chess.com_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chess.com Games Played Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Analysis and Data Visualization of your chess games on Chess.com\n",
    "\n",
    "NOTE: To use, first run chess.com_exporter.ipynb to download and your games played data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_user = \"markwk\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date, datetime as dt, timedelta as td\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Data Check and Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "games = pd.read_csv(\"data/\" + my_user + \"_games_played_detailed.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['end_time', 'fen', 'pgn', 'rated', 'rules', 'time_class',\n",
       "       'time_control', 'url', 'black_id', 'black_rating', 'black_result',\n",
       "       'black_username', 'white_id', 'white_rating', 'white_result',\n",
       "       'white_username', 'my_side', 'my_result', 'termination', 'total_moves',\n",
       "       'start_time', 'pgn_end_time', 'moves_times_white', 'moves_times_black'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "74 total games played\n"
     ]
    }
   ],
   "source": [
    "print('{:,} total games played'.format(len(games)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# date additions\n",
    "games['end_time'] = pd.to_datetime(games['end_time'])\n",
    "games['date'] = games['end_time'].apply(lambda x: x.strftime('%Y-%m-%d')) # note: not very efficient\n",
    "games['year'] = games['end_time'].dt.year\n",
    "games['month'] = games['end_time'].dt.month\n",
    "games['mnth_yr'] = games['end_time'].apply(lambda x: x.strftime('%Y-%m')) # note: not very efficient\n",
    "games['day'] = games['end_time'].dt.day\n",
    "games['dow'] = games['end_time'].dt.weekday\n",
    "games['hour'] = games['end_time'].dt.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>end_time</th>\n",
       "      <th>fen</th>\n",
       "      <th>pgn</th>\n",
       "      <th>rated</th>\n",
       "      <th>rules</th>\n",
       "      <th>time_class</th>\n",
       "      <th>time_control</th>\n",
       "      <th>url</th>\n",
       "      <th>black_id</th>\n",
       "      <th>black_rating</th>\n",
       "      <th>...</th>\n",
       "      <th>pgn_end_time</th>\n",
       "      <th>moves_times_white</th>\n",
       "      <th>moves_times_black</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>mnth_yr</th>\n",
       "      <th>day</th>\n",
       "      <th>dow</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2018-09-14 12:22:37</td>\n",
       "      <td>1k1q4/p7/1pQ4p/8/2B5/N1P5/PP3PPN/4R1K1 b - -</td>\n",
       "      <td>[Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...</td>\n",
       "      <td>True</td>\n",
       "      <td>chess</td>\n",
       "      <td>blitz</td>\n",
       "      <td>600</td>\n",
       "      <td>https://www.chess.com/live/game/3074572090</td>\n",
       "      <td>https://api.chess.com/pub/player/markwk</td>\n",
       "      <td>982</td>\n",
       "      <td>...</td>\n",
       "      <td>2018-09-14 12:22:37</td>\n",
       "      <td>0:09:59.9, 0:09:50.8, 0:09:49.3, 0:09:43.8, 0:...</td>\n",
       "      <td>0:09:59, 0:09:53.8, 0:09:40, 0:09:04.8, 0:08:4...</td>\n",
       "      <td>2018-09-14</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-09</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2018-09-14 13:06:03</td>\n",
       "      <td>R7/8/5k2/p7/1p6/1P6/P4K2/8 b - -</td>\n",
       "      <td>[Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...</td>\n",
       "      <td>True</td>\n",
       "      <td>chess</td>\n",
       "      <td>blitz</td>\n",
       "      <td>600</td>\n",
       "      <td>https://www.chess.com/live/game/3074644572</td>\n",
       "      <td>https://api.chess.com/pub/player/markwk</td>\n",
       "      <td>973</td>\n",
       "      <td>...</td>\n",
       "      <td>2018-09-14 13:06:03</td>\n",
       "      <td>0:09:59.9, 0:09:58, 0:09:56.7, 0:09:55.1, 0:09...</td>\n",
       "      <td>0:09:56.1, 0:09:48.5, 0:09:42, 0:09:36.2, 0:09...</td>\n",
       "      <td>2018-09-14</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-09</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2018-09-15 12:44:53</td>\n",
       "      <td>r4rk1/ppb1n1p1/2p1p2p/3pn3/1P3PP1/P1NBB1qP/2P2...</td>\n",
       "      <td>[Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...</td>\n",
       "      <td>True</td>\n",
       "      <td>chess</td>\n",
       "      <td>blitz</td>\n",
       "      <td>600</td>\n",
       "      <td>https://www.chess.com/live/game/3076863036</td>\n",
