtGYu3GA9i2p5Zqi8Wk5dde6ssQfube1uKJBKxmLfp3t4sc7tL1oukUCefL+QyE1yVbG1oeSSa/Cq1uAMkW4Xpnu45nq4ZQvsDqGbRjOJ1mfL7juChW+uarBuKdj7Lr2Etj++W2l1sHl6Yn1BLdntMRX95SnSPhZ5KuUqZ6BlJNfprPYfPO4/AHo0Q+nJZ/kSnHg+bLEK7XwN6OtJrNUp+BsL0cbj+bz0CYiyGnFgVJs0ju/X0maAjlC3nXJvL5fFi+fDm2bt2KhoYGke/g008/zdngXMHyDHJHJKnAbU98SuRaAeSkg9+niw02kxZPvPltGp8uJ//gnhtG4MdD9aK3BE6fPxiOiWLiuV+nPTpZYTVqUFPvh1aj5uPZaXWLF0wbDE8gguMnfVAAKHYYs3LjpM9cX/WeEIoLDIgnkqj3hFBg0cPVGEA4kuT5f6tJx+skzb+mgph/sGDaYERjCao/QRjbT7pvF88eCQBY/k66H0ya28CvXZkFaqUSVfV+dCuxEPn/JXNGotEfwYna9PVaOGOoSI+I0y8Kx1J9bN9TjYtH9ECDNwylQoEGTxANvogoxwMA6twB2C16US6C8PoatCq898VBjBvSFYlkElq1CnXuABr9UVE9CD4vo2leCqUCkVgchVJtIJMGHn+q/rdZp+bzaLLl1LQn5F2baMmSJaipqcG8efOwcOFCPP7443jllVdk1z2eN28ejh07BqVSCaPRiPvuuw/9+/eXbWguYHkGKdR7glm5VgCyuPElsyvhD0bJfLqM+HhvIJIW383p8x+u9oraCGsYLHq+uW5wtrrFnNb/a++lkiDlaACRPle5Ati+t1bEh6f06r/g+yXFvXv85HoG9Z5QxnoG3OdM962w1rEQUm5fqFnEcei0+gucXaT1oo0n7Ld/ryIgCSx/dwekuP03Q/CXJm0iaQ0DoY0HjzfyuQGkGg4A0upBc+PfPWsYz8/z2kAJSf1vQFZODUMOm8EXX3yB9957DwUFBVCpVJgwYQIGDhyIm2++Gddff33W9suWLYPFYgEAfPTRR1i0aBFWrVrVYsMzgeUZpOCwGjJy2DROlaRpo1aroNMoRXrzc6cMQIHFgHgikVV3p8BK1ouym3U4DC+xjTBnwaBXZdS657T+6z0hnmuXMy+pPr5ojQS2FNqbaxUkEknce8MIVLn8MOo0vC1WM5kzd1j1iETjxO+keQJEbtusAyzkmrxWib5OgUWLAosBiWSCX4dM8fchXUz0HTdHAHyd5gZfhB9PaK9eq0qrocx9J8y5oOVlSOsG0GoYkHITUhpTOnhCMWJd7er9tTDq1M3fneW6Qa0B2TRRZWUlvvjiC6jVaowbNw7r16+HyWTCsGHDiPkHmbB69Wq89tprWLlypew2zGeQO1riM8ikaSOM46bx6TROWKdJIhxVpF2Tw1VufPF9ddbau5k4bFrOglCvPpM+DhenL1ebiDZ3GuefKYZeqLtDq+VAyw2QtqfVI6hxedNqQXB5AodrfLw/gbTGpBoCH3x9jFjzQdhGqNMk957K1c/AXbtMdbUXTK1A/x42fLf/zMgBaA3k3Wdw3XXX4eabb8aoUaPwhz/8AQqFAiaTCbt27ZL9UL/nnnvwxRdfIJlM4uWXX0bfvn1lG5qrz+C19T+k6dvMuuK8DkUTFRVZUFvnFeurNHGqHI8ajiXgagyhyG6ASgn4QnFiTeCW+BmEseK0/IH7b6xEvTcEg0aNqvrUL21hrYJsOQsLplXAbNBQOXEu3yRTTV2Os+fqKXP2evwRXsfmhivPI9Y2EPa16PrhMOhVCEcScPvCKLQZ8PTb29NqDffsbIVKoYDJqIbHF8XxJs7eatLBoFPAZjGg0RcR5W7IqdNAyw1YMmck8e9hYJ9iAM28/KA+hXjob+SawNwa3X9jJb7bV8fXEI7FE3jrgz183ya9Go2+MLoUW4g1I3p2siKZBO9j6F5Kvi6Lrh8OlUqJaCwV7ZYpN0GnyVxXO1O+zNkiFZEL8u4zWLp0Ke80vueee/DEE0/A4/HkFG768MMPA0i9GTz22GNYsWKF7La5TGr3sUaivk2DN4QBvQsprdonigotKJIec9LP/35/7WnzMwhjxWl8eHV9QKRvI+WNs+UsHK72oqTASOXEs9UQEHL2wnrKnP+B47qlMfykvuoaQ1i+Ygd/7PZrhxBrDS+cMRSPNsXAL5wxVMTZC+ssi7h4GXUaPH5ybkC9J0TVewKa8xG6lpiz+zW8zVpI3+2vQ0mBkdi3NJ9AOHcu/p+bM3Utm3wDf7x+eNa5B6Jxal3teg85T6HBF8Y5PTP8MZzFKCqy5NxG9mbQtWtX/rPT6eQf7Hv3Ehw+WTB58mTcf//9aGhoQEFBgaw2ubwZZKpnIEueoZ2AmIEs4E6LCgxIJpKoa2zmUY0Z9GFy9TMI+XhaLkCpwwitWknk4IWRJzZKDYLupRaYKXr5Ug6exltzYxj1ar6egcOqR6M/jFuvOR8lDiOSyWTWvgrMOtxy1UDYzDr4gzEU2g3EGgQFFj1ft0CjVmLOpAEoLjAgEkvwc6fx/MTr0vSZlqNB80VI6ywUyKjvazWmfkmXOY04r6cDgXBMlGNiN2vgtBmRRJLI/xdY0vWuSL4QYW0EByU3QXh/GTUqQKGg1Kmg1Mgw69rl8yCvNJHP58PPP/+MTp06weFwAAD27NmDZ555Bhs3bsTOnTsztvf7/fB4PLzw3YYNG7B48WJs3LgxTRabBuYzyB1pm4FAP4VaAzlDjVeHRcdrAMn1M3BcM6mGAMfN1zaGsvofMvHZNE2aTDUQuPakGHaSXXJyIWicvVRPSKj1T+PJpX3Rcikytck2R2lsP8nnIb2O3+8/iT2H3S3KEZFbt1iaN0C6J4X98vw/KPpAhPbMZ5COrJvBp59+it///vcIBoPQaDR4/PHHsW3bNqxZswZXX301rr/+epSUlGQcpK6uDvPmzUMwGIRSqYTNZsNdd92F8847T7ahLM8gd0g3A6EGEY2DfuCmkXjqrfR49t9dUwG1SsF/16uLDTWuVL3dUqdJltYNKQZ/bEUXACDaIqwpnE1/qH93O2b84ly4fWGYDRqs3ZTK3BVy1XZLSven3tMcG1/iMGHZ6+m6/1zdXaFdwtq9XD2FogIjDh5P9ysI+1oyZyTqGoOwGrV8TL2c9ap2+VNvGaEY9FqVKLZfo1JCqVTA7QvDZtSm4u6jcdgtGigUStR7wiKfg/DNTa9L1TQm1TAW1pKwGDXQqZXwBKNQKhRYt+kArrm4H4KRGNF/kinHJJlMYu2mA+jVuUB0jhxfyNK5o/DEm98S619z52fyGZDqFreVblBrIG8+gyeffBJ33303Jk2ahH/961+4++67MX78eHz00Uew2WyyBiksLMQ777wj26hTBcszIEOkQZShHgEpvjwWi8MXaI49v/3aIXy9XTnx/J4AOQY/zRchaC+sKZxNf2j3YTe+218HQKwBJIxPf/T/tgJIcfmP/X/NMfBUnlyyRjStHaJfQdBXXWOQj7kHgBHndZK1Xs+v/B5SDD6nFIlEEo+9vi3tu4UzhuKPz6WEJaW+F2rdYeGcw+RaEsK+Gnxhca0CmTkmnJ+gV5cC8TkyfCEuie+HVD/B7Y9QfQbEusXtdCM4FWTdDI4dO4Zp06YBAKZPn45HH30UDz/8MAwGQ96Nayk6ZJ6BQIOI0wziYq2VitSv4UzaNdz/LUYtnz/gD0ZhNWugUioRDMdRYNWh8txijBvSFQoFeJ6ftt5SPSGq1r8CabWD1248INKxoXHoUn1+IQcurGsr9A1I8xey8eQkvwi3RolkktfUp/XF8ex8rLxORdSCkrNeDqse0Vic6hPLdn1Jvh/uO2ltBdJ1JK1LtjHl+G4yjem06jFpbA9UDugMty8kqmHAnWM3aQGFgtgX0yCSh6w0kbSOQWvVL5CC+QwyIEttY1I8fi55AtnaZ/MZZNP6L3Uaid8JuXWSvg5JT4jGVQv9B8K+Mun20HwGtFoB0pq8XF9S3f9s6yWtTSDtS5gbQBs/031AW69sWk4knSQ5NRjk1q8mjblgagX697Kl/T0L1ytrnkE71SCiIW8+g3PPPReDBw/m/79jxw5UVFSIzvnHP/6Rm7UtQK4+g9Wf7kuplgYiPFc7+X/6tkuayBOM8lxpNg62f3c7rrvyvBTv3KRdI4ztJ+n+cO2FsfrScUg69Lf86nwcrfGguMAIlUpJrMm76Prh0KhVeODldB/PouuHY/m7O3ie3mJUQ6FQwhuIQqVU8Bo2tFh1Ie98/+xKkSY+l78ABWDSqRCOJeBtqmfw3hcH+Tq6nNZOny42PNwU607zX9w/uxLHarwinp/j4AFkzVP44/XDoVQoUOsOoMxppq7JDwfrqddo+94aTLmwLxQKQKtRIZlIojEQgUmvQb0nCIfNAItBgwPH6tG7iwON/pSekFarhNsbgc2sxbGTPmhUKmr9BZVSIapFwa2RzaRDKBJFod2IeCIJk16d5rvp08WGYruez29xWvVw2rTw+JpzYaT1BWoayT7A+2dXwqRViXWGmt6QA9E4jBpVu9YgoiFvPgMuhJTD1Vdfnbt1rYx6T4hYC/XCoV3b5Wbg9gniy7NwsLsPuxEKx2DQqPgaBCIeNkP7TLH2pNwCbyDC156l+RV+OFSPrsXk+HZPIELk6W+/dggee735bVWOz0KqiS/MX1j88jZRX6R7R+hboPkG3N4wkecf2FdSQ4CyxsKaCzTdf08gkvEacfNaOGMoHvrbFkixcMZQfLe/TpTPwPkf5l9TgcffIPscOHgDEapukbDN3bOGYfGKr/jvhBpXZp0aZh3g5OibeHpdbmF9AZoPsNEXRllnya/+pESbqINtBKeCrJvBlClTWsOO0wqnTU/koM9on4G07gBBb4X4HZCmo5+Ng+X4Va7mQyAc42PCM7WXcuJZxzHrZNXkpWn62ExaPHjTKNS6A0BS0Rx3TomHl/5flOdAaeMg1Gwg8fHCmr4034CDor/UvdSSpuEjZ+0y+R+ytadpQRVY9Dhc7SXORar/RPJr2M06NCrCsnj+08Xfd0gfYBtAthxFMpnEu+++i3Xr1qGhoQFr167F1q1bUVtbi8svvzzfdrZvn4EiA9cJGTyoTJ+BqMarOn2NMsWqy9UmEvLLNS4vigrMGbWB3v14LzoXmTJq50v5dCk3n413JsW303jy/t3tWXMWaH4GUm3lbP6HXH0sW3adwIETnpzj+bn2NS4vdu538XMU5m8IP9Ou16HjDdh/rDGjntDcKQNRUe7A7kOnib9vwd+z7Prf7RB51yZ68sknsXnzZlx33XVYvHgxtm3bhqNHj+K2227LSXCupWjPeQZCzp+DTiMjdlrwWs2/PQi02znelFTjlbZGtHyAm68ahB8O1uNwlRuT/6cv3E2x7lX1fngDUV7vPhiN8THpMy4/V8TTS/0K9Y1+XDSsO+q9IXQuNiEcToj0gIRx5EJ9HCE3Hk8m4LQasOazfeheZqfGoQvbqFQK0RjCGgAWo1akqSMc/9V1P/D+i1AkhiK7EY3+MO+TmnRhXyLPL63v26uzFVV1/uZf3TwfPwj7jzXyPH2pw4BCuxG+YAQFFj3cHj/sVhM8/giqXc3tSWt/5djeVM0frUYl0mzizjfo1Lxfh+bX4OoGW80auBojqPeGeW0loW/hD78eAqdFK9bFOhX+XgPUuMJo8KbqSpQ4dRl/2LHNII/aRKtWrcKqVavgcDiwZMkSAECXLl1w9OjRnI3NN862PAMR59+EcFRe7DSPZDrvKtR0l9Z4pa1RXSM5z8ATiPDHLhrWDUkksfTv6VFlQt640Sfm6Ul+BYfdJOKmhXH7QruE+jhCbnzqhHIgiYya+NI2t19LrtU7f2oF/MEYcV1CkXjzeddUYPm736XNfdyQrhl9F0J9Hi5HQ4hGf4TXKRLizplDEQ7HsOyNHQAgyvEQQjj3CSPIfo0fDtWL6k9PnVDO5xaIfC8UvwRfNzieqvfr8oSINrs8ITjNWvE9eSr8fRQoseqa/37PxDf8sxyyN4N4PA6TKVVAgpOQ8Pv9MBqN+bHsFHC2cYy02rk5xU6T9NqBdH+DWY2TDWEqh67XUrTvzXpMnVCOwyfcsJlTbx60vAHuF7DZQNYMOqdbAe6cORTf7q7G+X0K0bXYzNeplmoYkXTsz+3hEPkSHAItqkya+NxnmoYPSZ+fND4tHl9ufV+hL0Vam4Dmi9BrVLwfTDoOSRcqU85AJt9PNr+G9L6j/a05rZK/tSx+L4a2h2ya6J577oFGo8GiRYtwwQUXYMuWLXjkkUcQjUb5N4V8gvkMMnCvSrImy7iKLvhqVxXftvLcYl5baPTAkjROOpO+jjS+nKYVJNTBycSNk/T5pRpGmeLWN39fk5MmvhwNHzl+kUxaP0IfidQvwmkASbX+aX4J0X1b7gCSwI59qXta6LPIxcZcNKZoa1/R1wEIXxgo955I9yfT/Z2nDYHRRHmugXzXXXdh48aNiMVi0Ol0GDNmDJYtWwazWf6ALUVOmwGQM8fY5hBw/mn8aqbvINYc4qDTqPDQ3FG4T3D8gTkjeb37qReX43CVm8/FcFr1UKmUCEVieOFfZA2hTHkG3JjSeH5S/kEmPaJF1w/Hp98cwYQRPRBLJIg69ouuH47FK77iuXyphhB33l0zh+FQVSPUKiXKCk2obQiguMAITyAKp1WHSCyBWDwJnVoJo1GNOncIVqMW3+6pRuWAzojG48Tx77lhBA6daEzj/G+dWpGWZ7Dx26O4fEwv1DWGeK3/IruRqIe06IbhUCkVOHbSx2sLbdpxDHfNGIpoPCm6xtnqPND6+t01FdCplbzWjzBPoGuJBSdqfbzeVJ07mDbHP/x6SHoNAOFbKUH3J5NPTER1nkawzSCPPgOz2Yxnn30WLpcLx48fR1lZGYqKpEr5ZxCaOMYBvQtTN8WZvBEA6Zw/IXaaxr26MvD/wuMivXsFiPH0t/9mCFVDSI6mvzSen+QnyKRH5AlE8Mm3J/DJtycyx9qDriHEfdfgC+P1/+wBkPJFcDkP0vk+9Gq6zk+3Mjv0WhWxX28gQuTsaXkG3TvZxfWUKXpIde5mDX9Rv/4IQhGxD0CYT0Dqyx+M4rHXv0nrKxaLIxYl5wncPWsYP6/511QQ58j5AkRIIKPuTyafWL42A4bcIXsz+Pzzz9G5c2f07NkTTmeqIMTBgwdRVVWFMWPG5M3AFkMFnHSHsee4B06bDkU2nfj1tj2g6Y1BpVKI9HgMOlVKK1+lEMWKO2x6XlsIABZMPR+FdiMafWHYzFrUNylrZuKahXkDNO2cTH6CtRsPEPVxuDcIjUqJh28ZjU+2HqbWQBDG2pO0crj/lxQY+TGlPD1XKxgU3X29VkX35VB8A7S5k+opk/0yOuJ1jMWT1DrCtDWS6hRxbxLBcBwOW0pjisuy5q6dU4ZmU5ovQAYy+sSkYL6FNoNsmujSSy/FG2+8geLiYv5YTU0NZs2ahffffz9vBnLIiSZSNfOrGfnOsxkEHlYaN58ptt9s1BBj5Um8Nce59+5k5blmWqw9qW4BSd/meK2fqIkv7KtHJyN+PhEgcutCn0G2+sBzpwyExxeE1Wyg2i618cMtP6NPFxuR2yfVI5COQfMZyNEAIp1D0/2naRhdMKgTtu6uwdPv7EibL6mvm68aiPP7OLD750ZiG6Iv4BTuVaLP4DT6FhhNlEefwdChQ/HNN+LXzmQyiaFDh4qE7PKFXDaDk94wsebpAzeNRLHlzAstbQloPOyCaRVZeX2pzpDwO6EeUJHdALcvBLVKiRKnCTaTls9NyFQH2BsIo8BqgC8YxaHj6TkD999YCbcvjO17qjF+eMo38PDfvk7rS1jDWJTz8KtB0KpVUKsUqK4PwGHR45NthzH4nFIAgAIKXsef62vxnJF4oMl2mrbQPTeMgEatxNFqN0qcFigUCjz/r++IORd6nQqBYAy+UFQU2//Gf3aLzv9+/0nMuuK8tPwJYZ0FWl6F1MYypxG3TR8MtzcMp1UPvU6Vql/t0MPjizX7xxw6FBU0178ORBKi/AfatVs2bzSsRg3vn3La9AiF46enBkAWvxdwen0LbDPIo8+ga9eu+PLLLzFq1Cj+2JYtW9ClS5fcLG0F0GLo6z2hdrMZ0HhYEbcsV2dI8B1ND+juWcPQ4M1eD0FYu5aWM1DvDfH6/v17FVG5eVptBV8gisffaNa9mTqhHB9tO46Pth1Prx3c1FeD4J6gzd0XjMCoVeO5lSnfAlfDWDr+DwINIWlsP+n8cCQGnVpJzm24poKaVyG1scoVQCgcQ3knK3/MVJgK9zZYVc0x+LGmL5t8TdUNHnFfNH9PE4cv9E+ZNKrTUwMgi98LYL6FtobszeDWW2/F/PnzcfXVV6Nr1644evQoVq5ciUceeSSf9rUItNhnRwv4zjMVUh5WXMc3pfcOyNcZ4r6zGrU8vxxPJHjO3WnVI4HsdYALbXrMuvwcqJRKKocu5PwLbXpoKbkNND48kzYRVTfIJk9bSK9p9ovQ8hGEmkfC/AVq/kGGfBGDTkX0vZDyPcqcRuh1auw94WnOJZHxgKb9PWTl8FuZv8/Jt8Bw2iGbJgKAnTt34p///Ceqq6tRWlqKq6++GoMGDcqnfTzadZ5BS5BFjyhb7Vuaz4CmaVNRnqoxu2NvfcYYfDn6Opt3Hsf3B+qzcvM6TRLhqCLteLdSA45UB/njQg6c5suwGBTwBpMZz6nol/IpZaoTTdNMovkCMuWL5FK3mMrzUzh8EU2ibr5utL4y6V2dKn/fknua+Qxajrz7DNoauWwGLl8Ef1u7i6/lyunK/3bigPSwuLMZTb/cvKEYlhI498WzR2Lf0QZRrHh9o7+pjm4IpU4TIk10jMOqh9mohscXI+rrLJ07ChqVAsve+IavRRuOxuCwGhCNx6FSKNN4+knjeuPg8QZMHNsb/lAUdrMOSSRQ7Qqh0KbHWx/swe7DbgDAxDHdMWpQF7h9IdjNeny58xjO6VmYxsFv2nEMC6YNhsWkhtcfE+WRnKwPo9EXgRIJmE16fl4799Wgf89CFFh18AViaPRH0OgNpdUd+O3EAdCoFCLemtct6mTFzwRu/54bRmD/MTevzcPF7HcrsaDQqsuYL6JUKuAJxvAQQQvpvhsrYTWokUgk4fZHoNepiX6wpXNHEe9p4cPQ5YuI8go4X8Z1V56HUDhG5PDbIjcAgCzfghywzSCPPoNIJIJVq1Zh9+7dCATE9VMfe+wx+Za2AlyeELGWKzFGuh3AG4hg0oW9sWHbEf5BFY6m9N6lseKFdj3+Z1h3GLVqKAEYtSqEtGoYdWoEQyn9JlJftY1BaNUqkabNhm1HMH5oN5Q4jKhp8KHBG+bH4XwT2/bUYtueWiycMRSLnt/Mfz91QjlqG0OYenE5T4888eY3uOHK87Do+S8AAD06FSAab/7Zq9cpcWlld9R7QjBoTamiNGE1DFoVEAf0aiXcySRq3CFAoUQonJrPtj216NfdCZNaBZNVhUYfOR/A5QlBL6EpOG7/9t8MIXL7vqBYT6jQrsf4od0QiyeAJtkWHgT9qHqPOC+D6zcWi8Os18MTiAJJoJHCp8u5p10U34vbG272P0geuG3G38vwLTDkB7I3g7vvvht79uzBRRddhMLCwnzadMqQrZdyNoPwSj3tknK8t/kQ6tyh1HwJOj9XjO7J/xLNFOoo7SuZBPYfa2zm3XWqNApF2kanUQIg8/x2M5mC0aqV/Hk2yjmvrvtBJDOhUSkxdUK5SBJBSuc4bc3XPtP9oRGML/xOSeH8hfMqtOtx+eieeJtEE1Eeapl4cuH1ve6K/mSbbdnv6Zb8PTD+vuNBKffETZs24a233sLChQtx6623iv6daXBatLj5qoEpZynA86tOa/u5kT2BKP+gAFK/2t7+cC/GD+3Gz7d3ZzsWTK3g12HC8O78g5Vr89aHezH5wj5px4V9zZ40AKs/24+Pth7G9EvKodOokEgkM7aZfkk5/wCdPWkAQuFIkx8gZYtTEKcvtKW6PoBpTWNUuQLEc8YP7Sb6PLaiC78RkM5bsWYXQuHmh1qm+8NqUIvWjNvkVn+2n7dL2KbYruPPHz+0G78RcHY8/c6O1K97CkjjLZhaAaVSIbq+SIJfe+686ZeUQ6fO/ifckr8Hml1WI4vqaa+Q/WZQVlaGSCSST1tOHxLA+b0dWDp3FBp8YRSYdacWI30GgvYa36OTJcUjW7XQalXo382GZfNGw+2PIBZPEtvQQi17dLJgwbQKrP5sP+8LWL/5EO67sRK+AHn8EqcRk8b1xvrNh/Dbiefx7Qf3K0FtvY/PMYgnyLZ4A1Fs2HYEk8b1hsOqJ54jkrPIIG0h/E5EpwjuD1IMPbdm1Q1BHDzu4d92GrxhTBrXGz06WVBkM6TaxMXn50ytJCG6RhxPfuSkX9RXMBLn14Xj/ddvPoSenazN8uQ0ZJlvLnYx2qb9QvZmMHnyZMybNw+zZs3i5Sg4CHMPzjQkAf6h0J5Ae403GzTi+Qo4WE8oRg1vJFICZh2Wv5MqfD64XwmAVNijWaeCWW8ktqlp4qZ1mlRJyVWf7sOM/9cfvmAUPcqs+Pv6H7DvaCPunDmU2B7JFE+/ZuMBLJ07inqO6LMCxDKn0jKMaTLfVoqeTtOaQaHAX9/czo/P2cUnZ/kFYZdGjXy5cSkIPDnp+nr9URHvnxNtk0U/SK5dDO0XsqOJxo8fT+5AocDHH398Wo0iIafQUjmyumc7KHIUHE9+81UD8T9DuqKhwZ+1DU0egRT2yK+jUhyuKB2fC9WUhvjKlZ1eMLUC/bvbsPswfY4kmQxSCOvNVw3E+X0d+G5fjvcELdSRYFfG4y0Jx5SMXeY0pvlFMvXdkaNpgI49fxZaKjyXIulMC8M7a9EUhlfrCePAsca0sMdH5o1BgUFNbCMMb6z3huGw6BCOJVDvCfPyCOOHdqPKFoRiCTz1VrNUhE6j5GUrDh5r5ENASaU1759dCa1KCaddC5e7+Ze6Tq1MK89JsvekO4QjNV4+nPO8ng5emps4jlULl6eF9wQh1NETyBB2KZBzOGVqRTq2qeltREbfHflhCHTs+ec9tBQAotEovvvuO5w8eRKXX345H2J6plU7o0k6t7vQUl5uIEgMe3Q1BlFgsBDbCDlsjnM26wB/INrcVwbZgkA4RgxXvP03Q/hjNFmQRl8Y53S2ATEJdYH08pzEcEylQhTOSZOE9gejKCu1AIlTuCcIVEm2sMvTRq1Ix04w2oYhf5C9Gfz000+45ZZboNVqUVNTg8svvxxbt27FqlWr8OSTT+bRxNzRrkNLm6S565t+TRfZdPT52gzp7WkSA03HNRp6SUTu/3aTFga9mlq6kUvUksouc8fVKiU8oZhY3iAH6QMpn06VWxbMP6d7IostLOySoT1CNk3061//GtOmTcPkyZMxfPhwbN26FYFAAJdddhk2bdqUbzuZzwCgS3MTuPm5UwbiwsFd0NgoSBCUwYFnK33I89RqsuRHjcsLvU6Ltz7cm7U8Y06lPYWQzKN/d3ua/yHNZyL3npAjidAWUg05oiPTJEDHnn/efQbDhw/H119/DYVCgREjRuDrr78GANHnfCLnspdNkSPtKbSUJs1Nk3pePHsUtIrmNaNJDCydO0rEp3O/4Pt0saHYruclEYQ8dSZbhH6CbOUZl80bDQC5Sx9I+XSzBq5GcenFIqfkgZClPGOmNUqz5TTJJuQLHflhCHTs+efdZ9C5c2fs2rULAwcO5I/t3LkT3bp1y83S1kJTKN05PZ2pm+Is3wgAOgff4CXLDdR7gygV0CA0rlvKp3MSDEtmV/IcvpSnzmSL8DhXnvHuWcOoPDuSmSWViZDy6XEZoZMywitlyzCwsEuGdgbZm8Ftt92GuXPnYvr06YhGo3jxxRfx1ltv4aGHHsratqGhAXfeeSeOHDkCrVaL7t2748EHH4TD4Tgl4zsaaLy3tMQhd9zRVNaRA43rNhk0xNKPmcoSWijlMWm2OCmy05y8M8n/0BYcPPMHMHRUyJajuOiii/Dyyy+jvr4ew4cPx/Hjx7F8+XJccMEFWdsqFArMnj0b77//PtauXYuuXbviz3/+8ykZ3hFRZNOJJB04nr7EoSNKB5Q1FT7hQJIYmH5JOZ56eztWfbofV4zuydfnJUoPNHHldz23Ga+99yPmTBqQbouTbIvTqqXKG1iNakydkKq+9c5He7HmswOYOqEcVlPrSx8wGQaGjoo2yTN4//338eabb+Lvf/+77DY5+wya0O64Q0E0kcOqR7Fdl6rrTOCwiwoJc286r84Txn5CbsJ9N1bCrFNlLUs49eJybNpxLM1PcdeMofRYewrPni+55BZf+zPcHyAH7e6+zxEdef558Rk8//zzuOWWWwAATz31FPW82267TfaAiUQCb775JjWjmYZcJiVFUZEl+0lnEYoc5PkUkY4R5l4EILC/lpiboFQCvbuR6bvq/bXND2wFiH6KQDSO3oUOoi00G0X9CmwJRONUW+SipdeeZv/ZhPZ23+eKjjz/lsw942ZQXV1N/HwqeOihh2A0GjFjxoyc2rE3gywgxMYT3wyaYNSpidy4UaOS3SbX9jS0xBY56DDXnoCOPHegY8//rJCjWLZsGX766Se88MIL0Gpzc8ixzSADKHHvF1R0hsvly6lNxlj5LKU2T5cOz+mK2+8Q156Cjjx3oGPPPy+bwdGjR2V10rVr16znPPHEE9i+fTteeuklGAyEzNgsYJsBHTTO/ak//I8ozyANLeHGBW0cFh0xB6FFyANP3xGuPQ0dee5Ax55/XnwGl1xyCRQKBZLJJBSCEn7S/+/evZvUnMe+ffvw4osvokePHpg+fToAoEuXLnj22WdlG8pABy02XppnkIaWxMoTtILyosNzljlsGRjOdmTcDPbs2cN//te//oXNmzdj/vz56NSpE06cOIFnn31WVi2Dvn374qeffsp6HkPLQIuNl+YZyEYOOkEMDAztA7J9BuPGjcMHH3wAvb75l2YwGMRll12GjRs35s1ADowmyoCW+Axy7OtM0t2Riw5x7SnoyHMHOvb88y5HkUgkcPz4cfTu3Zs/duLECSQS7UDn4WwHpUShUpl7iTdSbeWn39lxyjH/DAwMZzZkbwbXX389rrvuOlx11VUoLS1FdXU1Vq5cieuuuy6f9jHIxWni3GVr8zAwMLQryN4MZs+ejfLycvz3v//Fjz/+iKKiIjzyyCMYN25cPu1jaGUwbR4Gho6JnCqdjRs3jj382zk4bR6pz+BslGRgYGCQD9mbwemSo2A4w0HxP7CNgIGhfUP2ZiCVo6itrcXWrVsxYcKE024UQxuDxfwzMHQ4yN4MHn300bRjGzduxPr160+rQQytCJZPwMDA0IScfAZSXHDBBfj9739/umxhaE20o3wCBgaGU4fszUCqUxQMBrFu3TqUlZWddqMY8g+WT8DAwCCE7M1AqFMEAAaDAeeccw7+9Kc/5c04hvyB5RMwMDAIIXszEOoUMZz9YPkEHQDMJ8SQA2TXQJYikUjg008/ZWGlZylYrd/2jUQiyderXvLKFtz17BfYfaQxVaKUgYGAnB3Ie/bswapVq7Bu3ToEg0FMnjw5D2Yx5B0sn6Bdo6rOz3xCDDlB1mbgcrnw73//G6tWrcKBAwcwbNgwBAIBrF27Fl26dMm3jQz5AssnaLeo9wSZT4ghJ2TdDG666SZs3rwZ5eXlmDJlCi6//HKUlJTgggsuaFHFMgYGhvzDYTUwnxBDTsjqM9i6dStMJhOvS1RSUtIadjEwMJwCygpNzCfEkBOyvhl88cUX+OCDD7Bq1Sq8+OKLOOecczBx4kREo1FR6UsGBoYzB0qlgvmEGHJC1jcDo9GIyZMn4//+7//w0Ucf4ZJLLsHbb7+NxsZGLFy4EJ999llr2MnAwJArmnxC3QpNKT8B2wgYMiCn0NLOnTtj3rx5eP/99/Hmm2+ic+fOuPPOO/NlGwMDAwNDK0F2aOkrr7yCG2+8kf//4MGDMXjwYCZHwcDAwNAOIPvN4NlnnyUef/XVV0+bMQwMDAwMbYOsbwZffvklACAej+Orr77itYkA4NixYzCZTPmzjoGBgYGhVZB1M7jnnnsAANFoFIsWLeKPKxQKFBUV4d57782fdQwMDAwMrYKsm8GGDRsQi8VQUVGB//73v9BqWdIKAwMDQ3uDLJ+BWq1Gr1690NDQkG97GBgYGBjaALKjiSZOnIibb74Zs2bNQmlpqei7UaNGnXbDGBgYGBhaD7I3gzfffBMAsHz5ctFxhUKBjz/++PRaxcDAwMDQqpC9GWzYsCGfdjAwMDAwtCFaXNyGgYGBgaH9oFU2g2XLlmH8+PHo168f9u7d2xpDMjAwMDDkgFbZDC6++GL84x//QOfOnVtjOAYGBgaGHJFz2cuWYNiwYa0xDAMDAwNDC8F8BgwMDAwMrfNmcDrgdJpb3LaoyHIaLTm70JHnDnTs+XfkuQMde/4tmftZsxm4XD4kErlX5ygqsqC21psHi858dOS5Ax17/h157kDHnj83d6VSkdOPaEYTMTAwMDC0zmawdOlSjBs3DtXV1bjhhhtwxRVXtMawDAwMDAwy0So00b333sukrhkYGBjOYDCaiIGBgYGBbQYMDAwMDGwzYGBgYGAA2wwYGBgYGMA2AwYGBgYGsM2AgYGBgQFsM2BgYGBgANsMGBgYGBjANgMGBgYGBrDNgIGBgYEBbDNgYGBgYADbDBgYGBgYwDYDBgYGBgawzYCBgYGBAWwzYGBgYGAA2wwYGBgYGMA2AwYGBgYGsM2AgYGBgQFsM2BgYGBgANsMGBgYGBjANgMGBgYGBrDNgIGBgYEBbDNgYGBgYADbDBgYGBgYwDYDBgYGBgawzYCBgYGBAWwzYGBgYGAA2wwYGBgYGMA2AwYGBgYGsM2AgYGBgQFsM2BgYGBgAKBIJpPJ1hjo0KFDuPvuu+F2u2G327Fs2TL06NFDdnuXy4dEIgdTNUCNK4x6TwhOmx7FDh0Qzd3u0w4l4PJE4GqyS6dWot4Tht2ig1IB/rPVoAaSLWzTdH69LwyHRQe9VgWXO5Q6x6Lm16WowAAFgJMNQZQ6jYjGEnA1huC066FTq1BTH0CRw4BotOl40zpy7bt3MsPri6HeE0KhXQ+1WonqugBKnAYkEkBtQxBOmx4moxpHq33o3tkMjycmuiakvooLDECTXYV2PVQqJWpcAXQtNcMfaG6v1ahQVedP68tp08NsUuPwCR86FZkQCsdR7wmhrNCISNNchP0WNY3H2SvsSzoXq1WNQ0d9IluKCwyAAjhZH0w7X9iX0JZCux4qpRI19QGUFZkQbjrOrdeRKh9KC43UtRdeL+F1FK5LlxIzAsH0NZX21a3MDJ+fvK4Wsxo/H/dlbC9cP+G8ih0GJJOp48K1F91rkr4K7Xpo1EpU1QVEbUocBiSa+ioq0EOpTF074Xik+0A4F61WhapaP4oLmuxyB1HiMCCeAOrcQdHxtDnaDVAqgZr6oGi9hW1E18Guh0alRLWr2S6PJwq3L5L2d8t9dtj0SMQT/DmiZ0AOKCqyoLbWC6VSAafTLLtdq20Gs2bNwq9+9StMmjQJa9aswb/+9S+89tprstvntBlogB0/1ePFVd8jHI1Dp1Fh7pSBqOjnaNsNQQl8d6AeL6xstmv6JeVYv/kQvP6o6POCqRXo380GKHJs08OG7/aLz58zaQDe3/IzupeYcW6vItG6TL+kHD8crMPIAZ2wYs0uUZuvdp3Aeb0K8daHe0Xr+OGWnzGojxMlTktaXyS75k4ZCJ0miXBUkXZNYrFo6o+9qS+LSYMrRvcUjTln0gDUNvjSxss0r7lTBkKBOJJQ4cVV36NbqRmXVfYQzTGTve9+vBdVrkDaeXOnDITDokK9N061l9RX5yITRg/qLGvt504ZCI8vCLNRn3b8wy0/I5ZIZpyLdL1INnJ2ndPdjoF9ionreqTah7lTBiISiSAYSfLt+3e345LKHrKuvXSOpOvAzWv3YTdxXWj3BGcjN15FH2fafSCdy/f7T6JbqQ1vfbhX1K90jDKnEddcXJ5xjpu/P4HRAztRrz03ti8QbVFf/DMgxyf0Gb0ZuFwuXHbZZdiyZQtUKhXi8TgqKyvxwQcfwOFwyOxD/mZQ4wljyYqvEI7G+WM6jQpL5oxEiVXXojmcDrh8Edz74pdpdk0a1xvvfLw37fOyeaMRjSdzavPATSOx+KX0uS+YVgG7WYcHX9mS9t2i64fjkb9vlX18wbQKOKx64hrT7FoyZyT1mgDgv5t6cTnWbDxAPI/UPtO8hG0WzhiKp9/eIdte7jPpPGG/NHulfZ3Xy5HTGmeaL4Csc5Fr4/l9C4lrt2BaBR5/4xuiLbmupXCOtLbceKR1odkvtFHuXO6/sZI/R9ivdAw513XBtIqs67BgWgUOV3lb3NeyeaNhNWiQC1q6GahzGqWFqKqqQklJCVQqFQBApVKhuLgYVVVVsjeDXCa1+1ijaFEBIByNo8EbwoDehfINP83YV32CaBcU5M+BaBzeQDSnNvWeMPH8UCQOt4/8nScQyel4KJKiNHKzi3x+vSfUfD4AKEA9L9d5CduEwvGc7OU+Z50LxV5pXx5/bmucab5IZh9Tro20tQtF4lRbcl1L4RxpbbnxiOtCsV9oo9y5iM4R9isdQ8Z1lbMOoUhcXl8Rcl+BaBy9u8l7RgpRVGTJuU2rbAanA7m8GThteug0qrRdtsCiR22tN18mZoXDoiPaxb0GSj8bNSpoLMqc2jit5DH0WhXslPGtJi35uJF8XK9VwUFZY5pdtPMdVj2ggOg74nmU9pnmJWxj0Ktyslf4ap5tLnL6tZpzW2OHlT5fhSL7mNL2tPNpa6fXqqh95bqWwjnS2nLj8W0k92Q2G+XOxW7WUfsltc00R4Mu+zoIx852Hukco0aV8zOrpW8GrRJNVFZWhpqaGsTjqYnG43GcPHkSZWVleRmv2KFr4qmbL8TcKQNR4mw7iggAnBYtbr5KbNf0S8qx4ZsjaZ8XTK2A1ajJuU2RXZd2/pxJA7D6s/34ZOvhtHWZfkk51m48gDmTBqS1WbvpAKZfUp62jus2HcCOPdXEvkh2zZ0yEPVuH/GaHK12i/rasO1I2phzJg0gjpdpXnOnDER1rYc/vurT/WlzzGTvph3HiOfNnTIQ4VAoo72kvtZuPEBe+03paz93ykD89HMd8fi6TQeyzmXOpAHY8VPmNeXs+mjLz9R15c47fKJB1J42F9JaSudIsp2bF+2epN0TnI3ceKT7QDqXj77+me9L2K90jE3bj2Wd46rP9me89tzYcvpaTeiLewa0FlrNgTxz5kxcffXVvAP5n//8J15//XXZ7VsaTdTgDaHAok9tBGdqNJE3DLtJC6VSwX+2GjWZo4kytWk6v8EXRoFZB71OBVdjKHWOVcOvS6HNAIWCi6pIRXjUe0L8L8Ga+lSkDXecW0eufbeyVARQgzfVRqNJRXgUF6QiP+rcQRRYUpE9R6t96N7JDI83JrompL4K7amojFp3EA6bHmqVEifrA+hSkorg4drrtCpUu/xpfRVYUlEwqYicVKROgzeUNke1OtVvoT0VDcPZK+yr2JGKDuK+s9nU+PmYD52LU5E6vL2KVKSLdO7CvoS2OKxN82oIoNRpQjgS523n1ktob7pdRsSavhNeR+G6dCo2IxhMX1NpX11LU9FEpHW1WlJRWZnaF9pS0VR17qBoXkVNkTZ1kvtLaLu0L4dVD60mFYVT6kxFE3HRPMmma1Ro00PZdE8IxyPdB/xcrE2f6/ypvpJAXWMQRfbU9XI1BlP3QdNxaV9OmwEqZVOEm2C9hX0JjzusqaiomvpmuzyeKNz+SNrfLffZYdEhkUjy54ieATngjHYgA8CBAwdw9913w+PxwGq1YtmyZejVq5fs9jlvBk3gFqYjoiPPHejY8+/Icwc69vzPaAcyAPTu3Rvvvvtuaw3HwMDAwJADWAYyAwMDAwPbDBgYGBgY2GbAwMDAwICzKM9AqVRkPykPbc92dOS5Ax17/h157kDHnr9Sqch5/q0WTcTAwMDAcOaC0UQMDAwMDGwzYGBgYGBgmwEDAwMDA9hmwMDAwMAAthkwMDAwMIBtBgwMDAwMYJsBAwMDAwPYZsDAwMDAALYZMDAwMDCgHW8Ghw4dwrRp03DZZZdh2rRp+Pnnn9vapFZDQ0MD5syZg8suuwwTJ07Erbfeivr6+rY2q9XxzDPPoF+/fti7d29bm9JqCIfDWLx4MS699FJMnDgR9913X1ub1Kr45JNPMHnyZEyaNAm//OUv8cEHH7S1SXnDsmXLMH78+LR7vMXPvmQ7xcyZM5OrV69OJpPJ5OrVq5MzZ85sY4taDw0NDcmvvvqK//+f/vSn5B//+Mc2tKj1sWvXruSNN96YvOiii5I//fRTW5vTanjooYeSDz/8cDKRSCSTyWSytra2jS1qPSQSieSwYcP467179+5kRUVFMh6Pt7Fl+cHWrVuTJ06cSLvHW/rsa5dvBi6XCz/++COuvPJKAMCVV16JH3/8scP8Orbb7aisrOT/X1FRgRMnTrShRa2LSCSCBx98EEuWLGlrU1oVfr8fq1evxm233QaFIiVSVlhY2MZWtS6USiW83lSFM6/Xi+LiYiiV7fIxh2HDhqXVkT+VZ99Zo1qaC6qqqlBSUgKVKlVcWqVSobi4GFVVVXA4HG1sXesikUjgzTffxPjx49valFbDU089hV/+8pfo0qVLW5vSqjh69CjsdjueeeYZbNmyBSaTCbfddhuGDRvW1qa1ChQKBZ588knMmzcPRqMRfr8fL730Ulub1ao4lWdf+9wyGXg89NBDMBqNmDFjRlub0irYvn07du3ahWuvvbatTWl1xONxHD16FOeeey5WrlyJO+64A/Pnz4fP52tr01oFsVgML774Ip577jl88skneP755/G///u/8Pv9bW3aWYF2uRmUlZWhpqYG8XgcQOqP5OTJk2mvVO0dy5Ytw+HDh/Hkk0+221dlKbZu3YoDBw7g4osvxvjx41FdXY0bb7wRn3/+eVublneUlZVBrVbzFMH555+PgoICHDp0qI0tax3s3r0bJ0+exNChQwEAQ4cOhcFgwIEDB9rYstbDqTz72uUTwul0on///li3bh0AYN26dejfv3+HooieeOIJ7Nq1C88++yy0Wm1bm9NquOmmm/D5559jw4YN2LBhA0pLS/HKK6/gggsuaGvT8g6Hw4HKykp88cUXAFJRJS6XC927d29jy1oHpaWlqK6uxsGDBwEABw4cgMvlQrdu3drYstbDqTz72m1xmwMHDuDuu++Gx+OB1WrFsmXL0KtXr7Y2q1Wwb98+XHnllejRowf0ej0AoEuXLnj22Wfb2LLWx/jx4/HCCy+gvLy8rU1pFRw9ehSLFi2C2+2GWq3G//7v/+LCCy9sa7NaDf/+97+xYsUK3oG+YMECTJgwoY2tyg+WLl2KDz74AHV1dSgoKIDdbsf69etb/Oxrt5sBAwMDA4N8tEuaiIGBgYEhN7DNgIGBgYGBbQYMDAwMDGwzYGBgYGAA2wwYGBgYGMA2A4azHOPHj8fmzZsBAMuXL8cdd9xxSv3Nnj0bq1aton5///33n1EhuidOnMDgwYP5JCMGhpaCbQYMZwyED3Yh/H4/Bg8ejNmzZ+fUXyQSwfLly3HppZeioqIC48ePxx//+EccO3aM2ubll1/GlClTAAArV67Er3/9a9H3Dz74IH73u9/lZIcQK1euRP/+/TF48GAMGTIEv/zlL/HJJ5/Ibi9do06dOmH79u28Fg0DQ0vBNgOGMwKxWIz63QcffACtVovNmzejtrZWdp8LFizAhg0b8Oc//xnbtm3DmjVrMGDAAHz55Zdp5yaTSSQSiRbZnisqKiqwfft2bNu2Dddeey3+8Ic/wOPxtMrYDAw0sM2Aoc0wfvx4vPTSS5g4cSLOP/98nDhxAjfffDMGDx6MFStW8OetWrUK06dPR79+/fDvf/9bVt+bN2/G5s2b8dxzz2HQoEFQq9WwWCz4zW9+g2uuuQYAMHPmTPz1r3/F9OnTcf755+Po0aOYOXMm3n33XRw4cACLFy/Gjh07MHjwYF758+6778Zf//pXfpyPPvoIkyZNwpAhQzBhwgRs3LgRQOoN4OKLL8bgwYMxfvx4ot1KpRKTJk1CIBDgC5AcOXIEs2bNQmVlJSorK3H77bfzG8XChQvT1ujYsWPo168fv5nOnDkTTz75JKZPn47Bgwfjt7/9rUi+ePXq1bjoootQWVmJZ599lvo2xtDxwDYDhjbF+vXr8dJLL+Gbb75Bp06d8MILL2D79u2YM2cOAOD48eP4+uuvMXHiREycOBGrV6+W1e/mzZsxaNCgrAJda9aswUMPPYRvv/0WnTp14o/37t0bDzzwgOhXvBQ7d+7EXXfdhTvvvBPbtm3DP/7xD3Tu3BmBQABLly7FihUrsH37drz11lvo379/Wvt4PI6VK1dCo9Ggc+fOAFJvKHPnzsWmTZvwn//8B9XV1Vi+fDkA4PHHHyeukRTr1q3Do48+ii+//BLRaBR/+9vfAAD79+/HAw88gMcffxybNm2Cz+dDTU2NrPVkaP9gmwFDm2LmzJkoKyvjNZSkWLNmDfr164c+ffrgiiuuwP79+/Hjjz9m7dftdqOoqCjreVOmTEHfvn2hVquh0Whysv2f//wnfvWrX2HMmDFQKpUoKSlB7969AaR+9e/btw+hUAjFxcXo27cv3+67777DsGHDMGjQICxbtgyPPfYYnE4nAKB79+4YM2YMtFotHA4HbrjhBmzdujUnu6666ir07NkTer0e/+///T/s3r0bAPDf//4XF110EYYNGwatVosFCxbwGj4MDGwzYGhTyPnlPnHiRABASUkJhg8fnjHah4PdbpflXzgVWfOqqiqiIqbRaMRf//pXvPXWW7jgggtw0003iWSUzz//fGzbtg1ff/01xo8fj2+++Yb/rq6uDr///e8xduxYDBkyBAsXLkRDQ0NOdgk3QYPBgEAgAAA4efIkSktLRd/Z7fac+mZov2CbAUObItMv02+//RY///wzXnrpJYwZMwZjxozBzp07sW7duowOZwAYPXo0du7cierq6haPn+1Xc1lZGY4cOUL8buzYsXj11Vfx+eefo1evXsTC9CaTCUuWLMGaNWv4t50nnngCCoUCa9euxbfffovHH38cp0tLsri4WEQLhUIhuN3u09I3w9kPthkwnDEoLCzE0aNH+f+vXr0aY8aMwfr167F69WqsXr0aa9euRSgU4h21NIwePRqjR4/G7373O+zatQuxWAw+nw9vvvkm/vnPf8qyx+l0oqamBpFIhPj91VdfjZUrV+LLL79EIpFATU0NDhw4gLq6Onz00UcIBALQarUwGo3U4kJ2ux3XXHMNn7vg9/thNBphsVhQU1ODl19+OeMa5YLLLrsMGzZswLfffsuH3TLRYgYObDNgOGNw00034fnnn8ewYcPw3HPP4T//+Q9mzJiBoqIi/l/Xrl0xadIkWY7kp59+GhdeeCF+//vfY9iwYZg4cSJ27dqF0aNHy7Jn5MiR6NOnDy644AJUVlamfT9o0CA8+uijeOSRRzB06FDMmDEDJ06cQCKRwN///neMHTsWI0aMwNatW7FkyRLqONdddx0+++wz7NmzB7feeit+/PFHDBs2DDfddBMuvfRS6hq98sorsubBoW/fvrjvvvvwhz/8AWPHjoXRaITD4ehQxY8Y6GD1DBgYOij8fj+GDx+O999/H127dm1rcxjaGOzNgIGhA2HDhg0IBoMIBAJYtmwZysvL0aVLl7Y2i+EMANsMGBg6ED7++GOMHTsWY8eOxeHDh3mHNQMDo4kYGBgYGNibAQMDAwMD2wwYGBgYGMA2AwYGBgYGsM2AgYGBgQFsM2BgYGBgANsMGBgYGBgA/P+fEKzYyaShagAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# investigate rtCriticsRating vs. rtAudienceRating\n",
    "sns.scatterplot(x=\"rtAllCriticsRating\", y=\"rtAudienceRating\", data=movies);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "8fbf44ae-39c8-41d5-bc7c-ef5aad3f7812",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>imdbID</th>\n",
       "      <th>spanishTitle</th>\n",
       "      <th>imdbPictureURL</th>\n",
       "      <th>year</th>\n",
       "      <th>rtID</th>\n",
       "      <th>rtAllCriticsRating</th>\n",
       "      <th>rtAllCriticsNumReviews</th>\n",
       "      <th>rtAllCriticsNumFresh</th>\n",
       "      <th>rtAllCriticsNumRotten</th>\n",
       "      <th>rtAllCriticsScore</th>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "      <th>rtTopCriticsNumReviews</th>\n",
       "      <th>rtTopCriticsNumFresh</th>\n",
       "      <th>rtTopCriticsNumRotten</th>\n",
       "      <th>rtTopCriticsScore</th>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <th>rtAudienceNumRatings</th>\n",
       "      <th>rtAudienceScore</th>\n",
       "      <th>rtPictureURL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Twelve Monkeys</td>\n",
       "      <td>114746</td>\n",
       "      <td>Twelve monkeys: doce monos</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTQwNzg2OTUzMV5BMl5BanBnXkFtZTYwMTg4ODU5._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>prem-no-public-issue</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/93/02/10930244_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Wings of Courage</td>\n",
       "      <td>114952</td>\n",
       "      <td>Las alas del coraje</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTc3ODY1MjA3OF5BMl5BanBnXkFtZTcwODgzOTgyMQ@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/97/83/10978341_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Across the Sea of Time</td>\n",
       "      <td>112286</td>\n",
       "      <td>Across the Sea of Time</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BNTQyMTE3MzY4Nl5BMl5BanBnXkFtZTcwMzY5MTAyMQ@@._V1._SX78_SY140_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>across_the_sea_of_time</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>237.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/90/58/10905808_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>Clueless</td>\n",
       "      <td>112697</td>\n",
       "      <td>Clueless: fuera de onda</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BNjQxNTA1NjE5Ml5BMl5BanBnXkFtZTYwOTMwNzE5._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>school_of_senses</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content8.flixster.com/movie/10/85/01/10850110_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>56</td>\n",
       "      <td>Kids of the Round Table</td>\n",
       "      <td>113541</td>\n",
       "      <td>Los chicos de la tabla redonda</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTEwMTM0MzI3OTheQTJeQWpwZ15BbWU3MDQzNTQ2MTE@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1997</td>\n",
       "      <td>kids-of-the-round-table</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/85/20/10852069_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10186</th>\n",
       "      <td>64993</td>\n",
       "      <td>Byôsoku 5 senchimêtoru</td>\n",
       "      <td>983213</td>\n",
       "      <td>Byôsoku 5 senchimêtoru</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2007</td>\n",
       "      <td>5_centimeters_per_second</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1726.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>http://content7.flixster.com/movie/85/24/71/8524717_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10188</th>\n",
       "      <td>64999</td>\n",
       "      <td>War of the Worlds 2: The Next Wave</td>\n",
       "      <td>1183733</td>\n",
       "      <td>War of the Worlds 2: The Next Wave</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTIyODE1NDM4Ml5BMl5BanBnXkFtZTcwNDcxMTA3MQ@@._V1._SY314_CR2,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>war_of_the_worlds_2_the_next_wave</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/84/11/10841124_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10189</th>\n",
       "      <td>65006</td>\n",
       "      <td>Impulse</td>\n",
       "      <td>1078899</td>\n",
       "      <td>Impulse</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5NTc0MzI1Nl5BMl5BanBnXkFtZTcwMTUwMDY4Mw@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>impulse</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content8.flixster.com/movie/10/87/85/10878514_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10190</th>\n",
       "      <td>65011</td>\n",
       "      <td>Zona Zamfirova</td>\n",
       "      <td>326449</td>\n",
       "      <td>Zona Zamfirova</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2002</td>\n",
       "      <td>zona-zamfirova</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://images.rottentomatoescdn.com/images/defaults/poster_default.gif</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10196</th>\n",
       "      <td>65133</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>212579</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1999</td>\n",
       "      <td>blackadder-back-forth</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/34/10/69/3410693_det.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1526 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                               title   imdbID  \\\n",
