Steam Analyzer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Steam Library Analyzer\n",
    "## GitHub repository: [https://github.com/saulTejeda117/Steam-Data-Analyzer](https://github.com/saulTejeda117/Steam-Data-Analyzer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Steam Library Analyzer es un projecto de ciencia de datos enfocado principalmente en el analisis predictivo de los habitos de juego de los usuarios de [_`Steam`_](https://store.steampowered.com). Su objetivo principal es determinar el tiempo estimado para completar todos los juegos de la biblioteca de un jugador. Para ello se ha hecho uso de fuentes de información tales como la WEB dedicada a videojuegos [_`How Long To Beat`_](https://howlongtobeat.com) y la [_`Steam API`_](https://steamcommunity.com/dev) que hacen posible acceder a información necesaria como:\n",
    "\n",
    "- **Completion Rate:** Es la métrica que indica la proporción de juegos que un jugador ha completado en comparación con el total de juegos en su biblioteca.\n",
    "  \n",
    "- **Total games:** Hace referencia a la cantidad total de juegos que un usuario tiene actualmente en su biblioteca de juegos de Steam.\n",
    "  \n",
    "- **Perfect Games:** Se refiere aquellosjuegos cuyas metas y logros han sido alcanzados al 100%, según las estadísticas proporcionadas por Steam."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"SteamAnalyzerCover2.jpg\">\n",
    "\n",
    "\n",
    "</img>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "import time\n",
    "import pandas as pd\n",
    "from IPython import display\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import re\n",
    "from scipy import stats\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "\n",
    "\n",
    "from tqdm import tqdm\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtain User Steam Profile Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El proceso de análisis se inicia mediante la obtención de la información esencial de la cuenta de usuario que se pretende evaluar. En este sentido, se procede a extraer los datos pertinentes del archivo _JSON_ denominado  _`\"steam_credentials.json\"`_, dicho archivo alberga información crucial, incluyendo:\n",
    "\n",
    "- **Steam API key:** son identificadores únicos e irrepetibles proporcionados por Steam a desarrolladores y aplicaciones que desean acceder a la Steam API.\n",
    "  \n",
    "- **Steam ID:** se refiere a un identificador único utilizado para identificar de manera única a los usuarios y sus perfiles en la plataforma Steam."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the steam credentials JSON file \n",
    "with open('steam_credentials.json') as json_file:\n",
    "    credentials = json.load(json_file)\n",
    "\n",
    "api_key = credentials.get('api_key')\n",
    "#steam_id = credentials.get('steam_id')\n",
    "\n",
    "steam_id = \"76561198142358795\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Posteriormente se realiza una consulta a la [_`Steam API`_](https://steamcommunity.com/dev) para obtener los datos de la cuenta de usuario al que pertecenen las credenciales ingresadas. Se comprueba la  respuesta de la petición.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Username:  Abadon\n",
      "Avatar:  https://avatars.steamstatic.com/2488f0c70ca5b66019da25ec51a122e62d8c7d45_full.jpg\n",
      "Link:  https://steamcommunity.com/id/Abadon/\n"
     ]
    }
   ],
   "source": [
    "# Obtener la URL de la información del jugador utilizando la API de Steam\n",
    "player_info_url = f'http://api.steampowered.com/ISteamUser/GetPlayerSummaries/v0002/?key={api_key}&steamids={steam_id}'\n",
    "response = requests.get(player_info_url)\n",
    "\n",
    "if (response != None):\n",
    "    data = response.json()\n",
    "    # print(data, \"\\n\\n\\n\")\n",
    "    print(\"Username: \", data['response']['players'][0]['personaname'])\n",
    "    print(\"Avatar: \", data['response']['players'][0]['avatarfull'])\n",
    "    print(\"Link: \", data['response']['players'][0]['profileurl'])\n",
    "\n",
    "else:\n",
    "    print(\"Something  went wrong!\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtain User Steam Library Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Después de obtener los datos del usuario de la cuenta de Steam procedemos a obtener los datos de juego de su biblioteca, de los datos principales que nos interesan obtener en esta parte del proceso destacan principalmente\n",
    "  \n",
    "- **steam_id:** se refiere a un identificador único utilizado para identificar de manera única a los usuarios y sus perfiles en la plataforma Steam.\n",
    "\n",
    "- **appid:** son identificadores únicos e irrepetibles proporcionados por Steam a desarrolladores y aplicaciones que desean acceder a la Steam API.\n",
    "  \n",
    "- **playtime_forever:** se refiere a un identificador único utilizado para identificar de manera única a los usuarios y sus perfiles en la plataforma Steam.\n",
    "\n",
    "- **total_playtime:** hace referencia al tiempo total de juego acumulado por un usuario en todos los juegos de su biblioteca de Steam. Este dato puede ser esencial para comprender la dedicación y el nivel de participación de un jugador en su colección de juegos.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obtain AppID and Playtime Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>total_achievements</th>\n",
       "      <th>beat_time</th>\n",
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       "      <td>2478970</td>\n",
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       "<p>9497 rows × 12 columns</p>\n",
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      ],
      "text/plain": [
       "        appid                                              name  \\\n",
       "0         300                             Day of Defeat: Source   \n",
       "1          20                             Team Fortress Classic   \n",
       "2          30                                     Day of Defeat   \n",
       "3          40                                Deathmatch Classic   \n",
       "4          50                         Half-Life: Opposing Force   \n",
       "...       ...                                               ...   \n",
       "9492  2478970  Tomb Raider I-III Remastered Starring Lara Croft   \n",
       "9493  1086940                                   Baldur's Gate 3   \n",
       "9494   344740                                          CRYPTARK   \n",
       "9495   577940                                   Killer Instinct   \n",
       "9496  1176710                     Space Crew: Legendary Edition   \n",
       "\n",
       "      playtime_forever                              img_icon_url  \\\n",
       "0                 1917  062754bb5853b0534283ae27dc5d58200692b22d   \n",
       "1                    1  38ea7ebe3c1abbbbf4eabdbef174c41a972102b9   \n",
       "2                    0  aadc0ce51ff6ba2042d633f8ec033b0de62091d0   \n",
       "3                    0  c525f76c8bc7353db4fd74b128c4ae2028426c2a   \n",
       "4                    0  04e81206c10e12416908c72c5f22aad411b3aeef   \n",
       "...                ...                                       ...   \n",
       "9492                 0  7bd910d66157ffcadd96bcd9333dd45f318e5c58   \n",
       "9493                 0  d866cae7ea1e471fdbc206287111f1b642373bd9   \n",
       "9494                 0  c56bc2236cbcee87cab5c3d99e97be9f24d8cf50   \n",
       "9495                 0  10c39134ff17a0af1bba131a6036362606785167   \n",
       "9496                 0  c1c0a0c7c7dae3525bc6a4bb07bc0bd69bc62ab0   \n",
       "\n",
       "     has_community_visible_stats content_descriptorids has_leaderboards  \\\n",
       "0                           True                   NaN              NaN   \n",
       "1                            NaN                [2, 5]              NaN   \n",
       "2                            NaN                   NaN              NaN   \n",
       "3                            NaN                   NaN              NaN   \n",
       "4                            NaN                   NaN              NaN   \n",
       "...                          ...                   ...              ...   \n",
       "9492                        True                [2, 5]              NaN   \n",
       "9493                        True             [1, 2, 5]              NaN   \n",
       "9494                        True                   NaN             True   \n",
       "9495                        True                   NaN              NaN   \n",
       "9496                        True                   NaN              NaN   \n",
       "\n",
       "      playtime_2weeks achievement_percentage achievement_completed  \\\n",
       "0                 NaN                   None                  None   \n",
       "1                 NaN                   None                  None   \n",
       "2                 NaN                   None                  None   \n",
       "3                 NaN                   None                  None   \n",
       "4                 NaN                   None                  None   \n",
       "...               ...                    ...                   ...   \n",
       "9492              NaN                   None                  None   \n",
       "9493              NaN                   None                  None   \n",
       "9494              NaN                   None                  None   \n",
       "9495              NaN                   None                  None   \n",
       "9496              NaN                   None                  None   \n",
       "\n",
       "     total_achievements beat_time  \n",
       "0                  None      None  \n",
       "1                  None      None  \n",
       "2                  None      None  \n",
       "3                  None      None  \n",
       "4                  None      None  \n",
       "...                 ...       ...  \n",
       "9492               None      None  \n",
       "9493               None      None  \n",
       "9494               None      None  \n",
       "9495               None      None  \n",
       "9496               None      None  \n",
       "\n",
       "[9497 rows x 12 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get data from my Steam library\n",
    "games_endpoint = f\"https://api.steampowered.com/IPlayerService/GetOwnedGames/v1/?key={api_key}&include_appinfo=1&steamid={steam_id}\"\n",
    "\n",
    "response_games = requests.get(games_endpoint)\n",
    "data_games = response_games.json()\n",
    "df_games = pd.json_normalize(data_games['response']['games'])\n",
    "\n",
    "df_games['achievement_percentage'] = None\n",
    "df_games['achievement_completed'] = None\n",
    "df_games['total_achievements'] = None\n",
    "df_games['beat_time'] = None\n",
    "df_games"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obtain Games' names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Este paso es sumamente importante para el proceso de extracción de los datos, debido a que las fuentes de información de las cuales se extrae la información son diferentes y no es posible acceder a los datos de los juegos en [_`How Long To Beat`_](https://howlongtobeat.com) únicamente con el AppID de [_`Steam API`_](https://steamcommunity.com/dev), por lo que es necesario extraer el nombre de los juegos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total playtime:  6407347 minutes\n",
      "Favorite Game:  Sea of Thieves 396772\n"
     ]
    }
   ],
   "source": [
    "total_playtime  = df_games['playtime_forever'].sum()\n",
    "\n",
    "indice_max_playtime = df_games['playtime_forever'].idxmax()\n",
    "favorite_game_appid = df_games.loc[indice_max_playtime, 'name']\n",
    "\n",
    "print(\"Total playtime: \",total_playtime, \"minutes\")\n",
    "print(\"Favorite Game: \", df_games.loc[indice_max_playtime,'name'], df_games.loc[indice_max_playtime,'playtime_forever'] )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obtain games archivements information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "- **achievement_completion:** eEnestel contexto \"achievement_progress\" se refiere al progreso que un jugador ha alcanzado en desbloquear o completar logros dentro de un juego.\n",
    "\n",
    "- **achv_percentage** se refiere al porcentaje de logros o hitos que un jugador ha desbloqueado o completado en un juego en comparación con el total de logros disponibles\n",
    "\n",
    "- **achievement_completed:**\n",
    "\n",
    "- **total_games:**.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing Games: 100%|████████████████████████████████████████████████████████████| 9497/9497 [43:33<00:00,  3.63it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "**********PROCESO TERMINADO************\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "total_games = 0\n",
