switchgame_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "from matplotlib import pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "pd.set_option('display.max_row', None)\n",
    "pd.set_option('display.max_columns', 50)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions to ask"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Popularity\n",
    "\n",
    "* How do we define if a game is popular?\n",
    "\n",
    "* What kind of game is popular on switch?\n",
    "\n",
    "* Which developer's game is the most popular?\n",
    "\n",
    "* What is the distribution of the release date? Does it have a relationship with games' popularity?\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Success\n",
    "\n",
    "* How do we define if a game is successful?\n",
    "\n",
    "* What kind of game is successful on switch?\n",
    "\n",
    "* Which developer's game is the most successful?\n",
    "\n",
    "* What is the distribution of the release date? Does it have a relationship with games' success?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Online Service\n",
    "\n",
    "* Nitendo has a paid online service for people to play games together through internet, which game that has this features is the most popular? Is the games which have this feature more popular than those which do not?\n",
    "\n",
    "* How to make more people pay for the online service?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Different Platform makes a differece?\n",
    "\n",
    "* Some games are transfer from other platform such as PS4 and Wii, how is their ratings compared to games that only at switch?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selling Data vs scores a game is successful or not\n",
    "\n",
    "* what is the relationship between the sales of games and games’ popularity and success? \n",
    "* Can we use three criterion we defied before to predict the selling of a game?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('switchgame.csv')\n",
    "# df_1 = pd.read_csv('data/switchgame_10.csv')\n",
    "# df_2 = pd.read_csv('data/switchgame_11.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4150, 14)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 4150 observations here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Rating', 'critic_review_attitude', 'critic_review_count', 'developer',\n",
       "       'genre', 'meta_score', 'name', 'num_of_player', 'other_platform',\n",
       "       'rating_count', 'release_date', 'user_score', 'users_review_attitude',\n",
       "       'users_review_count'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rating                     object\n",
       "critic_review_attitude     object\n",
       "critic_review_count         int64\n",
       "developer                  object\n",
       "genre                      object\n",
       "meta_score                float64\n",
       "name                       object\n",
       "num_of_player              object\n",
       "other_platform             object\n",
       "rating_count                int64\n",
       "release_date               object\n",
       "user_score                float64\n",
       "users_review_attitude      object\n",
       "users_review_count          int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To do the data cleaning, here is something we need to do:\n",
    "\n",
    "* **Release date transfer**\n",
    "\n",
    "* **Create Online column**\n",
    "\n",
    "* **Manipulate meta_score and user_score:** \n",
    "\n",
    "* **Handling missing value**\n",
    "\n",
    "* **Order the columns** \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Release date transfer**\n",
    "\n",
    "Tranfer the release_date to datetime type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transfer release_date to datetime type\n",
    "df['release_date'] = df.release_date.apply(lambda s: datetime.datetime.strptime(s, '%b %d, %Y').strftime('%Y/%m/%d'))\n",
    "df['release_date'] = pd.to_datetime(df['release_date'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Create Online column and is_on_other_platfrom**\n",
    "\n",
    "Generate online columns to see if the game can be played online"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First let's look at distribution of num_of_palyer's colums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No Online Multiplayer    3400\n",
       "Online Multiplayer        127\n",
       "Up to 4                   112\n",
       "2                          73\n",
       "Up to 8                    69\n",
       "Up to 6                    22\n",
       "Up to 10                   15\n",
       "Up to 12                    9\n",
       "Up to 16                    9\n",
       "Up to 3                     6\n",
       "Up to 22                    3\n",
       "Up to 64                    3\n",
       "Up to 5                     2\n",
       "Up to 9                     1\n",
       "Up to 18                    1\n",
       "Up to more than 64          1\n",
       "Massively Multiplayer       1\n",
       "Up to 20                    1\n",
       "Up to 32                    1\n",
       "Name: num_of_player, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.num_of_player.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The games with 'No Online Multiplayer' cannot be player online while others can be played online. Next we generate a new columns 'online', which is True if the game can be played online, else False. Drop the num_of_player column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df['online'] = (df['num_of_player']!='No Online Multiplayer')\n",
    "df = df.drop(columns = ['num_of_player'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    3400\n",
       "True      750\n",
       "Name: online, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.online.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['is_on_other_platform'] = (~df[['other_platform']].isnull())\n",
    "df = df.drop(columns = ['other_platform'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Manipulate meta_score and user_score**\n",
    "\n",
    "Filter games which do have neither meta_score nor user_score. For games that have at least one meta_score and user_score, replace missing score with the exsiting score. Normalize two scores and calculate their mean as the average score."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we want to filter games which do have neither meta_score nor user_score, and normalize them to same scale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# check how many games have missing value in both meta_score and user_score\n",
    "mask = df[['meta_score','user_score']].isnull().all(axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a dataframe which either meta_score or user_score exist  \n",
    "df_filter = df.loc[~mask][['name','meta_score','user_score']]\n",
    "# normalize them to same scale\n",
    "df_filter['user_score'] = df_filter['user_score']*10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For games that have at least one meta_score and user_score, replace missing score with the exsiting score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "for row in df_filter.index:\n",
    "    if df_filter.loc[[row],'meta_score'].isnull().all(): #check if meta_score is missing\n",
    "        df_filter.loc[row,'meta_score'] = df_filter.loc[row,'user_score']\n",
    "    if df_filter.loc[[row],'user_score'].isnull().all(): #check if user_score is missing\n",
    "        df_filter.loc[row,'user_score'] = df_filter.loc[row,'meta_score']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now merge df_filter and df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df.drop(['meta_score','user_score'],axis=1),df_filter,how = 'left', on='name')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take average of the meta_score and user_score as avg_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['avg_score'] = (df['meta_score'] + df['user_score'])/2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate total reviews that a game received"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['total_review_counts'] = df['users_review_count'] + df['critic_review_count']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Handling Missing Value**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this dataset, missing value may have lots of meaning. For example, missing value in meta_score means that this game is not so popular that no one cares about it. For this reason we want to keep all missing value first, and when we come to the data analysis part we can do something with them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For users_attitude and critic_attitude, there should be some missing value such as an empty dictionary, \n",
    "0 count for all element in dictionary. We want to convert them to NaN first. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.replace('{}',np.nan)\n",
    "df = df.replace(\"{'Positive': 0, 'Mixed': 0, 'Negative': 0}\",np.nan)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then let's just check how many missing values in each column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rating                     776\n",
