{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/nnets/lib/python3.7/site-packages/smart_open/ssh.py:34: UserWarning: paramiko missing, opening SSH/SCP/SFTP paths will be disabled.  `pip install paramiko` to suppress\n",
      "  warnings.warn('paramiko missing, opening SSH/SCP/SFTP paths will be disabled.  `pip install paramiko` to suppress')\n",
      "WARNING:root:tensorflow or tensorflow-hub not found, loading tfhub models won't work\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import scipy\n",
    "\n",
    "import sklearn\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import scikitplot\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import mlutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File ‘../data/steam_reviews.csv’ already there; not retrieving.\r\n"
     ]
    }
   ],
   "source": [
    "!wget -nc https://query.data.world/s/plpwlqfrn2xqis5wvpnd6uucus76dq -O ../data/steam_reviews.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metacritic game reviews\n",
    "\n",
    "Data from [kaggle dataset](https://www.kaggle.com/dahlia25/metacritic-video-game-comments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_PATH = os.path.abspath('../data')\n",
    "metacritic_game_info_path = os.path.join(DATA_PATH, 'metacritic_game_info.csv')\n",
    "metacritic_game_comments_path = os.path.join(DATA_PATH, 'metacritic_game_user_comments.csv')\n",
    "steam_review_path = os.path.join(DATA_PATH, 'steam_reviews.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(os.path.abspath(metacritic_game_info_path)):\n",
    "    !unzip ../data/metacritic-video-game-comments.zip -d ../data\n",
    "    !chmod +rwx ../data/*csv "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_game_dfs(game_info_df, game_comments_df):\n",
    "    game_info_df = game_info_df[game_info_df['Metascore'] != 'not specified']\n",
    "    game_info_df = game_info_df[game_info_df['Avg_Userscore'] != 'not specified']\n",
    "    game_info_df = game_info_df[game_info_df['Avg_Userscore'] != 'tbd']\n",
    "    \n",
    "    for col in ['Metascore', 'Avg_Userscore', 'Year']:\n",
    "        game_info_df[col] = game_info_df[col].astype('float')\n",
    "    pc_game_info_df = game_info_df[game_info_df['Platform'] == 'PC']\n",
    "    pc_game_comments_df = game_comments_df[game_comments_df['Title'].isin(pc_game_info_df['Title'])]\n",
    "    return pc_game_info_df, pc_game_comments_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "game_info_df = pd.read_csv(metacritic_game_info_path, index_col='Unnamed: 0')\n",
    "game_comments_df = pd.read_csv(metacritic_game_comments_path, index_col='Unnamed: 0')\n",
    "\n",
    "pc_game_info_df, pc_game_comments_df = clean_game_dfs(game_info_df, game_comments_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Year</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Platform</th>\n",
       "      <th>Metascore</th>\n",
       "      <th>Avg_Userscore</th>\n",
       "      <th>No_Players</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Half-Life 2</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>ValveSoftware</td>\n",
       "      <td>Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...</td>\n",
       "      <td>PC</td>\n",
       "      <td>96.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>No Online Multiplayer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Grand Theft Auto V</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>RockstarNorth</td>\n",
       "      <td>Modern;Action Adventure;Open-World</td>\n",
       "      <td>PC</td>\n",
       "      <td>96.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Up to 32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>The Orange Box</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>ValveSoftware</td>\n",
       "      <td>Action;Miscellaneous;Shooter;Compilation;First...</td>\n",
       "      <td>PC</td>\n",
       "      <td>96.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>16  Online</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Half-Life</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>ValveSoftware</td>\n",
       "      <td>Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...</td>\n",
       "      <td>PC</td>\n",
       "      <td>96.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>1-32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>BioShock</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>IrrationalGames,2KMarin</td>\n",