    "for game in tqdm(range(len(df_games)), desc=\"Processing Games\"):\n",
    "    appid = df_games.iloc[game]['appid']\n",
    "    url_achievements = f'http://api.steampowered.com/ISteamUserStats/GetPlayerAchievements/v0001/?key={api_key}&steamid={steam_id}&appid={appid}'\n",
    "    response = requests.get(url_achievements)\n",
    "    data_achievements = response.json()\n",
    "\n",
    "    if(data_achievements['playerstats']['success'] != False):\n",
    "\n",
    "        try:\n",
    "            total_achievements = len(data_achievements['playerstats']['achievements'])\n",
    "            num_achievements_1 = sum(1 for achievement in data_achievements['playerstats']['achievements'] if achievement['achieved'] == 1)\n",
    "            num_achievements_0 = sum(1 for achievement in data_achievements['playerstats']['achievements'] if achievement['achieved'] == 0)\n",
    "\n",
    "            achievement_percentage = (num_achievements_1*100)/total_achievements\n",
    "\n",
    "            total_games += 1\n",
    "\n",
    "            df_games.loc[game, 'total_achievements'] = total_achievements\n",
    "            df_games.loc[game, 'achievement_completed'] = num_achievements_1\n",
    "            df_games.loc[game, 'achievement_percentage'] = achievement_percentage\n",
    "            \n",
    "        except:\n",
    "            pass\n",
    "        \n",
    "print(\"\\n**********PROCESO TERMINADO************\\n\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Games with Archivements: 5483\n"
     ]
    },
    {
     "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>appid</th>\n",
       "      <th>name</th>\n",
       "      <th>playtime_forever</th>\n",
       "      <th>img_icon_url</th>\n",
       "      <th>has_community_visible_stats</th>\n",
       "      <th>content_descriptorids</th>\n",
       "      <th>has_leaderboards</th>\n",
       "      <th>playtime_2weeks</th>\n",
       "      <th>achievement_percentage</th>\n",
       "      <th>achievement_completed</th>\n",
       "      <th>total_achievements</th>\n",
       "      <th>beat_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>300</td>\n",
       "      <td>Day of Defeat: Source</td>\n",
       "      <td>1917</td>\n",
       "      <td>062754bb5853b0534283ae27dc5d58200692b22d</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>Team Fortress Classic</td>\n",
       "      <td>1</td>\n",
       "      <td>38ea7ebe3c1abbbbf4eabdbef174c41a972102b9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>Day of Defeat</td>\n",
       "      <td>0</td>\n",
       "      <td>aadc0ce51ff6ba2042d633f8ec033b0de62091d0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>Deathmatch Classic</td>\n",
       "      <td>0</td>\n",
       "      <td>c525f76c8bc7353db4fd74b128c4ae2028426c2a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>Half-Life: Opposing Force</td>\n",
       "      <td>0</td>\n",
       "      <td>04e81206c10e12416908c72c5f22aad411b3aeef</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9492</th>\n",
       "      <td>2478970</td>\n",
       "      <td>Tomb Raider I-III Remastered Starring Lara Croft</td>\n",
       "      <td>0</td>\n",
       "      <td>7bd910d66157ffcadd96bcd9333dd45f318e5c58</td>\n",
       "      <td>True</td>\n",
       "      <td>[2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>269</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9493</th>\n",
       "      <td>1086940</td>\n",
       "      <td>Baldur's Gate 3</td>\n",
       "      <td>0</td>\n",
       "      <td>d866cae7ea1e471fdbc206287111f1b642373bd9</td>\n",
       "      <td>True</td>\n",
       "      <td>[1, 2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9494</th>\n",
       "      <td>344740</td>\n",
       "      <td>CRYPTARK</td>\n",
       "      <td>0</td>\n",
       "      <td>c56bc2236cbcee87cab5c3d99e97be9f24d8cf50</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9495</th>\n",
       "      <td>577940</td>\n",
       "      <td>Killer Instinct</td>\n",
       "      <td>0</td>\n",
       "      <td>10c39134ff17a0af1bba131a6036362606785167</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>463</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9496</th>\n",
       "      <td>1176710</td>\n",
       "      <td>Space Crew: Legendary Edition</td>\n",
       "      <td>0</td>\n",
       "      <td>c1c0a0c7c7dae3525bc6a4bb07bc0bd69bc62ab0</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9497 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        appid                                              name  \\\n",
       "0         300                             Day of Defeat: Source   \n",
       "1          20                             Team Fortress Classic   \n",
       "2          30                                     Day of Defeat   \n",
       "3          40                                Deathmatch Classic   \n",
       "4          50                         Half-Life: Opposing Force   \n",
       "...       ...                                               ...   \n",
       "9492  2478970  Tomb Raider I-III Remastered Starring Lara Croft   \n",
       "9493  1086940                                   Baldur's Gate 3   \n",
       "9494   344740                                          CRYPTARK   \n",
       "9495   577940                                   Killer Instinct   \n",
       "9496  1176710                     Space Crew: Legendary Edition   \n",
       "\n",
       "      playtime_forever                              img_icon_url  \\\n",
       "0                 1917  062754bb5853b0534283ae27dc5d58200692b22d   \n",
       "1                    1  38ea7ebe3c1abbbbf4eabdbef174c41a972102b9   \n",
       "2                    0  aadc0ce51ff6ba2042d633f8ec033b0de62091d0   \n",
       "3                    0  c525f76c8bc7353db4fd74b128c4ae2028426c2a   \n",
       "4                    0  04e81206c10e12416908c72c5f22aad411b3aeef   \n",
       "...                ...                                       ...   \n",
       "9492                 0  7bd910d66157ffcadd96bcd9333dd45f318e5c58   \n",
       "9493                 0  d866cae7ea1e471fdbc206287111f1b642373bd9   \n",
       "9494                 0  c56bc2236cbcee87cab5c3d99e97be9f24d8cf50   \n",
       "9495                 0  10c39134ff17a0af1bba131a6036362606785167   \n",
       "9496                 0  c1c0a0c7c7dae3525bc6a4bb07bc0bd69bc62ab0   \n",
       "\n",
       "     has_community_visible_stats content_descriptorids has_leaderboards  \\\n",
       "0                           True                   NaN              NaN   \n",
       "1                            NaN                [2, 5]              NaN   \n",
       "2                            NaN                   NaN              NaN   \n",
       "3                            NaN                   NaN              NaN   \n",
       "4                            NaN                   NaN              NaN   \n",
       "...                          ...                   ...              ...   \n",
       "9492                        True                [2, 5]              NaN   \n",
       "9493                        True             [1, 2, 5]              NaN   \n",
       "9494                        True                   NaN             True   \n",
       "9495                        True                   NaN              NaN   \n",
       "9496                        True                   NaN              NaN   \n",
       "\n",
       "      playtime_2weeks achievement_percentage achievement_completed  \\\n",
       "0                 NaN                    0.0                     0   \n",
       "1                 NaN                   None                  None   \n",
       "2                 NaN                   None                  None   \n",
       "3                 NaN                   None                  None   \n",
       "4                 NaN                   None                  None   \n",
       "...               ...                    ...                   ...   \n",
       "9492              NaN                    0.0                     0   \n",
       "9493              NaN                    0.0                     0   \n",
       "9494              NaN                    0.0                     0   \n",
       "9495              NaN                    0.0                     0   \n",
       "9496              NaN                    0.0                     0   \n",
       "\n",
       "     total_achievements beat_time  \n",
       "0                    54      None  \n",
       "1                  None      None  \n",
       "2                  None      None  \n",
       "3                  None      None  \n",
       "4                  None      None  \n",
       "...                 ...       ...  \n",
       "9492                269      None  \n",
       "9493                 54      None  \n",
       "9494                 27      None  \n",
       "9495                463      None  \n",
       "9496                 30      None  \n",
       "\n",
       "[9497 rows x 12 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Total Games with Archivements:\", total_games)\n",
    "df_games"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get data from howlongtobeat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERROR: Feeding Frenzy 2: Shipwreck Showdown Deluxe\n",
      "ERROR: Dark Messiah of Might  Magic Single Player\n",
      "ERROR: Dark Messiah of Might  Magic Multi-Player\n",
      "ERROR: 688I HunterKiller\n",
      "ERROR: Call of Duty 2003\n",
      "ERROR: Runaway: The Dream of the Turtle\n",
      "ERROR: Space Empires IV Deluxe\n",
      "ERROR: Heretic: Shadow of the Serpent Riders\n",
      "ERROR: Total War: MEDIEVAL II - Definitive Edition\n",
      "ERROR: Call of Duty 4: Modern Warfare 2007\n",
      "ERROR: Shadowgrounds: Survivor\n",
      "ERROR: Rayman: Raving Rabbids\n",
      "ERROR: Telltale Texas HoldEm\n",
      "ERROR: Insecticide Part 1\n",
      "ERROR: FlatOut: Ultimate Carnage Collectors Edition\n",
      "ERROR: Mass Effect 2007\n",
      "ERROR: Dead Space 2008\n",
      "ERROR: Company of Heroes - Legacy Edition\n",
      "ERROR: Star Wars: Battlefront 2 Classic, 2005\n",
      "ERROR: 3D Ultra Minigolf Adventures Deluxe\n",
      "ERROR: Call of Duty: Modern Warfare 2 2009\n",
      "ERROR: Call of Duty: Modern Warfare 2 2009 - Multiplayer\n",
      "ERROR: Mystery PI: The Vegas Heist\n",
      "ERROR: Serious Sam Fusion 2017 beta\n",
      "ERROR: 9th Company - Roots of Terror\n",
      "ERROR: Fallout 3 - Game of the Year Edition\n",
      "ERROR: Sherlock Holmes: The Secret of the Silver Earring\n",
      "ERROR: Sherlock Holmes: The Awakened 2008\n",
      "ERROR: Mass Effect 2 2010\n",
      "ERROR: Mass Effect 2 2010 Edition\n",
      "ERROR: SEGA Mega Drive  Genesis Classics\n",
      "ERROR: STAR WARS Empire at War: Gold Pack\n",
      "ERROR: Arma 2: Operation Arrowhead Beta Obsolete\n",
      "ERROR: Hacker Evolution - Untold\n",
      "ERROR: Age of Wonders 2: The Wizards Throne\n",
      "ERROR: Call of Duty: Black Ops - Multiplayer\n",
      "ERROR: Oddworld: Strangers Wrath HD\n",
      "ERROR: On the Rain-Slick Precipice of Darkness, Episode Two\n",
      "ERROR: The Witcher 2: Assassins of Kings Enhanced Edition\n",
      "ERROR: Portal 2 - The Final Hours\n",
      "ERROR: Mafia II Classic\n",
      "ERROR: Medal of HonorTM Single Player\n",
      "ERROR: Medal of HonorTM Multiplayer\n",
      "ERROR: King Arthur - Fallen Champions\n",
      "ERROR: Gothic II: Gold Classic\n",
      "ERROR: Gothic 1 Classic\n",
      "ERROR: Gothic 3 Forsaken Gods Enhanced Edition\n",
      "ERROR: Dungeon Siege 2\n",
      "ERROR: Call of Duty: Modern Warfare 3 2011\n",
      "ERROR: Call of Duty: Modern Warfare 3 2011 - Multiplayer\n",
      "ERROR: Grotesque Tactics 2 - Dungeons and Donuts\n",
      "ERROR: F.E.A.R.: Extraction Point\n",
      "ERROR: F.E.A.R.: Perseus Mandate\n",
      "ERROR: Fable - The Lost Chapters\n",
      "ERROR: Luxor Mahjong\n",
      "ERROR: SONIC THE HEDGEHOG 4 Episode II\n",
      "ERROR: Crysis 2 Maximum Edition\n",
      "ERROR: Red Faction: Guerrilla Steam Edition\n",
      "ERROR: RAW - Realms of Ancient War\n",
      "ERROR: Call of Duty: Black Ops II - Multiplayer\n",
      "ERROR: Call of Duty: Black Ops II - Zombies\n",
      "ERROR: Tomb Raider: Chronicles\n",
      "ERROR: Tomb Raider VI: The Angel of Darkness\n",
      "ERROR: GTR 2 - FIA GT Racing Game\n",
      "ERROR: STCC II\n",
      "ERROR: RACE 07 - Formula RaceRoom Add-On\n",
      "ERROR: GT Power Expansion\n",
      "ERROR: The WTCC 2010 Pack\n",
      "ERROR: DOOM 1993\n",
      "ERROR: Sonic  All-Stars Racing Transformed Collection\n",
      "ERROR: HOMEFRONT Demo\n",
