aggregate_genres.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "arctic-handling",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "animal-brazil",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"vgsales_clean_2.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "vocational-tours",
   "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>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Platform</th>\n",
       "      <th>Year</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>NA_Sales</th>\n",
       "      <th>EU_Sales</th>\n",
       "      <th>JP_Sales</th>\n",
       "      <th>Other_Sales</th>\n",
       "      <th>Global_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Wii Sports</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2006</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>41.49</td>\n",
       "      <td>29.02</td>\n",
       "      <td>3.77</td>\n",
       "      <td>8.46</td>\n",
       "      <td>82.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Super Mario Bros.</td>\n",
       "      <td>Nintendo Entertainment System</td>\n",
       "      <td>1985</td>\n",
       "      <td>Platform</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>29.08</td>\n",
       "      <td>3.58</td>\n",
       "      <td>6.81</td>\n",
       "      <td>0.77</td>\n",
       "      <td>40.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Mario Kart Wii</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2008</td>\n",
       "      <td>Racing</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>15.85</td>\n",
       "      <td>12.88</td>\n",
       "      <td>3.79</td>\n",
       "      <td>3.31</td>\n",
       "      <td>35.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Wii Sports Resort</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2009</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>15.75</td>\n",
       "      <td>11.01</td>\n",
       "      <td>3.28</td>\n",
       "      <td>2.96</td>\n",
       "      <td>33.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pokemon Red/Pokemon Blue</td>\n",
       "      <td>Game Boy</td>\n",
       "      <td>1996</td>\n",
       "      <td>Role-Playing</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>11.27</td>\n",
       "      <td>8.89</td>\n",
       "      <td>10.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>31.37</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16284</th>\n",
       "      <td>16596</td>\n",
       "      <td>Woody Woodpecker in Crazy Castle 5</td>\n",
       "      <td>Game Boy Advance</td>\n",
       "      <td>2002</td>\n",
       "      <td>Platform</td>\n",
       "      <td>Kemco</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16285</th>\n",
       "      <td>16597</td>\n",
       "      <td>Men in Black II: Alien Escape</td>\n",
       "      <td>GameCube</td>\n",
       "      <td>2003</td>\n",
       "      <td>Shooter</td>\n",
       "      <td>Infogrames</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16286</th>\n",
       "      <td>16598</td>\n",
       "      <td>SCORE International Baja 1000: The Official Game</td>\n",
       "      <td>PlayStation 2</td>\n",
       "      <td>2008</td>\n",
       "      <td>Racing</td>\n",
       "      <td>Activision</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16287</th>\n",
       "      <td>16599</td>\n",
       "      <td>Know How 2</td>\n",
       "      <td>Nintendo DS</td>\n",
       "      <td>2010</td>\n",
       "      <td>Puzzle</td>\n",
       "      <td>7G//AMES</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16288</th>\n",
       "      <td>16600</td>\n",
       "      <td>Spirits &amp; Spells</td>\n",
       "      <td>Game Boy Advance</td>\n",
       "      <td>2003</td>\n",
       "      <td>Platform</td>\n",
       "      <td>Wanadoo</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16289 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Rank                                              Name  \\\n",
       "0          1                                        Wii Sports   \n",
       "1          2                                 Super Mario Bros.   \n",
       "2          3                                    Mario Kart Wii   \n",
       "3          4                                 Wii Sports Resort   \n",