       "critic_review_attitude    1264\n",
       "critic_review_count          0\n",
       "developer                    0\n",
       "genre                        0\n",
       "name                         0\n",
       "rating_count                 0\n",
       "release_date                 0\n",
       "users_review_attitude     2069\n",
       "users_review_count           0\n",
       "online                       0\n",
       "is_on_other_platform         0\n",
       "meta_score                2227\n",
       "user_score                2227\n",
       "avg_score                 2227\n",
       "total_review_counts          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(df.isnull())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*  **Order columns**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also want to order the columns so that we have a clearer look at the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Order the columns so that we have a clearer look at the dataset.  \n",
    "columns = ['name','developer','release_date','is_on_other_platform','meta_score','user_score','avg_score','rating_count','genre','Rating',\\\n",
    "           'critic_review_count','users_review_count','total_review_counts','critic_review_attitude','users_review_attitude','online']\n",
    "df = df[columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
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       "\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>name</th>\n",
       "      <th>developer</th>\n",
       "      <th>release_date</th>\n",
       "      <th>is_on_other_platform</th>\n",
       "      <th>meta_score</th>\n",
       "      <th>user_score</th>\n",
       "      <th>avg_score</th>\n",
       "      <th>rating_count</th>\n",
       "      <th>genre</th>\n",
       "      <th>Rating</th>\n",
       "      <th>critic_review_count</th>\n",
       "      <th>users_review_count</th>\n",
       "      <th>total_review_counts</th>\n",
       "      <th>critic_review_attitude</th>\n",
       "      <th>users_review_attitude</th>\n",
       "      <th>online</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1078</th>\n",
       "      <td>The King's Bird</td>\n",
       "      <td>Graffiti Games</td>\n",
       "      <td>2019-02-12</td>\n",
       "      <td>True</td>\n",
       "      <td>67.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>53.5</td>\n",
       "      <td>5</td>\n",
       "      <td>Action,Platformer,2D</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>{'Positive': 2, 'Mixed': 7, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 1, 'Mixed': 0, 'Negative': 1}</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Robbotto</td>\n",
       "      <td>JMJ</td>\n",
       "      <td>2018-08-16</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Action,Platformer,2D</td>\n",
       "      <td>E</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 2, 'Negative': 0}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4075</th>\n",
       "      <td>Bubble Bobble 4 Friends</td>\n",
       "      <td>Taito Corporation,Strictly Limited Games,ININ ...</td>\n",
       "      <td>2019-11-19</td>\n",
       "      <td>False</td>\n",
       "      <td>68.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>14</td>\n",
       "      <td>Action,Platformer,2D</td>\n",
       "      <td>E</td>\n",
       "      <td>38</td>\n",
       "      <td>3</td>\n",
       "      <td>41</td>\n",
       "      <td>{'Positive': 13, 'Mixed': 22, 'Negative': 2}</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 3, 'Negative': 0}</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3764</th>\n",
       "      <td>Agartha-S</td>\n",
       "      <td>Mebius</td>\n",
       "      <td>2019-01-31</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Puzzle,Action</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>{'Positive': 1, 'Mixed': 0, 'Negative': 0}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3794</th>\n",
       "      <td>Arcade Archives: The Tin Star</td>\n",
       "      <td>Hamster</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Action,Beat-'Em-Up,2D</td>\n",
       "      <td>E10+</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               name  \\\n",
       "1078                The King's Bird   \n",
       "231                        Robbotto   \n",
       "4075        Bubble Bobble 4 Friends   \n",
       "3764                      Agartha-S   \n",
       "3794  Arcade Archives: The Tin Star   \n",
       "\n",
       "                                              developer release_date  \\\n",
       "1078                                     Graffiti Games   2019-02-12   \n",
       "231                                                 JMJ   2018-08-16   \n",
       "4075  Taito Corporation,Strictly Limited Games,ININ ...   2019-11-19   \n",
       "3764                                             Mebius   2019-01-31   \n",
       "3794                                            Hamster   2020-04-02   \n",
       "\n",
       "      is_on_other_platform  meta_score  user_score  avg_score  rating_count  \\\n",
       "1078                  True        67.0        40.0       53.5             5   \n",
       "231                   True         NaN         NaN        NaN             0   \n",
       "4075                 False        68.0        66.0       67.0            14   \n",
       "3764                 False         NaN         NaN        NaN             0   \n",
       "3794                  True         NaN         NaN        NaN             0   \n",
       "\n",
       "                      genre Rating  critic_review_count  users_review_count  \\\n",
       "1078   Action,Platformer,2D    NaN                    9                   2   \n",
       "231    Action,Platformer,2D      E                    2                   0   \n",
       "4075   Action,Platformer,2D      E                   38                   3   \n",
       "3764          Puzzle,Action    NaN                    1                   0   \n",
       "3794  Action,Beat-'Em-Up,2D   E10+                    0                   0   \n",
       "\n",
       "      total_review_counts                        critic_review_attitude  \\\n",
       "1078                   11    {'Positive': 2, 'Mixed': 7, 'Negative': 0}   \n",
       "231                     2    {'Positive': 0, 'Mixed': 2, 'Negative': 0}   \n",
       "4075                   41  {'Positive': 13, 'Mixed': 22, 'Negative': 2}   \n",
       "3764                    1    {'Positive': 1, 'Mixed': 0, 'Negative': 0}   \n",
       "3794                    0                                           NaN   \n",
       "\n",
       "                           users_review_attitude  online  \n",
       "1078  {'Positive': 1, 'Mixed': 0, 'Negative': 1}   False  \n",
       "231                                          NaN    True  \n",
       "4075  {'Positive': 0, 'Mixed': 3, 'Negative': 0}   False  \n",
       "3764                                         NaN   False  \n",
       "3794                                         NaN   False  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the clean data into file\n",
    "df.to_csv('switchgame_clean.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4150, 16)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', 'developer', 'release_date', 'is_on_other_platform',\n",
       "       'meta_score', 'user_score', 'avg_score', 'rating_count', 'genre',\n",
       "       'Rating', 'critic_review_count', 'users_review_count',\n",
       "       'total_review_counts', 'critic_review_attitude',\n",
       "       'users_review_attitude', 'online'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13de0872b88>"
      ]
     },
     "execution_count": 24,
     "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": [
    "df['avg_score'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13de055d948>"
      ]
     },
     "execution_count": 25,
     "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": [
    "#df.boxplot(column = 'rating_count')\n",
    "df.rating_count.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13de0cc8ec8>"
      ]
     },
     "execution_count": 26,
     "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": [
    "df['total_review_counts'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13de00fa088>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['release_date'].hist(figsize = (12,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Polularity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define popularity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First of all, let's decide how to measure if a game is popular.\n",
    "\n",
    "* Games that have more ratings\n",
    "* Games that have more reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>name</th>\n",
       "      <th>rating_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>The Legend of Zelda: Breath of the Wild</td>\n",