       "      <td>https://api.chess.com/pub/player/aguchi13</td>\n",
       "      <td>925</td>\n",
       "      <td>...</td>\n",
       "      <td>2018-09-15 12:44:53</td>\n",
       "      <td>0:09:59.9, 0:09:58.2, 0:09:55.1, 0:09:41.8, 0:...</td>\n",
       "      <td>0:09:57.7, 0:09:55.8, 0:09:53.4, 0:09:50.9, 0:...</td>\n",
       "      <td>2018-09-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-09</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2018-09-15 13:10:55</td>\n",
       "      <td>8/1ppb4/8/1p4p1/1kR5/6P1/Q4P1P/6K1 b - -</td>\n",
       "      <td>[Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...</td>\n",
       "      <td>True</td>\n",
       "      <td>chess</td>\n",
       "      <td>blitz</td>\n",
       "      <td>600</td>\n",
       "      <td>https://www.chess.com/live/game/3076901697</td>\n",
       "      <td>https://api.chess.com/pub/player/markwk</td>\n",
       "      <td>973</td>\n",
       "      <td>...</td>\n",
       "      <td>2018-09-15 13:10:55</td>\n",
       "      <td>0:09:59.9, 0:09:54.3, 0:09:28.2, 0:09:24, 0:09...</td>\n",
       "      <td>0:09:58.2, 0:09:49.9, 0:09:14, 0:09:10.3, 0:09...</td>\n",
       "      <td>2018-09-15</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-09</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2018-09-16 03:04:11</td>\n",
       "      <td>8/pb4k1/4p3/1pp4p/7q/3P4/PP6/3K1R2 w - -</td>\n",
       "      <td>[Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...</td>\n",
       "      <td>True</td>\n",
       "      <td>chess</td>\n",
       "      <td>blitz</td>\n",
       "      <td>600</td>\n",
       "      <td>https://www.chess.com/live/game/3078329073</td>\n",
       "      <td>https://api.chess.com/pub/player/markwk</td>\n",
       "      <td>980</td>\n",
       "      <td>...</td>\n",
       "      <td>2018-09-16 03:04:11</td>\n",
       "      <td>0:09:58.1, 0:09:56.5, 0:09:52.6, 0:09:46.9, 0:...</td>\n",
       "      <td>0:09:58, 0:09:56.1, 0:09:39.7, 0:09:28, 0:09:2...</td>\n",
       "      <td>2018-09-16</td>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-09</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              end_time                                                fen  \\\n",
       "69 2018-09-14 12:22:37       1k1q4/p7/1pQ4p/8/2B5/N1P5/PP3PPN/4R1K1 b - -   \n",
       "70 2018-09-14 13:06:03                   R7/8/5k2/p7/1p6/1P6/P4K2/8 b - -   \n",
       "71 2018-09-15 12:44:53  r4rk1/ppb1n1p1/2p1p2p/3pn3/1P3PP1/P1NBB1qP/2P2...   \n",
       "72 2018-09-15 13:10:55           8/1ppb4/8/1p4p1/1kR5/6P1/Q4P1P/6K1 b - -   \n",
       "73 2018-09-16 03:04:11           8/pb4k1/4p3/1pp4p/7q/3P4/PP6/3K1R2 w - -   \n",
       "\n",
       "                                                  pgn  rated  rules  \\\n",
       "69  [Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...   True  chess   \n",
       "70  [Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...   True  chess   \n",
       "71  [Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...   True  chess   \n",
       "72  [Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...   True  chess   \n",
       "73  [Event \"Live Chess\"]\\n[Site \"Chess.com\"]\\n[Dat...   True  chess   \n",
       "\n",
       "   time_class  time_control                                         url  \\\n",
       "69      blitz           600  https://www.chess.com/live/game/3074572090   \n",
       "70      blitz           600  https://www.chess.com/live/game/3074644572   \n",
       "71      blitz           600  https://www.chess.com/live/game/3076863036   \n",
       "72      blitz           600  https://www.chess.com/live/game/3076901697   \n",
       "73      blitz           600  https://www.chess.com/live/game/3078329073   \n",
       "\n",
       "                                     black_id  black_rating  ...   \\\n",
       "69    https://api.chess.com/pub/player/markwk           982  ...    \n",
       "70    https://api.chess.com/pub/player/markwk           973  ...    \n",
       "71  https://api.chess.com/pub/player/aguchi13           925  ...    \n",
       "72    https://api.chess.com/pub/player/markwk           973  ...    \n",
       "73    https://api.chess.com/pub/player/markwk           980  ...    \n",
       "\n",
       "           pgn_end_time                                  moves_times_white  \\\n",
       "69  2018-09-14 12:22:37  0:09:59.9, 0:09:50.8, 0:09:49.3, 0:09:43.8, 0:...   \n",
       "70  2018-09-14 13:06:03  0:09:59.9, 0:09:58, 0:09:56.7, 0:09:55.1, 0:09...   \n",
       "71  2018-09-15 12:44:53  0:09:59.9, 0:09:58.2, 0:09:55.1, 0:09:41.8, 0:...   \n",