       "4          5                          Pokemon Red/Pokemon Blue   \n",
       "...      ...                                               ...   \n",
       "16284  16596                Woody Woodpecker in Crazy Castle 5   \n",
       "16285  16597                     Men in Black II: Alien Escape   \n",
       "16286  16598  SCORE International Baja 1000: The Official Game   \n",
       "16287  16599                                        Know How 2   \n",
       "16288  16600                                  Spirits & Spells   \n",
       "\n",
       "                            Platform  Year         Genre   Publisher  \\\n",
       "0                                Wii  2006        Sports    Nintendo   \n",
       "1      Nintendo Entertainment System  1985      Platform    Nintendo   \n",
       "2                                Wii  2008        Racing    Nintendo   \n",
       "3                                Wii  2009        Sports    Nintendo   \n",
       "4                           Game Boy  1996  Role-Playing    Nintendo   \n",
       "...                              ...   ...           ...         ...   \n",
       "16284               Game Boy Advance  2002      Platform       Kemco   \n",
       "16285                       GameCube  2003       Shooter  Infogrames   \n",
       "16286                  PlayStation 2  2008        Racing  Activision   \n",
       "16287                    Nintendo DS  2010        Puzzle    7G//AMES   \n",
       "16288               Game Boy Advance  2003      Platform     Wanadoo   \n",
       "\n",
       "       NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  \n",
       "0         41.49     29.02      3.77         8.46         82.74  \n",
       "1         29.08      3.58      6.81         0.77         40.24  \n",
       "2         15.85     12.88      3.79         3.31         35.82  \n",
       "3         15.75     11.01      3.28         2.96         33.00  \n",
       "4         11.27      8.89     10.22         1.00         31.37  \n",
       "...         ...       ...       ...          ...           ...  \n",
       "16284      0.01      0.00      0.00         0.00          0.01  \n",
       "16285      0.01      0.00      0.00         0.00          0.01  \n",
       "16286      0.00      0.00      0.00         0.00          0.01  \n",
       "16287      0.00      0.01      0.00         0.00          0.01  \n",
       "16288      0.01      0.00      0.00         0.00          0.01  \n",
       "\n",
       "[16289 rows x 11 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "associate-universe",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.groupby(level = [\"Genre\",\"Year\"]).agg({\"NA_Sales\": sum, \"EU_Sales\": sum, \"JP_Sales\": sum, \"Other_Sales\": sum, \"Global_Sales\": sum})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "familiar-pizza",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales', 'Global_Sales'], dtype='object')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "juvenile-green",
   "metadata": {},
   "outputs": [],
   "source": [
    "genres = set()\n",
    "for (genre, year), row in data.iterrows():\n",
    "    genres.add(genre)\n",
    "genres = list(genres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "useful-printer",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "sharp-theta",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_data = {}\n",
    "for (genre, year), row in data.iterrows():\n",
    "    if year in out_data:\n",
    "        out_data[year][genre] = row[\"Global_Sales\"]\n",
    "    else:\n",
    "        out_data[year] = {}\n",
    "        out_data[year][genre] = row[\"Global_Sales\"]\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "falling-wagon",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = []\n",
    "for year in out_data:\n",
    "    x = [year]\n",
    "    d = out_data[year]\n",
    "    for genre in genres:\n",
    "        if genre in d:\n",
    "            x.append(d[genre])\n",
    "        else:\n",
    "            x.append(0)\n",
    "    X.append(x)\n",
    "\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "union-louisiana",
   "metadata": {},
   "outputs": [],
   "source": [
    "out = pd.DataFrame(X, columns = [\"year\"] + list(genres))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "backed-breeding",
   "metadata": {},