       "      <td>15248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3709</th>\n",
       "      <td>Animal Crossing: New Horizons</td>\n",
       "      <td>5401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>Super Mario Odyssey</td>\n",
       "      <td>5264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Pokemon Sword</td>\n",
       "      <td>5040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3933</th>\n",
       "      <td>Astral Chain</td>\n",
       "      <td>3173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>Super Smash Bros. Ultimate</td>\n",
       "      <td>2652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Pokemon Shield</td>\n",
       "      <td>2646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>Fire Emblem: Three Houses</td>\n",
       "      <td>2190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1553</th>\n",
       "      <td>Xenoblade Chronicles 2</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2981</th>\n",
       "      <td>Mario Kart 8 Deluxe</td>\n",
       "      <td>1851</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name  rating_count\n",
       "1071  The Legend of Zelda: Breath of the Wild         15248\n",
       "3709            Animal Crossing: New Horizons          5401\n",
       "900                       Super Mario Odyssey          5264\n",
       "66                              Pokemon Sword          5040\n",
       "3933                             Astral Chain          3173\n",
       "882                Super Smash Bros. Ultimate          2652\n",
       "67                             Pokemon Shield          2646\n",
       "2346                Fire Emblem: Three Houses          2190\n",
       "1553                   Xenoblade Chronicles 2          1910\n",
       "2981                      Mario Kart 8 Deluxe          1851"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='rating_count',ascending=False).head(10)[['name','rating_count']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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",
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       "    }\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>name</th>\n",
       "      <th>total_review_counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>The Legend of Zelda: Breath of the Wild</td>\n",
       "      <td>4270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3709</th>\n",
       "      <td>Animal Crossing: New Horizons</td>\n",
       "      <td>3613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Pokemon Sword</td>\n",
       "      <td>2758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3933</th>\n",
       "      <td>Astral Chain</td>\n",
       "      <td>1605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>Super Mario Odyssey</td>\n",
       "      <td>1537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Pokemon Shield</td>\n",
       "      <td>1392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>Super Smash Bros. Ultimate</td>\n",
       "      <td>1047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>Fire Emblem: Three Houses</td>\n",
       "      <td>881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Pokemon: Let's Go, Pikachu!</td>\n",
       "      <td>762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1553</th>\n",
       "      <td>Xenoblade Chronicles 2</td>\n",
       "      <td>645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name  total_review_counts\n",
       "1071  The Legend of Zelda: Breath of the Wild                 4270\n",
       "3709            Animal Crossing: New Horizons                 3613\n",
       "66                              Pokemon Sword                 2758\n",
       "3933                             Astral Chain                 1605\n",
       "900                       Super Mario Odyssey                 1537\n",
       "67                             Pokemon Shield                 1392\n",
       "882                Super Smash Bros. Ultimate                 1047\n",
       "2346                Fire Emblem: Three Houses                  881\n",
       "62                Pokemon: Let's Go, Pikachu!                  762\n",
       "1553                   Xenoblade Chronicles 2                  645"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by = 'total_review_counts',ascending = False ).head(10)[['name','total_review_counts']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, nine games are in top 10 using two criteria. The Legend of Zelda: Breath of the Wild is the most popular game, following Animal Crossing: New Horizons. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### genre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the genre, we need to do some tricky way to split the genre."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>name</th>\n",
       "      <th>developer</th>\n",
       "      <th>release_date</th>\n",
       "      <th>is_on_other_platform</th>\n",
       "      <th>meta_score</th>\n",
       "      <th>user_score</th>\n",
       "      <th>avg_score</th>\n",
       "      <th>rating_count</th>\n",
       "      <th>Rating</th>\n",
       "      <th>critic_review_count</th>\n",
       "      <th>users_review_count</th>\n",
       "      <th>total_review_counts</th>\n",
       "      <th>critic_review_attitude</th>\n",
       "      <th>users_review_attitude</th>\n",
       "      <th>online</th>\n",
       "      <th>index</th>\n",
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       "      <th>0</th>\n",
       "      <td>ACA NeoGeo: Galaxy Fight - Universal Warriors</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACA NeoGeo: Galaxy Fight - Universal Warriors</td>\n",
       "      <td>Hamster</td>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>True</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78.0</td>\n",
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       "      <td>4</td>\n",
       "      <td>T</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 0, 'Negative': 1}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>Fighting</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACA NeoGeo: Galaxy Fight - Universal Warriors</td>\n",
       "      <td>Hamster</td>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>True</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4</td>\n",
       "      <td>T</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 0, 'Negative': 1}</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>2D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Zumba Burn it Up!</td>\n",
       "      <td>505 Games</td>\n",
       "      <td>2019-11-19</td>\n",
       "      <td>False</td>\n",
       "      <td>69.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0</td>\n",
       "      <td>E</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>{'Positive': 2, 'Mixed': 4, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 0, 'Negative': 2}</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>Miscellaneous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Zumba Burn it Up!</td>\n",
       "      <td>505 Games</td>\n",
       "      <td>2019-11-19</td>\n",
       "      <td>False</td>\n",
       "      <td>69.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0</td>\n",
       "      <td>E</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>{'Positive': 2, 'Mixed': 4, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 0, 'Mixed': 0, 'Negative': 2}</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>Exercise / Fitness</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            name  developer release_date  \\\n",
       "0  ACA NeoGeo: Galaxy Fight - Universal Warriors    Hamster   2017-05-18   \n",
       "1  ACA NeoGeo: Galaxy Fight - Universal Warriors    Hamster   2017-05-18   \n",
       "2  ACA NeoGeo: Galaxy Fight - Universal Warriors    Hamster   2017-05-18   \n",
       "3                              Zumba Burn it Up!  505 Games   2019-11-19   \n",
       "4                              Zumba Burn it Up!  505 Games   2019-11-19   \n",
       "\n",
       "   is_on_other_platform  meta_score  user_score  avg_score  rating_count  \\\n",
       "0                  True        78.0        78.0       78.0             4   \n",
       "1                  True        78.0        78.0       78.0             4   \n",
       "2                  True        78.0        78.0       78.0             4   \n",
       "3                 False        69.0        69.0       69.0             0   \n",
       "4                 False        69.0        69.0       69.0             0   \n",
       "\n",
       "  Rating  critic_review_count  users_review_count  total_review_counts  \\\n",
       "0      T                    1                   0                    1   \n",
       "1      T                    1                   0                    1   \n",
       "2      T                    1                   0                    1   \n",
       "3      E                    6                   2                    8   \n",
       "4      E                    6                   2                    8   \n",
