Xbox Game Pass.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Xbox Game Pass\n",
    "\n",
    "My intent is to provide a better understanding of what is included in the Xbox Game Pass (XGP) subscription. I plan to cull stats on the service's content, to provide insight into what is offered and what value a subscriber can expect."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compiling the list of games\n",
    "Scraping the entire list of games through BeautifulSoup and Python proved difficult given how the Xbox Game Pass website was structured. Instead I opted to just save the webpage as two seperate HTML text documents and then parse relevant information from those local files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\tools\\anaconda3\\lib\\site-packages (1.0.5)\n",
      "Requirement already satisfied: pytz>=2017.2 in c:\\tools\\anaconda3\\lib\\site-packages (from pandas) (2020.1)\n",
      "Requirement already satisfied: numpy>=1.13.3 in c:\\tools\\anaconda3\\lib\\site-packages (from pandas) (1.18.5)\n",
      "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\tools\\anaconda3\\lib\\site-packages (from pandas) (2.8.1)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\parke\\appdata\\roaming\\python\\python38\\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)\n"
     ]
    }
   ],
   "source": [
    "# create dataframe\n",
    "!pip install pandas\n",
    "import pandas as pd\n",
    "\n",
    "columns = ['GameTitle', 'AvailableOn']\n",
    "df_games_list = pd.DataFrame(columns = columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: bs4 in c:\\tools\\anaconda3\\lib\\site-packages (0.0.1)\n",
      "Requirement already satisfied: beautifulsoup4 in c:\\tools\\anaconda3\\lib\\site-packages (from bs4) (4.9.1)\n",
      "Requirement already satisfied: soupsieve>1.2 in c:\\tools\\anaconda3\\lib\\site-packages (from beautifulsoup4->bs4) (2.0.1)\n"
     ]
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    {
     "data": {
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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>ProductName</th>\n",
       "      <th>Platform</th>\n",
       "      <th>ListPrice</th>\n",
       "      <th>MSProduct</th>\n",
       "      <th>Multiplayer</th>\n",
       "      <th>Rating</th>\n",
       "      <th>RatingSystem</th>\n",
       "      <th>ReleaseDate</th>\n",
       "      <th>MSStoreLink</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>49.99</td>\n",
       "      <td>false</td>\n",
       "      <td>false</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>2019-05-14</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/a-plag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Plague Tale: Innocence - Windows 10</td>\n",
       "      <td>PC</td>\n",
       "      <td>44.99</td>\n",
       "      <td>false</td>\n",
       "      <td>false</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/a-plag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Absolver</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>29.99</td>\n",
       "      <td>false</td>\n",
       "      <td>true</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>2019-01-07</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/absolv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACE COMBAT™ 7: SKIES UNKNOWN</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>59.99</td>\n",
       "      <td>false</td>\n",
       "      <td>true</td>\n",
       "      <td>Teen</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>2019-01-18</td>\n",
       "      <td>https://www.xbox.com/en-us/games/ace-combat-7-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afterparty</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>19.99</td>\n",
       "      <td>false</td>\n",
       "      <td>false</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>2019-10-29</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/afterp...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             ProductName  Platform ListPrice MSProduct  \\\n",
       "0               A Plague Tale: Innocence  Xbox One     49.99     false   \n",
       "1  A Plague Tale: Innocence - Windows 10        PC     44.99     false   \n",
       "2                               Absolver  Xbox One     29.99     false   \n",
       "3           ACE COMBAT™ 7: SKIES UNKNOWN  Xbox One     59.99     false   \n",