   "outputs": [],
   "source": [
    "out.to_csv(\"aggregated_genre.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "meaningful-belief",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "portuguese-guest",
   "metadata": {},
   "outputs": [],
   "source": [
    "out = out[[\"year\"] + sorted(genres)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "prerequisite-string",
   "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>year</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Fighting</th>\n",
       "      <th>Misc</th>\n",
       "      <th>Platform</th>\n",
       "      <th>Puzzle</th>\n",
       "      <th>Racing</th>\n",
       "      <th>Role-Playing</th>\n",
       "      <th>Shooter</th>\n",
       "      <th>Simulation</th>\n",
       "      <th>Sports</th>\n",
       "      <th>Strategy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1980</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.77</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981</td>\n",
       "      <td>14.84</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.93</td>\n",
       "      <td>2.24</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.04</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1982</td>\n",
       "      <td>6.52</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.87</td>\n",
       "      <td>5.03</td>\n",
       "      <td>10.03</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.79</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1983</td>\n",
       "      <td>2.86</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.14</td>\n",
       "      <td>6.93</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1984</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.45</td>\n",
       "      <td>0.69</td>\n",
       "      <td>3.14</td>\n",
       "      <td>5.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.18</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1985</td>\n",
       "      <td>3.52</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>43.17</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.96</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1986</td>\n",
       "      <td>13.74</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9.39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.96</td>\n",
       "      <td>2.52</td>\n",
       "      <td>3.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5.57</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1987</td>\n",
       "      <td>1.12</td>\n",
       "      <td>4.38</td>\n",
       "      <td>5.42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.74</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.72</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1988</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>27.73</td>\n",
       "      <td>5.58</td>\n",
       "      <td>2.14</td>\n",
       "      <td>5.88</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.03</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1989</td>\n",
       "      <td>4.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.28</td>\n",
       "      <td>20.66</td>\n",
       "      <td>37.75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.20</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5.72</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1990</td>\n",
       "      <td>6.39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>22.97</td>\n",
       "      <td>6.00</td>\n",
       "      <td>6.26</td>\n",
       "      <td>4.52</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.14</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1991</td>\n",
       "      <td>6.76</td>\n",
       "      <td>2.24</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.08</td>\n",
       "      <td>7.64</td>\n",
       "      <td>3.24</td>\n",
       "      <td>1.14</td>\n",
       "      <td>3.25</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.14</td>\n",
       "      <td>2.41</td>\n",
       "      <td>0.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1992</td>\n",
       "      <td>3.83</td>\n",
       "      <td>12.24</td>\n",
       "      <td>15.25</td>\n",
       "      <td>4.94</td>\n",
       "      <td>13.42</td>\n",
       "      <td>4.84</td>\n",
       "      <td>9.04</td>\n",
       "      <td>6.86</td>\n",
