data_analytics_19.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "<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>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1260759144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating   timestamp\n",
       "0       1       31     2.5  1260759144"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings = pd.read_csv('ratings_example.txt', sep='\\t')\n",
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32</td>\n",
       "      <td>Twelve Monkeys (a.k.a. 12 Monkeys) (1995)</td>\n",
       "      <td>Mystery|Sci-Fi|Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   movieId                                      title                   genres\n",
       "0       31                    Dangerous Minds (1995)                     Drama\n",
       "1       32  Twelve Monkeys (a.k.a. 12 Monkeys) (1995)  Mystery|Sci-Fi|Thriller\n",
       "2       31                    Dangerous Minds (1995)                     Drama"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies = pd.read_csv('movies_example.txt', sep='\\t')\n",
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1260759144</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1260759144</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
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      ],
      "text/plain": [
       "   userId  movieId  rating   timestamp                    title genres\n",
       "0       1       31     2.5  1260759144  Dangerous Minds (1995)   Drama\n",
       "1       1       31     2.5  1260759144  Dangerous Minds (1995)   Drama"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.merge(movies, on='movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.drop_duplicates(subset='movieId', keep='first', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32</td>\n",
       "      <td>Twelve Monkeys (a.k.a. 12 Monkeys) (1995)</td>\n",
       "      <td>Mystery|Sci-Fi|Thriller</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   movieId                                      title                   genres\n",
       "0       31                    Dangerous Minds (1995)                     Drama\n",
       "1       32  Twelve Monkeys (a.k.a. 12 Monkeys) (1995)  Mystery|Sci-Fi|Thriller"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "genres = ['Drama', 'Action', 'Thriller']\n",
    "\n",
    "ratings = pd.read_csv('ratings.csv')\n",
    "\n",
    "movies = pd.read_csv('movies.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined = ratings.merge(movies, on='movieId', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drama 44752\n",
      "Action 27056\n",
      "Thriller 25240\n",
      "Comedy 38026\n",
      "Romance 19336\n",
      "War 5025\n",
      "Mystery 7625\n",
      "Crime 16266\n"
     ]
    }
   ],
   "source": [
    "genres = ['Drama', 'Action', 'Thriller', 'Comedy', 'Romance', 'War', 'Mystery', 'Crime']\n",
    "\n",
    "def genres_ratings(row):\n",
    "    return pd.Series([row['rating'] if genre in row['genres'] else np.NaN for genre in genres])\n",
    "\n",
    "joined[genres] = joined.apply(genres_ratings, axis=1)\n",
    "\n",
    "# Определяем, сколько оценок имеет жанр с наименьшим кол-вом оценок\n",
    "for genre in genres:\n",
    "    print(genre, len(joined[genre]) - joined[genre].isna().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "years = [str(x) for x in range(1950, 2011)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def production_year(row):\n",
    "    for year in years:\n",
    "        if year in row['title']:\n",
    "            return year\n",
    "    else:\n",
    "        return '1900'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined['year'] = joined.apply(production_year, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "      <th>Drama</th>\n",
       "      <th>Action</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>Comedy</th>\n",
       "      <th>Romance</th>\n",
       "      <th>War</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Crime</th>\n",
       "      <th>year</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1260759144</td>\n",
       "      <td>Dangerous Minds (1995)</td>\n",
       "      <td>Drama</td>\n",
       "      <td>2.5</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>1995</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1029</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1260759179</td>\n",
       "      <td>Dumbo (1941)</td>\n",
       "      <td>Animation|Children|Drama|Musical</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1061</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1260759182</td>\n",
       "      <td>Sleepers (1996)</td>\n",