       "      <td>Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...</td>\n",
       "      <td>PC</td>\n",
       "      <td>96.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>No Online Multiplayer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Title    Year                Publisher  \\\n",
       "20         Half-Life 2  2004.0            ValveSoftware   \n",
       "21  Grand Theft Auto V  2015.0            RockstarNorth   \n",
       "28      The Orange Box  2007.0            ValveSoftware   \n",
       "34           Half-Life  1998.0            ValveSoftware   \n",
       "38            BioShock  2007.0  IrrationalGames,2KMarin   \n",
       "\n",
       "                                                Genre Platform  Metascore  \\\n",
       "20  Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...       PC       96.0   \n",
       "21                 Modern;Action Adventure;Open-World       PC       96.0   \n",
       "28  Action;Miscellaneous;Shooter;Compilation;First...       PC       96.0   \n",
       "34  Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...       PC       96.0   \n",
       "38  Action;Shooter;Shooter;First-Person;Sci-Fi;Sci...       PC       96.0   \n",
       "\n",
       "    Avg_Userscore             No_Players  \n",
       "20            9.1  No Online Multiplayer  \n",
       "21            7.7              Up to 32   \n",
       "28            9.2             16  Online  \n",
       "34            9.1                  1-32   \n",
       "38            8.5  No Online Multiplayer  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pc_game_info_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f10e5579a58>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc_game_info_df['Genre'].str.split(\";\").apply(len).plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1368 entries, 20 to 4995\n",
      "Data columns (total 8 columns):\n",
      "Title            1368 non-null object\n",
      "Year             1368 non-null float64\n",
      "Publisher        1368 non-null object\n",
      "Genre            1368 non-null object\n",
      "Platform         1368 non-null object\n",
      "Metascore        1368 non-null float64\n",
      "Avg_Userscore    1368 non-null float64\n",
      "No_Players       1367 non-null object\n",
      "dtypes: float64(3), object(5)\n",
      "memory usage: 96.2+ KB\n"
     ]
    }
   ],
   "source": [
    "pc_game_info_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(187517, 5)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pc_game_comments_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation between user and metascore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.21381816860581535"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(pc_game_info_df['Avg_Userscore'], pc_game_info_df['Metascore'])[0,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Spearman rank correlation coefficient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpearmanrResult(correlation=0.2678004214955681, pvalue=6.729732567969086e-24)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scipy.stats.spearmanr(pc_game_info_df['Avg_Userscore'], pc_game_info_df['Metascore'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average user vs metascore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(pc_game_info_df[['Avg_Userscore', 'Metascore']]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Steam reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "steam_reviews_df = pd.read_csv(steam_review_path)\n",
    "genre_columns = [col for col in steam_reviews_df if 'Genre' in col]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 13357 entries, 0 to 13356\n",
      "Data columns (total 78 columns):\n",
      "QueryID                        13357 non-null int64\n",
      "ResponseID                     13357 non-null int64\n",
      "QueryName                      13356 non-null object\n",
      "ResponseName                   13357 non-null object\n",
      "ReleaseDate                    13357 non-null object\n",
      "RequiredAge                    13357 non-null int64\n",
      "DemoCount                      13357 non-null int64\n",
      "DeveloperCount                 13357 non-null int64\n",
      "DLCCount                       13357 non-null int64\n",
      "Metacritic                     13357 non-null int64\n",
      "MovieCount                     13357 non-null int64\n",