       "      <td>0.29</td>\n",
       "      <td>2.14</td>\n",
       "      <td>2.95</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1993</td>\n",
       "      <td>1.81</td>\n",
       "      <td>0.07</td>\n",
       "      <td>8.75</td>\n",
       "      <td>0.30</td>\n",
       "      <td>18.67</td>\n",
       "      <td>3.17</td>\n",
       "      <td>0.36</td>\n",
       "      <td>5.59</td>\n",
       "      <td>3.08</td>\n",
       "      <td>0.19</td>\n",
       "      <td>3.18</td>\n",
       "      <td>0.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1994</td>\n",
       "      <td>1.55</td>\n",
       "      <td>3.74</td>\n",
       "      <td>8.47</td>\n",
       "      <td>2.86</td>\n",
       "      <td>28.74</td>\n",
       "      <td>1.53</td>\n",
       "      <td>2.19</td>\n",
       "      <td>7.11</td>\n",
       "      <td>8.30</td>\n",
       "      <td>2.73</td>\n",
       "      <td>8.39</td>\n",
       "      <td>3.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1995</td>\n",
       "      <td>3.57</td>\n",
       "      <td>0.72</td>\n",
       "      <td>14.85</td>\n",
       "      <td>6.40</td>\n",
       "      <td>16.69</td>\n",
       "      <td>2.71</td>\n",
       "      <td>6.09</td>\n",
       "      <td>14.26</td>\n",
       "      <td>4.15</td>\n",
       "      <td>4.18</td>\n",
       "      <td>7.98</td>\n",
       "      <td>6.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1996</td>\n",
       "      <td>20.58</td>\n",
       "      <td>4.19</td>\n",
       "      <td>18.06</td>\n",
       "      <td>10.68</td>\n",
       "      <td>28.23</td>\n",
       "      <td>3.91</td>\n",
       "      <td>28.24</td>\n",
       "      <td>43.96</td>\n",
       "      <td>6.91</td>\n",
       "      <td>11.33</td>\n",
       "      <td>17.45</td>\n",
       "      <td>5.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1997</td>\n",
       "      <td>27.58</td>\n",
       "      <td>4.96</td>\n",
       "      <td>11.76</td>\n",
       "      <td>5.69</td>\n",
       "      <td>21.85</td>\n",
       "      <td>5.89</td>\n",
       "      <td>31.91</td>\n",
       "      <td>21.79</td>\n",
       "      <td>22.17</td>\n",
       "      <td>9.65</td>\n",
       "      <td>30.02</td>\n",
       "      <td>7.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1998</td>\n",
       "      <td>39.44</td>\n",
       "      <td>9.05</td>\n",
       "      <td>31.66</td>\n",
       "      <td>11.94</td>\n",
       "      <td>29.88</td>\n",
       "      <td>6.34</td>\n",
       "      <td>27.90</td>\n",
       "      <td>28.09</td>\n",
       "      <td>9.80</td>\n",
       "      <td>7.11</td>\n",
       "      <td>41.79</td>\n",
       "      <td>13.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1999</td>\n",
       "      <td>27.78</td>\n",
       "      <td>7.60</td>\n",
       "      <td>14.26</td>\n",
       "      <td>20.65</td>\n",
       "      <td>20.82</td>\n",
       "      <td>1.36</td>\n",
       "      <td>37.27</td>\n",
       "      <td>49.09</td>\n",
       "      <td>12.25</td>\n",
       "      <td>11.44</td>\n",
       "      <td>30.29</td>\n",
       "      <td>18.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2000</td>\n",
       "      <td>34.04</td>\n",
       "      <td>2.98</td>\n",
       "      <td>20.22</td>\n",
       "      <td>15.54</td>\n",
       "      <td>16.06</td>\n",
       "      <td>3.82</td>\n",
       "      <td>19.99</td>\n",
       "      <td>29.03</td>\n",
       "      <td>6.81</td>\n",
       "      <td>3.38</td>\n",
       "      <td>41.19</td>\n",
       "      <td>8.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2001</td>\n",
       "      <td>59.39</td>\n",
       "      <td>9.12</td>\n",
       "      <td>18.12</td>\n",
       "      <td>16.40</td>\n",
       "      <td>39.28</td>\n",
       "      <td>8.00</td>\n",
       "      <td>55.81</td>\n",
       "      <td>22.06</td>\n",
       "      <td>24.77</td>\n",
       "      <td>19.54</td>\n",
       "      <td>51.43</td>\n",
       "      <td>7.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2002</td>\n",
       "      <td>86.77</td>\n",
       "      <td>11.05</td>\n",
       "      <td>25.02</td>\n",
       "      <td>15.67</td>\n",
       "      <td>45.97</td>\n",
       "      <td>5.34</td>\n",