       "      <td>Thriller</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1129</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1260759185</td>\n",
       "      <td>Escape from New York (1981)</td>\n",
       "      <td>Action|Adventure|Sci-Fi|Thriller</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1172</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1260759205</td>\n",
       "      <td>Cinema Paradiso (Nuovo cinema Paradiso) (1989)</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating   timestamp  \\\n",
       "0       1       31     2.5  1260759144   \n",
       "1       1     1029     3.0  1260759179   \n",
       "2       1     1061     3.0  1260759182   \n",
       "3       1     1129     2.0  1260759185   \n",
       "4       1     1172     4.0  1260759205   \n",
       "\n",
       "                                            title  \\\n",
       "0                          Dangerous Minds (1995)   \n",
       "1                                    Dumbo (1941)   \n",
       "2                                 Sleepers (1996)   \n",
       "3                     Escape from New York (1981)   \n",
       "4  Cinema Paradiso (Nuovo cinema Paradiso) (1989)   \n",
       "\n",
       "                             genres  Drama  Action  Thriller  Comedy  Romance  \\\n",
       "0                             Drama    2.5     NaN       NaN     NaN      NaN   \n",
       "1  Animation|Children|Drama|Musical    3.0     NaN       NaN     NaN      NaN   \n",
       "2                          Thriller    NaN     NaN       3.0     NaN      NaN   \n",
       "3  Action|Adventure|Sci-Fi|Thriller    NaN     2.0       2.0     NaN      NaN   \n",
       "4                             Drama    4.0     NaN       NaN     NaN      NaN   \n",
       "\n",
       "   War  Mystery  Crime  year  \n",
       "0  NaN      NaN    NaN  1995  \n",
       "1  NaN      NaN    NaN  1900  \n",
       "2  NaN      NaN    NaN  1996  \n",
       "3  NaN      NaN    NaN  1981  \n",
       "4  NaN      NaN    NaN  1989  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>Drama</th>\n",
       "      <th>Action</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>Comedy</th>\n",
       "      <th>Romance</th>\n",
       "      <th>War</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Crime</th>\n",
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       "    <tr>\n",
       "      <th>year</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",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1957</th>\n",
       "      <td>360.933544</td>\n",
       "      <td>2750.965190</td>\n",
       "      <td>4.014241</td>\n",
       "      <td>1.083707e+09</td>\n",
       "      <td>4.056569</td>\n",
       "      <td>4.136364</td>\n",
       "      <td>3.842105</td>\n",
       "      <td>3.785714</td>\n",
       "      <td>3.671429</td>\n",
       "      <td>4.123656</td>\n",
       "      <td>3.687500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>359.694878</td>\n",
       "      <td>3983.538976</td>\n",
       "      <td>4.011136</td>\n",
       "      <td>1.122759e+09</td>\n",
       "      <td>4.108000</td>\n",
       "      <td>3.239130</td>\n",
       "      <td>3.736364</td>\n",
       "      <td>3.655738</td>\n",
       "      <td>3.470588</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.684211</td>\n",
       "      <td>4.420561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1952</th>\n",
       "      <td>346.394737</td>\n",
       "      <td>4107.796053</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.090512e+09</td>\n",
       "      <td>3.902778</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.068750</td>\n",
       "      <td>3.978495</td>\n",
       "      <td>3.166667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954</th>\n",
       "      <td>358.228324</td>\n",
       "      <td>2867.661850</td>\n",
       "      <td>3.994220</td>\n",
       "      <td>1.070591e+09</td>\n",
       "      <td>3.967456</td>\n",
       "      <td>4.263636</td>\n",
       "      <td>4.197581</td>\n",
       "      <td>3.634146</td>\n",
       "      <td>3.576087</td>\n",
       "      <td>3.666667</td>\n",
       "      <td>4.233051</td>\n",
       "      <td>4.205357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1951</th>\n",
       "      <td>347.106996</td>\n",
       "      <td>2605.588477</td>\n",
       "      <td>3.983539</td>\n",
       "      <td>1.052714e+09</td>\n",
       "      <td>3.949541</td>\n",
       "      <td>4.125000</td>\n",
       "      <td>4.046512</td>\n",
       "      <td>4.341667</td>\n",
       "      <td>4.234940</td>\n",
       "      <td>4.398148</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.196429</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>348.509719</td>\n",