      "ERROR: EverQuest Free-to-Play\n",
      "ERROR: PlanetSide 2 - Test\n",
      "ERROR: Construct 2 Free\n",
      "ERROR: Shadow Warrior Classic 1997\n",
      "ERROR: Dragon Nest Europe\n",
      "ERROR: Fiesta Online NA\n",
      "ERROR: RetroGrade IGF Demo\n",
      "ERROR: Between IGF Demo\n",
      "ERROR: Age of Conan: Unchained US Version\n",
      "ERROR: iPi Mocap Studio 2\n",
      "ERROR: iPi Recorder 2\n",
      "ERROR: Ohm Studio\n",
      "ERROR: Saints Row IV Inauguration Station\n",
      "ERROR: Terrain Test\n",
      "ERROR: Spiral Knights Preview\n",
      "ERROR: Trash TV demo\n",
      "ERROR: Vanguard: Saga of Heroes F2P\n",
      "ERROR: Jagged Alliance Online - Steam Edition\n",
      "ERROR: Dogs of War Online - Beta\n",
      "ERROR: Brtal Legend\n",
      "ERROR: Final Hours of Tomb Raider\n",
      "ERROR: Organ Trail: Directors Cut\n",
      "ERROR: Jagged Alliance - Back in Action\n",
      "ERROR: Agricultural Simulator 2013 Steam Edition\n",
      "ERROR: MotoGP13\n",
      "ERROR: The Apogee Throwback Pack\n",
      "ERROR: Jack Keane 2 - The Fire Within\n",
      "ERROR: Shelter 1\n",
      "ERROR: Secrets of Rtikon\n",
      "ERROR: Brothers - A Tale of Two Sons\n",
      "ERROR: Divinity: Dragon Commander Beta\n",
      "ERROR: ENSLAVED: Odyssey to the West Premium Edition\n",
      "ERROR: Paranautical Activity: Deluxe Atonement Edition\n",
      "ERROR: Warhammer 40,000: Dawn of War - Game of the Year Edition\n",
      "ERROR: Wizardry 6: Bane of the Cosmic Forge\n",
      "ERROR: Wizardry 7: Crusaders of the Dark Savant\n",
      "ERROR: Alien Rage - Unlimited\n",
      "ERROR: KickBeat Steam Edition\n",
      "ERROR: Omikron - The Nomad Soul\n",
      "ERROR: Deadly Premonition: The Directors Cut\n",
      "ERROR: Wasteland 1 - The Original Classic\n",
      "ERROR: Marc Ecks Getting Up: Contents Under Pressure\n",
      "ERROR: Valiant Hearts: The Great War  Soldats Inconnus : Mmoires de la Grande Guerre\n",
      "ERROR: Dragons Lair 2: Time Warp\n",
      "ERROR: Desperados - Wanted Dead or Alive\n",
      "ERROR: The Walking Dead: Season Two\n",
      "ERROR: Air Conflicts - Secret Wars\n",
      "ERROR: YOU DONT KNOW JACK Vol. 1 XL\n",
      "ERROR: YOU DONT KNOW JACK Vol. 2\n",
      "ERROR: YOU DONT KNOW JACK Vol. 3\n",
      "ERROR: YOU DONT KNOW JACK Vol. 4 The Ride\n",
      "ERROR: Call of Duty: Ghosts - Multiplayer\n",
      "ERROR: Stronghold Crusader Extreme HD\n",
      "ERROR: FootLOL: Epic Soccer League\n",
      "ERROR: Anarchy Arcade\n",
      "ERROR: Batman: Arkham Origins Blackgate - Deluxe Edition\n",
      "ERROR: Realms of Arkania 1 - Blade of Destiny Classic\n",
      "ERROR: VelocityUltra\n",
      "ERROR: Dark Fall 1: The Journal\n",
      "ERROR: Dark Fall 2: Lights Out\n",
      "ERROR: Paranormal State: Poison Spring Collectors Edition\n",
      "ERROR: EVGA Precision X1\n",
      "ERROR: Realms of Arkania 3 - Shadows over Riva Classic\n",
      "ERROR: Dungeon Lords Steam Edition\n",
      "ERROR: Counter-Strike Nexon: Studio\n",
      "ERROR: Agricultural Simulator 2012: Deluxe Edition\n",
      "ERROR: Joe Devers Lone Wolf HD Remastered\n",
      "ERROR: Dracula 4 and  5 - Special Steam Edition\n",
      "ERROR: Millennium - A New Hope\n",
      "ERROR: O.R.B.\n",
      "ERROR: SuperPower 2 Steam Edition\n",
      "ERROR: Easy eSports\n",
      "ERROR: Resident Evil 4 2005\n",
      "ERROR: The Entente Gold\n",
      "ERROR: Hard Truck Apocalypse  Ex Machina\n",
      "ERROR: Sledgehammer  Gear Grinder\n",
      "ERROR: Shadows on the Vatican - Act I: Greed\n",
      "ERROR: Hard Truck: Apocalypse Rise Of Clans  Ex Machina: Meridian 113\n",
      "ERROR: Hard Truck Apocalypse: Arcade  Ex Machina: Arcade\n",
      "ERROR: Dreamscapes: The Sandman - Premium Edition\n",
      "ERROR: Construction-Simulator 2015\n",
      "ERROR: Time Ramesside A New Reckoning\n",
      "ERROR: Mirror Mysteries 2: Forgotten Kingdoms\n",
      "ERROR: Final Hours of Titanfall\n",
      "ERROR: Princess Isabella - Return of the Curse\n",
      "ERROR: Action - Gameplay Recording and Streaming\n",
      "ERROR: Pajama Sam in No Need to Hide When Its Dark Outside\n",
      "ERROR: SPY Fox in: Dry Cereal\n",
      "ERROR: SPY Fox in: Cheese Chase\n",
      "ERROR: SPY Fox in: Hold the Mustard\n",
      "ERROR: Pajama Sam: Games to Play on Any Day\n",
      "ERROR: SplitSecond\n",
      "ERROR: Millennium 2 - Take Me Higher\n",
      "ERROR: Millennium 3 - Cry Wolf\n",
      "ERROR: Millennium 4 - Beyond Sunset\n",
      "ERROR: Forgotten Myths CCG\n",
      "ERROR: Q.U.B.E: Directors Cut\n",
      "ERROR: Disney-Pixar Brave\n",
      "ERROR: Disney Pirates of the Caribbean: At Worlds End\n",
      "ERROR: 1999 - Amerzone: The Explorers Legacy\n",
      "ERROR: WatchDogs\n",
      "ERROR: Bloons TD5\n",
      "ERROR: Wildlife Park 2 - Fantasy\n",
      "ERROR: Cube Samurai: RUN\n",
      "ERROR: The Stalin Subway: Red Veil\n",
      "ERROR: Red Johnsons Chronicles - 12 - Steam Special Edition\n",
      "ERROR: Warface: Clutch\n",
      "ERROR: Wilson Chronicles - Beta\n",
      "ERROR: Microsoft Flight Simulator X: Steam Edition\n",
      "ERROR: Fall of the New Age Premium Edition\n",
      "ERROR: Cars Toon: Maters Tall Tales\n",
      "ERROR: Uncharted Waters Online: Episode Atlantis\n",
      "ERROR: Phineas and Ferb: New Inventions\n",
      "ERROR: Disney Tangled\n",
      "ERROR: Questerium: Sinister Trinity HD\n",
      "ERROR: Season Match 3 - Curse of the Witch Crow\n",
      "ERROR: The Chronicles of Narnia - Prince Caspian\n",
      "ERROR: Disneys Princess Enchanted Journey\n",
      "ERROR: The Guild II - Pirates of the European Seas\n",
      "ERROR: Sea Legends: Phantasmal Light Collectors Edition\n",
      "ERROR: Loadout Campaign Beta\n",
      "ERROR: Killing Floor - Toy Master\n",
      "ERROR: Disney Epic Mickey 2\n",
      "ERROR: MotoGP14\n",
      "ERROR: Pirates Gold Plus Classic\n",
      "ERROR: Sid Meiers Covert Action Classic\n",
      "ERROR: Sid Meiers Colonization Classic\n",
      "ERROR: The Interactive Adventures of Dog Mendona and Pizzaboy\n",
      "ERROR: planktOs\n",
      "ERROR: Luna: Shattered Hearts: Episode 1\n",
      "ERROR: Disneys Treasure Planet: Battle of Procyon\n",
      "ERROR: Raptor: Call of The Shadows - 2015 Edition\n",
      "ERROR: Ratz Instagib 2.0\n",
      "ERROR: Terra Lander Remastered\n",
      "ERROR: Rescue Team 1\n",
      "ERROR: The Ship Tutorial\n",
      "ERROR: Teddy Floppy Ear - Mountain Adventure\n",
      "ERROR: Teddy Floppy Ear - Kayaking\n",
      "ERROR: You Are Not a Banana: Better Edition\n",
      "ERROR: Hotline Miami 2: Wrong Number Digital Comic\n",
      "ERROR: TRIP Steam Edition\n",
      "ERROR: Witchs Pranks: Frogs Fortune Collectors Edition\n",
      "ERROR: Firefly Online Cortex\n",
      "ERROR: Boring Man - Online Tactical Stickman Combat\n",
      "ERROR: samuraijazz\n",
      "ERROR: RIDE: Game\n",
      "ERROR: Corrosion: Cold Winter Waiting Enhanced Edition\n",
      "ERROR: MANOS: The Hands of Fate  Directors Cut\n",
      "ERROR: Breach  Clear: Deadline Rebirth 2016\n",
      "ERROR: Ghost Encounters: Deadwood - Collectors Edition\n",
      "ERROR: Dreamscapes: Nightmares Heir - Premium Edition\n",
      "ERROR: Ankh - Anniversary Edition\n",
      "ERROR: Bunker - The Underground Game\n",
      "ERROR: Adventures of Bertram Fiddle: Episode 1: A Dreadly Business\n",
      "ERROR: GlassWire\n",
      "ERROR: MotoGP15\n",
      "ERROR: Leadwerks Game Launcher\n",
      "ERROR: Home is Where One Starts...\n",
      "ERROR: DriveDriveDrive\n",
      "ERROR: Battle Fantasia -Revised Edition-\n",
      "ERROR: No Turning Back: The Pixel Art Action-Adventure Roguelike\n",
      "ERROR: Raptor: Call of the Shadows 1994 Classic Edition\n",
      "ERROR: Lethis - Path of Progress\n",
      "ERROR: The Mean Greens - Plastic Warfare\n",
      "ERROR: STAR WARS X-Wing vs TIE Fighter: Balance of Power Campaigns\n",
      "ERROR: Portal of Evil: Stolen Runes Collectors Edition\n",
      "ERROR: Face It - A game to fight inner demons\n",
      "ERROR: Warlocks Citadel\n",
      "ERROR: Star Trek: Starfleet Command Gold Edition\n",
      "ERROR: Unheard Screams - King Leopold IIs Rule Over The Congo\n",
      "ERROR: iaidokainterlude\n",
      "ERROR: Platfinity\n",
      "ERROR: Skyrim Script Extender SKSE\n",
      "ERROR: Esenthel Engine\n",
      "ERROR: Lead and Gold - Gangs of the Wild West\n",
      "ERROR: Yargis - Space Melee\n",
      "ERROR: Risen 3 - Titan Lords\n",
      "ERROR: Teddy Floppy Ear - The Race\n",
      "ERROR: Tree of Savior English Ver.\n",
      "ERROR: Kung Fury: Street Rage - Ultimate Edition\n",
      "ERROR: Cast of the Seven Godsends - Redux\n",
      "ERROR: Mactabilis\n",
      "ERROR: Agatha Christie - The ABC Murders\n",
      "ERROR: Sherlock Holmes Consulting Detective: The Case of the Mummys Curse\n",
      "ERROR: Sherlock Holmes Consulting Detective: The Case of the Tin Soldier\n",
      "ERROR: Sherlock Holmes Consulting Detective: The Case of the Mystified Murderess\n",
      "ERROR: IRFaceRig\n",
      "ERROR: Killing Time at Lightspeed: Enhanced Edition\n",
      "ERROR: DGU: Death God University\n",
      "ERROR: Epic Cards BattleTCG\n",
      "ERROR: Shred Remastered\n",
      "ERROR: Allods Online RU\n",
      "ERROR: Cakewalk Loop Manager\n",
      "ERROR: Cakewalk Sound Center\n",
      "ERROR: Expert Rifleman - Reloaded\n",
      "ERROR: Battle for Blood - Epic battles within 30 seconds\n",
      "ERROR: Radiator 2: Anniversary Edition\n",
      "ERROR: Vendetta - Curse of Ravens Cry\n",
      "ERROR: SMITE - Public Test\n",
      "ERROR: Clown House Palyao Evi\n",
      "ERROR: Glow Ball - The billiard puzzle game\n",
      "ERROR: BlazBlue: Chronophantasma Extend\n",
      "ERROR: Project Druid - 2D Labyrinth Explorer-\n",
      "ERROR: Layers of Fear 2016\n",
      "ERROR: Littlstar VR Cinema\n",
      "ERROR: Silver Creek Falls - Chapter 1\n",
      "ERROR: Home Legacy\n",
      "ERROR: DISTRAINT: Deluxe Edition\n",
      "ERROR: LocoSoccer Classic\n",
      "ERROR: Decay - The Mare\n",
      "ERROR: Cultures - Northland\n",
      "ERROR: Cultures - 8th Wonder of the World\n",
      "ERROR: Hyperspace Invaders II: DX\n",
      "ERROR: Business Tour - Online Multiplayer Board Game\n",
      "ERROR: Massive Cleavage vs Zombies: Awesome Edition\n",
      "ERROR: ShareX\n",
      "ERROR: Wuppo - Definitive Edition\n",
      "ERROR: VERGE:Lost chapter\n",
      "ERROR: NASCAR 15 Victory Edition\n",
      "ERROR: Undead Blackout: Reanimated Edition\n",
      "ERROR: Dungeons of Betrayal\n",
      "ERROR: MotoGP15 Compact\n",
      "ERROR: PresenZ\n",
      "ERROR: SC2VN - The eSports Visual Novel\n",
      "ERROR: Godot Engine\n",
      "ERROR: UTOPIA 9 - A Volatile Vacation\n",
      "ERROR: The Last NightMary - A Lenda do Cabea de Cuia\n",
      "ERROR: Slime Jumper\n",
      "ERROR: ePic Character Generator\n",
      "ERROR: Perraw - FPS Clone War\n",
      "ERROR: AGON - The Mysterious Codex Trilogy\n",
      "ERROR: AGON - The Lost Sword of Toledo\n",
      "ERROR: Driver Booster 3 for STEAM\n",
      "ERROR: Conflicks - Revolutionary Space Battles Demo\n",
      "ERROR: TyranoBuilder Visual Novel Studio Demo\n",
      "ERROR: Star Crusade CCG\n",
      "ERROR: Red Comrades Save the Galaxy: Reloaded\n",
      "ERROR: Goblin Defenders: Steeln Wood\n",
      "ERROR: The Hurricane of the Varstray -Collateral hazard-\n",
      "ERROR: Oh...Sir Prototype\n",
      "ERROR: Home Design 3D\n",
      "ERROR: KRUM - Edge Of Darkness\n",
      "ERROR: I Must Kill: Fresh Meat\n",
      "ERROR: CUPID - A free to play Visual Novel\n",
      "ERROR: Block N Load PTR\n",
      "ERROR: Age of Magic CCG\n",
      "ERROR: Tom Clancys Rainbow Six Siege - Test Server\n",
      "ERROR: Solitaire Christmas. Match 2 Cards\n",
      "ERROR: Rytmik Player\n",
      "ERROR: Recourse Demo\n",
      "ERROR: Space Pilgrim Episode II: Epsilon Indi\n",
      "ERROR: Wallpaper Engine\n",
      "ERROR: Wooden Floor 2 - Resurrection\n",
      "ERROR: MOAI 3: Trade Mission Collectors Edition\n",
      "ERROR: Toys of War\n",
      "ERROR: Falling Stars: War of Empires\n",
      "ERROR: Mysteries of the Past: Shadow of the Daemon Collectors Edition\n",
      "ERROR: TRON RUNr\n",
      "ERROR: Paladins - Public Test\n",
      "ERROR: Lets Eat Seaside Cafe\n",
      "ERROR: Doctor Watson - Treasure Island\n",
      "ERROR: Doctor Watson - The Riddle of the Catacombs\n",
      "ERROR: Space Pilgrim Episode IV: Sol\n",
      "ERROR: Verdict Guilty -  \n",
      "ERROR: A grande baguna espacial - The big space mess\n",
      "ERROR: Daughter of Shadows: An SCP Breach Event\n",
      "ERROR: Insane Decay of Mind: The Labyrinth\n",
      "ERROR: Overload Playable Teaser\n",
      "ERROR: Demetrios - The BIG Cynical Adventure\n",
      "ERROR: Thorne - Death Merchants\n",