      "PackageCount                   13357 non-null int64\n",
      "RecommendationCount            13357 non-null int64\n",
      "PublisherCount                 13357 non-null int64\n",
      "ScreenshotCount                13357 non-null int64\n",
      "SteamSpyOwners                 13357 non-null int64\n",
      "SteamSpyOwnersVariance         13357 non-null int64\n",
      "SteamSpyPlayersEstimate        13357 non-null int64\n",
      "SteamSpyPlayersVariance        13357 non-null int64\n",
      "AchievementCount               13357 non-null int64\n",
      "AchievementHighlightedCount    13357 non-null int64\n",
      "ControllerSupport              13357 non-null bool\n",
      "IsFree                         13357 non-null bool\n",
      "FreeVerAvail                   13357 non-null bool\n",
      "PurchaseAvail                  13357 non-null bool\n",
      "SubscriptionAvail              13357 non-null bool\n",
      "PlatformWindows                13357 non-null bool\n",
      "PlatformLinux                  13357 non-null bool\n",
      "PlatformMac                    13357 non-null bool\n",
      "PCReqsHaveMin                  13357 non-null bool\n",
      "PCReqsHaveRec                  13357 non-null bool\n",
      "LinuxReqsHaveMin               13357 non-null bool\n",
      "LinuxReqsHaveRec               13357 non-null bool\n",
      "MacReqsHaveMin                 13357 non-null bool\n",
      "MacReqsHaveRec                 13357 non-null bool\n",
      "CategorySinglePlayer           13357 non-null bool\n",
      "CategoryMultiplayer            13357 non-null bool\n",
      "CategoryCoop                   13357 non-null bool\n",
      "CategoryMMO                    13357 non-null bool\n",
      "CategoryInAppPurchase          13357 non-null bool\n",
      "CategoryIncludeSrcSDK          13357 non-null bool\n",
      "CategoryIncludeLevelEditor     13357 non-null bool\n",
      "CategoryVRSupport              13357 non-null bool\n",
      "GenreIsNonGame                 13357 non-null bool\n",
      "GenreIsIndie                   13357 non-null bool\n",
      "GenreIsAction                  13357 non-null bool\n",
      "GenreIsAdventure               13357 non-null bool\n",
      "GenreIsCasual                  13357 non-null bool\n",
      "GenreIsStrategy                13357 non-null bool\n",
      "GenreIsRPG                     13357 non-null bool\n",
      "GenreIsSimulation              13357 non-null bool\n",
      "GenreIsEarlyAccess             13357 non-null bool\n",
      "GenreIsFreeToPlay              13357 non-null bool\n",
      "GenreIsSports                  13357 non-null bool\n",
      "GenreIsRacing                  13357 non-null bool\n",
      "GenreIsMassivelyMultiplayer    13357 non-null bool\n",
      "PriceCurrency                  13357 non-null object\n",
      "PriceInitial                   13357 non-null float64\n",
      "PriceFinal                     13357 non-null float64\n",
      "SupportEmail                   13355 non-null object\n",
      "SupportURL                     13356 non-null object\n",
      "AboutText                      13357 non-null object\n",
      "Background                     13357 non-null object\n",
      "ShortDescrip                   13357 non-null object\n",
      "DetailedDescrip                13357 non-null object\n",
      "DRMNotice                      13357 non-null object\n",
      "ExtUserAcctNotice              13357 non-null object\n",
      "HeaderImage                    13357 non-null object\n",
      "LegalNotice                    13356 non-null object\n",
      "Reviews                        13357 non-null object\n",
      "SupportedLanguages             13357 non-null object\n",
      "Website                        13357 non-null object\n",
      "PCMinReqsText                  13357 non-null object\n",
      "PCRecReqsText                  13357 non-null object\n",
      "LinuxMinReqsText               13357 non-null object\n",
      "LinuxRecReqsText               13357 non-null object\n",
      "MacMinReqsText                 13357 non-null object\n",
      "MacRecReqsText                 13357 non-null object\n",
      "dtypes: bool(35), float64(2), int64(18), object(23)\n",
      "memory usage: 4.8+ MB\n"
     ]
    }
   ],
   "source": [
    "steam_reviews_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>QueryID</th>\n",