       "      <td>37156.244600</td>\n",
       "      <td>3.448434</td>\n",
       "      <td>1.273459e+09</td>\n",
       "      <td>3.503771</td>\n",
       "      <td>3.394326</td>\n",
       "      <td>3.433043</td>\n",
       "      <td>3.328800</td>\n",
       "      <td>3.467153</td>\n",
       "      <td>3.589552</td>\n",
       "      <td>3.630719</td>\n",
       "      <td>3.602697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>340.186204</td>\n",
       "      <td>8154.379187</td>\n",
       "      <td>3.444777</td>\n",
       "      <td>1.238031e+09</td>\n",
       "      <td>3.652257</td>\n",
       "      <td>3.434502</td>\n",
       "      <td>3.274419</td>\n",
       "      <td>3.378599</td>\n",
       "      <td>3.437204</td>\n",
       "      <td>3.507194</td>\n",
       "      <td>3.579235</td>\n",
       "      <td>3.385331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>347.970249</td>\n",
       "      <td>909.740849</td>\n",
       "      <td>3.426600</td>\n",
       "      <td>1.020020e+09</td>\n",
       "      <td>3.635562</td>\n",
       "      <td>3.353952</td>\n",
       "      <td>3.466407</td>\n",
       "      <td>3.385918</td>\n",
       "      <td>3.436452</td>\n",
       "      <td>3.618182</td>\n",
       "      <td>3.638889</td>\n",
       "      <td>3.767471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>357.747044</td>\n",
       "      <td>1970.257389</td>\n",
       "      <td>3.415764</td>\n",
       "      <td>1.085420e+09</td>\n",
       "      <td>3.624688</td>\n",
       "      <td>3.196109</td>\n",
       "      <td>3.291697</td>\n",
       "      <td>3.418568</td>\n",
       "      <td>3.552135</td>\n",
       "      <td>3.821678</td>\n",
       "      <td>3.590435</td>\n",
       "      <td>3.702297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>342.165228</td>\n",
       "      <td>4376.611591</td>\n",
       "      <td>3.356104</td>\n",
       "      <td>1.146331e+09</td>\n",
       "      <td>3.559960</td>\n",
       "      <td>3.257085</td>\n",
       "      <td>3.401544</td>\n",
       "      <td>3.211358</td>\n",
       "      <td>3.525045</td>\n",
       "      <td>3.288136</td>\n",
       "      <td>3.678715</td>\n",
       "      <td>3.433227</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          userId       movieId    rating     timestamp     Drama    Action  \\\n",
       "year                                                                         \n",
       "1957  360.933544   2750.965190  4.014241  1.083707e+09  4.056569  4.136364   \n",
       "1972  359.694878   3983.538976  4.011136  1.122759e+09  4.108000  3.239130   \n",
       "1952  346.394737   4107.796053  4.000000  1.090512e+09  3.902778  2.500000   \n",
       "1954  358.228324   2867.661850  3.994220  1.070591e+09  3.967456  4.263636   \n",
       "1951  347.106996   2605.588477  3.983539  1.052714e+09  3.949541  4.125000   \n",
       "...          ...           ...       ...           ...       ...       ...   \n",
       "2005  348.509719  37156.244600  3.448434  1.273459e+09  3.503771  3.394326   \n",
       "2003  340.186204   8154.379187  3.444777  1.238031e+09  3.652257  3.434502   \n",
       "1996  347.970249    909.740849  3.426600  1.020020e+09  3.635562  3.353952   \n",
       "1997  357.747044   1970.257389  3.415764  1.085420e+09  3.624688  3.196109   \n",
       "2000  342.165228   4376.611591  3.356104  1.146331e+09  3.559960  3.257085   \n",
       "\n",
       "      Thriller    Comedy   Romance       War   Mystery     Crime  \n",
       "year                                                              \n",
       "1957  3.842105  3.785714  3.671429  4.123656  3.687500       NaN  \n",
       "1972  3.736364  3.655738  3.470588  3.000000  3.684211  4.420561  \n",
       "1952       NaN  4.068750  3.978495  3.166667       NaN  4.333333  \n",
       "1954  4.197581  3.634146  3.576087  3.666667  4.233051  4.205357  \n",
       "1951  4.046512  4.341667  4.234940  4.398148  4.000000  4.196429  \n",
       "...        ...       ...       ...       ...       ...       ...  \n",
       "2005  3.433043  3.328800  3.467153  3.589552  3.630719  3.602697  \n",
       "2003  3.274419  3.378599  3.437204  3.507194  3.579235  3.385331  \n",
       "1996  3.466407  3.385918  3.436452  3.618182  3.638889  3.767471  \n",
       "1997  3.291697  3.418568  3.552135  3.821678  3.590435  3.702297  \n",
       "2000  3.401544  3.211358  3.525045  3.288136  3.678715  3.433227  \n",
       "\n",
       "[62 rows x 12 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined.groupby('year').mean().sort_values('rating', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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