      "ERROR: The Body VR: Journey Inside a Cell\n",
      "ERROR: The Cubicle.\n",
      "ERROR: PITCH-HIT : DEMO\n",
      "ERROR: LostWinds 2: Winter of the Melodias\n",
      "ERROR: PaintLab\n",
      "ERROR: Spell Fighter VR\n",
      "ERROR: Project RPG Remastered\n",
      "ERROR: 8-Bit Commando Demo\n",
      "ERROR: Nokori\n",
      "ERROR: Jaunt VR - Experience Cinematic Virtual Reality\n",
      "ERROR: Slime  Friends\n",
      "ERROR: Bigscreen Beta\n",
      "ERROR: Stonehenge VR SANDBOX\n",
      "ERROR: Vrideo\n",
      "ERROR: VR0GU3\n",
      "ERROR: Thorne - Son of Slaves Ep.2\n",
      "ERROR: Bulby - Diamond Course\n",
      "ERROR: One Way Flight\n",
      "ERROR: A Shooty Bit\n",
      "ERROR: ChuSingura461 S\n",
      "ERROR: Planescape: Torment: Enhanced Edition\n",
      "ERROR: Kathy Rain Demo\n",
      "ERROR: Within VR - Cinematic Virtual Reality\n",
      "ERROR: Destinations\n",
      "ERROR: Eclipse --- Defending the motherland\n",
      "ERROR: MOAI 4: Terra Incognita Collectors Edition\n",
      "ERROR: Johnny GravesThe Unchosen One\n",
      "ERROR: Space Hole 2016\n",
      "ERROR: Legends of the Universe - StarCore\n",
      "ERROR: Milford Heaven - Lukens Chronicles\n",
      "ERROR: Sphoxie\n",
      "ERROR: Brutl\n",
      "ERROR: Daily Chthonicle: Editors Edition\n",
      "ERROR: Orbital Strike: Arena\n",
      "ERROR: Noob Squad\n",
      "ERROR: LineDash\n",
      "ERROR: Weather Lord: Legendary Hero Collectors Edition\n",
      "ERROR: TormentorPunisher\n",
      "ERROR: Airport Fire Department - The Simulation\n",
      "ERROR: BRAINPIPE: A Plunge to Unhumanity\n",
      "ERROR: The Return Home Remastered\n",
      "ERROR: Manual Samuel - Anniversary Edition\n",
      "ERROR: Music Maker 2017 Steam Edition\n",
      "ERROR: Sorcery Part 4\n",
      "ERROR: Valentino Rossi The Game Compact\n",
      "ERROR: Mini Z Racers Turbo\n",
      "ERROR: Worldy Cup\n",
      "ERROR: Gravity Shot\n",
      "ERROR: Through Abandoned: The Forest\n",
      "ERROR: Arkham Nightmares\n",
      "ERROR: Beautiful Japanese Scenery - Animated Jigsaws\n",
      "ERROR: MetalNoise\n",
      "ERROR: MinosMaze - The Minotaurs Labyrinth\n",
      "ERROR: MAGICALSPIRAL\n",
      "ERROR: EDMtv VR\n",
      "ERROR: Globe Rush\n",
      "ERROR: Ceggtcher VR\n",
      "ERROR: Sullen: Light is Your Friend\n",
      "ERROR: .hackG.U. Last Recode\n",
      "ERROR: hackme\n",
      "ERROR:  Armies of Riddle CLASSIC\n",
      "ERROR: Rustangelo\n",
      "ERROR: Rugby Union Team Manager 2017\n",
      "ERROR: Creature Clicker - Capture, Train, Ascend\n",
      "ERROR: Thread Studio\n",
      "ERROR: HEBEREKE: March Red Army Girls Brigade\n",
      "ERROR: TankCraft\n",
      "ERROR: Deformers Open Beta\n",
      "ERROR: Tropical Girls VR\n",
      "ERROR: Dolphin Up\n",
      "ERROR: Pixvana SPIN Technology Preview\n",
      "ERROR: 3D Arcade Fishing\n",
      "ERROR: MOORHUHN  CRAZY CHICKEN strikes back\n",
      "ERROR: Legions of Tyrandel\n",
      "ERROR: MagixHome VR\n",
      "ERROR: Rocksmith 2014 Edition - Remastered\n",
      "ERROR: PRO EVOLUTION SOCCER 2017 TRIAL EDITION\n",
      "ERROR: TRI.DEFENDER\n",
      "ERROR: Super Puzzle Sisters\n",
      "ERROR: Drift GEAR Racing Free\n",
      "ERROR: Void  Nothingness\n",
      "ERROR: Empire of the Fallen Steel\n",
      "ERROR: World of DASM: DASM Spell Quest\n",
      "ERROR: VRCapture\n",
      "ERROR: Organ Quarter Pre-Alpha Demo\n",
      "ERROR: KARDS - The WWII Card Game\n",
      "ERROR: ALFINE\n",
      "ERROR: A Trip to Yugoslavia: Directors Cut\n",
      "ERROR: Wild Animals - Animated Jigsaws\n",
      "ERROR: Alone in the Dark 2008\n",
      "ERROR: Gimbal Gravity\n",
      "ERROR: NightZ\n",
      "ERROR: The Torus Syndicate\n",
      "ERROR: peakvox Route Candle for Steam\n",
      "ERROR: A Haunting: Witching Hour\n",
      "ERROR: The Night Christmas Ended\n",
      "ERROR: Abduction Prologue: The Story Of Jonathan Blake\n",
      "ERROR: MotoGP17\n",
      "ERROR: WatchDogs 2\n",
      "ERROR: Zahalia: The Knights of Galiveth\n",
      "ERROR: Attempt42\n",
      "ERROR: Project Almighty\n",
      "ERROR: Rescue Team 6 Collectors Edition\n",
      "ERROR: Santa Rockstar Steam Edition\n",
      "ERROR: Moorhuhn - Tiger and Chicken\n",
      "ERROR: GunHero\n",
      "ERROR: The Existence Abstract\n",
      "ERROR: Weather Lord: Royal Holidays Collectors Edition\n",
      "ERROR: Incredible Dracula II: The Last Call Collectors Edition\n",
      "ERROR: Score a goal Physical football\n",
      "ERROR: EnterVR\n",
      "ERROR: Ultimagus\n",
      "ERROR: State of Anarchy Complete: Master of Mayhem\n",
      "ERROR: Titanic VR Demo\n",
      "ERROR: Swatcher\n",
      "ERROR: VRemin\n",
      "ERROR: Eraser  Builder\n",
      "ERROR: MultiVR.se\n",
      "ERROR: Tom Clancys Ghost Recon Wildlands Open Beta\n",
      "ERROR: GameMaker Studio 2 Desktop\n",
      "ERROR: GameMaker Studio 2 Web\n",
      "ERROR: GameMaker Studio 2 Mobile\n",
      "ERROR: BlazBlue Centralfiction\n",
      "ERROR: For Honor - Public Test\n",
      "ERROR: Power Tools VR\n",
      "ERROR: Hoop Route\n",
      "ERROR: Hunt: Showdown Test Server\n",
      "ERROR: Survivalizm The Animal Survival Simulator\n",
      "ERROR: REVOLT 1917\n",
      "ERROR: Alien Insanity\n",
      "ERROR: Umpire Simulator\n",
      "ERROR: Mister Mart\n",
      "ERROR: Kautic - The Bald Wizard\n",
      "ERROR: TROID BLASTER\n",
      "ERROR: hackme 2\n",
      "ERROR: Schlag den Star - Das Spiel\n",
      "ERROR: Accel World VS. Sword Art Online Deluxe Edition\n",
      "ERROR: Sword Art Online: Hollow Realization Deluxe Edition\n",
      "ERROR: PIXEL ZUMBI\n",
      "ERROR: Bug Invaders\n",
      "ERROR: Trapped Within\n",
      "ERROR: Endless Winter\n",
      "ERROR: Cannons-Defenders: Steam Edition\n",
      "ERROR: Zombie Buster VR\n",
      "ERROR: EGOS - Tales of Fallen Souls\n",
      "ERROR: Tower2011:SE\n",
      "ERROR: Promethium\n",
      "ERROR: Food Truck VR\n",
      "ERROR: Trajectory of summer flower\n",
      "ERROR:  Consummate:Missing World\n",
      "ERROR: Fall of Light: Darkest Edition\n",
      "ERROR: Freeze Climbing\n",
      "ERROR: Puppy Doge VR\n",
      "ERROR: Stone Rage\n",
      "ERROR: Chickens Madness\n",
      "ERROR: Spartan VR\n",
      "ERROR: Wisdom of War\n",
      "ERROR: Windstorm: Start of a Great Friendship\n",
      "ERROR: Crushing Blow\n",
      "ERROR: Cavern Crumblers\n",
      "ERROR: Spin the Beat\n",
      "ERROR: Dreamblaster\n",
      "ERROR: Beast Mode: Night of the Werewolf Silver Bullet Edition\n",
      "ERROR: SkiFy\n",
      "ERROR: Chicken Daddy\n",
      "ERROR: Hidden Animals: English - Spanish\n",
      "ERROR: Douarnenez VR\n",
      "ERROR: Bullyparade - DER Spiel\n",
      "ERROR: Dragons Prophet Turkiye\n",
      "ERROR: -A Bit Crosser-Three Kingdoms\n",
      "ERROR: Ghostie Quest\n",
      "ERROR: Flow:The Sliding\n",
      "ERROR: Keep It Safe 2\n",
      "ERROR: MysteriaOccult Shadows\n",
      "ERROR: RectRacer\n",
      "ERROR: Fungoids - Steam version\n",
      "ERROR: Triangulate\n",
      "ERROR: Behind These Eyes\n",
      "ERROR: Undead Souls\n",
      "ERROR: Snappy Turtle Ultimate\n",
      "ERROR: Spaceship Trucker\n",
      "ERROR: Princess Sahirah is a Spoiled Brat\n",
      "ERROR: LOGistICAL: Earth\n",
      "ERROR: Dreams of Greatness\n",
      "ERROR: Time Lock VR 1 \n",
      "ERROR: Squadron: Sky Guardians\n",
      "ERROR: Spears n Spades\n",
      "ERROR: Rush to Adventure\n",
      "ERROR: Piece of Memory\n",
      "ERROR: Blind Witch -Peek Window-\n",
      "ERROR: Bystander\n",
      "ERROR: Laika 2.0\n",
      "ERROR: The Lonely Gorilla\n",
      "ERROR: GameDevDan vs Life\n",
      "ERROR: Matryoshka Strike\n",
      "ERROR: Call of Duty: Modern Warfare Remastered 2017\n",
      "ERROR: Call of Duty: Modern Warfare Remastered - Multiplayer\n",
      "ERROR: HELI-COMMANDO 2017\n",
      "ERROR: Brain Crush\n",
      "ERROR: Puzzle: Underwater World\n",
      "ERROR: Zombie Waiting\n",
      "ERROR: Funtoons World\n",
      "ERROR: Alienzix\n",
      "ERROR: Jewels of the Mysterious Woodland\n",
      "ERROR: Neon Coliseum\n",
      "ERROR: Sobreviva - Low Poly\n",
      "ERROR: Space Panic Arena\n",
      "ERROR: BoidWatch\n",
      "ERROR: Denki Gakas Bombshell\n",
      "ERROR: Nebula Nuker\n",
      "ERROR: Endless Reality\n",
      "ERROR: Leons crusade La cruzada de Len\n",
      "ERROR: Klondike Solitaire Kings\n",
      "ERROR: The Mines of Morseph\n",
      "ERROR: Dont Explode\n",
      "ERROR: Mahjong Challenge\n",
      "ERROR: Taking Valhalla VR\n",
      "ERROR: Molten Armor\n",
      "ERROR: Coffee Pixes\n",
      "ERROR: The Flying Turtle Jewel Quest\n",
      "ERROR: Soldiers Of Freedom\n",
      "ERROR: Piatka\n",
      "ERROR: Hippo Sports\n",
      "ERROR: Monopolka\n",
      "ERROR: Commands  Colors: Ancients\n",
      "ERROR: Bees Knees\n",
      "ERROR: EZ4u\n",
      "ERROR: Mystic Miracles - Strategy card board game\n",
      "ERROR: Water Pipeline\n",
      "ERROR: Wuxing Master CCG\n",
      "ERROR: BLOCKPOST LEGACY\n",
      "ERROR: Anahita\n",
      "ERROR: Prison Chainball Massacre\n",
      "ERROR: Food Mahjong\n",
      "ERROR: The Exorcist: Legion VR - Chapter 1: First Rites\n",
      "ERROR: Low Desert Punk\n",
      "ERROR: The Red Front\n",
      "ERROR: Weapon and Armor: Mahjong\n",
      "ERROR: SwapQuest Demo\n",
      "ERROR: Interworlds\n",
      "ERROR: Think of the Children Beta\n",
      "ERROR: Onironauta\n",
      "ERROR: No God for Us\n",
      "ERROR: Dungeon Rustlers\n",
      "ERROR: Hidden Object - Food\n",
      "ERROR: Qbike: Crypto Motorcycles\n",
      "ERROR: Live2D VR Girls\n",
      "ERROR: Zula Trkiye\n",
      "ERROR: Endless Treasure Hunt\n",
      "ERROR: Hidden Object - Tools\n",
      "ERROR: DashPanel\n",
      "ERROR: Jewel of WonderLand\n",
      "ERROR: SKIMMERZ\n",
      "ERROR: The Flight Of Dowran\n",
      "ERROR: Konrad the Rocket\n",
      "ERROR: Game-Ready Assets\n",
      "ERROR: Mulletman and the Molemen\n",
      "ERROR: Super Dungeon Master Ace\n",
      "ERROR: Halloween Pumpkin Story\n",
      "ERROR: Loot Collection: Mahjong\n",
      "ERROR: LeftRight\n",
      "ERROR: DiamondFalls\n",
      "ERROR: Ghost Recon Wildlands Ghost War Open Beta\n",
      "ERROR: Vinewing\n",
      "ERROR: Ancestors Legacy Free Peasant Edition\n",
      "ERROR: TRIPLE TWENTY - VR Darts\n",
      "ERROR: Soundpad\n",
      "ERROR: La Aventura De Axel\n",
      "ERROR: Frontiers.io\n",
      "ERROR: EEP 14 Basic\n",
      "ERROR: Captain vs Sky Pirates\n",
      "ERROR: The Killbox: LEO\n",
      "ERROR: Scrolls of the Lord\n",
      "ERROR: Sniper Hunter Adventure 3D\n",
      "ERROR: Buffy Stole Your Sandwich\n",
      "ERROR: Duralumin Wind\n",
      "ERROR: Merper VR\n",
      "ERROR: Mission Ammunition\n",
      "ERROR: The Adventures of Sam Carlisle: The Hunt for the Lost Treasure\n",
      "ERROR: Museu do Crio de Nazar em Realidade Virtual\n",
      "ERROR:  Heroes of Hexaluga \n",
      "ERROR: San Matias - Mafia City\n",
      "ERROR: Kanova\n",
      "ERROR: Loud or Quiet\n",
      "ERROR: Merv Reborn\n",
      "ERROR: Crawl Space: The Mansion\n",
      "ERROR: Hinterhalt\n",
      "ERROR: War Trigger 2\n",
      "ERROR: Zen Blocks\n",
      "ERROR: I Cant Believe Its Not Gambling GOTY Edition\n",
      "ERROR: Wheel Riders Online OBT\n",
      "ERROR: Oneirogen\n",
      "ERROR: Driver Booster 5 for Steam\n",
      "ERROR: SpaceCoaster VR\n",
      "ERROR: Brutal Alice  -The Handred Days War-\n",
      "ERROR: AchBall\n",
      "ERROR: Verzaken\n",
      "ERROR: Djilyaro\n",
      "ERROR: The Song of Terminus  :\n",
      "ERROR: A Day For A Kitten\n",
      "ERROR: Quake Champions PTS\n",
      "ERROR: Starfighter Neon\n",
      "ERROR: Cut 2017\n",
      "ERROR: Tale of Alamar\n",
      "ERROR: Cosmic Buddies Town\n",
      "ERROR: Space Rocks\n",
      "ERROR: You Are a Torpedo AI\n",
      "ERROR: Puzzle Tactics\n",
      "ERROR: Battlerite Public Test\n",
      "ERROR: Virtual Reality Girls\n",
      "ERROR: Intergalactic traveler: The Omega Sector\n",
      "ERROR: National Rugby Manager\n",
      "ERROR: W4RR-io-RS\n",
      "ERROR: Orbitality\n",
      "ERROR: Twinstack\n",
      "ERROR: Medicalholodeck\n",
      "ERROR: High School Simulator 2018\n",
      "ERROR: Rocket Blasters\n",
      "ERROR: Impossibox\n",
      "ERROR: Call of Duty: WWII - Multiplayer\n",
      "ERROR: TOKYO GHOULre CALL to EXIST\n",
      "ERROR: Vexius\n",
      "ERROR: Ship Ahoy Open BETA\n",
      "ERROR: Limit of defense\n",
      "ERROR: Mahlone One\n",
      "ERROR: Musical Reflex\n"
     ]
    },
    {
     "ename": "SSLError",