       "4                             Afterparty  Xbox One     19.99     false   \n",
       "\n",
       "  Multiplayer      Rating RatingSystem ReleaseDate  \\\n",
       "0       false  Mature 17+         ESRB  2019-05-14   \n",
       "1       false  Mature 17+         ESRB  2020-01-23   \n",
       "2        true    Everyone         ESRB  2019-01-07   \n",
       "3        true        Teen         ESRB  2019-01-18   \n",
       "4       false  Mature 17+         ESRB  2019-10-29   \n",
       "\n",
       "                                         MSStoreLink  \n",
       "0  https://www.microsoft.com/en-us/store/p/a-plag...  \n",
       "1  https://www.microsoft.com/en-us/store/p/a-plag...  \n",
       "2  https://www.microsoft.com/en-us/store/p/absolv...  \n",
       "3  https://www.xbox.com/en-us/games/ace-combat-7-...  \n",
       "4  https://www.microsoft.com/en-us/store/p/afterp...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in html and parse info\n",
    "import requests\n",
    "!pip install bs4\n",
    "from bs4 import BeautifulSoup\n",
    "\n",
    "columns = ['ProductName', 'Platform', 'ListPrice', 'MSProduct', 'Multiplayer', 'Rating', 'RatingSystem', 'ReleaseDate', 'MSStoreLink']\n",
    "df_game_list = pd.DataFrame(columns = columns)\n",
    "for i in [1, 2]:\n",
    "    file_name = 'Xbox Game Pass {}.txt'.format(i)\n",
    "    soup = BeautifulSoup(open(file_name, 'rb'), 'html.parser')\n",
    "    games = soup.find_all(lambda tag: tag.name == 'section' and tag.get('class') == ['m-product-placement-item', 'f-size-medium', 'context-game', 'gameDiv'])\n",
    "    for game in games:\n",
    "        list_price = game.get('data-listprice')\n",
    "        ms_product = game.get('data-msproduct')\n",
    "        multiplayer = game.get('data-multiplayer')\n",
    "        rating = game.get('data-rating')\n",
    "        rating_system = game.get('data-ratingsystem')\n",
    "        release_date = game.get('data-releasedate')[:game.get('data-releasedate').find('T')]\n",
    "        ms_store_link = game.find(lambda tag: tag.name == 'a' and tag.get('class') == ['gameDivLink']).get('href')\n",
    "        product_name = game.find(lambda tag: tag.name == 'h3' and tag.get('class') == ['c-heading']).text\n",
    "        if len(game.find_all(lambda tag: tag.name == 'div' and tag.get('class') == ['c-tag'])) > 1:\n",
    "            platform = 'Both'\n",
    "        else:\n",
    "            platform = game.find(lambda tag: tag.name == 'div' and tag.get('class') == ['c-tag']).text\n",
    "        row = df_game_list.shape[0]\n",
    "        df_game_list.loc[row, :] = [product_name, platform, list_price, ms_product, multiplayer, rating, rating_system, release_date, ms_store_link]\n",
    "df_game_list.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# saving dataframe as csv\n",
    "df_game_list.to_csv('df_game_list.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Closer inspection of the csv file reveals some formatting issues with the parsed data, namely inconsistent title schemas and character conversion errors. Corrections were applied manually and then imported as 'df_game_list_clean'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>ProductName</th>\n",
       "      <th>Platform</th>\n",
       "      <th>ListPrice</th>\n",
       "      <th>MSProduct</th>\n",
       "      <th>Multiplayer</th>\n",
       "      <th>Rating</th>\n",
       "      <th>RatingSystem</th>\n",
       "      <th>ReleaseDate</th>\n",
       "      <th>MSStoreLink</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>49.99</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>5/14/2019</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/a-plag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>PC</td>\n",
       "      <td>44.99</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>1/23/2020</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/a-plag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Absolver</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>29.99</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>1/7/2019</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/absolv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACE COMBAT 7: SKIES UNKNOWN</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>59.99</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>Teen</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>1/18/2019</td>\n",