       "31        32                      Twelve Monkeys   114746   \n",
       "32        33                    Wings of Courage   114952   \n",
       "36        37              Across the Sea of Time   112286   \n",
       "38        39                            Clueless   112697   \n",
       "54        56             Kids of the Round Table   113541   \n",
       "...      ...                                 ...      ...   \n",
       "10186  64993              Byôsoku 5 senchimêtoru   983213   \n",
       "10188  64999  War of the Worlds 2: The Next Wave  1183733   \n",
       "10189  65006                             Impulse  1078899   \n",
       "10190  65011                      Zona Zamfirova   326449   \n",
       "10196  65133             Blackadder Back & Forth   212579   \n",
       "\n",
       "                             spanishTitle  \\\n",
       "31             Twelve monkeys: doce monos   \n",
       "32                    Las alas del coraje   \n",
       "36                 Across the Sea of Time   \n",
       "38                Clueless: fuera de onda   \n",
       "54         Los chicos de la tabla redonda   \n",
       "...                                   ...   \n",
       "10186              Byôsoku 5 senchimêtoru   \n",
       "10188  War of the Worlds 2: The Next Wave   \n",
       "10189                             Impulse   \n",
       "10190                      Zona Zamfirova   \n",
       "10196             Blackadder Back & Forth   \n",
       "\n",
       "                                                                                                         imdbPictureURL  \\\n",
       "31         http://ia.media-imdb.com/images/M/MV5BMTQwNzg2OTUzMV5BMl5BanBnXkFtZTYwMTg4ODU5._V1._SX214_CR0,0,214,314_.jpg   \n",
       "32     http://ia.media-imdb.com/images/M/MV5BMTc3ODY1MjA3OF5BMl5BanBnXkFtZTcwODgzOTgyMQ@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "36              http://ia.media-imdb.com/images/M/MV5BNTQyMTE3MzY4Nl5BMl5BanBnXkFtZTcwMzY5MTAyMQ@@._V1._SX78_SY140_.jpg   \n",
       "38         http://ia.media-imdb.com/images/M/MV5BNjQxNTA1NjE5Ml5BMl5BanBnXkFtZTYwOTMwNzE5._V1._SY314_CR3,0,214,314_.jpg   \n",
       "54     http://ia.media-imdb.com/images/M/MV5BMTEwMTM0MzI3OTheQTJeQWpwZ15BbWU3MDQzNTQ2MTE@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "...                                                                                                                 ...   \n",
       "10186                                                                                                               NaN   \n",
       "10188  http://ia.media-imdb.com/images/M/MV5BMTIyODE1NDM4Ml5BMl5BanBnXkFtZTcwNDcxMTA3MQ@@._V1._SY314_CR2,0,214,314_.jpg   \n",
       "10189  http://ia.media-imdb.com/images/M/MV5BMjA5NTc0MzI1Nl5BMl5BanBnXkFtZTcwMTUwMDY4Mw@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "10190                                                                                                               NaN   \n",
       "10196  http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "\n",
       "       year                               rtID  rtAllCriticsRating  \\\n",
       "31     1995               prem-no-public-issue                 0.0   \n",
       "32     1995                                NaN                 0.0   \n",
       "36     1995             across_the_sea_of_time                 0.0   \n",
       "38     1995                   school_of_senses                 0.0   \n",
       "54     1997            kids-of-the-round-table                 0.0   \n",
       "...     ...                                ...                 ...   \n",
       "10186  2007           5_centimeters_per_second                 0.0   \n",
       "10188  2008  war_of_the_worlds_2_the_next_wave                 0.0   \n",
       "10189  2008                            impulse                 0.0   \n",
       "10190  2002                     zona-zamfirova                 0.0   \n",
       "10196  1999              blackadder-back-forth                 0.0   \n",
       "\n",
       "       rtAllCriticsNumReviews  rtAllCriticsNumFresh  rtAllCriticsNumRotten  \\\n",
       "31                        0.0                   0.0                    0.0   \n",
       "32                        4.0                   2.0                    2.0   \n",
       "36                        4.0                   2.0                    2.0   \n",
       "38                        0.0                   0.0                    0.0   \n",
       "54                        0.0                   0.0                    0.0   \n",
       "...                       ...                   ...                    ...   \n",
       "10186                     2.0                   2.0                    0.0   \n",
       "10188                     0.0                   0.0                    0.0   \n",
       "10189                     2.0                   0.0                    2.0   \n",
       "10190                     0.0                   0.0                    0.0   \n",
       "10196                     0.0                   0.0                    0.0   \n",
       "\n",
       "       rtAllCriticsScore  rtTopCriticsRating  rtTopCriticsNumReviews  \\\n",
       "31                   0.0                 0.0                     0.0   \n",
       "32                  50.0                 0.0                     2.0   \n",
       "36                  50.0                 0.0                     1.0   \n",
       "38                   0.0                 0.0                     0.0   \n",
       "54                   0.0                 0.0                     0.0   \n",
       "...                  ...                 ...                     ...   \n",
       "10186              100.0                 0.0                     1.0   \n",
       "10188                0.0                 0.0                     0.0   \n",
       "10189                0.0                 0.0                     0.0   \n",
       "10190                0.0                 0.0                     0.0   \n",
       "10196                0.0                 0.0                     0.0   \n",
       "\n",
       "       rtTopCriticsNumFresh  rtTopCriticsNumRotten  rtTopCriticsScore  \\\n",
       "31                      0.0                    0.0                0.0   \n",
       "32                      1.0                    1.0               50.0   \n",
       "36                      0.0                    1.0                0.0   \n",
       "38                      0.0                    0.0                0.0   \n",
       "54                      0.0                    0.0                0.0   \n",
       "...                     ...                    ...                ...   \n",