     "evalue": "HTTPSConnectionPool(host='hltb-api.vercel.app', port=443): Max retries exceeded with url: /api?name=Star%20Sweet (Caused by SSLError(SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1006)')))",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mSSLEOFError\u001b[0m                               Traceback (most recent call last)",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:468\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[1;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[0;32m    467\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 468\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_conn(conn)\n\u001b[0;32m    469\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (SocketTimeout, BaseSSLError) \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:1097\u001b[0m, in \u001b[0;36mHTTPSConnectionPool._validate_conn\u001b[1;34m(self, conn)\u001b[0m\n\u001b[0;32m   1096\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m conn\u001b[38;5;241m.\u001b[39mis_closed:\n\u001b[1;32m-> 1097\u001b[0m     conn\u001b[38;5;241m.\u001b[39mconnect()\n\u001b[0;32m   1099\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m conn\u001b[38;5;241m.\u001b[39mis_verified:\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:642\u001b[0m, in \u001b[0;36mHTTPSConnection.connect\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    634\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m    635\u001b[0m         (\n\u001b[0;32m    636\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSystem time is way off (before \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mRECENT_DATE\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m). This will probably \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    639\u001b[0m         SystemTimeWarning,\n\u001b[0;32m    640\u001b[0m     )\n\u001b[1;32m--> 642\u001b[0m sock_and_verified \u001b[38;5;241m=\u001b[39m _ssl_wrap_socket_and_match_hostname(\n\u001b[0;32m    643\u001b[0m     sock\u001b[38;5;241m=\u001b[39msock,\n\u001b[0;32m    644\u001b[0m     cert_reqs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcert_reqs,\n\u001b[0;32m    645\u001b[0m     ssl_version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mssl_version,\n\u001b[0;32m    646\u001b[0m     ssl_minimum_version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mssl_minimum_version,\n\u001b[0;32m    647\u001b[0m     ssl_maximum_version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mssl_maximum_version,\n\u001b[0;32m    648\u001b[0m     ca_certs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mca_certs,\n\u001b[0;32m    649\u001b[0m     ca_cert_dir\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mca_cert_dir,\n\u001b[0;32m    650\u001b[0m     ca_cert_data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mca_cert_data,\n\u001b[0;32m    651\u001b[0m     cert_file\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcert_file,\n\u001b[0;32m    652\u001b[0m     key_file\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkey_file,\n\u001b[0;32m    653\u001b[0m     key_password\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkey_password,\n\u001b[0;32m    654\u001b[0m     server_hostname\u001b[38;5;241m=\u001b[39mserver_hostname,\n\u001b[0;32m    655\u001b[0m     ssl_context\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mssl_context,\n\u001b[0;32m    656\u001b[0m     tls_in_tls\u001b[38;5;241m=\u001b[39mtls_in_tls,\n\u001b[0;32m    657\u001b[0m     assert_hostname\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massert_hostname,\n\u001b[0;32m    658\u001b[0m     assert_fingerprint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massert_fingerprint,\n\u001b[0;32m    659\u001b[0m )\n\u001b[0;32m    660\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m sock_and_verified\u001b[38;5;241m.\u001b[39msocket\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:783\u001b[0m, in \u001b[0;36m_ssl_wrap_socket_and_match_hostname\u001b[1;34m(sock, cert_reqs, ssl_version, ssl_minimum_version, ssl_maximum_version, cert_file, key_file, key_password, ca_certs, ca_cert_dir, ca_cert_data, assert_hostname, assert_fingerprint, server_hostname, ssl_context, tls_in_tls)\u001b[0m\n\u001b[0;32m    781\u001b[0m         server_hostname \u001b[38;5;241m=\u001b[39m normalized\n\u001b[1;32m--> 783\u001b[0m ssl_sock \u001b[38;5;241m=\u001b[39m ssl_wrap_socket(\n\u001b[0;32m    784\u001b[0m     sock\u001b[38;5;241m=\u001b[39msock,\n\u001b[0;32m    785\u001b[0m     keyfile\u001b[38;5;241m=\u001b[39mkey_file,\n\u001b[0;32m    786\u001b[0m     certfile\u001b[38;5;241m=\u001b[39mcert_file,\n\u001b[0;32m    787\u001b[0m     key_password\u001b[38;5;241m=\u001b[39mkey_password,\n\u001b[0;32m    788\u001b[0m     ca_certs\u001b[38;5;241m=\u001b[39mca_certs,\n\u001b[0;32m    789\u001b[0m     ca_cert_dir\u001b[38;5;241m=\u001b[39mca_cert_dir,\n\u001b[0;32m    790\u001b[0m     ca_cert_data\u001b[38;5;241m=\u001b[39mca_cert_data,\n\u001b[0;32m    791\u001b[0m     server_hostname\u001b[38;5;241m=\u001b[39mserver_hostname,\n\u001b[0;32m    792\u001b[0m     ssl_context\u001b[38;5;241m=\u001b[39mcontext,\n\u001b[0;32m    793\u001b[0m     tls_in_tls\u001b[38;5;241m=\u001b[39mtls_in_tls,\n\u001b[0;32m    794\u001b[0m )\n\u001b[0;32m    796\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\util\\ssl_.py:471\u001b[0m, in \u001b[0;36mssl_wrap_socket\u001b[1;34m(sock, keyfile, certfile, cert_reqs, ca_certs, server_hostname, ssl_version, ciphers, ssl_context, ca_cert_dir, key_password, ca_cert_data, tls_in_tls)\u001b[0m\n\u001b[0;32m    469\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m--> 471\u001b[0m ssl_sock \u001b[38;5;241m=\u001b[39m _ssl_wrap_socket_impl(sock, context, tls_in_tls, server_hostname)\n\u001b[0;32m    472\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ssl_sock\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\util\\ssl_.py:515\u001b[0m, in \u001b[0;36m_ssl_wrap_socket_impl\u001b[1;34m(sock, ssl_context, tls_in_tls, server_hostname)\u001b[0m\n\u001b[0;32m    513\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m SSLTransport(sock, ssl_context, server_hostname)\n\u001b[1;32m--> 515\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ssl_context\u001b[38;5;241m.\u001b[39mwrap_socket(sock, server_hostname\u001b[38;5;241m=\u001b[39mserver_hostname)\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\ssl.py:517\u001b[0m, in \u001b[0;36mSSLContext.wrap_socket\u001b[1;34m(self, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, session)\u001b[0m\n\u001b[0;32m    511\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrap_socket\u001b[39m(\u001b[38;5;28mself\u001b[39m, sock, server_side\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    512\u001b[0m                 do_handshake_on_connect\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m    513\u001b[0m                 suppress_ragged_eofs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m    514\u001b[0m                 server_hostname\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, session\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m    515\u001b[0m     \u001b[38;5;66;03m# SSLSocket class handles server_hostname encoding before it calls\u001b[39;00m\n\u001b[0;32m    516\u001b[0m     \u001b[38;5;66;03m# ctx._wrap_socket()\u001b[39;00m\n\u001b[1;32m--> 517\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msslsocket_class\u001b[38;5;241m.\u001b[39m_create(\n\u001b[0;32m    518\u001b[0m         sock\u001b[38;5;241m=\u001b[39msock,\n\u001b[0;32m    519\u001b[0m         server_side\u001b[38;5;241m=\u001b[39mserver_side,\n\u001b[0;32m    520\u001b[0m         do_handshake_on_connect\u001b[38;5;241m=\u001b[39mdo_handshake_on_connect,\n\u001b[0;32m    521\u001b[0m         suppress_ragged_eofs\u001b[38;5;241m=\u001b[39msuppress_ragged_eofs,\n\u001b[0;32m    522\u001b[0m         server_hostname\u001b[38;5;241m=\u001b[39mserver_hostname,\n\u001b[0;32m    523\u001b[0m         context\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m    524\u001b[0m         session\u001b[38;5;241m=\u001b[39msession\n\u001b[0;32m    525\u001b[0m     )\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\ssl.py:1108\u001b[0m, in \u001b[0;36mSSLSocket._create\u001b[1;34m(cls, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, context, session)\u001b[0m\n\u001b[0;32m   1107\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdo_handshake_on_connect should not be specified for non-blocking sockets\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m-> 1108\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdo_handshake()\n\u001b[0;32m   1109\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mOSError\u001b[39;00m, \u001b[38;5;167;01mValueError\u001b[39;00m):\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\ssl.py:1383\u001b[0m, in \u001b[0;36mSSLSocket.do_handshake\u001b[1;34m(self, block)\u001b[0m\n\u001b[0;32m   1382\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msettimeout(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m-> 1383\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mdo_handshake()\n\u001b[0;32m   1384\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
      "\u001b[1;31mSSLEOFError\u001b[0m: [SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1006)",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mSSLError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:791\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[1;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[0;32m    790\u001b[0m \u001b[38;5;66;03m# Make the request on the HTTPConnection object\u001b[39;00m\n\u001b[1;32m--> 791\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_request(\n\u001b[0;32m    792\u001b[0m     conn,\n\u001b[0;32m    793\u001b[0m     method,\n\u001b[0;32m    794\u001b[0m     url,\n\u001b[0;32m    795\u001b[0m     timeout\u001b[38;5;241m=\u001b[39mtimeout_obj,\n\u001b[0;32m    796\u001b[0m     body\u001b[38;5;241m=\u001b[39mbody,\n\u001b[0;32m    797\u001b[0m     headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[0;32m    798\u001b[0m     chunked\u001b[38;5;241m=\u001b[39mchunked,\n\u001b[0;32m    799\u001b[0m     retries\u001b[38;5;241m=\u001b[39mretries,\n\u001b[0;32m    800\u001b[0m     response_conn\u001b[38;5;241m=\u001b[39mresponse_conn,\n\u001b[0;32m    801\u001b[0m     preload_content\u001b[38;5;241m=\u001b[39mpreload_content,\n\u001b[0;32m    802\u001b[0m     decode_content\u001b[38;5;241m=\u001b[39mdecode_content,\n\u001b[0;32m    803\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mresponse_kw,\n\u001b[0;32m    804\u001b[0m )\n\u001b[0;32m    806\u001b[0m \u001b[38;5;66;03m# Everything went great!\u001b[39;00m\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:492\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[1;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[0;32m    491\u001b[0m         new_e \u001b[38;5;241m=\u001b[39m _wrap_proxy_error(new_e, conn\u001b[38;5;241m.\u001b[39mproxy\u001b[38;5;241m.\u001b[39mscheme)\n\u001b[1;32m--> 492\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m new_e\n\u001b[0;32m    494\u001b[0m \u001b[38;5;66;03m# conn.request() calls http.client.*.request, not the method in\u001b[39;00m\n\u001b[0;32m    495\u001b[0m \u001b[38;5;66;03m# urllib3.request. It also calls makefile (recv) on the socket.\u001b[39;00m\n",
      "\u001b[1;31mSSLError\u001b[0m: [SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1006)",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mMaxRetryError\u001b[0m                             Traceback (most recent call last)",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\adapters.py:486\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[1;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[0;32m    485\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 486\u001b[0m     resp \u001b[38;5;241m=\u001b[39m conn\u001b[38;5;241m.\u001b[39murlopen(\n\u001b[0;32m    487\u001b[0m         method\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mmethod,\n\u001b[0;32m    488\u001b[0m         url\u001b[38;5;241m=\u001b[39murl,\n\u001b[0;32m    489\u001b[0m         body\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mbody,\n\u001b[0;32m    490\u001b[0m         headers\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mheaders,\n\u001b[0;32m    491\u001b[0m         redirect\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    492\u001b[0m         assert_same_host\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    493\u001b[0m         preload_content\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    494\u001b[0m         decode_content\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    495\u001b[0m         retries\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_retries,\n\u001b[0;32m    496\u001b[0m         timeout\u001b[38;5;241m=\u001b[39mtimeout,\n\u001b[0;32m    497\u001b[0m         chunked\u001b[38;5;241m=\u001b[39mchunked,\n\u001b[0;32m    498\u001b[0m     )\n\u001b[0;32m    500\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:845\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[1;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[0;32m    843\u001b[0m     new_e \u001b[38;5;241m=\u001b[39m ProtocolError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection aborted.\u001b[39m\u001b[38;5;124m\"\u001b[39m, new_e)\n\u001b[1;32m--> 845\u001b[0m retries \u001b[38;5;241m=\u001b[39m retries\u001b[38;5;241m.\u001b[39mincrement(\n\u001b[0;32m    846\u001b[0m     method, url, error\u001b[38;5;241m=\u001b[39mnew_e, _pool\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m, _stacktrace\u001b[38;5;241m=\u001b[39msys\u001b[38;5;241m.\u001b[39mexc_info()[\u001b[38;5;241m2\u001b[39m]\n\u001b[0;32m    847\u001b[0m )\n\u001b[0;32m    848\u001b[0m retries\u001b[38;5;241m.\u001b[39msleep()\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\urllib3\\util\\retry.py:515\u001b[0m, in \u001b[0;36mRetry.increment\u001b[1;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[0;32m    514\u001b[0m     reason \u001b[38;5;241m=\u001b[39m error \u001b[38;5;129;01mor\u001b[39;00m ResponseError(cause)\n\u001b[1;32m--> 515\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m MaxRetryError(_pool, url, reason) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mreason\u001b[39;00m  \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n\u001b[0;32m    517\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIncremented Retry for (url=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m): \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, url, new_retry)\n",