       "\n",
       "                       critic_review_attitude  \\\n",
       "0  {'Positive': 0, 'Mixed': 0, 'Negative': 1}   \n",
       "1  {'Positive': 0, 'Mixed': 0, 'Negative': 1}   \n",
       "2  {'Positive': 0, 'Mixed': 0, 'Negative': 1}   \n",
       "3  {'Positive': 2, 'Mixed': 4, 'Negative': 0}   \n",
       "4  {'Positive': 2, 'Mixed': 4, 'Negative': 0}   \n",
       "\n",
       "                        users_review_attitude  online  index  \\\n",
       "0                                         NaN   False      0   \n",
       "1                                         NaN   False      0   \n",
       "2                                         NaN   False      0   \n",
       "3  {'Positive': 0, 'Mixed': 0, 'Negative': 2}   False      1   \n",
       "4  {'Positive': 0, 'Mixed': 0, 'Negative': 2}   False      1   \n",
       "\n",
       "                genre  \n",
       "0              Action  \n",
       "1            Fighting  \n",
       "2                  2D  \n",
       "3       Miscellaneous  \n",
       "4  Exercise / Fitness  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a copy of the original dataframe\n",
    "df_genre = df.copy()\n",
    "# Split the column the column using '|'\n",
    "df_genre.genre = df_genre.genre.apply(lambda x: x.split(','))\n",
    "# i keeps tracks of index\n",
    "index=0\n",
    "# save [index, genre] in a nested list\n",
    "list_ = []\n",
    "for item in df_genre.genre:\n",
    "    list_.extend(map(lambda x: [index, x], item))\n",
    "    index += 1\n",
    "genre = pd.DataFrame(list_, columns=['index', 'genre'])\n",
    "df_genre = pd.merge(df_genre.drop('genre', axis=1), genre, how='right', left_index=True, right_on='index')\n",
    "df_genre.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_genre = df_genre[df_genre['genre']!='Other'] # Exclude other in genre\n",
    "df_genre = df_genre.replace('Tactical','Tactics')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Action                   1796\n",
       "General                   994\n",
       "2D                        668\n",
       "Platformer                530\n",
       "Adventure                 450\n",
       "Puzzle                    446\n",
       "Shooter                   427\n",
       "Arcade                    345\n",
       "Miscellaneous             317\n",
       "Role-Playing              314\n",
       "Shoot-'Em-Up              310\n",
       "Action Adventure          306\n",
       "Strategy                  296\n",
       "Simulation                203\n",
       "3D                        187\n",
       "Sports                    179\n",
       "Fighting                  148\n",
       "Top-Down                  144\n",
       "Action RPG                135\n",
       "Racing                    129\n",
       "First-Person              128\n",
       "Turn-Based                115\n",
       "Automobile                105\n",
       "Visual Novel              102\n",
       "Compilation               102\n",
       "Beat-'Em-Up                99\n",
       "Vertical                   99\n",
       "Individual                 98\n",
       "Tactics                    91\n",
       "Party / Minigame           87\n",
       "Japanese-Style             86\n",
       "Logic                      80\n",
       "Horizontal                 74\n",
       "Team                       74\n",
       "Point-and-Click            71\n",
       "Real-Time                  68\n",
       "Management                 66\n",
       "Virtual                    66\n",
       "Open-World                 65\n",
       "Board / Card Game          65\n",
       "Survival                   63\n",
       "Third-Person               57\n",
       "Business / Tycoon          54\n",
       "Combat                     54\n",
       "Career                     53\n",
       "Matching                   43\n",
       "Rhythm                     43\n",
       "Music                      38\n",
       "Pinball                    37\n",
       "Soccer                     37\n",
       "Hidden Object              32\n",
       "Edutainment                32\n",
       "Vehicle                    32\n",
       "Civilian                   31\n",
       "Linear                     30\n",
       "Defense                    28\n",
       "Flight                     27\n",
       "Roguelike                  25\n",
       "Sim                        20\n",
       "Sandbox                    18\n",
       "Card Battle                18\n",
       "Futuristic                 16\n",
       "Golf                       16\n",
       "Western-Style              16\n",
       "Stacking                   14\n",
       "Nature                     13\n",
       "Tennis                     13\n",
       "Space                      12\n",
       "Light Gun                  11\n",
       "Baseball                   11\n",
       "Virtual Life               11\n",
       "Rail                       10\n",
       "Gambling                   10\n",
       "Basketball                  9\n",
       "Trivia / Game Show          8\n",
       "Command                     8\n",
       "Bowling                     8\n",
       "Fishing                     8\n",
       "Football                    7\n",
       "Horse Racing                7\n",
       "Government                  7\n",
       "Biking                      6\n",
       "Application                 6\n",
       "Marine                      6\n",
       "Billiards                   6\n",
       "Athletics                   6\n",
       "Boxing / Martial Arts       6\n",
       "Trainer                     6\n",
       "Dancing                     5\n",
       "Text                        5\n",
       "Hunting                     5\n",
       "MOBA                        5\n",
       "4X                          5\n",
       "Wrestling                   4\n",
       "Ski / Snowboard             4\n",
       "Exercise / Fitness          4\n",
       "Massively Multiplayer       3\n",
       "Pet                         3\n",
       "Cricket                     2\n",
       "Volleyball                  2\n",
       "Train                       2\n",
       "Rugby                       1\n",
       "Ice Hockey                  1\n",
       "Skate / Skateboard          1\n",
       "Artillery                   1\n",
       "Name: genre, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_genre.genre.value_counts()#.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# draw top 10 genres that have highest average ratings count\n",
    "group_genre = df_genre.groupby('genre')['rating_count'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_genre = group_genre[group_genre['count']>10] #Filter genre that has less than 10 games\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(1,2,1)\n",
    "group_genre.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Genre',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge rating count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 genres that have highest average ratings count',fontsize=12)\n",
    "\n",
    "\n",
    "# draw top 10 genres that have higest Averge total reviews count\n",
    "group_genre = df_genre.groupby('genre')['total_review_counts'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_genre = group_genre[group_genre['count']>10] #Filter genre that has less than 10 games\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "group_genre.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Genre',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge total reviews count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 genres that have highest Averge total reviews count',fontsize=12)\n",
    "plt.savefig('genre_popular.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Developer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a copy of the original dataframe\n",
    "df_developer = df.copy()\n",
    "# Split the column the column using '|'\n",
    "df_developer.developer = df_developer.developer.apply(lambda x: x.split(','))\n",
    "# i keeps tracks of index\n",
    "index=0\n",
    "# save [index, genre] in a nested list\n",
    "list_ = []\n",
    "for item in df_developer.developer:\n",
    "    list_.extend(map(lambda x: [index, x], item))\n",
    "    index += 1\n",
    "developer = pd.DataFrame(list_, columns=['index', 'developer'])\n",
    "df_developer = pd.merge(df_developer.drop('developer', axis=1), developer, how='right', left_index=True, right_on='index')\n",
    "#df_developer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Hamster                  213\n",
       "Nintendo                 104\n",
       "Ratalaika Games           74\n",
       "Forever Entertainment     62\n",
       "Ultimate Games            54\n",
       "Sega                      49\n",
       "Arc System Works          45\n",
       "Bandai Namco Games        44\n",
       "Digerati Distribution     42\n",
       "Ubisoft                   40\n",
       "Name: developer, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_developer.developer.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot Top 10 developer that have highest average ratings count\n",