       "      <th>ResponseID</th>\n",
       "      <th>RequiredAge</th>\n",
       "      <th>DemoCount</th>\n",
       "      <th>DeveloperCount</th>\n",
       "      <th>DLCCount</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>MovieCount</th>\n",
       "      <th>PackageCount</th>\n",
       "      <th>RecommendationCount</th>\n",
       "      <th>PublisherCount</th>\n",
       "      <th>ScreenshotCount</th>\n",
       "      <th>SteamSpyOwners</th>\n",
       "      <th>SteamSpyOwnersVariance</th>\n",
       "      <th>SteamSpyPlayersEstimate</th>\n",
       "      <th>SteamSpyPlayersVariance</th>\n",
       "      <th>AchievementCount</th>\n",
       "      <th>AchievementHighlightedCount</th>\n",
       "      <th>PriceInitial</th>\n",
       "      <th>PriceFinal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>1.335700e+04</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>1.335700e+04</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>1.335700e+04</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "      <td>13357.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>353637.916149</td>\n",
       "      <td>353471.814030</td>\n",
       "      <td>0.837688</td>\n",
       "      <td>0.089541</td>\n",
       "      <td>1.032492</td>\n",
       "      <td>0.805944</td>\n",
       "      <td>12.285319</td>\n",
       "      <td>1.321255</td>\n",
       "      <td>1.088418</td>\n",
       "      <td>1.180463e+03</td>\n",
       "      <td>0.989668</td>\n",
       "      <td>9.561204</td>\n",
       "      <td>1.668493e+05</td>\n",
       "      <td>5486.408550</td>\n",
       "      <td>1.081638e+05</td>\n",
       "      <td>4082.329490</td>\n",
       "      <td>14.434678</td>\n",
       "      <td>4.170098</td>\n",
       "      <td>9.155717</td>\n",
       "      <td>8.798596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>146988.380337</td>\n",
       "      <td>147085.351999</td>\n",
       "      <td>3.625701</td>\n",
       "      <td>0.286058</td>\n",
       "      <td>0.437113</td>\n",
       "      <td>10.034901</td>\n",
       "      <td>27.510876</td>\n",
       "      <td>1.178400</td>\n",
       "      <td>0.855219</td>\n",
       "      <td>1.517606e+04</td>\n",
       "      <td>0.336972</td>\n",
       "      <td>6.442893</td>\n",
       "      <td>1.127122e+06</td>\n",
       "      <td>9044.093874</td>\n",
       "      <td>1.006635e+06</td>\n",
       "      <td>7454.869744</td>\n",
       "      <td>41.467021</td>\n",
       "      <td>4.831106</td>\n",
       "      <td>14.345029</td>\n",
       "      <td>13.606061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>282860.000000</td>\n",
       "      <td>282640.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.970000e+02</td>\n",
       "      <td>906.000000</td>\n",
       "      <td>5.370000e+02</td>\n",
       "      <td>745.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.990000</td>\n",
       "      <td>1.990000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>374040.000000</td>\n",
       "      <td>373870.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>9.506000e+03</td>\n",
       "      <td>2551.000000</td>\n",
       "      <td>4.125000e+03</td>\n",
       "      <td>1717.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.990000</td>\n",
       "      <td>5.990000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>465920.000000</td>\n",
       "      <td>465860.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.430000e+02</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>6.044100e+04</td>\n",
       "      <td>6434.000000</td>\n",
       "      <td>2.815800e+04</td>\n",
       "      <td>4392.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>9.990000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>568150.000000</td>\n",
       "      <td>568150.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>630.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.427633e+06</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>9.068758e+07</td>\n",
       "      <td>215972.000000</td>\n",
       "      <td>9.068758e+07</td>\n",
       "      <td>215972.000000</td>\n",
       "      <td>1629.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>449.990000</td>\n",
       "      <td>449.990000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             QueryID     ResponseID   RequiredAge     DemoCount  \\\n",