      "\u001b[1;31mMaxRetryError\u001b[0m: HTTPSConnectionPool(host='hltb-api.vercel.app', port=443): Max retries exceeded with url: /api?name=Star%20Sweet (Caused by SSLError(SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1006)')))",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mSSLError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[8], line 11\u001b[0m\n\u001b[0;32m      9\u001b[0m beat_time_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://hltb-api.vercel.app/api?name=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mgame_name1\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m     10\u001b[0m \u001b[38;5;66;03m#print(beat_time_data) \u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m beat_time_response \u001b[38;5;241m=\u001b[39m requests\u001b[38;5;241m.\u001b[39mget(beat_time_data)\n\u001b[0;32m     13\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (beat_time_response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m200\u001b[39m):\n\u001b[0;32m     14\u001b[0m     beat_time_data \u001b[38;5;241m=\u001b[39m beat_time_response\u001b[38;5;241m.\u001b[39mjson()\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\api.py:73\u001b[0m, in \u001b[0;36mget\u001b[1;34m(url, params, **kwargs)\u001b[0m\n\u001b[0;32m     62\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget\u001b[39m(url, params\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m     63\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Sends a GET request.\u001b[39;00m\n\u001b[0;32m     64\u001b[0m \n\u001b[0;32m     65\u001b[0m \u001b[38;5;124;03m    :param url: URL for the new :class:`Request` object.\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[38;5;124;03m    :rtype: requests.Response\u001b[39;00m\n\u001b[0;32m     71\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 73\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m request(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mget\u001b[39m\u001b[38;5;124m\"\u001b[39m, url, params\u001b[38;5;241m=\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\api.py:59\u001b[0m, in \u001b[0;36mrequest\u001b[1;34m(method, url, **kwargs)\u001b[0m\n\u001b[0;32m     55\u001b[0m \u001b[38;5;66;03m# By using the 'with' statement we are sure the session is closed, thus we\u001b[39;00m\n\u001b[0;32m     56\u001b[0m \u001b[38;5;66;03m# avoid leaving sockets open which can trigger a ResourceWarning in some\u001b[39;00m\n\u001b[0;32m     57\u001b[0m \u001b[38;5;66;03m# cases, and look like a memory leak in others.\u001b[39;00m\n\u001b[0;32m     58\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m sessions\u001b[38;5;241m.\u001b[39mSession() \u001b[38;5;28;01mas\u001b[39;00m session:\n\u001b[1;32m---> 59\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m session\u001b[38;5;241m.\u001b[39mrequest(method\u001b[38;5;241m=\u001b[39mmethod, url\u001b[38;5;241m=\u001b[39murl, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\sessions.py:589\u001b[0m, in \u001b[0;36mSession.request\u001b[1;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[0;32m    584\u001b[0m send_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m    585\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m: timeout,\n\u001b[0;32m    586\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_redirects\u001b[39m\u001b[38;5;124m\"\u001b[39m: allow_redirects,\n\u001b[0;32m    587\u001b[0m }\n\u001b[0;32m    588\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[1;32m--> 589\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msend(prep, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39msend_kwargs)\n\u001b[0;32m    591\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\sessions.py:703\u001b[0m, in \u001b[0;36mSession.send\u001b[1;34m(self, request, **kwargs)\u001b[0m\n\u001b[0;32m    700\u001b[0m start \u001b[38;5;241m=\u001b[39m preferred_clock()\n\u001b[0;32m    702\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[1;32m--> 703\u001b[0m r \u001b[38;5;241m=\u001b[39m adapter\u001b[38;5;241m.\u001b[39msend(request, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    705\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n\u001b[0;32m    706\u001b[0m elapsed \u001b[38;5;241m=\u001b[39m preferred_clock() \u001b[38;5;241m-\u001b[39m start\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\requests\\adapters.py:517\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[1;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[0;32m    513\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m ProxyError(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[0;32m    515\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, _SSLError):\n\u001b[0;32m    516\u001b[0m         \u001b[38;5;66;03m# This branch is for urllib3 v1.22 and later.\u001b[39;00m\n\u001b[1;32m--> 517\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m SSLError(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[0;32m    519\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mConnectionError\u001b[39;00m(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[0;32m    521\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ClosedPoolError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "\u001b[1;31mSSLError\u001b[0m: HTTPSConnectionPool(host='hltb-api.vercel.app', port=443): Max retries exceeded with url: /api?name=Star%20Sweet (Caused by SSLError(SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1006)')))"
     ]
    }
   ],
   "source": [
    "games = 0\n",
    "\n",
    "for game in tqdm(range(len(df_games)), desc=\"How long to beat Games\"):\n",
    "    game_name = df_games.iloc[game]['name']\n",
    "\n",
    "    if(game_name != None):\n",
    "        game_name1 = re.sub(r'[^a-zA-Z0-9\\s\\:\\.\\-\\,]', '', game_name)\n",
    "    \n",
    "        beat_time_data = f\"https://hltb-api.vercel.app/api?name={game_name1}\"\n",
    "        #print(beat_time_data) \n",
    "        beat_time_response = requests.get(beat_time_data)\n",
    "        \n",
    "        if (beat_time_response.status_code == 200):\n",
    "            beat_time_data = beat_time_response.json()\n",
    "            #print(beat_time_data) \n",
    "            try:\n",
    "                if(beat_time_data[0]['gameplayCompletionist'] != 0):\n",
    "                    \n",
    "                    df_games.loc[game, 'beat_time'] = (beat_time_data[0]['gameplayCompletionist'])*60\n",
    "\n",
    "                else:\n",
    "                    df_games.loc[game, 'beat_time'] = (beat_time_data[0]['gameplayMain'])*60\n",
    "                    \n",
    "                games += 1\n",
    "            except:\n",
    "                print(\"ERROR:\", game_name1)\n",
    "               \n",
    "print(\"\\n**********PROCESO TERMINADO************\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>appid</th>\n",
       "      <th>name</th>\n",
       "      <th>playtime_forever</th>\n",
       "      <th>img_icon_url</th>\n",
       "      <th>has_community_visible_stats</th>\n",
       "      <th>content_descriptorids</th>\n",
       "      <th>has_leaderboards</th>\n",
       "      <th>playtime_2weeks</th>\n",
       "      <th>achievement_percentage</th>\n",
       "      <th>achievement_completed</th>\n",
       "      <th>total_achievements</th>\n",
       "      <th>beat_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>300</td>\n",
       "      <td>Day of Defeat: Source</td>\n",
       "      <td>1917</td>\n",
       "      <td>062754bb5853b0534283ae27dc5d58200692b22d</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>Team Fortress Classic</td>\n",
       "      <td>1</td>\n",
       "      <td>38ea7ebe3c1abbbbf4eabdbef174c41a972102b9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>1140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>Day of Defeat</td>\n",
       "      <td>0</td>\n",
       "      <td>aadc0ce51ff6ba2042d633f8ec033b0de62091d0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>5040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>Deathmatch Classic</td>\n",
       "      <td>0</td>\n",
       "      <td>c525f76c8bc7353db4fd74b128c4ae2028426c2a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>Half-Life: Opposing Force</td>\n",
       "      <td>0</td>\n",
       "      <td>04e81206c10e12416908c72c5f22aad411b3aeef</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   appid                       name  playtime_forever  \\\n",
       "0    300      Day of Defeat: Source              1917   \n",
       "1     20      Team Fortress Classic                 1   \n",
       "2     30              Day of Defeat                 0   \n",
       "3     40         Deathmatch Classic                 0   \n",
       "4     50  Half-Life: Opposing Force                 0   \n",
       "\n",
       "                               img_icon_url has_community_visible_stats  \\\n",
       "0  062754bb5853b0534283ae27dc5d58200692b22d                        True   \n",
       "1  38ea7ebe3c1abbbbf4eabdbef174c41a972102b9                         NaN   \n",
       "2  aadc0ce51ff6ba2042d633f8ec033b0de62091d0                         NaN   \n",
       "3  c525f76c8bc7353db4fd74b128c4ae2028426c2a                         NaN   \n",
       "4  04e81206c10e12416908c72c5f22aad411b3aeef                         NaN   \n",
       "\n",
       "  content_descriptorids has_leaderboards  playtime_2weeks  \\\n",
       "0                   NaN              NaN              NaN   \n",
       "1                [2, 5]              NaN              NaN   \n",
       "2                   NaN              NaN              NaN   \n",
       "3                   NaN              NaN              NaN   \n",
       "4                   NaN              NaN              NaN   \n",
       "\n",
       "  achievement_percentage achievement_completed total_achievements beat_time  \n",
       "0                    0.0                     0                 54       120  \n",
       "1                   None                  None               None      1140  \n",
       "2                   None                  None               None      5040  \n",
       "3                   None                  None               None       720  \n",
       "4                   None                  None               None       420  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_games.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_games.to_csv(\"df_games.csv\") "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9497 entries, 0 to 9496\n",
      "Data columns (total 12 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   appid                        9497 non-null   int64  \n",
      " 1   name                         9497 non-null   object \n",
      " 2   playtime_forever             9497 non-null   int64  \n",
      " 3   img_icon_url                 9497 non-null   object \n",
      " 4   has_community_visible_stats  5546 non-null   object \n",
      " 5   content_descriptorids        1132 non-null   object \n",
      " 6   has_leaderboards             844 non-null    object \n",
      " 7   playtime_2weeks              3 non-null      float64\n",
      " 8   achievement_percentage       5483 non-null   object \n",
      " 9   achievement_completed        5483 non-null   object \n",
      " 10  total_achievements           5483 non-null   object \n",
      " 11  beat_time                    5271 non-null   object \n",