    "group_developer = df_developer.groupby('developer')['rating_count'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_developer = group_developer[group_developer['count']>10] #Filter developer that has less than 10 games\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(1,2,1)\n",
    "group_developer.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Developer',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge rating count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 developers that have highest average ratings count',fontsize=10)\n",
    "\n",
    "# plot Top 10 developers that have highest Averge total reviews count\n",
    "group_developer = df_developer.groupby('developer')['total_review_counts'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_developer = group_developer[group_developer['count']>10] #Filter developer that has less than 10 games\n",
    "plt.subplot(1,2,2)\n",
    "group_developer.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Developer',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge total reviews count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 developers that have highest Averge total reviews count',fontsize=10)\n",
    "plt.savefig('developer_popular.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Release Date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='release_date',y='rating_count',figsize=(12,6))\n",
    "plt.xlabel('Release date',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Ratings count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Rating count vs Release date',fontsize=15)\n",
    "plt.savefig('date_ratingcount.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='release_date',y='total_review_counts',figsize=(12,6))\n",
    "plt.xlabel('Release date',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Total Reviews count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Total reviews count vs Release date',fontsize=15)\n",
    "plt.savefig('date_reviewcount.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Success"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define Success of a game"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's decide how to measure if a game is success. Meta_score is the critics' attitude toward the game. User_score is the user's attitude toward the game. In the data cleaning we have already combined them into avg_score. So if the avg_score of a game is high, that means both user and critics love the game. Let's now measure the avg_score of all games."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>name</th>\n",
       "      <th>avg_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>Super Mario Odyssey</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>The Legend of Zelda: Breath of the Wild</td>\n",
       "      <td>91.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>Divinity: Original Sin II - Definitive Edition</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>906</th>\n",
       "      <td>Super Kickers League</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>Super Smash Bros. Ultimate</td>\n",
       "      <td>89.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1546</th>\n",
       "      <td>Xenoblade Chronicles: Definitive Edition</td>\n",
       "      <td>89.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2612</th>\n",
       "      <td>Hollow Knight</td>\n",
       "      <td>89.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2981</th>\n",
       "      <td>Mario Kart 8 Deluxe</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4037</th>\n",
       "      <td>Bayonetta 2</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1700</th>\n",
       "      <td>Celeste</td>\n",
       "      <td>88.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                name  avg_score\n",
       "900                              Super Mario Odyssey       93.0\n",
       "1071         The Legend of Zelda: Breath of the Wild       91.5\n",
       "2008  Divinity: Original Sin II - Definitive Edition       90.0\n",
       "906                             Super Kickers League       90.0\n",
       "882                       Super Smash Bros. Ultimate       89.5\n",
       "1546        Xenoblade Chronicles: Definitive Edition       89.5\n",
       "2612                                   Hollow Knight       89.5\n",
       "2981                             Mario Kart 8 Deluxe       89.0\n",
       "4037                                     Bayonetta 2       89.0\n",
       "1700                                         Celeste       88.5"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['name','avg_score']].sort_values(by = 'avg_score',ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most success game is Super Mario Odyssey following by The Legend of Zelda: Breath of the Wild"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "group_genre = df_genre.groupby('genre')['avg_score'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_genre = group_genre[group_genre['count']>10] #Filter genre that has less than 10 games\n",
    "plt.figure(figsize=(12,6))\n",
    "group_genre.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Genre',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge scores',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 genres that have highest Averge scores',fontsize=10)\n",
    "plt.savefig('genre_success.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Developer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "group_developer = df_developer.groupby('developer')['avg_score'].agg(['count','mean']).sort_values(by='mean',ascending=False)\n",
    "group_developer = group_developer[group_developer['count']>10] #Filter developer that has less than 10 games\n",
    "plt.figure(figsize=(12,6))\n",
    "group_developer.head(10)['mean'].plot.bar()\n",
    "plt.xlabel('Developer',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Averge scores',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Top 10 developers that have highest Averge scores',fontsize=10)\n",
    "plt.savefig('developer_success.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Release Date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='release_date',y='avg_score',figsize=(12,6))\n",
    "plt.xlabel('Release date',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Average score',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Average score vs Release date',fontsize=15)\n",
    "plt.savefig('date_score.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Online Service\n",
    "\n",
    "5.Nitendo has a paid online service for people to play games together through internet, which game that has this features is the most popular and successful? Is the games which have this feature more popular than those which do not?\n",
    "\n",
    "6.How to make more people pay for the online service?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    3400\n",
       "True      750\n",
       "Name: online, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.online.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', 'developer', 'release_date', 'is_on_other_platform',\n",
       "       'meta_score', 'user_score', 'avg_score', 'rating_count', 'genre',\n",
       "       'Rating', 'critic_review_count', 'users_review_count',\n",
       "       'total_review_counts', 'critic_review_attitude',\n",
       "       'users_review_attitude', 'online'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are only 750 games which can play online.Let's compare two groups' popularity and success."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "group = df.groupby('online').agg('mean')[['avg_score','rating_count','total_review_counts',]]\n",
    "group.plot.bar(figsize=(12,6))\n",
    "plt.xlabel('Online or not',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Compare online games with not online game',fontsize=15)\n",
    "plt.savefig('online.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "df.boxplot(by = 'online',column = 'avg_score')\n",
    "plt.xlabel('Online or not',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Average score',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('',fontsize=15)\n",
    "plt.savefig('online_score.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-0.0071820668647326665, pvalue=0.9942703347343751)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy import stats\n",
    "# Perform two sample t-test to see it the mean of avg_score of two groups are the same\n",
    "online_group = df[df.online == True]\n",
    "not_online_group = df[df.online != True]\n",
    "stats.ttest_ind(online_group['avg_score'].dropna(), not_online_group['avg_score'].dropna())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check what is the most popular top100 games in each group, and calculate the count of their genres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot top10 Genre with most count for online game\n",
    "online_game = df[df['online']==True]\n",
    "online_game = online_game.sort_values(by='rating_count',ascending = False)[['name']].head(100)\n",