       "count   13357.000000   13357.000000  13357.000000  13357.000000   \n",
       "mean   353637.916149  353471.814030      0.837688      0.089541   \n",
       "std    146988.380337  147085.351999      3.625701      0.286058   \n",
       "min        10.000000      10.000000      0.000000      0.000000   \n",
       "25%    282860.000000  282640.000000      0.000000      0.000000   \n",
       "50%    374040.000000  373870.000000      0.000000      0.000000   \n",
       "75%    465920.000000  465860.000000      0.000000      0.000000   \n",
       "max    568150.000000  568150.000000     18.000000      2.000000   \n",
       "\n",
       "       DeveloperCount      DLCCount    Metacritic    MovieCount  PackageCount  \\\n",
       "count    13357.000000  13357.000000  13357.000000  13357.000000  13357.000000   \n",
       "mean         1.032492      0.805944     12.285319      1.321255      1.088418   \n",
       "std          0.437113     10.034901     27.510876      1.178400      0.855219   \n",
       "min          0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%          1.000000      0.000000      0.000000      1.000000      1.000000   \n",
       "50%          1.000000      0.000000      0.000000      1.000000      1.000000   \n",
       "75%          1.000000      0.000000      0.000000      2.000000      1.000000   \n",
       "max         12.000000    630.000000     96.000000     20.000000     18.000000   \n",
       "\n",
       "       RecommendationCount  PublisherCount  ScreenshotCount  SteamSpyOwners  \\\n",
       "count         1.335700e+04    13357.000000     13357.000000    1.335700e+04   \n",
       "mean          1.180463e+03        0.989668         9.561204    1.668493e+05   \n",
       "std           1.517606e+04        0.336972         6.442893    1.127122e+06   \n",
       "min           0.000000e+00        0.000000         0.000000    0.000000e+00   \n",
       "25%           0.000000e+00        1.000000         6.000000    8.970000e+02   \n",
       "50%           0.000000e+00        1.000000         8.000000    9.506000e+03   \n",
       "75%           2.430000e+02        1.000000        12.000000    6.044100e+04   \n",
       "max           1.427633e+06        4.000000       114.000000    9.068758e+07   \n",
       "\n",
       "       SteamSpyOwnersVariance  SteamSpyPlayersEstimate  \\\n",
       "count            13357.000000             1.335700e+04   \n",
       "mean              5486.408550             1.081638e+05   \n",
       "std               9044.093874             1.006635e+06   \n",
       "min                  0.000000             0.000000e+00   \n",
       "25%                906.000000             5.370000e+02   \n",
       "50%               2551.000000             4.125000e+03   \n",
       "75%               6434.000000             2.815800e+04   \n",
       "max             215972.000000             9.068758e+07   \n",
       "\n",
       "       SteamSpyPlayersVariance  AchievementCount  AchievementHighlightedCount  \\\n",
       "count             13357.000000      13357.000000                 13357.000000   \n",
       "mean               4082.329490         14.434678                     4.170098   \n",
       "std                7454.869744         41.467021                     4.831106   \n",
       "min                   0.000000          0.000000                     0.000000   \n",
       "25%                 745.000000          0.000000                     0.000000   \n",
       "50%                1717.000000          0.000000                     0.000000   \n",
       "75%                4392.000000         20.000000                    10.000000   \n",
       "max              215972.000000       1629.000000                    10.000000   \n",
       "\n",
       "       PriceInitial    PriceFinal  \n",
       "count  13357.000000  13357.000000  \n",
       "mean       9.155717      8.798596  \n",
       "std       14.345029     13.606061  \n",
       "min        0.000000      0.000000  \n",
       "25%        1.990000      1.990000  \n",
       "50%        5.990000      5.990000  \n",
       "75%        9.990000      9.990000  \n",