       "72  2018-09-15 13:10:55  0:09:59.9, 0:09:54.3, 0:09:28.2, 0:09:24, 0:09...   \n",
       "73  2018-09-16 03:04:11  0:09:58.1, 0:09:56.5, 0:09:52.6, 0:09:46.9, 0:...   \n",
       "\n",
       "                                    moves_times_black        date  year month  \\\n",
       "69  0:09:59, 0:09:53.8, 0:09:40, 0:09:04.8, 0:08:4...  2018-09-14  2018     9   \n",
       "70  0:09:56.1, 0:09:48.5, 0:09:42, 0:09:36.2, 0:09...  2018-09-14  2018     9   \n",
       "71  0:09:57.7, 0:09:55.8, 0:09:53.4, 0:09:50.9, 0:...  2018-09-15  2018     9   \n",
       "72  0:09:58.2, 0:09:49.9, 0:09:14, 0:09:10.3, 0:09...  2018-09-15  2018     9   \n",
       "73  0:09:58, 0:09:56.1, 0:09:39.7, 0:09:28, 0:09:2...  2018-09-16  2018     9   \n",
       "\n",
       "    mnth_yr day dow  hour  \n",
       "69  2018-09  14   4    12  \n",
       "70  2018-09  14   4    13  \n",
       "71  2018-09  15   5    12  \n",
       "72  2018-09  15   5    13  \n",
       "73  2018-09  16   6     3  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monthly Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-09    74\n",
       "Name: mnth_yr, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "month_counts = games['mnth_yr'].value_counts().sort_index()\n",
    "month_counts.columns = ['Count']\n",
    "month_counts.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# not every month necessarily has a game, so fill in missing months with zero counts\n",
    "#date_range = pd.date_range(start=min(highlights_10['timestamp']), end=max(highlights_10['timestamp']))\n",
    "#months_range = date_range.map(lambda x: str(x.date())[:-3])\n",
    "#index = np.unique(months_range)\n",
    "# month_counts = month_counts.reindex(index, fill_value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total months\n",
    "len(month_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GaEmSJKklQ7QkSZLUkiFakiRJamkYX7YiSdrCkhwO/C69+/CvA1YDH6yqS4Za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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10abc4400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# a bit of a hackish solution, could use improvement\n",
    "dataset = month_counts.tail(20)\n",
    "chart_title = 'Number of Games per month'\n",
    "\n",
    "max = np.max(np.array(month_counts)) + 5\n",
    "n_groups = len(dataset)\n",
    "index = np.arange(n_groups)\n",
    "\n",
    "ax = dataset.plot(kind='line', figsize=[12, 5], linewidth=4, alpha=1, marker='o', color='#6684c1', \n",
    "                      markeredgecolor='#6684c1', markerfacecolor='w', markersize=8, markeredgewidth=2)\n",
    "\n",
    "# ax.set_xlim((year_counts.index[0], year_counts.index[-1]))\n",
    "\n",
    "ax.yaxis.grid(True)\n",
    "ax.xaxis.grid(True)\n",
    "ax.set_ylim(0, max)\n",
    "ax.set_xticks(index)\n",
    "ax.set_ylabel('Number of Games')\n",
    "# ax.set_xlabel('')\n",
    "plt.xticks(index, dataset.index, rotation=90)\n",
    "ax.set_title(chart_title)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Games Per Day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_counts = games['date'].value_counts().sort_index()\n",
    "daily_counts.columns = ['Count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# daily_counts.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FqZOPVdR04pmXqqddEx0Vhq2FqSgtTse6VUkI88MyiR3F6YYk+szFTnzhvrWICPdMFxAi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\niMgQaRAtIiIiIjJEGkSLiIiIiAzR/wc7T2bjsGEZIAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10abc4128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# a bit of a hackish solution, could use improvement\n",
    "dataset = daily_counts.tail(30)\n",
    "chart_title = 'Number of Games per day'\n",
    "\n",
    "max = np.max(np.array(dataset)) + 5\n",
    "n_groups = len(dataset)\n",
    "index = np.arange(n_groups)\n",
    "\n",
    "ax = dataset.plot(kind='line', figsize=[12, 5], linewidth=4, alpha=1, marker='o', color='#6684c1', \n",
    "                      markeredgecolor='#6684c1', markerfacecolor='w', markersize=8, markeredgewidth=2)\n",
    "\n",
    "# ax.set_xlim((year_counts.index[0], year_counts.index[-1]))\n",
    "\n",
    "ax.yaxis.grid(True)\n",
    "ax.xaxis.grid(True)\n",
    "# ax.set_ylim(0, 1000)\n",
    "ax.set_xticks(index)\n",
    "ax.set_ylabel('Number of Games')\n",
    "# ax.set_xlabel('')\n",
    "plt.xticks(index, dataset.index, rotation=90)\n",
    "ax.set_title(chart_title)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_counts.to_csv(\"data/\" + my_user + \"_daily_games_count.csv\")"
   ]
  }
 ],
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