    "online_game = pd.merge(online_game,df_genre,how='left',on='name')\n",
    "#online_game = online_game[online_game.avg_score>80]\n",
    "plt.figsize=(12,6)\n",
    "plt.subplot(1,2,1)\n",
    "online_game.genre.value_counts().head(10).plot.bar()\n",
    "plt.xlabel('Genre',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Genre count for online game',fontsize=15)\n",
    "\n",
    "# plot top10 Genre with most count for not online game\n",
    "no_online_game = df[df['online']!=True]\n",
    "no_online_game = no_online_game.sort_values(by='rating_count',ascending = False)[['name']].head(100)\n",
    "no_online_game = pd.merge(no_online_game,df_genre,how='left',on='name')\n",
    "#no_online_game = no_online_game[no_online_game.avg_score>80]\n",
    "plt.subplot(1,2,2)\n",
    "no_online_game.genre.value_counts().head(10).plot.bar(figsize=(12,6))\n",
    "plt.xlabel('Genre',fontweight='bold',fontsize=15)\n",
    "plt.ylabel('Count',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Genre count for not online game',fontsize=15)\n",
    "plt.savefig('online1.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Different Platform makes a differece?\n",
    "\n",
    "* Some games are transfer from other platform such as PS4 and Wii, how is their performance compared to games that only at switch?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby('is_on_other_platform').agg('mean')[['avg_score','rating_count','total_review_counts']].plot.bar(figsize=(12,6))\n",
    "plt.xlabel('On other platform',fontweight='bold',fontsize=15)\n",
    "plt.xticks(fontweight='bold',fontsize=12)\n",
    "plt.yticks(fontweight='bold',fontsize=12)\n",
    "plt.title('Compare games that on other platfrom with games that only on switch',fontsize=15)\n",
    "plt.savefig('platform.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_on_other_platform</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>False</th>\n",
       "      <td>857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True</th>\n",
       "      <td>3293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count\n",
       "is_on_other_platform       \n",
       "False                   857\n",
       "True                   3293"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('is_on_other_platform').agg(['count'])['total_review_counts']#.plot.bar(figsize=(12,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selling Data vs scores a game is successful or not\n",
    "\n",
    "* what is the relationship between the sales of games and games’ popularity and success? \n",
    "* Can we use three criterion we defied before to predict the selling of a game?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>name</th>\n",
       "      <th>developer</th>\n",
       "      <th>release_date</th>\n",
       "      <th>is_on_other_platform</th>\n",
       "      <th>meta_score</th>\n",
       "      <th>user_score</th>\n",
       "      <th>avg_score</th>\n",
       "      <th>rating_count</th>\n",
       "      <th>genre</th>\n",
       "      <th>Rating</th>\n",
       "      <th>critic_review_count</th>\n",
       "      <th>users_review_count</th>\n",
       "      <th>total_review_counts</th>\n",
       "      <th>critic_review_attitude</th>\n",
       "      <th>users_review_attitude</th>\n",
       "      <th>online</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Pokemon: Let's Go, Pikachu!</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>2018-11-16</td>\n",
       "      <td>False</td>\n",
       "      <td>79.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1597</td>\n",
       "      <td>Action RPG,Role-Playing,Trainer</td>\n",
       "      <td>E</td>\n",
       "      <td>92</td>\n",
       "      <td>670</td>\n",
       "      <td>762</td>\n",
       "      <td>{'Positive': 65, 'Mixed': 19, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 305, 'Mixed': 75, 'Negative': 290}</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Pokemon: Let's Go, Eevee!</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>2018-11-16</td>\n",
       "      <td>False</td>\n",
       "      <td>80.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>971</td>\n",
       "      <td>Action RPG,Role-Playing,Trainer</td>\n",
       "      <td>E</td>\n",
       "      <td>86</td>\n",
       "      <td>405</td>\n",
       "      <td>491</td>\n",
       "      <td>{'Positive': 62, 'Mixed': 15, 'Negative': 1}</td>\n",
       "      <td>{'Positive': 198, 'Mixed': 42, 'Negative': 165}</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Pokemon Sword</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>2019-11-15</td>\n",
       "      <td>False</td>\n",
       "      <td>80.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>5040</td>\n",
       "      <td>Role-Playing,Trainer</td>\n",
       "      <td>E</td>\n",
       "      <td>94</td>\n",
       "      <td>2664</td>\n",
       "      <td>2758</td>\n",
       "      <td>{'Positive': 66, 'Mixed': 21, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 778, 'Mixed': 330, 'Negative': 1556}</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Pokemon Shield</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>2019-11-15</td>\n",
       "      <td>False</td>\n",
       "      <td>80.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>62.5</td>\n",
       "      <td>2646</td>\n",
       "      <td>Role-Playing,Trainer</td>\n",
       "      <td>E</td>\n",
       "      <td>96</td>\n",
       "      <td>1296</td>\n",
       "      <td>1392</td>\n",
       "      <td>{'Positive': 69, 'Mixed': 20, 'Negative': 0}</td>\n",
       "      <td>{'Positive': 404, 'Mixed': 170, 'Negative': 722}</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           name developer release_date  is_on_other_platform  \\\n",
       "62  Pokemon: Let's Go, Pikachu!  Nintendo   2018-11-16                 False   \n",
       "63    Pokemon: Let's Go, Eevee!  Nintendo   2018-11-16                 False   \n",
       "66                Pokemon Sword  Nintendo   2019-11-15                 False   \n",
       "67               Pokemon Shield  Nintendo   2019-11-15                 False   \n",
       "\n",
       "    meta_score  user_score  avg_score  rating_count  \\\n",
       "62        79.0        61.0       70.0          1597   \n",
       "63        80.0        62.0       71.0           971   \n",
       "66        80.0        46.0       63.0          5040   \n",
       "67        80.0        45.0       62.5          2646   \n",
       "\n",
       "                              genre Rating  critic_review_count  \\\n",
       "62  Action RPG,Role-Playing,Trainer      E                   92   \n",
       "63  Action RPG,Role-Playing,Trainer      E                   86   \n",
       "66             Role-Playing,Trainer      E                   94   \n",
       "67             Role-Playing,Trainer      E                   96   \n",
       "\n",
       "    users_review_count  total_review_counts  \\\n",
       "62                 670                  762   \n",
       "63                 405                  491   \n",
       "66                2664                 2758   \n",
       "67                1296                 1392   \n",
       "\n",
       "                          critic_review_attitude  \\\n",
       "62  {'Positive': 65, 'Mixed': 19, 'Negative': 0}   \n",
       "63  {'Positive': 62, 'Mixed': 15, 'Negative': 1}   \n",
       "66  {'Positive': 66, 'Mixed': 21, 'Negative': 0}   \n",
       "67  {'Positive': 69, 'Mixed': 20, 'Negative': 0}   \n",
       "\n",
       "                                users_review_attitude  online  \n",
       "62    {'Positive': 305, 'Mixed': 75, 'Negative': 290}    True  \n",
       "63    {'Positive': 198, 'Mixed': 42, 'Negative': 165}    True  \n",
       "66  {'Positive': 778, 'Mixed': 330, 'Negative': 1556}   False  \n",
       "67   {'Positive': 404, 'Mixed': 170, 'Negative': 722}    True  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['name'].isin([\"Pokemon: Let's Go, Pikachu!\" ,\"Pokemon: Let's Go, Eevee!\",\"Pokemon Sword\",\"Pokemon Shield\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create datafram that combine Pokemon Sword and Shield ,Pokemon: Let's Go, Pikachu! and Eevee!\n",
    "df_poke = pd.DataFrame([\n",
    "                       [\"Pokemon: Let's Go, Pikachu! and Let's Go, Eevee!\",\"Nintendo\",pd.to_datetime('2018-11-16'),False,79.5,61.5,70.5,1597+971,\n",
    "                         \"Action RPG,Role-Playing,Trainer\",'E',92+86,670+405,762+491,{'Positive': 65+62, 'Mixed': 19+15, 'Negative': 1},\n",
    "                        {'Positive': 305+198, 'Mixed': 75+42, 'Negative': 290+165},True],\n",
    "                       [\"Pokemon Sword and Shield\",\"Nintendo\",pd.to_datetime('2019-11-15'),False,80,45.5,62.75,2646+5040,\n",
    "                         \"Role-Playing,Trainer\",'E',94+96,2664+1296,2758+1392,{'Positive': 66+69, 'Mixed': 21+20, 'Negative': 0},\n",
    "                        {'Positive': 778+404, 'Mixed': 330+170, 'Negative': 1556+722},False]\n",
    "                       ],\n",