       "      <td>30.20</td>\n",
       "      <td>45.13</td>\n",
       "      <td>48.58</td>\n",
       "      <td>10.81</td>\n",
       "      <td>65.42</td>\n",
       "      <td>5.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2003</td>\n",
       "      <td>67.93</td>\n",
       "      <td>2.14</td>\n",
       "      <td>23.73</td>\n",
       "      <td>23.82</td>\n",
       "      <td>42.89</td>\n",
       "      <td>2.42</td>\n",
       "      <td>52.19</td>\n",
       "      <td>30.28</td>\n",
       "      <td>27.14</td>\n",
       "      <td>21.21</td>\n",
       "      <td>56.11</td>\n",
       "      <td>7.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2004</td>\n",
       "      <td>76.26</td>\n",
       "      <td>8.51</td>\n",
       "      <td>16.78</td>\n",
       "      <td>26.21</td>\n",
       "      <td>47.34</td>\n",
       "      <td>8.43</td>\n",
       "      <td>47.86</td>\n",
       "      <td>53.95</td>\n",
       "      <td>46.95</td>\n",
       "      <td>10.85</td>\n",
       "      <td>63.68</td>\n",
       "      <td>7.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2005</td>\n",
       "      <td>85.69</td>\n",
       "      <td>8.53</td>\n",
       "      <td>19.72</td>\n",
       "      <td>59.81</td>\n",
       "      <td>23.56</td>\n",
       "      <td>20.45</td>\n",
       "      <td>56.42</td>\n",
       "      <td>28.55</td>\n",
       "      <td>41.60</td>\n",
       "      <td>49.27</td>\n",
       "      <td>59.54</td>\n",
       "      <td>5.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2006</td>\n",
       "      <td>66.58</td>\n",
       "      <td>11.47</td>\n",
       "      <td>22.55</td>\n",
       "      <td>67.35</td>\n",
       "      <td>49.80</td>\n",
       "      <td>10.90</td>\n",
       "      <td>34.09</td>\n",
       "      <td>57.73</td>\n",
       "      <td>38.37</td>\n",
       "      <td>21.77</td>\n",
       "      <td>136.16</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2007</td>\n",
       "      <td>106.50</td>\n",
       "      <td>24.39</td>\n",
       "      <td>17.61</td>\n",
       "      <td>91.06</td>\n",
       "      <td>35.59</td>\n",
       "      <td>24.00</td>\n",
       "      <td>39.17</td>\n",
       "      <td>43.89</td>\n",
       "      <td>71.04</td>\n",
       "      <td>48.97</td>\n",
       "      <td>98.20</td>\n",
       "      <td>9.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2008</td>\n",
       "      <td>136.39</td>\n",
       "      <td>25.02</td>\n",
       "      <td>35.38</td>\n",
       "      <td>87.03</td>\n",
       "      <td>35.70</td>\n",
       "      <td>15.59</td>\n",
       "      <td>70.66</td>\n",
       "      <td>59.83</td>\n",
       "      <td>59.51</td>\n",
       "      <td>46.76</td>\n",
       "      <td>95.34</td>\n",
       "      <td>11.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2009</td>\n",
       "      <td>139.36</td>\n",
       "      <td>20.68</td>\n",
       "      <td>32.15</td>\n",
       "      <td>76.94</td>\n",
       "      <td>41.09</td>\n",
       "      <td>20.31</td>\n",
       "      <td>34.19</td>\n",
       "      <td>47.90</td>\n",
       "      <td>69.89</td>\n",
       "      <td>33.71</td>\n",
       "      <td>138.52</td>\n",
       "      <td>12.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2010</td>\n",
       "      <td>117.64</td>\n",
       "      <td>16.53</td>\n",
       "      <td>14.89</td>\n",
       "      <td>96.86</td>\n",
       "      <td>31.90</td>\n",
       "      <td>11.18</td>\n",
       "      <td>34.93</td>\n",
       "      <td>70.52</td>\n",
       "      <td>77.41</td>\n",
       "      <td>21.99</td>\n",
       "      <td>92.53</td>\n",
       "      <td>13.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2011</td>\n",
       "      <td>118.96</td>\n",
       "      <td>15.98</td>\n",
       "      <td>22.68</td>\n",
       "      <td>56.08</td>\n",
       "      <td>28.11</td>\n",
       "      <td>5.11</td>\n",
       "      <td>35.00</td>\n",
       "      <td>53.37</td>\n",
       "      <td>99.36</td>\n",
       "      <td>15.26</td>\n",
       "      <td>56.99</td>\n",
       "      <td>8.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2012</td>\n",
       "      <td>122.01</td>\n",
       "      <td>5.99</td>\n",
       "      <td>9.51</td>\n",