       "10186                   1.0                    0.0              100.0   \n",
       "10188                   0.0                    0.0                0.0   \n",
       "10189                   0.0                    0.0                0.0   \n",
       "10190                   0.0                    0.0                0.0   \n",
       "10196                   0.0                    0.0                0.0   \n",
       "\n",
       "       rtAudienceRating  rtAudienceNumRatings  rtAudienceScore  \\\n",
       "31                  0.0                   0.0              0.0   \n",
       "32                  0.0                   0.0              0.0   \n",
       "36                  2.9                 237.0             27.0   \n",
       "38                  0.0                   0.0              0.0   \n",
       "54                  0.0                   0.0              0.0   \n",
       "...                 ...                   ...              ...   \n",
       "10186               4.3                1726.0             91.0   \n",
       "10188               0.0                   0.0              0.0   \n",
       "10189               0.0                   0.0              0.0   \n",
       "10190               0.0                   0.0              0.0   \n",
       "10196               0.0                   0.0              0.0   \n",
       "\n",
       "                                                                 rtPictureURL  \n",
       "31               http://content6.flixster.com/movie/10/93/02/10930244_det.jpg  \n",
       "32               http://content7.flixster.com/movie/10/97/83/10978341_det.jpg  \n",
       "36               http://content6.flixster.com/movie/10/90/58/10905808_det.jpg  \n",
       "38               http://content8.flixster.com/movie/10/85/01/10850110_det.jpg  \n",
       "54               http://content7.flixster.com/movie/10/85/20/10852069_det.jpg  \n",
       "...                                                                       ...  \n",
       "10186             http://content7.flixster.com/movie/85/24/71/8524717_det.jpg  \n",
       "10188            http://content6.flixster.com/movie/10/84/11/10841124_det.jpg  \n",
       "10189            http://content8.flixster.com/movie/10/87/85/10878514_det.jpg  \n",
       "10190  http://images.rottentomatoescdn.com/images/defaults/poster_default.gif  \n",
       "10196             http://content7.flixster.com/movie/34/10/69/3410693_det.jpg  \n",
       "\n",
       "[1526 rows x 21 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# investigate 0 ratings for critics\n",
    "movies.query(\"rtAllCriticsRating == 0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "c6b2775f-a28d-43e3-a09f-904b867fbf56",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>imdbID</th>\n",
       "      <th>spanishTitle</th>\n",
       "      <th>imdbPictureURL</th>\n",
       "      <th>year</th>\n",
       "      <th>rtID</th>\n",
       "      <th>rtAllCriticsRating</th>\n",
       "      <th>rtAllCriticsNumReviews</th>\n",
       "      <th>rtAllCriticsNumFresh</th>\n",
       "      <th>rtAllCriticsNumRotten</th>\n",
       "      <th>rtAllCriticsScore</th>\n",
       "      <th>rtTopCriticsRating</th>\n",
       "      <th>rtTopCriticsNumReviews</th>\n",
       "      <th>rtTopCriticsNumFresh</th>\n",
       "      <th>rtTopCriticsNumRotten</th>\n",
       "      <th>rtTopCriticsScore</th>\n",
       "      <th>rtAudienceRating</th>\n",
       "      <th>rtAudienceNumRatings</th>\n",
       "      <th>rtAudienceScore</th>\n",
       "      <th>rtPictureURL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Twelve Monkeys</td>\n",
       "      <td>114746</td>\n",
       "      <td>Twelve monkeys: doce monos</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTQwNzg2OTUzMV5BMl5BanBnXkFtZTYwMTg4ODU5._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>prem-no-public-issue</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/93/02/10930244_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Wings of Courage</td>\n",
       "      <td>114952</td>\n",
       "      <td>Las alas del coraje</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTc3ODY1MjA3OF5BMl5BanBnXkFtZTcwODgzOTgyMQ@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/97/83/10978341_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>Clueless</td>\n",
       "      <td>112697</td>\n",
       "      <td>Clueless: fuera de onda</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BNjQxNTA1NjE5Ml5BMl5BanBnXkFtZTYwOTMwNzE5._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>school_of_senses</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content8.flixster.com/movie/10/85/01/10850110_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>56</td>\n",
       "      <td>Kids of the Round Table</td>\n",
       "      <td>113541</td>\n",
       "      <td>Los chicos de la tabla redonda</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTEwMTM0MzI3OTheQTJeQWpwZ15BbWU3MDQzNTQ2MTE@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1997</td>\n",
       "      <td>kids-of-the-round-table</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/85/20/10852069_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>59</td>\n",
       "      <td>Le confessionnal</td>\n",
       "      <td>112714</td>\n",
       "      <td>Le confessionnal</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTk2MDE1MTYyNl5BMl5BanBnXkFtZTcwMzc3NDEzMQ@@._V1._SX214_CR0,0,214,314_.jpg</td>\n",
       "      <td>1995</td>\n",
       "      <td>confessional</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://images.rottentomatoescdn.com/images/defaults/poster_default.gif</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10182</th>\n",
       "      <td>64976</td>\n",
       "      <td>Hexed</td>\n",
       "      <td>107107</td>\n",
       "      <td>Linda, loca y peligrosa</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTYyNjE1MjMwOF5BMl5BanBnXkFtZTcwNTgwMDAzMQ@@._V1._SY314_CR0,0,214,314_.jpg</td>\n",
       "      <td>1993</td>\n",
       "      <td>hexed</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/10/92/33/10923349_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10188</th>\n",
       "      <td>64999</td>\n",
       "      <td>War of the Worlds 2: The Next Wave</td>\n",
       "      <td>1183733</td>\n",
       "      <td>War of the Worlds 2: The Next Wave</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMTIyODE1NDM4Ml5BMl5BanBnXkFtZTcwNDcxMTA3MQ@@._V1._SY314_CR2,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>war_of_the_worlds_2_the_next_wave</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content6.flixster.com/movie/10/84/11/10841124_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10189</th>\n",
       "      <td>65006</td>\n",