    "                        columns=df.columns)\n",
    "df_combine = pd.concat([df_poke,df],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(33, 2)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sell = pd.read_csv('switchsell.csv')#.drop('No.',axis = 1)\n",
    "df_sell.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>name</th>\n",
       "      <th>Copies sold in million</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mario Kart 8 Deluxe</td>\n",
       "      <td>24.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Super Smash Bros. Ultimate</td>\n",
       "      <td>18.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Legend of Zelda: Breath of the Wild</td>\n",
       "      <td>17.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Super Mario Odyssey</td>\n",
       "      <td>17.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pokemon Sword and Shield</td>\n",
       "      <td>17.37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      name  Copies sold in million\n",
       "0                      Mario Kart 8 Deluxe                   24.77\n",
       "1               Super Smash Bros. Ultimate                   18.84\n",
       "2  The Legend of Zelda: Breath of the Wild                   17.41\n",
       "3                      Super Mario Odyssey                   17.41\n",
       "4                 Pokemon Sword and Shield                   17.37"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sell.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_withsell = pd.merge(df_sell,df_combine,on = 'name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('rating_count','Copies sold in million', df_withsell)\n",
    "plt.savefig('rc.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wKPBcEduiVOjYgX4320ELqZcFOzTkgnfDHW5KJowG77kX4TWWJnjTcg3ge4E7jDE/Bl7NvENEflTwVikVArqLRfmwQ0Pwhwex6387NnjTQw2NwRTszzWAzwFeBi4Yd9wCGsCq7Nj+Pmjbp7V8I84ODWEfvR+7/g63YhH84D0d77y3BBa8abkuRT6/2A1RKizCsIuFmhk7NASbH6Lt/rXYff5uKIkELD7d9XjnFu/C2nRMGMDGGC9detIYM+GKORHRKxNqSlGpQ2F7urWQeoTZ4eHRoYa2fVjwg/eNrsc7jeBNPf0kbLzTfT8U6Xt2sh5wO24HDHDbyo/vDnj+sYqCtkiVndSWTa4ORTI5tg7FFVeHKoRtdxd0tgfdDJWH0eC9w100BUgkqD71HAbOWIY3b//9fkcCtrUFGpvg7AtJHLdw9L41N7kpaUX8np0sgBdm3D6qYO+oYseuvWW0DgX4//a54yEJYN3FIprs8DBsfgi77rejwet5cNJpeEsvpuGY12bdlHNMwNbWu1+8a24idenlLoQ33unuq6oerZ1ShO/ZCQNYRF7KuL29YO+o4qdll+tFZApRHQrdxSJ6XPA+jF1/u1sgA2OCN1uPd4zMgIXR1aEb74TjFrpecW392OcU4XtWa0Go4mua76b+hLAOhe5iES12eBgef9j1eFv9i2ueByeehnd+DsGbli1gK6tGX7OxyfWK0wENRfme1QBWRectX+HGgENUh8IVUm+Fvt7A2qBy54L3EXdxbd8ed9Dz4MRTXY93usGYLWAHB9xxgLMvdEMUA/2QrCza96wGsCq6xKIlpEJUh0J3sYgOOzwMTzzieryZwbvoVLylb8E78OD8XjgzYCurXPgOD7vjQOK4haQuvTzQWRBKFUxY6lC4Qur7tJB6yLngfRS77vbCBq9vTMBmmQWRfgzHLcQ7+JAZvddkJpsHfD/7Tz3bj5ajVFExuovFQNBNUROww8Ow5fcuePfudgc9Dxad4ubxHrSgYO+VDtggTdYD/mHG7dcAfw3cAGwHDgeuQpchq4jQXSzCbcLgPWGJG+MtYPCGyWTT0G5I3zbGPAQsF5EnM46txgXw54raQqVmyA4PwT7dxSKMbCrlgve+38QqeNNyHQM+nv1LUb4AvK6wzVGqsOzQkNuKScM3VEaCd93to3NrPQ8WvgHv/EvKPnjTcg3g9cBPjDGfxVVFOwz4PHB/kdql1Iyld7Gws2dP/WBVEpMG79KL8eY3B9vAEss1gN8PfB94Elf7YQi4Bfir4jRLqZnRXSzCxaZS8MdN2Ptuh5aMkuIL3+AWUMwv3kyDMMu1HOU+4HK/KtqBwB6tgqbCSnexCI+R4F13O+wZF7xLLy7qFK8omGwa2tGTPK/eGAOAiDxf6EYplS/b74ev1vINlE2l4Mk/uItre3aO3vH6k90Yb8yDN22yHvCzuHnA3iSP0XKUKjR0F4vgjQTvut/A7szgXYy39BK8BYcG17gQmmwa2oRF2JUKG9vX62o7aPgGwqZS8JTf480M3uMXux6vBm9W01qKbIw5HDgEeDmzXKVSQdIthILjgnezH7w7Ru84frG7uLbgsOAaFwE5BbAxZgFwE3AGsBeY5y/OuFxEdkz6ZKWKyPb1QNv+BbdVcdlUCrZudrMadr0yesfxJ7mhhmYN3lzk2gP+AfA4cLGIdBtj6oGvAP8FvLVYjVNqMhq+peeC93HX480M3ted5Hq8zYcH17hiqCjuJa5cA/hsYIGIDAL4IfxJ4JXJn+YYY34EXArsFpET/GOfBz4I+KWOuEZEbp9G21WMafiWlk2l4E9PuOB99eXRO167CG/ZpeUXvMkk1DVAbV1x3ybHx7UCr8f1gtNeC+S6fexPgP8Efjru+LdF5Bs5voZSgG6eWUrW2tEe7/jgPf8SvEOOCK5xxVBVDfUNeJm7txRRrgH8deBuY8z1uGpoR+BWwX02lyeLyAZjzJF5tVCpDLajDXq6g25G2bPWuh7vvWviEbw1tS54K6tK+ra5roS7zhjzHHAFcCKwA3iPiNw7w/f/B2PM+4DfAx8XEf2bUmWlWwiVxkjw3vcb2Jkx0em4E1zwHnpkYG0ruITn9oWrrcdLBrM3Rc7v6oftTAM30w+AL+EWc3wJ+Cau5vB+jDErgZV+O2hqasrrDZPJZN7Pjboon7tNpUjta8HW1kDt9P80rEhW0NjYWISWRUMu52+tZXDLJnpu/yXDL28bOV75+sXUXvxOKo88psitLI6s515RQaJ+Fl5dPV6RL7JNJddpaB8D7hWRzcaYNwK/wBXkea+IPJDPG4vIyP7OxpjrgDWTPHYVsMr/1La0tOTzljQ1NZHvc6MuqufuCqnvc3t25amxsZHW1vj+cTXZ+Vtr4c9bsPetgR0ZPd5jF+KdfwnDhx1FF0BEv35jzr2y0l1Yq6rC6x+A/tLtjNLcnL3KW6494H8Crvdvfw34FtAJfBt4Yz4NMsYsEJH0kpm/AP6Yz+uo8mWHh11FM63lW3DWWnj6j26o4ZXto3cc+3o31HDYZKVgIsTz3PhuXT1e5g7IIZFrAM8RkXZjzCzgJODNIjJsjPlmLk82xvwcWAo0GWNexu2isdQYsxg3BLENuHq6jVflyw4NufAdHg66KWVlwuA9xg/ew8skeCsqoLaOivkL8FpznaxVerkG8EvGmDOBhcAGP3xnAzn9dIjIe7Icvj7LMaVGCqlr+BaOtRaeedLNaijn4K2qhro6qK7F8zy8inBv/J5r6/4P8EtgAHiHf+xS4JFiNErFlx0ccOGrhdQLwlrLwJN/wN52M2RcXOOY4/3gfU1gbSuYhAc1dW42Q2Vl0K2Zllynod0OjB9F/oX/oVRBaCH1wrHWwrNPYe9dQ2dm8L7GD94jyiB4k0moq4eaOrxENIs35t0/Ty9LVqoQtJZvYbjg3epmNbz0wugdR7/WLRk+IprTycaoqYHaBrzq8F1Um65wD5CoWNBykjNnrYXntmLv/Q28lLFJzdGvZfZbL6dr3sHBNa4QQrBoohjK50xUJNneHrfCTeXFBe+fXI/3xbHB651/Cd6Rx1LZ2BjZebzlMMwwGQ1gFRjb0wUdWlQnH9ZaeP5Prsf74nOjdxx1nAveo44LrnEz5XlQXeN6u2UwzDCZXFfCnQ9sE5EX/OLsX8NNQbtGRF6d/NlK7c92d0JnR9DNiBwXvH92Pd7t0Qze1NNPwsY73TzvxiY4+0ISxy10c3frGqC2Fi8Rj60mc+0Bfx9Y7t9OL74Ywi0P1oLsalpsZwd0dwbdjEix1sILf3bzeDOD98hj3cW1CAQv+OG75iZ/oUS9Kyu65mZSl/8NFW84I+jmlVyuAXyIiLxojEnigvgI3Jxg3Y5ITYuWk5weF7xP+8H77OgdRxyDt+xS1/P1Jtu4PGQ23unCt6oaEgmobICBfrh3DWgAT6jDGDMfOAF4SkS6jDFVQLRmPatA2fZW6O0JuhmRYdPBu+2Z0YNHHIO37BI46rXRCt601r1QP8uFcLr9VdXQsmvy55WpXAP4u8CjQBXwUf/YWcCfitEoVV5cLd990NcXdFMiIXvwvsbv8UY0eNOVyA5aAB1tbnZD2kA/NM0Prm0BynUl3L8bY34FDItIegDqFeBvitYyVRastW6BRb+G71TsC0+7IjkvPD168HA/eI+OaPBW10Dd6KIJ76J3YFdfC/S5nu9APwwN4S1fEWw7AzKdaWgvAKcbY04RkZvJcUNOFV82lXJLiwdKV3c1iuy2Z1yPNzN4DzvaBe9rXhe94PU8qK11wZscO0qZWLSE1BVXY9fe4oYdmubjLV9BYtGSgBobrFynoS0CbgX6gUOBm4HzgKuAdxetdSqyClFIvdzZbc+4Hu/zfx49eNjRboz3NcdHL3gTCbdooq5+0mlkiUVLIKaBO16uPeAfAP8qIj8zxqSX1KwHritOs1SUufDdC4NaLiQbu/1Z1+MdE7xH+T3eCAZveny3pjZ6bQ9YrgG8EPhv/7YFEJFuY0xtUVqlIkt3sZiY3f4c9t7bxgbvoUfiLbvMlYeMWniVeAv3cpRrAG8DluB2LwbAGHMa8OxET1Dxo7tYZGdffM71eJ/LmDR06JF451/i9l6LUvCObPHTELnau2GUawB/FviNMea/gCpjzGeAvwU+WLSWqUjRQur7sy8+75YMP7t19GBUgzfH8V01PblOQ1tjjHkLbtrZetxKuBUisqmYjVPRoOUkx8oavIcc4cZ4oxa8lZV+Gci6aLU7InKehiYijwEfKmJbVAiltmyadMqQFtUZZV963lUne/ap0YNRDN4YVSML2oQBbIz5ZxH5sn/7ixM9TkT+tRgNU8FLbdnkJs0nk275aHsrdvW1pK64msSiJdjuLg1fwL70guvxPpMRvM2Hu+A97oToBG9FxWjt3QodZiiFyXrAh2bcPmyCx+jfnGXMrr3FhW/6Knd1DdCHXXsL9jWvc5WsYsy+vM1dXHvmydGDzYe5WQ1RCt7qGje2q7MZSm7CABaRv8u4/VelaY4KlZZdruebqaoadu906/ljyr68zS2gePqPowcXHOYurr3uxGgEbyIxOrZbRlv8RE3OX3ljzLGAwe2OvAMQEXlm8mepSGua77YLyuwZ9fXCAXODa1OAsgbvwYe6oYaoBG9VlRtmqNZFE2GQ0yZLxpgrgD8AJwLdwCLgMf+4KlPe8hVuQUV/n5vh0NvjlhaffWHQTSsp+8p2Uj/7Hvbafx8N34MPxXvP1Xgfugbv+JPCHWbpKWTzDsKbeyBejc5oCItce8D/BlwsIhvSB4wx5wA/A1YXo2EqeGMKp+ze6Xq+6e1jYsC+st31eP+8ZfTgwYe6oYawhy6MXFSrmN+Mt29f0K1RWeQawLOAB8cdewioL2xzVNgkFi1xF9xiNOZrd7zogvdPT4wenH/I6FBD2Hfnra5xY7s1rlJA6NsbY7kG8LeArxhjPisifX4NiC/4x1UZs309sQnfCYM33eMNc5DpRbVIyvV/6kPAwcA/+tXQGgEP2GmMyZwtcXjhm6iCYvt63Qq3Mmd3vOQH7+OjBw9qdsH7+sXhDt6qKhe8WoksknIN4PcWtRUqdFz4tpb18mK782W3gGJrxII34UFNnVuppgVxIi3XWhDri90QFR7lXtvBBe9vYOvm0YMHLfCD9+TwBm+6LkNNbXjbqKYl1x0xKoF/Aa5kdB7wz4Avi4hueVAmrLVudVuZbhtvX33F9XifygjeA/3gXRjS4E345R9r6/Eqq4JujSqwXIcgvg6chitBuR1XDe2zwGzgn4rTNFVK5byF0NArL5K69SZ48rHRg2EP3kp/wYSO7Za1XAP4XcBJIrLX//zPxpjHgMfRAI68ci2kbl99BbvudtrHBO/BeEsvhhOWhC94R4qda283LnIN4Il+Beuv5oizQ4OukHoZha/d9Qr2vtvH9nibDsY7P6TBm65CVlunxc5jJtcA/gVwmzHmC8CLuCGIfwGkWA0Lk6lq4s708UGxA/3Qtq9sdrGwu3Zg1/nBm76A2DSfhkveRffRx4cveLUKWezlGsCfxAXu93AX4V4BbsItUZ6SMeZHwKXAbhE5wT82F7e9/ZG4PeeMiLRO9BpBmaom7kwfH5Rymulgd+90sxrGBa+39GJYdArV8+bR0xqSby1dMKEy5DoNbQD4V/8jHz8B/hP4acaxTwP3iMjXjDGf9j//VJ6vXzST1cQlS6BO9/GlZq2F7k7o6gy6KTNmd+90Pd4/bhoN3nkHuYtri04JV4+3qhrq6rQKmRpj0gA2xpwFvFVE9gtGY8zXgP8VkYemehMR2WCMOXLc4bcBS/3bNwDrCGEAT1gTt2VXYR5fQnZo0PV6Iz7TYcLgXXoxnHhqeIJXe7tqClN9V1wDfH+C+9YD/wxclud7zxeRnQAistMYc9BEDzTGrARW+o+lqakprzdMJpPTfu6+BYeSat07UtgE3CqxxIJDmZvltab7+FKw1pLo7aYxNQQN9US1htLwq6/Q89v/YeCxB0eCN3HgwdRdtIKqU86acBudimQFjY2NJWunV12NV98QmrKP+Xzfl4uwn/tUAbwYuGOC++4Cri9sc7ITkVXAKv9T29LSktfrNDU1Md3nppZd5sZ0h4ddT3agH4aGSC27LGptYC0AABnRSURBVOtrTffxxWYHB6CjjcaGBlrDMg46TXbPq9h1v4Utj472eOceiLf0YuyJp9JTUUFPx8R70zU2Nhb/3D0PamuhtgGPCujudR8hkM/3fbkIy7k3NzdnPT5VAM8GqoBs30mVuDKV+dpljFng934XALtn8FpFM6Ymbg6zGqb7+GKx1kJXB3R3lfR9C2my4OXEU8OxcWQiAfUNOoVM5WWqAP4TcCHw6yz3Xejfn69bgauAr/n/ZnuPUEgsWjKtC2jTfXyh2cEBV0hnaCiwNsyEbdnlxnifyAjexiYXvCedFo7graiAugY3jSwEwwwqmqYK4G8D1xpjKnAX3FLGmATwdtyUtI/l8ibGmJ/jLrg1GWNeBj6HC14xxnwAN7f4Xfmdgspku7tczzeC08vs3t1uAcUTj4wN3vPeAovfGJ7grW9wtRk0eNUMeXaKH1RjzMdwxdergRagCegDPici3y56C/dnd+zYkdcTwzIeVAw2lYKOVujry3p/ScZB82T37sau/y1sfjgjeOf5Pd6ZB++Mz93zoLralYCsrolc8Jbz9/1UwnLuzc3NWb9pppwbIyLfMsb8EDgDmAfsBR4UkYmveqiSsoMDbkVbxJYTjwTv44+MrsY7wA/eMPR405tZ1tYH3xZVlnJdiNEBrC1yW1QebE+3KyEZoSEHu2+Pu7j2+MMZwTvXH2o4Pfg5s+lVjFqJTBWZzg6PKJtKueDt7Qm6KTmz+/aMDjWEMXgrq6C+YcwcbqWKSQM4guzQoBtyiMgsBxe8d8Dmh0aDd85cvKUhCd6qKqifpUVxVMlpAEeM7fV3KY7AkINtbXE93j+MC97zLoKTzwhB8Fb7wVsdbDtUbGkAR0SUhhyyB2+jG2oIQ/BW10DDLC16rgKnARwBdqDf9XpDPuRgW/f6wfvg2OA99yJ4wxl4yQB38PU8F7z1s3QnYRUaGsAhFpXlxLZtrxvjfeyB0eCd3eiGGoIO3ooKErPmQLJap5Kp0NEADimbGnYX2gbCWzpyJHj/8ODoHOTZB7ge75IzgwveRMLtrVZTi1dVTWL2HLyBwWDaotQkNIBDKOz7tNm2fdgNfo833cZZc/zgPSu4P/Grqt3CiQiuVlPxpAEcIjaVgp4u95EK3ywH275vdKhhTPAuhyVnBxe8NbU6tqsiSQM4JGx3F3R3hDd4N6yFTb8LT/Cm6+/WNQQ7xqzUDGgAh4DtaIOe7qCbsR/b3uqGGjY9AMP+DIxZc/DOuRBOOSeY4E1v81On9RlU9GkAB8ha66aXhWxur21vxd6/Fn7/u9HgbZjterynnB3M/Nlk0tXfrQ3