       "      <td>22.92</td>\n",
       "      <td>18.53</td>\n",
       "      <td>1.76</td>\n",
       "      <td>14.46</td>\n",
       "      <td>47.81</td>\n",
       "      <td>72.86</td>\n",
       "      <td>13.38</td>\n",
       "      <td>30.93</td>\n",
       "      <td>3.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2013</td>\n",
       "      <td>125.22</td>\n",
       "      <td>6.61</td>\n",
       "      <td>7.21</td>\n",
       "      <td>25.65</td>\n",
       "      <td>25.12</td>\n",
       "      <td>0.99</td>\n",
       "      <td>13.04</td>\n",
       "      <td>44.92</td>\n",
       "      <td>62.80</td>\n",
       "      <td>8.67</td>\n",
       "      <td>41.55</td>\n",
       "      <td>6.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2014</td>\n",
       "      <td>99.02</td>\n",
       "      <td>6.06</td>\n",
       "      <td>16.15</td>\n",
       "      <td>23.68</td>\n",
       "      <td>8.89</td>\n",
       "      <td>1.49</td>\n",
       "      <td>16.69</td>\n",
       "      <td>45.85</td>\n",
       "      <td>66.00</td>\n",
       "      <td>5.55</td>\n",
       "      <td>46.66</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2015</td>\n",
       "      <td>70.70</td>\n",
       "      <td>8.03</td>\n",
       "      <td>7.78</td>\n",
       "      <td>11.69</td>\n",
       "      <td>6.05</td>\n",
       "      <td>0.70</td>\n",
       "      <td>7.92</td>\n",
       "      <td>36.44</td>\n",
       "      <td>66.15</td>\n",
       "      <td>5.62</td>\n",
       "      <td>41.54</td>\n",
       "      <td>1.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2016</td>\n",
       "      <td>19.90</td>\n",
       "      <td>1.79</td>\n",
       "      <td>3.86</td>\n",
       "      <td>1.17</td>\n",
       "      <td>2.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.64</td>\n",
       "      <td>6.76</td>\n",
       "      <td>18.22</td>\n",
       "      <td>0.39</td>\n",
       "      <td>14.60</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2017</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2020</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  Action  Adventure  Fighting   Misc  Platform  Puzzle  Racing  \\\n",
       "0   1980    0.34       0.00      0.77   2.71      0.00    0.00    0.00   \n",
       "1   1981   14.84       0.00      0.00   0.00      6.93    2.24    0.48   \n",
       "2   1982    6.52       0.00      0.00   0.87      5.03   10.03    1.57   \n",
       "3   1983    2.86       0.40      0.00   2.14      6.93    0.78    0.00   \n",
       "4   1984    1.85       0.00      0.00   1.45      0.69    3.14    5.95   \n",
       "5   1985    3.52       0.00      1.05   0.00     43.17    3.21    0.00   \n",
       "6   1986   13.74       0.00      0.00   0.00      9.39    0.00    1.96   \n",
       "7   1987    1.12       4.38      5.42   0.00      1.74    0.00    0.00   \n",
       "8   1988    1.75       0.00      0.00   0.00     27.73    5.58    2.14   \n",
       "9   1989    4.64       0.00      0.00   1.28     20.66   37.75    0.00   \n",
       "10  1990    6.39       0.00      0.00   0.00     22.97    6.00    6.26   \n",
       "11  1991    6.76       2.24      0.39   0.08      7.64    3.24    1.14   \n",
       "12  1992    3.83      12.24     15.25   4.94     13.42    4.84    9.04   \n",
       "13  1993    1.81       0.07      8.75   0.30     18.67    3.17    0.36   \n",
       "14  1994    1.55       3.74      8.47   2.86     28.74    1.53    2.19   \n",
       "15  1995    3.57       0.72     14.85   6.40     16.69    2.71    6.09   \n",
       "16  1996   20.58       4.19     18.06  10.68     28.23    3.91   28.24   \n",
       "17  1997   27.58       4.96     11.76   5.69     21.85    5.89   31.91   \n",
       "18  1998   39.44       9.05     31.66  11.94     29.88    6.34   27.90   \n",
       "19  1999   27.78       7.60     14.26  20.65     20.82    1.36   37.27   \n",
       "20  2000   34.04       2.98     20.22  15.54     16.06    3.82   19.99   \n",
       "21  2001   59.39       9.12     18.12  16.40     39.28    8.00   55.81   \n",
       "22  2002   86.77      11.05     25.02  15.67     45.97    5.34   30.20   \n",
       "23  2003   67.93       2.14     23.73  23.82     42.89    2.42   52.19   \n",
       "24  2004   76.26       8.51     16.78  26.21     47.34    8.43   47.86   \n",