       "      <td>https://www.microsoft.com/en-us/p/ace-combat-7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afterparty</td>\n",
       "      <td>Xbox One</td>\n",
       "      <td>19.99</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>ESRB</td>\n",
       "      <td>10/29/2019</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/afterp...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   ProductName  Platform  ListPrice  MSProduct  Multiplayer  \\\n",
       "0     A Plague Tale: Innocence  Xbox One      49.99      False        False   \n",
       "1     A Plague Tale: Innocence        PC      44.99      False        False   \n",
       "2                     Absolver  Xbox One      29.99      False         True   \n",
       "3  ACE COMBAT 7: SKIES UNKNOWN  Xbox One      59.99      False         True   \n",
       "4                   Afterparty  Xbox One      19.99      False        False   \n",
       "\n",
       "       Rating RatingSystem ReleaseDate  \\\n",
       "0  Mature 17+         ESRB   5/14/2019   \n",
       "1  Mature 17+         ESRB   1/23/2020   \n",
       "2    Everyone         ESRB    1/7/2019   \n",
       "3        Teen         ESRB   1/18/2019   \n",
       "4  Mature 17+         ESRB  10/29/2019   \n",
       "\n",
       "                                         MSStoreLink  \n",
       "0  https://www.microsoft.com/en-us/store/p/a-plag...  \n",
       "1  https://www.microsoft.com/en-us/store/p/a-plag...  \n",
       "2  https://www.microsoft.com/en-us/store/p/absolv...  \n",
       "3  https://www.microsoft.com/en-us/p/ace-combat-7...  \n",
       "4  https://www.microsoft.com/en-us/store/p/afterp...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing 'df_games_list_clean'\n",
    "df_game_list_clean = pd.read_csv('df_game_list_clean.csv').drop(columns = 'Unnamed: 0')\n",
    "df_game_list_clean.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Platform availability breakdown\n",
    "\n",
    "All games will be separated into one of three groups: 'Xbox One', 'PC', or 'Both'. These represent games that are available on Xbox only, PC only, or both platforms, respectively. The Xbox Game Pass subscription is avilable in three flavors, PC games only for 10USD a month, Xbox games only for 10USD a month, or the entire catalog for 15USD a month. It should be interesting to see how the entire list of games splits based on these offerings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BREAKDOWN NUMBERS (% of total, count)\n",
      "  Single platform: 48%, 142\n",
      "    Xbox only: 31%, 92\n",
      "    PC only: 17%, 50\n",
      "  Dual platform: 52%, 154\n",
      "Total: 100%, 296\n"
     ]
    }
   ],
   "source": [
    "# platform availability breakdown\n",
    "duplicate_count = int(df_game_list_clean[df_game_list_clean.duplicated('ProductName', keep = False)].shape[0]/2)\n",
    "xbox_count = df_game_list_clean[(df_game_list_clean.duplicated('ProductName', keep = False) == False) & (df_game_list_clean.Platform == 'Xbox One')].shape[0]\n",
    "pc_count = df_game_list_clean[(df_game_list_clean.duplicated('ProductName', keep = False) == False) & (df_game_list_clean.Platform == 'PC')].shape[0]\n",
    "both_count = df_game_list_clean[(df_game_list_clean.duplicated('ProductName', keep = False) == False) & (df_game_list_clean.Platform == 'Both')].shape[0]\n",
    "total_count = duplicate_count + xbox_count + pc_count + both_count\n",
    "print(r'BREAKDOWN NUMBERS (% of total, count)')\n",
    "print('  Single platform: {}, {}'.format('{:.0%}'.format((xbox_count + pc_count)/total_count), xbox_count + pc_count))\n",
    "print('    Xbox only: {}, {}'.format('{:.0%}'.format(xbox_count/total_count), xbox_count))\n",
    "print('    PC only: {}, {}'.format('{:.0%}'.format(pc_count/total_count), pc_count))\n",
    "print('  Dual platform: {}, {}'.format('{:.0%}'.format((both_count + duplicate_count)/total_count), both_count + duplicate_count))\n",
    "print('Total: {}, {}'.format('100%', total_count))"
   ]
  },
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   "cell_type": "code",
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   "metadata": {
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      ],
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
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     },
     "metadata": {
      "needs_background": "light"
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     "output_type": "display_data"