HNj9KFYIGcEDcLIdWt2VRSNiONjfU8PuN4Qhezxu5sKbLhFU50gAOQNjKR9qONr/Hu3F0sUfDbDfUcOo5pQ/eyko3zFBTo9v8qLKmAVxC1lo3w6GrMxS1HCYN3lPOwasqYfAmPKiudb1dXSKsYkIDuERsfz90hmM5se1s94ca7h9tT/0sv8d7bmmDt6oaav2dJhKJ0r2vUiGgAVxkdmjQLSeeYKugkralsx17/53w6P0w5K8Mq2/AO2d5aYM3mfQXTNTqTAYVaxrARWKHhtxwQ29P4MMNtrOd7ntvxd5/d5bgPQevqkTlGKtr3LxdLf+oFKABXHB2cNAtqAhLj3fjXfDIBvrSwVvXgHfOBXDaeaUJXs9zK9XqGnSlmlLjaAD7Uls2YdfeAi27oGk+3vIVJBYtyfn5NjXshhp6gp/Ta7s6/KGGDTDogtdrmAVnvhlOO7c0U7o8z43t1s/SYQalJqABjB++q68d3YyxvRW7+lpSV1ydUwjb3h5XLD1dijEgtqvD7/GuHwle6urxzrqAxoveTltPb/EbkfCgtgHq63UKmVJT0AAG1/NNJt0YJfj/9rnjkwSwTQ27lWwBDzeMBu8GGPTLV/rByxvPw6uucb3eYgZwIgH1DW4Ld53NoFRONIDBDTvUzxp7rKraHc/Czefthu7OCXu9qaefhI13QmsLNDbB2ReSOG5hQZttuzqwv7sbHl4/Gry19XhnvRlOX1qaoYaKCrdEuK5elwgrNU0awABN86G9dbQHDG6JcNP8/R5q+/vccMMk83lTTz8Ja25y4VRb7x6/5iZSl15ekBC23Z3YjXfDw+uCDd76WVqbQakZ0AAGvOUr3Bgwfa7nO9APQ0N4y1eMPMYODbkg7c9huGHjnS6g0rMM0q+58U6YQQDb7i7s7+5yPd50DYnaOrwz/eCtqc37tXPmj5N7tXXFfy+lypwGMJBYtITUFVdnnQVhUym3J1tPV+7zeVtbXM83U2WVO54HF7x+jzeo4K2scnOHS/FeSsWEBrAvsWjJmAtu1lpsepx3ukVzGptcbzlznu3ggDs+DVmDt6bWBe8Z55cmDKuqXI9Xq5EpVXAawOPY/n7o64H+3vx3pzj7QjcGPNDveo6DAy7Ez74wtzb0+MH70Lrggrem1vV4tTCOUkWjAYxfr6G31wVvAUpEJo5bSOrSy6c9C8L2dGMfuBsevG9s8J6xDM5YVvxx15FtfmbhJfVbQ6lii+1PmU0Nj4buYH5blk821Sxx3MKcL7iNBO9D60Yv8pUyeBOev81Pg65aU6qEYhfArkhOpwvfGRTJKcRUM9vbjf3dPfDQfaPBW13jQvfMN5UoeHXVmlJBiV0A099XmHoNM5hqZnu7sQ/cCw/emyV4l+GNn0FRaImEKwdZ16Cr1pQKUPwCuFDymGpme3uwD9wTbPDqcmGlQiPwADbGbAM6gWFgSEROCbZFOZrGVDPb24N90O/x9vn1GNLBe8YyvLriB29i9gFQqbtOKBUmgQew73wRyW+VQlBymGpm+3rhgXtc+GYG7+lL8c58c/GDN6NOQ2LWbLz+geK+n1JqWsISwJEz2VQz29cLD97nZjakg7eq2s3hPfNNeHUNxW2c1mlQKhI8G/B2OcaYF4BWwALXisiqLI9ZCawEEJElAwP59eSSySQDbftItbfNoMUTS/X20Lfut/Tdezu2t9sdrK6h9ryLqFl2CYmGWZO/wEx4Hl5tHYm6+qyr1pLJJEMh2BA0CHE+d4j3+Yfl3KuqqrL2hMIQwM0issMYcxBwF/BhEdkwyVPsjh078nqvpqYm9mzf5sZuC2jCHm96qKG+iD3eigo3o6G2btKpZE1NTbS0RGuUp1DifO4Q7/MPy7k3NzdnDeDAhyBEZIf/725jzK+A04DJAjg0bF8vPHSfm9nQ609tq6p2RdDPuqC4wVtV7WrwanEcpSIr0AA2xtQDCRHp9G9fCHwxyDblwvb3ueD93T2QHmqorHI93rPejJdR3L2ghdnT+6zVNehSYaXKQNA/xfOBXxlj0m1ZLSJ3BNukibngXecK5WQG7xuX4p09NnihgIXZE97orhO6Yk2pshFoAIvI88BJQbYhFxMH73l4Z1+wX/COmGlh9pHg1RVrSpWjoHvAoWb7++Dh9W4Xip508FbCaX7wNsye/AXyLczuee7CWn2D9niVKmMawFnMOHjTpluYXcd4lYoV/SnPYAf6XfBuvMttQQQueE89F++cC3MP3rRcC7OPFMfRMV6l4kQDGD94H1mPvT8jeJOVcOo5LnhnzcnrdacszK7FcZSKtVgHsAveDdiNd7qNN6EgwZspa2F2DV6lFDENYDswAI9uwN5/p9t0EwoevFnprAalVIZYBbDt78Pe9xvs3bdmBG/SD97lGrxKqZKKVQC3fuGfsFsfd58kk3CK3+OdfUBx3lC3/FFKTSJWAVx7wVsZfOYpOOUs1+PV4FVKBShWAVxz7gV0zp0/6c6/M6rdoNPJlFLTEKsA9iqSeAfMnbAcZd61GwKc1ZDasgm79hZo2QVN8/GWryCxaElJ26CUyk+sAnhK2Wo3dHaAXE+qtjbLPN5gL66ltmzCrr7WjWfXz4L2Vuzqa0ldcbWGsFIREPsAHjPk0NkBmePCvb1utoS1MLdptEd82eUkFr8x8FoNdu0tLnzTO2BU1wB97rgGsFKhF+s5USNDDp3tbsjB86B9nwtegK4OSA27AN61A9rb3FLih9bhzZoT/Dhvy66xdSbAfd6yK5j2KKWmJdYBPGbIwfNGe79dbS50B/vd5wnPjfOmhl2PeMdLwbU5U9N8V2ci00C/O66UCr14B3BriyuSk1ZTC3PmuvDt7Xah7HlQkXQBXFEBWBgOfpM/AG/5Chgagv4+1+b+PhgacseVUqEX7wBubHIVyjJVVMBhR8M7/gq8hAu2oUE39JBKucdUVpa+rVkkFi3Bu+JqmNPoeuZzGvH0ApxSkRHvi3BZy0WmYOEb4Nc3up4v1gVvutebTEKxliznIbFoiV5wUyqiYt0DThy3EC693AVqbzccMA/vyg/BM0+6oG2cu/+TrIXODlJbNgEwfNtNDH/kPQxf/Xb37203lfgslFJRFcse8H6r3c57C4nTzsXzhxaGb/yBm1ebHv9N+cMUngfzDoJEBXbtLQxvewbW3Awe7nEDfbDmZoaBissuD+z8lFLRELsATj21eexqt65OuO0m7OwD8NJ/yjfNh/ZWN682lXLDE9a6kK2td7dbdsGLz4+GL/6/w0Nw169hGgGsq9mUiqf4DUHcu8afelbjagDX1UNlpQtA35jZBcmkm36GhTn+NLX0VK/+Xhg/FzhR4Y7naGQ1W3vr2NVs/hCHUqp8xS+A9+52PdukP7UM9lu8MGZ2QWW1e9ysOVBTN3aqV3WtH84ZUsPueI7GrGbzvJG2Zf5CUEqVp9gNQXDgwdDR5nq/aVkWL2TOLphoiGD4gre5MeDhIdfzTQ2DBS54W+7tadnler6ZdDWbUrEQuwD2LnqH+5OfPhd0A/1TLl6YaKpXxWWXMwxuzLe/1/V8L3jb9C7AZY43p+lqNqViIXYBnFi0hNQVV4/2aGtq3Z/8N/6A4do6d4Gtrzfni2EVl10+rQtu43nLV0z7F4JSqjzELoDH6OmGfXvcsEFlpbsNbnhi7x7s039kuKYODj+6aDMT9vuFEJNZEDrzQynwrLVBt2G67I4dO/J6YsP2Z2j/yXfhle3+K+V47o3zoKIy0st8m5qaaGlpCboZwLg6xpm9/iJ9fcN07kGI8/mH5dybm5u9bMdjMwsitWUTXdd9E3a+7II3l/D1/K9ZT4/OTCggnfmhlBObAHY/9JWuqA5ZfxlleRIuIIYGdWZCIWkdY6WAGAUwLbsyZhpM0ftN93yxbg5wslJnJhSS1jFWCohTADfNd4soJisl6SVc4KbzOb1Qo65OZyYUkNYxVsqJTQC7H/pBaJjlgnbMnR4ccgTehz+L9w+fhdeeAA1z3Lze+llwUHOkL8CFjdYxVsqJzTS0xKIlNMyeTfsvfuLGgQcHXfGcQw7ffwqUBkHRaR1jpWIUwAA1S86g64hjg26GUkoBMRqCUEqpsAm8B2yMuQj4DlAB/FBEvhZwk5RSqiQC7QEbYyqA7wFvAV4PvMcY8/og26SUUqUS9BDEacCzIvK8iAwANwHTqOWolFLRFfQQxCHASxmfvwy8cfyDjDErgZUAIkJTU1Neb5ZMJvN+btTpucfz3CHe5x/2cw86gLOtCd5vmZqIrAJWpe/Pt7hGWApzBEHPPZ7nDvE+/7Cce3Nzc9bjQQ9BvAwclvH5oUB+pc6UUipigu4BPwoca4w5CngFuBy4ItgmKaVUaQTaAxaRIeAfgLXAVndIngyyTUopVSqRLMgedAOUUioP+13zCnoMOB9evh/GmE0zeX6UP/Tcg2+Hnn/sz30/UQxgpZQqCxrASikVkLgF8KqpH1K29NzjK87nH+pzj+JFOKWUKgtx6wErpVRoaAArpVRAgl4JVxLlWnPYGPMj4FJgt4ic4B+bC9wMHAlsA4yItBpjPNzX4GKgB3i/iDzmP+cq4F/8l/03EbmhlOcxXcaYw4CfAgcDKWCViHwnDucOYIypATYA1bif4V+KyOf8FaU3AXOBx4ArRWTAGFON+3otAfYC7xaRbf5rfQb4ADAMfERE1pb6fPLhl7L9PfCKiFwa1XMv+x5wmdcc/glw0bhjnwbuEZFjgXv8z8Gd/7H+x0rgBzAS2J/DVaE7DficMaax6C2fmSHg4yJyPHA68Pf+/2kczh2gH1gmIicBi4GLjDGnA/8OfNs//1ZcuOD/2yoixwDf9h+H/zW7HFiI+z76vv/zEgX/iFs9mxbJcy/7AKaMaw6LyAZg37jDbwPSvbgbgLdnHP+piFgReQg4wBizAFgO3CUi+0SkFbiL/UM9VERkZ7oHKyKduB/EQ4jBuQP459Hlf1rpf1hgGfBL//j4809/XX4JvMn/q+BtwE0i0i8iLwDP4n5eQs0YcyhwCfBD/3OPiJ57HAI4W83hQwJqSynMF5Gd4IIKOMg/PtHXIdJfH2PMkcDJwMPE6NyNMRXGmM3AbtwvjueANr++Cow9l5Hz9O9vB+YR3fP/D+CTuOEncOcSyXOPQwBnWwIYx7l3E30dIvv1McY0AP8DfFREOiZ5aNmdu4gMi8hiXAnX04DjszwsfS5lc/7GmPQ1j00Zhyc7j1CfexwCOG41h3f5f17j/7vbPz7R1yGSXx9jTCUufG8UkVv8w7E490wi0gasw42FH2CMSV9YzzyXkfP075+DG7qK4vmfBbzVGLMNN5y4DNcjjuS5xyGAR2oOG2OqcAPvtwbcpmK6FbjKv30V8OuM4+8zxnj+BZt2/8/0tcCFxphG/wLUhf6x0PLH8K4HtorItzLuKvtzBzDGHGiMOcC/XQu8GTcOfh/wTv9h488//XV5J3CviFj/+OXGmGp/FsGxwCOlOYv8iMhnRORQETkS97N8r4j8JRE997IP4HKuOWyM+TnwIPBaY8zLxpgPAF8DLjDGPANc4H8OcDvwPO5iw3XAhwBEZB/wJdwvqkeBL/rHwuws4EpgmTFms/9xMfE4d4AFwH3GmCdw7b5LRNYAnwI+Zox5FjfOeb3/+OuBef7xj+HPDvF/DgR4CrgD+HsRGS7pmRROJM9dlyIrpVRAyr4HrJRSYaUBrJRSAdEAVkqpgGgAK6VUQDSAlVIqIBrASikVEA1gFRhjzE+MMf9W4vf8rV+CUqnAxaIesMqfv+Tzb0Tk7kI+Nigi8pag21AsfmGiF4DKjMI0KsS0B6wiJWO9v1KRp9/MakLGmJ8BhwO3GWOGgS8CfwK+iivdtxn4OxHZmu2xIvJ1Y8wvgHOAWuBx//E5LwU3xiwF/hv4LvBPuNKLV/pVsf4Nt/vFU8DfisgTxphPA6eIyDszXuM7gCciHzHGrAP+W0TStWT/Gvg/uN01HgFWish2Y8wXgLki8mG/8E8b8D0R+aRff6EVWODXEZ6o7WcDX8dtBNAJfFZEfmKMmeOfz1twO3RcB3xFRFLGmM8Dx4jIe/3XOJKMXq3f/vtxRWhOxC1Fv0JEWnC7ZAC0GWPALcfeg1uOuxgYxBWsf3euX39VXNoDVhMSkSuBF4HLRKQB+F/g58BHgQNxNRZuM8ZUjX+siHzdf5nf4gqdHITbKubGPJpyMG6rmSOAlcaYNwA/Aq7Grfu/FrjV337m58DFxpjZMLIjigFWj39RY8zbgWuAFf753O8/H2A9sNS/fSrwKnCe//kZwJ+nCN/Dcef+Xf+1F+N+YeEfmwMc7b/m+4C/yvWLAVzhP/4goAr4hH/8XP/fA/z/gwdxtS7uBBpxFb++O433UUWmPWA1He8GfiMidwEYY76B2xrmTFxJxP2IyI/St/3eXasxZo6ItE/jfVPA50Sk33+dDwLXisjD/v03GGOuAU4XkfXGmMdwOyL8FNdT7PF3whjvauCrIrLVf92vANcYY47A9SyPNcbMwwXb9cCH/BrE5+ECejJ/CdwtIulA3wvs9X8hvBs42d/No9MY801ccaHrs7/Ufn4sIk/7bRbgrZM8dhD3i6tZRF4GNub4HqoENIDVdDQD29Of+H8yv8QEOwn4YfNl4F24XmB6B4Mm3M4EudojIn0Znx8BXGWM+XDGsSq/feB6u+/BBfAVZOn9ZrzOd/wATPOAQ/xhiN/jwvZc/zwW4yqxncfUPcnDcLtUjNfkt3V7xrHtTG83hlczbvcADZM89pO4XvAjxphW4JuZvxRVsDSA1VQyy+XtABalP/Hr8h4GvJLlseDC7224erXbcH92t5J9N4Jc2wBuK5kvi8iXJ3j8L4Bv+nuH/QVuyCCb9OtMNCyyHteDPhlX9nE9bh+50xgdb53IS2TfY6yF0V7pU/6xwxn9GnYDdRmPP3iK98m0X2lDEXkV+CCMjEnfbYzZICLPTuN1VZFoAKup7MKNVYKrn/ppY8ybcAH0j7gdeh/I8liAWf79e3Gh8pUCtek64FfGmLtxF87qcOO1G0SkU0T2+Berfgy8kB5iyOK/gC8ZYzaLyJP+xbELReQX/v3rcRs5Pupvcb4OdwHyBRHZM0Ubb8QNZxjgFtwvn8NEZLM/bPBlY8z7cGPbHwO+4T9vM/Apfwy5HfjMNL4ue3B/ZRwNpIco3gU86A8/tOJCOqo1f8uOXoRTU/kq8C/GmDbgMuC9uD+/W/zPL/N3mx7zWGPMJ3BDANtxvbungGzjsNMmIr/H9er+ExcqzwLvH/ew1bie90TDD4jIr3DblN9kjOkA/oibmZD2AG72Rrq3+xTQx9S9X0TkReBi4OO4LXA2Ayf5d38Y19N9Hjcmuxp3URF/fP1m4AlgE7BmqvfKeM8e3FDJ7/z/g9NxFxAfNsZ04XaB+Ed/F2AVAlqQXSmlAqI9YKWUCoiOAavA+VPIrsly1/1hXjpsjPlL3Bzk8baLyMJSt0dFjw5BKKVUQHQIQimlAqIBrJRSAdEAVkqpgGgAK6VUQP4/dhDAQqugbl0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('total_review_counts','Copies sold in million', df_withsell)\n",
    "plt.savefig('trc.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('avg_score','Copies sold in million', df_withsell)\n",
    "plt.savefig('as.png',bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "* The most popular game genre: Virtual Life, Open-World\n",
    "* Developer that makes the most popular games: Nintendo. However, their games is not considered the most successful. It will be very   useful to look at Nintendo games strategy.\n",
    "* Nintendo should make more games which can take advantage of online service such as arcade, shooter games to make more people pay for the online service.\n",
    "* Games that are transferred from other platform perform bad than games that are only on switch. Reason may be that those transfer games are not originally designed for playing on switch.\n",
    "* We can consider using popularity to predict the games selling, but with caution. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Future Work\n",
    "\n",
    "* Some games have high user and meta score may because of insufficient rating and reviews, how can we overcome this issue?\n",
    "* What is the distribution of the release date? Does it have a relationship with games' popularity or success?\n",
    "* For some specific games, is there any difference between their critic reviews and user reviews?\n",
    "* Scrap all user review and critic review and do sentiment analysis to see how people actually think of a specific game."
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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