      "dtypes: float64(1), int64(2), object(9)\n",
      "memory usage: 890.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df_games.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "appid                           0.000000\n",
      "name                            0.000000\n",
      "playtime_forever                0.000000\n",
      "img_icon_url                    0.000000\n",
      "has_community_visible_stats    41.602611\n",
      "content_descriptorids          88.080446\n",
      "has_leaderboards               91.112983\n",
      "playtime_2weeks                99.968411\n",
      "achievement_percentage         42.265979\n",
      "achievement_completed          42.265979\n",
      "total_achievements             42.265979\n",
      "beat_time                      44.498263\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print((df_games.isnull().sum()/(len(df_games)))*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>appid</th>\n",
       "      <th>name</th>\n",
       "      <th>playtime_forever</th>\n",
       "      <th>img_icon_url</th>\n",
       "      <th>has_community_visible_stats</th>\n",
       "      <th>content_descriptorids</th>\n",
       "      <th>has_leaderboards</th>\n",
       "      <th>playtime_2weeks</th>\n",
       "      <th>achievement_percentage</th>\n",
       "      <th>achievement_completed</th>\n",
       "      <th>total_achievements</th>\n",
       "      <th>beat_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9.497000e+03</td>\n",
       "      <td>9497</td>\n",
       "      <td>9497.000000</td>\n",
       "      <td>9497</td>\n",
       "      <td>5546</td>\n",
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       "      <td>5483.0</td>\n",
       "      <td>5271.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9488</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9331</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>237.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Maelstrom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74698583248254ff59f137a1c19e03b5169b4879</td>\n",
       "      <td>True</td>\n",
       "      <td>[2, 5]</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>5546</td>\n",
       "      <td>428</td>\n",
       "      <td>844</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5149.0</td>\n",
       "      <td>5149.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>1770.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.520148e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>674.670633</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>633.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.228489e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7173.553971</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1060.994345</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.540500e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.779400e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.206000e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>947.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.478970e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>396772.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1858.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               appid       name  playtime_forever  \\\n",
       "count   9.497000e+03       9497       9497.000000   \n",
       "unique           NaN       9488               NaN   \n",
       "top              NaN  Maelstrom               NaN   \n",
       "freq             NaN          2               NaN   \n",
       "mean    6.520148e+05        NaN        674.670633   \n",
       "std     4.228489e+05        NaN       7173.553971   \n",
       "min     1.000000e+01        NaN          0.000000   \n",
       "25%     3.540500e+05        NaN          0.000000   \n",
       "50%     5.779400e+05        NaN          0.000000   \n",
       "75%     8.206000e+05        NaN          0.000000   \n",
       "max     2.478970e+06        NaN     396772.000000   \n",
       "\n",
       "                                    img_icon_url has_community_visible_stats  \\\n",
       "count                                       9497                        5546   \n",
       "unique                                      9331                           1   \n",
       "top     74698583248254ff59f137a1c19e03b5169b4879                        True   \n",
       "freq                                          36                        5546   \n",
       "mean                                         NaN                         NaN   \n",
       "std                                          NaN                         NaN   \n",
       "min                                          NaN                         NaN   \n",
       "25%                                          NaN                         NaN   \n",
       "50%                                          NaN                         NaN   \n",
       "75%                                          NaN                         NaN   \n",
       "max                                          NaN                         NaN   \n",
       "\n",
       "       content_descriptorids has_leaderboards  playtime_2weeks  \\\n",
       "count                   1132              844         3.000000   \n",
       "unique                     9                1              NaN   \n",
       "top                   [2, 5]             True              NaN   \n",
       "freq                     428              844              NaN   \n",
       "mean                     NaN              NaN       633.000000   \n",
       "std                      NaN              NaN      1060.994345   \n",
       "min                      NaN              NaN         5.000000   \n",
       "25%                      NaN              NaN        20.500000   \n",
       "50%                      NaN              NaN        36.000000   \n",
       "75%                      NaN              NaN       947.000000   \n",
       "max                      NaN              NaN      1858.000000   \n",
       "\n",
       "        achievement_percentage  achievement_completed  total_achievements  \\\n",
       "count                   5483.0                 5483.0              5483.0   \n",
       "unique                   125.0                  197.0               351.0   \n",
       "top                        0.0                    0.0                12.0   \n",
       "freq                    5149.0                 5149.0               208.0   \n",
       "mean                       NaN                    NaN                 NaN   \n",
       "std                        NaN                    NaN                 NaN   \n",
       "min                        NaN                    NaN                 NaN   \n",
       "25%                        NaN                    NaN                 NaN   \n",
       "50%                        NaN                    NaN                 NaN   \n",
       "75%                        NaN                    NaN                 NaN   \n",
       "max                        NaN                    NaN                 NaN   \n",
       "\n",
       "        beat_time  \n",
       "count      5271.0  \n",
       "unique      237.0  \n",
       "top           0.0  \n",
       "freq       1770.0  \n",
       "mean          NaN  \n",
       "std           NaN  \n",
       "min           NaN  \n",
       "25%           NaN  \n",
       "50%           NaN  \n",
       "75%           NaN  \n",
       "max           NaN  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_games.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>appid</th>\n",
       "      <th>name</th>\n",
       "      <th>playtime_forever</th>\n",
       "      <th>img_icon_url</th>\n",
       "      <th>has_community_visible_stats</th>\n",
       "      <th>content_descriptorids</th>\n",
       "      <th>has_leaderboards</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>300</td>\n",
       "      <td>Day of Defeat: Source</td>\n",
       "      <td>1917</td>\n",
       "      <td>062754bb5853b0534283ae27dc5d58200692b22d</td>\n",
       "      <td>True</td>\n",
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       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>Team Fortress Classic</td>\n",
       "      <td>1</td>\n",
       "      <td>38ea7ebe3c1abbbbf4eabdbef174c41a972102b9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>1140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>Day of Defeat</td>\n",
       "      <td>0</td>\n",
       "      <td>aadc0ce51ff6ba2042d633f8ec033b0de62091d0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>5040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>Deathmatch Classic</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>Half-Life: Opposing Force</td>\n",
       "      <td>0</td>\n",
       "      <td>04e81206c10e12416908c72c5f22aad411b3aeef</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9492</th>\n",
       "      <td>2478970</td>\n",
       "      <td>Tomb Raider I-III Remastered Starring Lara Croft</td>\n",
       "      <td>0</td>\n",
       "      <td>7bd910d66157ffcadd96bcd9333dd45f318e5c58</td>\n",
       "      <td>True</td>\n",
       "      <td>[2, 5]</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>269</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9493</th>\n",
       "      <td>1086940</td>\n",
       "      <td>Baldur's Gate 3</td>\n",
       "      <td>0</td>\n",
       "      <td>d866cae7ea1e471fdbc206287111f1b642373bd9</td>\n",
       "      <td>True</td>\n",
       "      <td>[1, 2, 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9494</th>\n",
       "      <td>344740</td>\n",
       "      <td>CRYPTARK</td>\n",
       "      <td>0</td>\n",
       "      <td>c56bc2236cbcee87cab5c3d99e97be9f24d8cf50</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9495</th>\n",
       "      <td>577940</td>\n",
       "      <td>Killer Instinct</td>\n",
       "      <td>0</td>\n",
       "      <td>10c39134ff17a0af1bba131a6036362606785167</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>463</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9496</th>\n",
       "      <td>1176710</td>\n",
       "      <td>Space Crew: Legendary Edition</td>\n",
       "      <td>0</td>\n",
       "      <td>c1c0a0c7c7dae3525bc6a4bb07bc0bd69bc62ab0</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9497 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        appid                                              name  \\\n",
       "0         300                             Day of Defeat: Source   \n",
       "1          20                             Team Fortress Classic   \n",
       "2          30                                     Day of Defeat   \n",
       "3          40                                Deathmatch Classic   \n",
       "4          50                         Half-Life: Opposing Force   \n",
       "...       ...                                               ...   \n",
       "9492  2478970  Tomb Raider I-III Remastered Starring Lara Croft   \n",
       "9493  1086940                                   Baldur's Gate 3   \n",
       "9494   344740                                          CRYPTARK   \n",
       "9495   577940                                   Killer Instinct   \n",
       "9496  1176710                     Space Crew: Legendary Edition   \n",
       "\n",
       "      playtime_forever                              img_icon_url  \\\n",
       "0                 1917  062754bb5853b0534283ae27dc5d58200692b22d   \n",
       "1                    1  38ea7ebe3c1abbbbf4eabdbef174c41a972102b9   \n",
       "2                    0  aadc0ce51ff6ba2042d633f8ec033b0de62091d0   \n",
       "3                    0  c525f76c8bc7353db4fd74b128c4ae2028426c2a   \n",
       "4                    0  04e81206c10e12416908c72c5f22aad411b3aeef   \n",
       "...                ...                                       ...   \n",
       "9492                 0  7bd910d66157ffcadd96bcd9333dd45f318e5c58   \n",
       "9493                 0  d866cae7ea1e471fdbc206287111f1b642373bd9   \n",
       "9494                 0  c56bc2236cbcee87cab5c3d99e97be9f24d8cf50   \n",
       "9495                 0  10c39134ff17a0af1bba131a6036362606785167   \n",
       "9496                 0  c1c0a0c7c7dae3525bc6a4bb07bc0bd69bc62ab0   \n",
       "\n",
       "     has_community_visible_stats content_descriptorids has_leaderboards  \\\n",
       "0                           True                   NaN              NaN   \n",
       "1                            NaN                [2, 5]              NaN   \n",
       "2                            NaN                   NaN              NaN   \n",
       "3                            NaN                   NaN              NaN   \n",