       "max      449.990000    449.990000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "steam_reviews_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Return to the Black Mesa Research Facility as one of the military specialists assigned to eliminate Gordon Freeman. Experience an entirely new episode of single player action. Meet fierce alien opponents and experiment with new weaponry. Named Game of the Year by the Academy of Interactive Arts and Sciences.'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "steam_reviews_df['AboutText'][4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1226"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(steam_reviews_df['DetailedDescrip'] != steam_reviews_df['AboutText'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GenreIsNonGame</th>\n",
       "      <th>GenreIsIndie</th>\n",
       "      <th>GenreIsAction</th>\n",
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       "      <th>count</th>\n",
       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
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       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
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       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
       "      <td>13357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>13038</td>\n",
       "      <td>7780</td>\n",
       "      <td>7724</td>\n",
       "      <td>9038</td>\n",
       "      <td>9793</td>\n",
       "      <td>10734</td>\n",
       "      <td>11270</td>\n",
       "      <td>11255</td>\n",
       "      <td>11887</td>\n",
       "      <td>12692</td>\n",
       "      <td>12816</td>\n",
       "      <td>12881</td>\n",
       "      <td>12968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       GenreIsNonGame GenreIsIndie GenreIsAction GenreIsAdventure  \\\n",
       "count           13357        13357         13357            13357   \n",
       "unique              2            2             2                2   \n",
       "top             False         True         False            False   \n",
       "freq            13038         7780          7724             9038   \n",
       "\n",
       "       GenreIsCasual GenreIsStrategy GenreIsRPG GenreIsSimulation  \\\n",
       "count          13357           13357      13357             13357   \n",
       "unique             2               2          2                 2   \n",
       "top            False           False      False             False   \n",
       "freq            9793           10734      11270             11255   \n",
       "\n",
       "       GenreIsEarlyAccess GenreIsFreeToPlay GenreIsSports GenreIsRacing  \\\n",
       "count               13357             13357         13357         13357   \n",
       "unique                  2                 2             2             2   \n",
       "top                 False             False         False         False   \n",
       "freq                11887             12692         12816         12881   \n",
       "\n",
       "       GenreIsMassivelyMultiplayer  \n",
       "count                        13357  \n",
       "unique                           2  \n",
       "top                          False  \n",
       "freq                         12968  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "steam_reviews_df[genre_columns].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[==================================================] 100.0% 128.1/128.1MB downloaded\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:smart_open.smart_open_lib:this function is deprecated, use smart_open.open instead\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 46.7 s, sys: 4.22 s, total: 50.9 s\n",
      "Wall time: 1min 31s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "word_embedding_vectorizer = mlutil.embeddings.WordEmbeddingsVectorizer.from_gensim_embedding_model('glove-wiki-gigaword-100')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5.6 s, sys: 0 ns, total: 5.6 s\n",
      "Wall time: 5.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "steam_description_vectors = word_embedding_vectorizer.transform(steam_reviews_df['DetailedDescrip'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13357, 100)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "steam_description_vectors.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Genre classification using description\n",
    "\n",
    "Note this is multilabel classification, as games on steam can have several genres\n",
    "\n",
    "We'll use Random Forest algorithm as it supports mutlilabel classification out of the box"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = steam_description_vectors\n",
    "Y = steam_reviews_df[genre_columns]\n",