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   ],
   "source": [
    "# basic visualization\n",
    "!pip install numpy\n",
    "import numpy as np\n",
    "!pip install matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "labels = ['Single', 'Dual', 'Total']\n",
    "xbox = [xbox_count, 0, 0]\n",
    "pc = [pc_count, 0, 0]\n",
    "both = [0, both_count + duplicate_count, 0]\n",
    "total = [0, 0, total_count]\n",
    "width = .4\n",
    "fig, ax = plt.subplots(figsize = (20, 10))\n",
    "ax.bar(labels, xbox, width, bottom = pc, label = 'Xbox only')\n",
    "ax.bar(labels, pc, width, label = 'PC only')\n",
    "ax.bar(labels, both, width, label = 'Both')\n",
    "ax.bar(labels, total, width, label = 'Total')\n",
    "ax.set_ylabel('Count')\n",
    "ax.set_xlabel('Platform Type')\n",
    "ax.set_title('Breakdown of Xbox Game Pass Library by Platform Availability, 08/27/2020')\n",
    "ax.legend()\n",
    "for p in ax.patches:\n",
    "    width, height = p.get_width(), p.get_height()\n",
    "    if height == 0:\n",
    "        continue\n",
    "    x, y = p.get_xy() \n",
    "    ax.text(x+width/2, \n",
    "        y+height/2, \n",
    "        '{}'.format(height), \n",
    "        horizontalalignment='center', \n",
    "        verticalalignment='center')\n",
    "plt.savefig('Xbox Game Pass Platform Breakdown.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Owning or having access to both a Xbox One and PC allows for unrestricted access to the full Xbox Game Pass library. In the unfortunate situation of singular platform access, Xbox-only individuals would have access to 14% (42) more games than their PC-only counterparts. These individuals would be able to play 83% (246) and 69% (204) of the game catalog, respectively."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Microsoft Store price analysis\n",
    "\n",
    "All the prices in 'df_game_list_clean' were pulled from Microsoft Store listings. This section compiles some key price stats for all games included, and also attempts to compare the PC only catalog's total value with what it would cost to outright purchase all games."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MS unique price count: 26\n",
      "MS mean price: 26.36\n",
      "MS top 4 prices, counts: (19.99, 108), (29.99, 51), (39.99, 46), (14.99, 43)\n",
      "MS total value: 10120.76\n",
      "MS total value, PC: 5321.06\n",
      "MS total value, Xbox: 6524.04\n"
     ]
    }
   ],
   "source": [
    "# Microsoft Store list price stats\n",
    "list_prices = df_game_list_clean.ListPrice.value_counts()\n",
    "print(f'MS unique price count: {len(list_prices)}')\n",
    "print(f'MS mean price: {round(df_game_list_clean.ListPrice.mean(), 2)}')\n",
    "print('MS top 4 prices, counts: {}, {}, {}, {}'.format(*list_prices.items()))\n",
    "microsoft_all_sum = df_game_list_clean.ListPrice.sum()\n",
    "print(f'MS total value: {microsoft_all_sum}')\n",
    "microsoft_pc_sum = round(df_game_list_clean.ListPrice[df_game_list_clean.Platform.isin(['PC', 'Both'])].sum(), 2)\n",
    "print('MS total value, PC: {}'.format(microsoft_pc_sum))\n",
    "microsoft_xbox_sum = round(df_game_list_clean.ListPrice[df_game_list_clean.Platform.isin(['Xbox One', 'Both'])].sum(), 2)\n",
    "print('MS total value, Xbox: {}'.format(microsoft_xbox_sum))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The MS total values for Xbox and PC do not add up to overall MS total value. The single platform total values represent the cumulative value of games accessible on solely that platform, so there will be some overlap between the Xbox-only and PC-only tags (some games are offered on both platforms simultaneously).\n",
    "\n",
    "A cursory inspection of this pricing information would appear to highlight a rather high bulk value to cost ratio for Xbox Game Pass. Rough calculations would put it at 532 (PC only) and 652 (Xbox only) months of sustained subscriptions to match the cost of purchasing all included games today. Combined, it would take just over 675 months of subscriptions to equal the cost of purchasing the entire library of games."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
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     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot prices as histogram\n",
    "from matplotlib import colors\n",
    "\n",
    "fig, ax = plt.subplots(figsize = (20, 10))\n",