       "      <td>Impulse</td>\n",
       "      <td>1078899</td>\n",
       "      <td>Impulse</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5NTc0MzI1Nl5BMl5BanBnXkFtZTcwMTUwMDY4Mw@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>2008</td>\n",
       "      <td>impulse</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content8.flixster.com/movie/10/87/85/10878514_det.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10190</th>\n",
       "      <td>65011</td>\n",
       "      <td>Zona Zamfirova</td>\n",
       "      <td>326449</td>\n",
       "      <td>Zona Zamfirova</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2002</td>\n",
       "      <td>zona-zamfirova</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://images.rottentomatoescdn.com/images/defaults/poster_default.gif</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10196</th>\n",
       "      <td>65133</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>212579</td>\n",
       "      <td>Blackadder Back &amp; Forth</td>\n",
       "      <td>http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg</td>\n",
       "      <td>1999</td>\n",
       "      <td>blackadder-back-forth</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://content7.flixster.com/movie/34/10/69/3410693_det.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2622 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                               title   imdbID  \\\n",
       "31        32                      Twelve Monkeys   114746   \n",
       "32        33                    Wings of Courage   114952   \n",
       "38        39                            Clueless   112697   \n",
       "54        56             Kids of the Round Table   113541   \n",
       "57        59                    Le confessionnal   112714   \n",
       "...      ...                                 ...      ...   \n",
       "10182  64976                               Hexed   107107   \n",
       "10188  64999  War of the Worlds 2: The Next Wave  1183733   \n",
       "10189  65006                             Impulse  1078899   \n",
       "10190  65011                      Zona Zamfirova   326449   \n",
       "10196  65133             Blackadder Back & Forth   212579   \n",
       "\n",
       "                             spanishTitle  \\\n",
       "31             Twelve monkeys: doce monos   \n",
       "32                    Las alas del coraje   \n",
       "38                Clueless: fuera de onda   \n",
       "54         Los chicos de la tabla redonda   \n",
       "57                       Le confessionnal   \n",
       "...                                   ...   \n",
       "10182             Linda, loca y peligrosa   \n",
       "10188  War of the Worlds 2: The Next Wave   \n",
       "10189                             Impulse   \n",
       "10190                      Zona Zamfirova   \n",
       "10196             Blackadder Back & Forth   \n",
       "\n",
       "                                                                                                         imdbPictureURL  \\\n",
       "31         http://ia.media-imdb.com/images/M/MV5BMTQwNzg2OTUzMV5BMl5BanBnXkFtZTYwMTg4ODU5._V1._SX214_CR0,0,214,314_.jpg   \n",
       "32     http://ia.media-imdb.com/images/M/MV5BMTc3ODY1MjA3OF5BMl5BanBnXkFtZTcwODgzOTgyMQ@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "38         http://ia.media-imdb.com/images/M/MV5BNjQxNTA1NjE5Ml5BMl5BanBnXkFtZTYwOTMwNzE5._V1._SY314_CR3,0,214,314_.jpg   \n",
       "54     http://ia.media-imdb.com/images/M/MV5BMTEwMTM0MzI3OTheQTJeQWpwZ15BbWU3MDQzNTQ2MTE@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "57     http://ia.media-imdb.com/images/M/MV5BMTk2MDE1MTYyNl5BMl5BanBnXkFtZTcwMzc3NDEzMQ@@._V1._SX214_CR0,0,214,314_.jpg   \n",
       "...                                                                                                                 ...   \n",
       "10182  http://ia.media-imdb.com/images/M/MV5BMTYyNjE1MjMwOF5BMl5BanBnXkFtZTcwNTgwMDAzMQ@@._V1._SY314_CR0,0,214,314_.jpg   \n",
       "10188  http://ia.media-imdb.com/images/M/MV5BMTIyODE1NDM4Ml5BMl5BanBnXkFtZTcwNDcxMTA3MQ@@._V1._SY314_CR2,0,214,314_.jpg   \n",
       "10189  http://ia.media-imdb.com/images/M/MV5BMjA5NTc0MzI1Nl5BMl5BanBnXkFtZTcwMTUwMDY4Mw@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "10190                                                                                                               NaN   \n",
       "10196  http://ia.media-imdb.com/images/M/MV5BMjA5MjU4MTUxM15BMl5BanBnXkFtZTcwNTI4MzQyMQ@@._V1._SY314_CR3,0,214,314_.jpg   \n",
       "\n",
       "       year                               rtID  rtAllCriticsRating  \\\n",
       "31     1995               prem-no-public-issue                 0.0   \n",
       "32     1995                                NaN                 0.0   \n",
       "38     1995                   school_of_senses                 0.0   \n",
       "54     1997            kids-of-the-round-table                 0.0   \n",
       "57     1995                       confessional                 0.0   \n",
       "...     ...                                ...                 ...   \n",
       "10182  1993                              hexed                 2.0   \n",
       "10188  2008  war_of_the_worlds_2_the_next_wave                 0.0   \n",
       "10189  2008                            impulse                 0.0   \n",
       "10190  2002                     zona-zamfirova                 0.0   \n",
       "10196  1999              blackadder-back-forth                 0.0   \n",
       "\n",
       "       rtAllCriticsNumReviews  rtAllCriticsNumFresh  rtAllCriticsNumRotten  \\\n",
       "31                        0.0                   0.0                    0.0   \n",
       "32                        4.0                   2.0                    2.0   \n",
       "38                        0.0                   0.0                    0.0   \n",
       "54                        0.0                   0.0                    0.0   \n",
       "57                        1.0                   1.0                    0.0   \n",
       "...                       ...                   ...                    ...   \n",
       "10182                     8.0                   1.0                    7.0   \n",
       "10188                     0.0                   0.0                    0.0   \n",
       "10189                     2.0                   0.0                    2.0   \n",
       "10190                     0.0                   0.0                    0.0   \n",
       "10196                     0.0                   0.0                    0.0   \n",
       "\n",
       "       rtAllCriticsScore  rtTopCriticsRating  rtTopCriticsNumReviews  \\\n",
       "31                   0.0                 0.0                     0.0   \n",