       "25  2005   85.69       8.53     19.72  59.81     23.56   20.45   56.42   \n",
       "26  2006   66.58      11.47     22.55  67.35     49.80   10.90   34.09   \n",
       "27  2007  106.50      24.39     17.61  91.06     35.59   24.00   39.17   \n",
       "28  2008  136.39      25.02     35.38  87.03     35.70   15.59   70.66   \n",
       "29  2009  139.36      20.68     32.15  76.94     41.09   20.31   34.19   \n",
       "30  2010  117.64      16.53     14.89  96.86     31.90   11.18   34.93   \n",
       "31  2011  118.96      15.98     22.68  56.08     28.11    5.11   35.00   \n",
       "32  2012  122.01       5.99      9.51  22.92     18.53    1.76   14.46   \n",
       "33  2013  125.22       6.61      7.21  25.65     25.12    0.99   13.04   \n",
       "34  2014   99.02       6.06     16.15  23.68      8.89    1.49   16.69   \n",
       "35  2015   70.70       8.03      7.78  11.69      6.05    0.70    7.92   \n",
       "36  2016   19.90       1.79      3.86   1.17      2.07    0.00    1.64   \n",
       "37  2017    0.01       0.00      0.00   0.00      0.00    0.00    0.00   \n",
       "38  2020    0.00       0.00      0.00   0.00      0.00    0.00    0.00   \n",
       "\n",
       "    Role-Playing  Shooter  Simulation  Sports  Strategy  \n",
       "0           0.00     7.07        0.00    0.49      0.00  \n",
       "1           0.00    10.04        0.45    0.79      0.00  \n",
       "2           0.00     3.79        0.00    1.05      0.00  \n",
       "3           0.00     0.48        0.00    3.20      0.00  \n",
       "4           0.00    31.10        0.00    6.18      0.00  \n",
       "5           0.00     1.00        0.03    1.96      0.00  \n",
       "6           2.52     3.89        0.00    5.57      0.00  \n",
       "7           4.65     0.71        0.00    3.72      0.00  \n",
       "8           5.88     0.51        0.03    3.60      0.00  \n",
       "9           2.20     1.20        0.00    5.72      0.00  \n",
       "10          4.52     0.00        1.14    2.11      0.00  \n",
       "11          3.25     2.00        2.14    2.41      0.94  \n",
       "12          6.86     0.29        2.14    2.95      0.36  \n",
       "13          5.59     3.08        0.19    3.18      0.81  \n",
       "14          7.11     8.30        2.73    8.39      3.56  \n",
       "15         14.26     4.15        4.18    7.98      6.51  \n",
       "16         43.96     6.91       11.33   17.45      5.61  \n",
       "17         21.79    22.17        9.65   30.02      7.71  \n",
       "18         28.09     9.80        7.11   41.79     13.47  \n",
       "19         49.09    12.25       11.44   30.29     18.46  \n",
       "20         29.03     6.81        3.38   41.19      8.50  \n",
       "21         22.06    24.77       19.54   51.43      7.55  \n",
       "22         45.13    48.58       10.81   65.42      5.56  \n",
       "23         30.28    27.14       21.21   56.11      7.99  \n",
       "24         53.95    46.95       10.85   63.68      7.19  \n",
       "25         28.55    41.60       49.27   59.54      5.37  \n",
       "26         57.73    38.37       21.77  136.16      4.27  \n",
       "27         43.89    71.04       48.97   98.20      9.42  \n",
       "28         59.83    59.51       46.76   95.34     11.69  \n",
       "29         47.90    69.89       33.71  138.52     12.56  \n",
       "30         70.52    77.41       21.99   92.53     13.87  \n",
       "31         53.37    99.36       15.26   56.99      8.90  \n",
       "32         47.81    72.86       13.38   30.93      3.33  \n",
       "33         44.92    62.80        8.67   41.55      6.33  \n",
       "34         45.85    66.00        5.55   46.66      0.99  \n",
       "35         36.44    66.15        5.62   41.54      1.82  \n",
       "36          6.76    18.22        0.39   14.60      0.50  \n",
       "37          0.04     0.00        0.00    0.00      0.00  \n",
       "38          0.00     0.00        0.29    0.00      0.00  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "thousand-effectiveness",
   "metadata": {},
   "outputs": [],
   "source": [
    "out.to_csv(\"aggregated_genre.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "plastic-movie",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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