    "N, bins, patches = ax.hist(df_game_list_clean.ListPrice, bins = 30)\n",
    "fracs = N / N.max()\n",
    "norm = colors.Normalize(fracs.min(), fracs.max())\n",
    "for thisfrac, thispatch in zip(fracs, patches):\n",
    "    color = plt.cm.viridis(norm(thisfrac))\n",
    "    thispatch.set_facecolor(color)\n",
    "ax.set_ylabel('Prices in USD')\n",
    "ax.set_xlabel('Count')\n",
    "ax.set_title('Xbox Game Pass Price Histogram')\n",
    "plt.savefig('Xbox Game Pass Price Plot.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Far and away, the most common Microsoft Store game value in Xbox Game Pass is right around \\$20. Outside of that, the game prices look to group around the \\$5 and \\$10 multiples. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price comparison to outside game stores\n",
    "\n",
    "I mentioned a cursory inspection because digging any deeper into Microsoft Store's own pricing reveals a rather large disparity between itself and other competing game marketplaces. Using Microsoft Store prices to gauge the total value of the Xbox Game Pass catalog is likely overinflating its true value. A more fair metric would be to use the lowest historical prices for games across all other stores, as this is far more likely to represent the decision a potential consumer would be facing: a subscription service for a slowly revolving assortment of games, or individual purchases of the same games whenever they are heavily discounted. Using historical lowest ever prices for game prices outside of the Microsoft Store represents the absolute lowest dollar sum that a customer could have paid to have the same game selection (a best case scenario for a non-Xbox Game Pass customer). The above mentioned historical PC game prices will be pulled from isthereanydeal.com.\n",
    "\n",
    "A couple things to note, first that this section and onwards will only cover PC games as it vastly simplifies analysis. Next, local running of this notebook requires installation of the following things: Chrome / Chromium, Chromedriver, and Selenium. These are used to aid in web-scraping, specifically queries within a webpage and locating elements more easily than allowed through BeautifulSoup. Finally, you will need to substitute in your own 'chromium_driver_path' in the below cell, your path will likely not match mine. Onwards!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: selenium in c:\\tools\\anaconda3\\lib\\site-packages (3.141.0)\n",
      "Requirement already satisfied: urllib3 in c:\\tools\\anaconda3\\lib\\site-packages (from selenium) (1.25.9)\n",
      "Title: A Plague Tale: Innocence, Historical Low: $14.99\n"
     ]
    }
   ],
   "source": [
    "# web scraping historical low prices from isthereanydeal.com, with the help of selenium\n",
    "!pip install selenium\n",
    "from selenium import webdriver\n",
    "from selenium.webdriver.chrome.options import Options\n",
    "\n",
    "chromium_driver_path = '/ProgramData/chocolatey/lib/chromedriver/tools/chromedriver'\n",
    "driver = webdriver.Chrome(executable_path = chromium_driver_path)\n",
    "driver.get('https://isthereanydeal.com/')\n",
    "search_box = driver.find_element_by_xpath('//input[@id = \"searchbox\"]')\n",
    "search_button = driver.find_element_by_xpath('//input[@type = \"submit\"]')\n",
    "game_title = df_game_list_clean.ProductName[0]\n",
    "search_box.send_keys(game_title)\n",
    "search_button.click()\n",
    "item_title = driver.find_element_by_xpath('//a[@class = \"card__title\"]').text\n",
    "historical_low = driver.find_element_by_xpath('//div[@class = \"numtag__primary\"]').text\n",
    "print(f'Title: {item_title}, Historical Low: {historical_low}')\n",
    "driver.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the above cell, the first game title from df_game_list_clean was queried on isthereanydeal.com. The printed result is the title of isthereanydeal.com's first query result along with the historical low value, in this case 'A Plague Tale: Innocence' and '$14.99'. It should be noted that since this is a simple query, it may return first results that do not match the desired game title. Manual clean-up of these conflicts will be required."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function that replicates the above cell, but in a headless fashion\n",
    "def is_there_any_deal(game_title):\n",
    "    options = Options()\n",
    "    options.headless = True\n",