    "\n",
    "X_train, X_test, Y_train, Y_test = sklearn.model_selection.train_test_split(X, Y, test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_clf = RandomForestClassifier(n_estimators=50, n_jobs=-1)\n",
    "rf_clf.fit(X_train, Y_train)\n",
    "\n",
    "Y_test_pred = rf_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2672, 13)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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S9gNOJGtFL0nbTl7Z8WtW+XT0HLlvO5yZtZd5Uy4oOgRrod7d9UhEbJlnH73W2CDWGXd+s/We+9XuzR5L0uXAXsBb9a9TpobXRGAY8DKwb0TMU5a9zwX2BBYB346IaWmbccApabdnRMSEpo7bbpf2DZNoKns+IjaNiM0i4oT6OhHxcv1JR8RZETEqXcLvHhHvpvKJqWzTiBjTVBI1swpSxmV9CxqsVwANX1kZD9wdESOAu9MywB7AiDQdAfwOlifenwJbA2OBn0rqTxPcs8nMCiWgpkbNTuWIiH8C7zYo3huob1FOAPYpKb8yMpOBfpLWBHYD7oyIdyNiHnAnn0zOK3BfezMrXJktzoGSppYsX5Le1GnO4Iiof/L3BlD/OsUQYFZJvdmpbGXlK+VEamaFK/Nh09y892MjIiS1+YMhX9qbWbHa9h5pY95Ml+ykn/XvoM8B1iqpNzSVrax8pZxIzaxQQtTU1DQ75XAzMC7NjwNuKik/WJltgPnpFsAdwK6S+qeHTLumspXypb2ZFa6tXiOVdDWwA9n91NlkT9/PAq6VdBjwClD/XuQkslefZpK9/nQIQHrd8nRgSqr3s/q3h1bGidTMCtdWL+RHxAErWbVzI3UDOGol+7kcuLzc4zqRmlmxKqALaHOcSM2sUFlf+8rOpE6kZla4Cs+jTqRmVrxyey51Vk6kZlasLjAeqROpmRWqfjzSSuZEamYFq/zxSJ1IzaxwFZ5HnUjNrGDywyYzs1z8HqmZWRtwIjUzy6nC86gTqZkVzy1SM7M8PGiJmVk+2cDOlZ1JnUjNrHA1Fd4kdSI1s8JVeB51IjWzYqkrD1oiabWmNoyIf7d9OGZWjSr8FmmTLdIZQJB1PKhXvxzA2u0Yl5lVkS77sCki1lrZOjOztiKyJ/eVrKyPRUvaX9JJaX6opDHtG5aZVZMaNT91Zs0mUkkXADsCB6WiRcBF7RmUmVURZeORNjd1ZuU8td82IraQ9ChARLwrqUc7x2VmVaST58lmlZNIl0iqIXvAhKQBwLJ2jcrMqoaojhfyfwtcDwySdBqwL3Bau0ZlZlWlyz61rxcRV0p6BNglFX0jIp5s37DMrFqoigYtqQWWkF3el/Wk38ysXJV+aV/OU/uTgauBzwBDgT9LOrG9AzOz6qEyps6snBbpwcDmEbEIQNKZwKPAL9ozMDOrHp399abmlJNIX29Qr1sqMzPLLXtqX3QU+TQ1aMk5ZPdE3wVmSLojLe8KTOmY8Mysy1PXHti5/sn8DOBvJeWT2y8cM6tGbXVpL+kY4L/IGn1PAIcAawLXAAOAR4CDIuIjST2BK4ExwDvAfhHxcmuO29SgJZe1ZodmZi3RVpf2koYAPwQ2jojFkq4F9gf2BM6JiGskXQQcBvwu/ZwXEcMl7Q/8EtivNccu56n9+pKukfS4pOfqp9YczMysMW3Y174b0FtSN2AVsuc5OwHXpfUTgH3S/N5pmbR+Z7WyaVzOO6FXAH8g+4djD+BaYGJrDmZm1pgyX38aKGlqyXRE6T4iYg7wP8CrZAl0Ptml/HsRsTRVmw0MSfNDgFlp26Wp/oDWxF9OIl0lIu5IB3shIk4hS6hmZrlJUFujZidgbkRsWTJdsuJ+1J+slbku2XvvqwK7d8Q5lPP604dp0JIXJB0JzAH6tm9YZlZN2uhh0y7ASxHxdtrnDcB2QD9J3VKrcyhZDiP9XAuYnW4FrE720KnFymmRHkOW2X+YgjocOLQ1BzMza0x9f/umpjK8CmwjaZV0r3Nn4CngHuDrqc444KY0f3NaJq3/R0REa+IvZ9CSh9LsAj4e3NnMrE0ItUlf+4h4SNJ1wDRgKVkPzEvIXt+8RtIZqaz+jaTLgD9Kmkn2vvz+rT12Uy/k30gag3QlQX+1tQc1M1uuDUd/ioifAj9tUPwiMLaRuh8A32iL4zbVIr2gLQ5QlI1GDOXaW88qOgxrgfP/9ULRIVhBumxf+4i4uyMDMbPqJKC2qyZSM7OOUuFd7Z1Izax4VZNIJfWMiA/bMxgzqz7Z602VnUnL6Ws/VtITwPNpeTNJ57d7ZGZWNWrU/NSZlfNC/nnAXqQ3/iPiMWDH9gzKzKpLG72QX5hyLu1rIuKVBk3vunaKx8yqjIBunT1TNqOcRDpL0lggJNUCPwA8jJ6ZtZkKz6NlJdLvkl3erw28CdyVyszMcpPapotokcrpa/8WOfqgmpk1p8LzaPOJVNLvaaTPfUQc0Uh1M7MW6+xP5ZtTzqX9XSXzvYCvkEaVNjPLS1A/cHPFKufSfoXPikj6I/CvdovIzKpLBbwn2pzWdBFdFxjc1oGYWfUSlZ1Jy7lHOo+P75HWkA2AOr49gzKz6tFWn2MuUpOJNA3Xvxkff+NkWWuH4jczW5lKT6RNdhFNSXNSRNSlyUnUzNpcG37XvhDl9LWfLmnzdo/EzKpS9jnm5qfOrKlvNtV/vnRzYIqkF4CFZLc0IiK26KAYzayL68o9mx4GtgC+3EGxmFkV6uoPmwQQEf4imZm1qwpvkDaZSAdJOnZlKyPif9shHjOrOqKmC79HWgv0gQo/QzPr1ETXbpG+HhE/67BIzKw6CbpV+E3SZu+Rmpm1p67eIt25w6Iws6rWZV9/ioh3OzIQM6teFZ5HWzX6k5lZmxHldbHszJxIzaxY6sKX9mZmHSHr2eREamaWS2WnUSdSM+sEKrxBWvH3eM2s4jU/Fmm545FK6ifpOknPSHpa0mclfUrSnZKeTz/7p7qSdJ6kmZIel9TqEe2cSM2sUPVP7ZubynQucHtEbEj2dY+nyT6NdHdEjADu5uNPJe0BjEjTEcDvWnsOTqRmVrgaqdmpOZJWB7YHLgOIiI8i4j1gb2BCqjYB2CfN7w1cGZnJQD9Ja7Yq/tZsZGbWZlT2p0YGSppaMh3RYE/rAm8Df5D0qKRLJa0KDI6I11OdN/j4K8hDgFkl289OZS3mh01mVqgWvJA/NyK2bGJ9N7LB6H8QEQ9JOpcGXzyOiJDU5t+ec4vUzArXRg+bZgOzI+KhtHwdWWJ9s/6SPf18K62fA6xVsv1QPv5icos4kZpZ4VTG1JyIeAOYJWlkKtoZeAq4GRiXysYBN6X5m4GD09P7bYD5JbcAWsSX9mZWKAG1bfci6Q+AqyT1AF4EDiFrMF4r6TDgFWDfVHcSsCcwE1iU6raKE6mZFa6t8mhETAcau4/6iWFBIyKAo9riuE6kZlYwoQrvJOpEamaFq/Quok6kZlao7PWnys6kTqRmViy5RWpmlpvHIzUzyyEb2LnoKPJxIjWzwvmpvZlZThV+Ze9E2lnV1dWx357b8+k11uTCCdfxkx9/jxmPP0pEMGy94Zx5zkWssmofJlxyPtdfPYHa2m58asBATv/1hXxm6NpFh191enarYbeRgxi4ag8IuP3Zt1hSF+y6wSC614r5Hyzlb0+/yUd1H4+X0bdnNw4duxYPvPwuU2bNLzD64lV6i7RD+tpLGiBpeprekDSnZLlHR8RQaf502YWsN3zk8uUTTj2LG+58kBvvmsyaQ4by5z9cDMBGozZj4qR/cuNdk/nil/bh12f+pKiQq9pOwwfy0ruLuPzhWVwxdRbvLFrCbiMH8X8vvsMVU2fz/NyFbLVWvxW22XH4AF56Z1FBEXce9fdIm5s6sw5JpBHxTkSMjojRwEXAOfXLEfERLB/234OoAG+8Nod/3n0HX/vmuOVlffquBkBE8MEHHywfDWfsdtvTu/cqAGy2xVa8+XqrBq+xHHrU1jB09V488foCAJYFfLh0GZ9apTuz538AwCvzFrHBoD7Ltxk+cBXmL17K3EUfFRJzp1LGoM6d/al+oYlL0nBJT0m6CpgBrCXpvZL1+0u6NM0PlnRDGtD14TRaS5f0y1NP4NiTT6fhvyunHHskX9h8fV6a+RzfPPTIT2x3w9VX8vkdd+2oMC3p17sbi5fUsceGgzh4zFB2GzmI7jVi7sIlDB+Y/SM3clAfVuuZ3UnrXiu2Xqs/D7zybpFhdyptMfpTkTpDC3BDshbqxjQ9FuB5wK/SwK77Apc2rCDpiPrRs+e9M7d9om1n9951G58aOIhRm27+iXVn/O9F3PPI86w3YiS333z9Cutuuf4aZjw+jUOOPLqjQrVEEoP79mT6nH9z5SOzWVK3jLFr9+P2Z99i88+szkFjhtKjtoa6yO6PbjfsU0yd/R5L6tp8fOGKVP9d+0pukXaGh00vRMTUMurtAowsGeC1v6TeEbG4viAiLgEuARi12RYV+bf00SmTuffvk7jvH3/nww8/YOGCBZzwg//il+dn/27U1tayx5e/xuW/+w1f2e8gAB687x4uOf9srrjudnr07Flk+FXp/Q+XsuDDpby+4EMAnn17IVuv3Y/7X57HXx7Phrfs37s76w3IWqdr9u3JBoNW5QvrD6BntxoiYOmy4NE5/y7sHIrWudNk8zpDIl1YMr+MFX+nvUrmBYytv6faVR1z4mkcc+JpADz8wH1ccfG5nHXe73n1pRdYe931iQjuuXMS6w7fAICnn3yM08YfzcV/vIEBAwcVGXrVWvhRHQs+WEr/3t2Zt3gJ6/TvzTsLl7BK91oWLakD4LPr9Gf6a1mivHr6a8u33XZYf5bULavqJApUfCbtDIl0uYhYJmmepBHAC8BXyD5mBXAX2diB5wBIGp3GHuzyIoKTjvkOCxcsIAhGbvQf/OQX5wDw6zNOYdHC9zn2yIMBWHPIUC74w7VFhluV7p45l702/jS1Eu99sJTbnnmLUYP7svmQ7CHh83MX8uQbCwqOsvPq7JfuzelUiTQ5AbiD7LsqjwD116pHAb+TdAhZ3PfQRoOydlZjt/08Y7f9PAB/+utdjda59JpbOjIkW4m33v+IPz6y4i3+aXPmM21O0++HPvDyvPYMq2JUdhotIJFGxKkl8zOB0Q3WTwQmNrLd28DX2zs+MytAhWfSztgiNbMqkr3eVNmZ1InUzIrl8UjNzPKr8DzqRGpmRROq8CapE6mZFa7C86gTqZkVqxL60jfHidTMilfhmdSJ1MwK59efzMxy8j1SM7M8/B6pmVl+vrQ3M8tBuEVqZpZbhedRJ1Iz6wQqPJM6kZpZ4Sp9YOfO8PE7M6tybfkVUUm1kh6VdGtaXlfSQ5JmSpooqUcq75mWZ6b1w1obvxOpmRWvbb/HfDTwdMnyL8m+VDwcmAcclsoPA+al8nNSvVZxIjWzQtUP7Nzcf2XtSxoKfIn0uXZlw0rtBFyXqkwA9knze6dl0vqd1cphqJxIzaxY6YX85iZgoKSpJdMRjeztN8DxZF8kBhgAvBcRS9PybGBImh8CzAJI6+en+i3mh01mVrgym4FzI2LLle5D2gt4KyIekbRD20RWHidSMytYmw3svB3wZUl7Ar2A1YBzgX6SuqVW51Cg/nOvc4C1gNmSugGrA++05sC+tDezwpV5ad+kiDgxIoZGxDBgf+AfEXEg2afb679APA64Kc3fnJZJ6/8REdGa+J1IzaxQ5Tywz9lePQE4VtJMsnugl6Xyy4ABqfxYYHxrD+BLezMrXhu/jx8R9wL3pvkXgbGN1PkA+EZbHM+J1MwK59GfzMxyqvAeok6kZlYwQY0TqZlZXpWdSZ1IzaxQHtjZzKwNVHgedSI1s+K5RWpmllMbdREtjBOpmRWustOoE6mZFazcvvSdmROpmRXOPZvMzPKq7DzqRGpmxavwPOpEamZFU8V/jtmJ1MwK1RV6NnlgZzOznNwiNbPCVXqL1InUzArn15/MzPLwC/lmZvl0hYdNTqRmVjhf2puZ5eQWqZlZThWeR51IzawTqPBM6kRqZoUSVHwXUUVE0TG0C0lvA68UHUc7GQjMLToIK1tX/vNaJyIG5dmBpNvJfkfNmRsRu+c5Vnvpsom0K5M0NSK2LDoOK4//vLo+97U3M8vJidTMLCcn0sp0SdEBWIv4z6uL8z1SM7Oc3CI1M8vJidTMLCe/kN8JSKoDnigp2iciXl5J3WHArRGxSftHZisjaQBwd1pcA6gD3k7LYyPio0ICs0I4kXYOiyNidNFBWPki4h1gNICkU4H3I+J/SutIEtlziGUdH6F1JF/ad1KShkm6T9K0NG3bSJ1Rkh6WNF3S45JGpPJvlZRfLKm248+gOkkI+e+rAAAElklEQVQaLukpSVcBM4C1JL1Xsn5/SZem+cGSbpA0Nf15bVNU3JaPE2nn0DslvemSbkxlbwFfjIgtgP2A8xrZ7kjg3NSa3RKYLWmjVH+7VF4HHNj+p2AlNgTOiYiNgTlN1DsP+FXq9bQvcGlHBGdtz5f2nUNjl/bdgQsk1SfDDRrZ7kHgZElDgRsi4nlJOwNjgCnZlSW9yZKydZwXImJqGfV2AUbq4wE7+kvqHRGL2y80aw9OpJ3XMcCbwGZkVw4fNKwQEX+W9BDwJWCSpO+QDaYzISJO7MhgbQULS+aXseIgcb1K5oUfTHUJvrTvvFYHXk8PKg4CPnGfU9J6wIsRcR5wE7Ap2ZPkr0v6dKrzKUnrdFzYVir9+c2TNEJSDfCVktV3AUfVL6SrD6tATqSd14XAOEmPkd1zW9hInX2BJyVNBzYBroyIp4BTgL9Lehy4E1izg2K2xp0A3AE8AMwuKT8K2C49KHwKOLyI4Cw/dxE1M8vJLVIzs5ycSM3McnIiNTPLyYnUzCwnJ1Izs5ycSKuYpLrULfVJSX+RtEqOfe0g6dY0/2VJ45uo20/S91pxjFMl/Xe55Q3qXCHp6y041jBJT7Y0RqtOTqTVbXFEjE5D8n1E1nd/OWVa/HckIm6OiLOaqNIPaHEiNeusnEit3n3A8NQSe1bSlcCTZKMX7SrpwTQK1V8k9QGQtLukZyRNA75avyNJ35Z0QZofLOlGSY+laVvgLGD91Bo+O9U7TtKU9HL6aSX7OlnSc5L+BYxs7iQkHZ7285ik6xu0sndJIy09J2mvVL9W0tklx/5O3l+kVR8nUkNSN2APPh5cegRwYUSMIutRdQqwSxqJaipwrKRewO+B/yQbJGWNlez+POD/ImIzYAuyoeXGkw3sMToijpO0azrmWLIxPsdI2l7SGGD/VLYnsFUZp3NDRGyVjvc0cFjJumHpGF8CLkrncBgwPyK2Svs/XNK6ZRzHbDkPWlLdeqfupZC1SC8DPgO8EhGTU/k2wMbA/WmUoh5ko05tCLwUEc8DSPoTcEQjx9gJOBggIuqA+ZL6N6iza5oeTct9yBJrX+DGiFiUjnFzGee0iaQzyG4f9CHrmlnv2tT3/XlJL6Zz2BXYtOT+6erp2M+VcSwzwIm02n1i+L6ULEv79Qu4MyIOaFCvLQfYEPCLiLi4wTF+1Ip9XUH2qZbHJH0b2KFkXcP+0JGO/YOIKE249Z90MSuLL+2tOZPJBtYYDiBpVUkbAM8AwyStn+odsJLt7wa+m7atlbQ6sICstVnvDuDQknuvQ9LoVf8E9pHUW1JfstsIzekLvC6pO58c0PobkmpSzOsBz6ZjfzfVR9IGklYt4zhmy7lFak2KiLdTy+5qST1T8SkR8ZykI4C/SVpEdmugbyO7OBq4RNJhZANUfzciHpR0f3q96LZ0n3Qj4MHUIn4f+FZETJM0EXiMbHDqKWWE/BPgIbIP0T3UIKZXgYeB1YAjI+IDZZ/9GAZMU3bwt4F9yvvtmGU8+pOZWU6+tDczy8mJ1MwsJydSM7OcnEjNzHJyIjUzy8mJ1MwsJydSM7Oc/j9/Aqe4M5iBoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/nnets/lib/python3.7/site-packages/sklearn/metrics/classification.py:1439: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no true samples.\n",
      "  'recall', 'true', average, warn_for)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, col in enumerate(genre_columns):\n",
    "    pred = Y_test_pred[:, i]\n",
    "    y = Y_test.iloc[:, i]\n",
    "    f1_score = round(sklearn.metrics.f1_score(pred, y), 3)\n",
    "    scikitplot.metrics.plot_confusion_matrix(y, pred)\n",
    "    plt.title(col + '\\nf1: ' + str(f1_score))\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "nnets",
   "language": "python",
   "name": "nnets"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}