       "32                  50.0                 0.0                     2.0   \n",
       "38                   0.0                 0.0                     0.0   \n",
       "54                   0.0                 0.0                     0.0   \n",
       "57                 100.0                 0.0                     0.0   \n",
       "...                  ...                 ...                     ...   \n",
       "10182               12.0                 0.0                     2.0   \n",
       "10188                0.0                 0.0                     0.0   \n",
       "10189                0.0                 0.0                     0.0   \n",
       "10190                0.0                 0.0                     0.0   \n",
       "10196                0.0                 0.0                     0.0   \n",
       "\n",
       "       rtTopCriticsNumFresh  rtTopCriticsNumRotten  rtTopCriticsScore  \\\n",
       "31                      0.0                    0.0                0.0   \n",
       "32                      1.0                    1.0               50.0   \n",
       "38                      0.0                    0.0                0.0   \n",
       "54                      0.0                    0.0                0.0   \n",
       "57                      0.0                    0.0                0.0   \n",
       "...                     ...                    ...                ...   \n",
       "10182                   0.0                    2.0                0.0   \n",
       "10188                   0.0                    0.0                0.0   \n",
       "10189                   0.0                    0.0                0.0   \n",
       "10190                   0.0                    0.0                0.0   \n",
       "10196                   0.0                    0.0                0.0   \n",
       "\n",
       "       rtAudienceRating  rtAudienceNumRatings  rtAudienceScore  \\\n",
       "31                  0.0                   0.0              0.0   \n",
       "32                  0.0                   0.0              0.0   \n",
       "38                  0.0                   0.0              0.0   \n",
       "54                  0.0                   0.0              0.0   \n",
       "57                  0.0                   0.0              0.0   \n",
       "...                 ...                   ...              ...   \n",
       "10182               0.0                   0.0              0.0   \n",
       "10188               0.0                   0.0              0.0   \n",
       "10189               0.0                   0.0              0.0   \n",
       "10190               0.0                   0.0              0.0   \n",
       "10196               0.0                   0.0              0.0   \n",
       "\n",
       "                                                                 rtPictureURL  \n",
       "31               http://content6.flixster.com/movie/10/93/02/10930244_det.jpg  \n",
       "32               http://content7.flixster.com/movie/10/97/83/10978341_det.jpg  \n",
       "38               http://content8.flixster.com/movie/10/85/01/10850110_det.jpg  \n",
       "54               http://content7.flixster.com/movie/10/85/20/10852069_det.jpg  \n",
       "57     http://images.rottentomatoescdn.com/images/defaults/poster_default.gif  \n",
       "...                                                                       ...  \n",
       "10182            http://content7.flixster.com/movie/10/92/33/10923349_det.jpg  \n",
       "10188            http://content6.flixster.com/movie/10/84/11/10841124_det.jpg  \n",
       "10189            http://content8.flixster.com/movie/10/87/85/10878514_det.jpg  \n",
       "10190  http://images.rottentomatoescdn.com/images/defaults/poster_default.gif  \n",
       "10196             http://content7.flixster.com/movie/34/10/69/3410693_det.jpg  \n",
       "\n",
       "[2622 rows x 21 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# investigate 0 ratings for audience\n",
    "movies.query(\"rtAudienceRating == 0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "184b1432-593c-4f54-9b5d-abf745aaee79",
   "metadata": {},
   "outputs": [],
   "source": [
    "# either remove movies from dataset or set 0 values to na\n",
    "movies[\"rtAllCriticsRating\"].replace(0, np.nan, inplace=True)\n",
    "movies[\"rtAudienceRating\"].replace(0, np.nan, inplace=True)\n",
    "movies[\"rtTopCriticsRating\"].replace(0, np.nan, inplace=True)\n",
    "\n",
    "# removing rows with na would work as follows after the replacement\n",
    "# movies = movies.dropna(how='any', axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f9778d75-a095-498b-a048-e8b293879b4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# alternatively, replace via loc\n",
    "movies.loc[movies[\"rtAllCriticsRating\"] == 0, \"rtAllCriticsRating\"] = np.nan\n",
    "movies.loc[movies[\"rtAudienceRating\"] == 0, \"rtAudienceRating\"] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "bc0c9e38-4878-4988-b94e-8925d877e501",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='rtAllCriticsRating', ylabel='rtAudienceRating'>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# resulting scatterplot\n",
    "sns.scatterplot(x=\"rtAllCriticsRating\", y=\"rtAudienceRating\", data=movies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "eb2b5055-388f-498c-aed1-5acf32f281de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fit a regression model (trend line) to this data\n",
    "sns.set_theme(color_codes=True)\n",
    "\n",
    "ax = sns.regplot(\n",
    "    x=\"rtAllCriticsRating\",\n",
    "    y=\"rtAudienceRating\",\n",
    "    data=movies,\n",
    "    color=\"b\",\n",
    "    line_kws={\"color\": \"red\"},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "358d5098-afdf-46a5-9f3a-1744f035ebaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# use scatterplot and include distributions of individual variables: jointplot\n",
    "sns.jointplot(x=\"rtAllCriticsRating\", y=\"rtAudienceRating\", data=movies);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03cb4fed-f157-4c86-a40a-f0c6813499cf",
   "metadata": {},
   "source": [
    "In our previous examples we have focused on investigating the relationship between two variables, however, we can also investigate the (pairwise) relationships between multiple variables by using multiple scatterplots in a matrix by using Seaborns `pairplot` (or e.g., Pandas `scatter_matrix`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "932bf977-13d7-4a10-8922-419a7dfb97c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(\n",
    "    movies[[\"rtAllCriticsRating\", \"rtTopCriticsRating\", \"rtAudienceRating\"]]\n",
    ");"
   ]
  }
 ],
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