    "    options.add_argument('--window-size=1920,1080')\n",
    "    driver = webdriver.Chrome(options = options, executable_path = chromium_driver_path)\n",
    "    driver.get('https://isthereanydeal.com/')\n",
    "    search_box = driver.find_element_by_xpath('//input[@id = \"searchbox\"]')\n",
    "    search_button = driver.find_element_by_xpath('//input[@type = \"submit\"]')\n",
    "    search_box.send_keys(game_title)\n",
    "    search_button.click()\n",
    "    first_result = driver.find_element_by_xpath('//a[@class = \"card__title\"]').text\n",
    "    historical_low = driver.find_element_by_xpath('//div[@class = \"numtag__primary\"]').text\n",
    "    driver.close()\n",
    "    return (first_result, historical_low)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Title: A Plague Tale: Innocence, Historical Low: $14.99\n"
     ]
    }
   ],
   "source": [
    "# a quick test to confirm it works\n",
    "output = is_there_any_deal(game_title)\n",
    "print(f'Title: {output[0]}, Historical Low: {output[1]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The below two cells were converted to raw so as to not run when executing this notebook (they take a while to complete). They will need to be converted back to code cells to run properly."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# inserting all 'pc' and 'both' games from 'df_game_title_clean' into this function, storing in new dataframe\n",
    "df_itad_prices = pd.DataFrame(data = {'Query': df_game_list_clean.ProductName[df_game_list_clean.Platform.isin(['PC', 'Both'])].reset_index(drop = True).values})\n",
    "df_itad_prices['Result'] = ''\n",
    "df_itad_prices['Price'] = ''\n",
    "for row in range(df_itad_prices.shape[0]):\n",
    "    try:\n",
    "        output = is_there_any_deal(df_itad_prices.Query[row])\n",
    "        df_itad_prices.loc[row, 'Result':'Price'] = [output[0], output[1].replace('$', '')]\n",
    "    except:\n",
    "        continue\n",
    "df_itad_prices.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "tags": []
   },
   "source": [
    "# saving dataframe to csv for later use\n",
    "df_itad_prices.to_csv('df_itad_prices.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Query</th>\n",
       "      <th>Result</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>14.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Age of Empires Definitive Edition</td>\n",
       "      <td>Age of Empires Definitive Edition</td>\n",
       "      <td>4.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Age of Empires II: Definitive Edition</td>\n",
       "      <td>Age of Empires II: Definitive Edition</td>\n",
       "      <td>13.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Age of Empires III: Definitive Edition</td>\n",
       "      <td>Age of Empires III: Definitive Edition</td>\n",
       "      <td>19.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Age of Wonders: Planetfall</td>\n",
       "      <td>Age of Wonders: Planetfall</td>\n",
       "      <td>8.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Query  \\\n",
       "0                A Plague Tale: Innocence   \n",
       "1       Age of Empires Definitive Edition   \n",
       "2   Age of Empires II: Definitive Edition   \n",
       "3  Age of Empires III: Definitive Edition   \n",
       "4              Age of Wonders: Planetfall   \n",
       "\n",
       "                                   Result  Price  \n",
       "0                A Plague Tale: Innocence  14.99  \n",
       "1       Age of Empires Definitive Edition   4.99  \n",
       "2   Age of Empires II: Definitive Edition  13.79  \n",
       "3  Age of Empires III: Definitive Edition  19.99  \n",
       "4              Age of Wonders: Planetfall   8.46  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing df_itad_prices from a previous run, with corrections made for price query issues\n",
    "df_itad_prices = pd.read_csv('df_itad_prices.csv').drop(columns = 'Unnamed: 0')\n",
    "df_itad_prices.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Value of games at historical lows: 2034.33\n",
      "Value of games in Microsoft Store: 5321.06\n",
      "\n",
      "Difference: 3286.73\n"
     ]
    }
   ],
   "source": [
    "# total value of xbox game pass with historical low game prices\n",
    "outside_value = df_itad_prices.Price.sum()\n",
    "microsoft_value = round(df_game_list_clean.ListPrice[df_game_list_clean.Platform.isin(['PC', 'Both'])].sum(), 2)\n",
    "print(f'Value of games at historical lows: {outside_value}\\nValue of games in Microsoft Store: {microsoft_value}\\n\\nDifference: {round(microsoft_value - outside_value, 2)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks to be that the same lot of games is north of 2.6 times as expensive if purchased only inside the Microsoft Store. Intuitively this makes sense, on account that the outside game market prices are all historical lows. Summed together, they represent the absolute lowest dollar sum the consumer can pay today to purchase all games from Xbox Game Pass.\n",
    "\n",
    "Realistically, though, it is very unlikely that any one user would choose to purchase all these games at once. Moreover, the above being historical prices means that their current price may not necessarily be lower. The above summed historical lows figure just represents the absolute lowest a consumer could have paid to accrue all the games in Xbox Game Pass.\n",
    "\n",
    "It isn't exactly fair to compare the subscription fee of the Xbox Game Pass catalog to the total purchase price of those same games. Being a subscription service, the consumer does not own any actual game, and therefore the consumer's ability to play a given game can be restricted at a future date once that game is dropped from the service. Still, if game prices and current catalog were all held as constant, it would take at minimum 203 months of sustained subscription before the cummulative subscription cost of Xbox Game Pass equaled the absolute lowest total price of the same games. Assuming the consumer only played each game once, they would have almost 17 years to finish the entire catalog. Once can dream!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Developer, publisher, and game genre trends\n",
    "\n",
    "This final section of the notebook will take a look at trends between games, particularly who developed / published them and their unique characteristics (genre, features, rating, et cetera). All of this game data will come directly from Microsoft Store game webpages, links that were scraped way back in the first section of this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# new dataframe for game details\n",
    "titles = df_game_list_clean.ProductName[df_game_list_clean.Platform.isin(['PC', 'Both'])].values\n",
    "links = df_game_list_clean.MSStoreLink[df_game_list_clean.Platform.isin(['PC', 'Both'])].values\n",
    "df_game_details = pd.DataFrame(data = {'Title': titles, 'Link': links})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Title: A Plague Tale: Innocence\n",
      "Categories: Action & adventure, Role playing\n"
     ]
    }
   ],
   "source": [
    "# scraping additional game information from links collected in 'Collecting the list of games' section\n",
    "chromium_driver_path = '/ProgramData/chocolatey/lib/chromedriver/tools/chromedriver'\n",
    "driver = webdriver.Chrome(executable_path = chromium_driver_path)\n",
    "driver.get(df_game_details.Link[0])\n",
    "category_elements = driver.find_elements_by_xpath('//div[@id=\"category\"]/div[1]/a')\n",
    "print(f'Title: {df_game_details.Title[0]}')\n",
    "print('Categories:',', '.join([str(item.get_attribute('aria-label'))[22:] for item in category_elements]))\n",
    "driver.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to repeat the above cell\n",
    "def pull_details(row):\n",
    "    driver.get(df_game_details.Link[row])\n",
    "    category_elements = driver.find_elements_by_xpath('//div[@id=\"category\"]/div[1]/a')\n",
    "    categories = ', '.join([str(item.get_attribute('aria-label'))[22:] for item in category_elements])\n",
    "    try:\n",
    "        publishers = driver.find_element_by_xpath('//h4[text()=\"Published by\"]//following-sibling::span').text.strip()\n",
    "    except:\n",
    "        publishers = ''\n",
    "    try:\n",
    "        developers = driver.find_element_by_xpath('//h4[text()=\"Published by\"]//following-sibling::span').text.strip()\n",
    "    except:\n",
    "        developers = ''\n",
    "    return categories, publishers, developers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next two cells are a bit time consuming to run, so they have been converted to raw. If you wish to manually execute them when running the entire notebook, they will need to be switched back to code cells."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# loop through df_game_details\n",
    "columns = ['Categories', 'Publishers', 'Developers']\n",
    "df_game_details = pd.concat([df_game_details, pd.DataFrame(columns = columns)])\n",
    "options = Options()\n",
    "options.headless = True\n",
    "options.add_argument('--window-size=1920,1080') \n",
    "driver = webdriver.Chrome(options = options, executable_path = chromium_driver_path)\n",
    "for row in range(df_game_details.shape[0]):\n",
    "    categories, publishers, developers = pull_details(row)\n",
    "    df_game_details.loc[row, 'Categories':'Developers'] = [categories, publishers, developers]\n",
    "driver.close()\n",
    "df_game_details.head()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# save df_game_details to csv for manual inspection\n",
    "df_game_details.to_csv('df_game_details.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Link</th>\n",
       "      <th>Categories</th>\n",
       "      <th>Publishers</th>\n",
       "      <th>Developers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A Plague Tale: Innocence</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/a-plag...</td>\n",
       "      <td>Action &amp; adventure, Role playing</td>\n",
       "      <td>Focus Home Interactive</td>\n",
       "      <td>Focus Home Interactive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Age of Empires Definitive Edition</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/age-of...</td>\n",
       "      <td>Strategy</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Age of Empires II: Definitive Edition</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/age-of...</td>\n",
       "      <td>Strategy</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Age of Empires III: Definitive Edition</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/age-of...</td>\n",
       "      <td>Strategy</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "      <td>Xbox Game Studios</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Age of Wonders: Planetfall</td>\n",
       "      <td>https://www.microsoft.com/en-us/store/p/age-of...</td>\n",
       "      <td>Simulation, Strategy</td>\n",
       "      <td>Paradox Interactive</td>\n",
       "      <td>Triumph Studios</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Title  \\\n",
       "0                A Plague Tale: Innocence   \n",
       "1       Age of Empires Definitive Edition   \n",
       "2   Age of Empires II: Definitive Edition   \n",
       "3  Age of Empires III: Definitive Edition   \n",
       "4              Age of Wonders: Planetfall   \n",
       "\n",
       "                                                Link  \\\n",
       "0  https://www.microsoft.com/en-us/store/p/a-plag...   \n",
       "1  https://www.microsoft.com/en-us/store/p/age-of...   \n",
       "2  https://www.microsoft.com/en-us/store/p/age-of...   \n",
       "3  https://www.microsoft.com/en-us/store/p/age-of...   \n",
       "4  https://www.microsoft.com/en-us/store/p/age-of...   \n",
       "\n",
       "                         Categories              Publishers  \\\n",
       "0  Action & adventure, Role playing  Focus Home Interactive   \n",
       "1                          Strategy       Xbox Game Studios   \n",
       "2                          Strategy       Xbox Game Studios   \n",
       "3                          Strategy       Xbox Game Studios   \n",
       "4              Simulation, Strategy     Paradox Interactive   \n",
       "\n",
       "               Developers  \n",
       "0  Focus Home Interactive  \n",
       "1       Xbox Game Studios  \n",
       "2       Xbox Game Studios  \n",
       "3       Xbox Game Studios  \n",
       "4         Triumph Studios  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import cleaned df_game_details_clean\n",
    "df_game_details_clean = pd.read_csv('df_game_details_clean.csv').drop(columns = 'Unnamed: 0')\n",
    "df_game_details_clean.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To do:\n",
    "\n",
    "1. trends on most popular developers / publishers, along with ratings, features, genre\n",
    "2. game churn: rate of games leaving and entering store, value of content entering and exiting (make determination on value of sustained subscription: enough games added to counter continued cost of subsciption)"
   ]
  }
 ],
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