       "4                            NaN                   NaN              NaN   \n",
       "...                          ...                   ...              ...   \n",
       "9492                        True                [2, 5]              NaN   \n",
       "9493                        True             [1, 2, 5]              NaN   \n",
       "9494                        True                   NaN             True   \n",
       "9495                        True                   NaN              NaN   \n",
       "9496                        True                   NaN              NaN   \n",
       "\n",
       "      playtime_2weeks achievement_percentage achievement_completed  \\\n",
       "0                 NaN                    0.0                     0   \n",
       "1                 NaN                   None                  None   \n",
       "2                 NaN                   None                  None   \n",
       "3                 NaN                   None                  None   \n",
       "4                 NaN                   None                  None   \n",
       "...               ...                    ...                   ...   \n",
       "9492              NaN                    0.0                     0   \n",
       "9493              NaN                    0.0                     0   \n",
       "9494              NaN                    0.0                     0   \n",
       "9495              NaN                    0.0                     0   \n",
       "9496              NaN                    0.0                     0   \n",
       "\n",
       "     total_achievements beat_time  \n",
       "0                    54       120  \n",
       "1                  None      1140  \n",
       "2                  None      5040  \n",
       "3                  None       720  \n",
       "4                  None       420  \n",
       "...                 ...       ...  \n",
       "9492                269      None  \n",
       "9493                 54      None  \n",
       "9494                 27      None  \n",
       "9495                463      None  \n",
       "9496                 30      None  \n",
       "\n",
       "[9497 rows x 12 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_games"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## Dataset Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['playtime_windows_forever', 'playtime_mac_forever', 'playtime_linux_forever', 'rtime_last_played', 'playtime_disconnected'] not found in axis\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[14], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m df_games\u001b[38;5;241m.\u001b[39mdrop(\n\u001b[0;32m      2\u001b[0m     [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mplaytime_windows_forever\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m      3\u001b[0m      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mplaytime_mac_forever\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m      4\u001b[0m      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mplaytime_linux_forever\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m      5\u001b[0m      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrtime_last_played\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m      6\u001b[0m      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mplaytime_disconnected\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m      7\u001b[0m      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mplaytime_2weeks\u001b[39m\u001b[38;5;124m'\u001b[39m],\n\u001b[0;32m      8\u001b[0m     axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m,\n\u001b[0;32m      9\u001b[0m     inplace\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m     10\u001b[0m )\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\pandas\\core\\frame.py:5344\u001b[0m, in \u001b[0;36mDataFrame.drop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   5196\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdrop\u001b[39m(\n\u001b[0;32m   5197\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   5198\u001b[0m     labels: IndexLabel \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   5205\u001b[0m     errors: IgnoreRaise \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraise\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m   5206\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m   5207\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   5208\u001b[0m \u001b[38;5;124;03m    Drop specified labels from rows or columns.\u001b[39;00m\n\u001b[0;32m   5209\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   5342\u001b[0m \u001b[38;5;124;03m            weight  1.0     0.8\u001b[39;00m\n\u001b[0;32m   5343\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 5344\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mdrop(\n\u001b[0;32m   5345\u001b[0m         labels\u001b[38;5;241m=\u001b[39mlabels,\n\u001b[0;32m   5346\u001b[0m         axis\u001b[38;5;241m=\u001b[39maxis,\n\u001b[0;32m   5347\u001b[0m         index\u001b[38;5;241m=\u001b[39mindex,\n\u001b[0;32m   5348\u001b[0m         columns\u001b[38;5;241m=\u001b[39mcolumns,\n\u001b[0;32m   5349\u001b[0m         level\u001b[38;5;241m=\u001b[39mlevel,\n\u001b[0;32m   5350\u001b[0m         inplace\u001b[38;5;241m=\u001b[39minplace,\n\u001b[0;32m   5351\u001b[0m         errors\u001b[38;5;241m=\u001b[39merrors,\n\u001b[0;32m   5352\u001b[0m     )\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\pandas\\core\\generic.py:4711\u001b[0m, in \u001b[0;36mNDFrame.drop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4709\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m axis, labels \u001b[38;5;129;01min\u001b[39;00m axes\u001b[38;5;241m.\u001b[39mitems():\n\u001b[0;32m   4710\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m labels \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 4711\u001b[0m         obj \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39m_drop_axis(labels, axis, level\u001b[38;5;241m=\u001b[39mlevel, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m   4713\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m inplace:\n\u001b[0;32m   4714\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_update_inplace(obj)\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\pandas\\core\\generic.py:4753\u001b[0m, in \u001b[0;36mNDFrame._drop_axis\u001b[1;34m(self, labels, axis, level, errors, only_slice)\u001b[0m\n\u001b[0;32m   4751\u001b[0m         new_axis \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mdrop(labels, level\u001b[38;5;241m=\u001b[39mlevel, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m   4752\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 4753\u001b[0m         new_axis \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mdrop(labels, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m   4754\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mget_indexer(new_axis)\n\u001b[0;32m   4756\u001b[0m \u001b[38;5;66;03m# Case for non-unique axis\u001b[39;00m\n\u001b[0;32m   4757\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32mE:\\Users\\saul\\anaconda3\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:7000\u001b[0m, in \u001b[0;36mIndex.drop\u001b[1;34m(self, labels, errors)\u001b[0m\n\u001b[0;32m   6998\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mask\u001b[38;5;241m.\u001b[39many():\n\u001b[0;32m   6999\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m errors \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m-> 7000\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mlabels[mask]\u001b[38;5;241m.\u001b[39mtolist()\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found in axis\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m   7001\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m indexer[\u001b[38;5;241m~\u001b[39mmask]\n\u001b[0;32m   7002\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdelete(indexer)\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['playtime_windows_forever', 'playtime_mac_forever', 'playtime_linux_forever', 'rtime_last_played', 'playtime_disconnected'] not found in axis\""
     ]
    }
   ],
   "source": [
    "df_games.drop(\n",
    "    ['playtime_windows_forever',\n",
    "     'playtime_mac_forever',\n",
    "     'playtime_linux_forever',\n",
    "     'rtime_last_played',\n",
    "     'playtime_disconnected',\n",
    "     'playtime_2weeks'],\n",
    "    axis=1,\n",
    "    inplace=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "appid                           0.000000\n",
      "name                            0.000000\n",
      "playtime_forever                0.000000\n",
      "img_icon_url                    0.000000\n",
      "has_community_visible_stats    41.602611\n",
      "content_descriptorids          88.080446\n",
      "has_leaderboards               91.112983\n",
      "playtime_2weeks                99.968411\n",
      "achievement_percentage         42.265979\n",
      "achievement_completed          42.265979\n",
      "total_achievements             42.265979\n",
      "beat_time                      44.498263\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print((df_games.isnull().sum()/(len(df_games)))*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "appid                             0\n",
      "name                              0\n",
      "playtime_forever                  0\n",
      "img_icon_url                      0\n",
      "has_community_visible_stats       1\n",
      "content_descriptorids          2589\n",
      "has_leaderboards               2397\n",
      "playtime_2weeks                2859\n",
      "achievement_percentage            0\n",
      "achievement_completed             0\n",
      "total_achievements                0\n",
      "beat_time                         0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Eliminar filas con valores vacíos en 'total_achievements' y 'beat_time'\n",
    "df_games = df_games.dropna(subset=['total_achievements', 'beat_time', 'achievement_completed'])\n",
    "df_games[['total_achievements', 'beat_time']] = df_games[['total_achievements', 'beat_time']].astype(int)\n",
    "\n",
    "print(df_games.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 2859 entries, 0 to 5939\n",
      "Data columns (total 12 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   appid                        2859 non-null   int64  \n",
      " 1   name                         2859 non-null   object \n",
      " 2   playtime_forever             2859 non-null   int64  \n",
      " 3   img_icon_url                 2859 non-null   object \n",
      " 4   has_community_visible_stats  2858 non-null   object \n",
      " 5   content_descriptorids        270 non-null    object \n",
      " 6   has_leaderboards             462 non-null    object \n",
      " 7   playtime_2weeks              0 non-null      float64\n",
      " 8   achievement_percentage       2859 non-null   object \n",
      " 9   achievement_completed        2859 non-null   int64  \n",
      " 10  total_achievements           2859 non-null   int32  \n",
      " 11  beat_time                    2859 non-null   int32  \n",
      "dtypes: float64(1), int32(2), int64(3), object(6)\n",
      "memory usage: 268.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df_games.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcula los Z-scores para las dos columnas\n",
    "z_scores_achievements = stats.zscore(df_games['total_achievements'])\n",
    "z_scores_beat_time = stats.zscore(df_games['beat_time'])\n",
    "\n",
    "# Define el umbral para identificar outliers\n",
    "threshold = 4\n",
    "\n",
    "# Crea un DataFrame para los Z-scores\n",
    "df_z_scores = pd.DataFrame({'total_achievements_zscore': z_scores_achievements,'beat_time_zscore': z_scores_beat_time})\n",
    "\n",
    "# Identifica outliers\n",
    "outliers = df_z_scores[(abs(df_z_scores['total_achievements_zscore']) > threshold) | (abs(df_z_scores['beat_time_zscore']) > threshold)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5558rPj5esbGxeW7PysrKcx+SdPPNN0vKea4XL16sP//8M8+8X375perXr6877rijwPsvzusqSe3bt1elSpUc0+fOndOaNWvUu3dv+fr6OvUaGxurc+fOafPmzZKkli1b6rvvvlNcXJxWrlxZ4AUtCtK/f3+nU4/Cw8PVpk0bp3Xl9OnTevLJJxURESF3d3e5u7vL399fZ86c0Z49e/Is86677sozlpmZqUmTJikqKkqenp5yd3eXp6enfv7553yXUVQ//vijDh48qEGDBqlChfO7LH9/f911113avHlzkU47/d///qf+/fsrNDRUbm5u8vDwUHR0tCSVqD9jjON0u9z3ad26dRUTE6OPP/7Y8TqlpaUpMTFR99xzT5E+03HnnXc6TTdr1kyS8pwGeaFly5YpKChIPXr0cFqXbrjhBoWGhjpOP3R3d9fAgQO1ZMkSx2m+WVlZeu+999SzZ09VqVLFsTybzaaBAwc6LS80NFTXX399niuoVa9eXTfddJNjunLlygoODtYNN9ygGjVqOMYbNWrk9FiK8z64lOcnV8uWLXXy5En169dPn376aZGvOFexYkXde++9mjdvnmMbtXbtWv3www8aMWJEkZZx6623OvYX//3vfzV79mwdPXpU7du3d/Txyy+/aO/evY7tu/X5OHTokNNphm+99ZZuvPFGeXt7y93dXR4eHlqzZs0lvd8u1ZVcF4ArgaAElFCjRo3UokULtWjRQl26dNGsWbPUqVMnjR071nF54mPHjik0NDTPB92Dg4Pl7u6uY8eOOY3fd999stvtcnd318iRI/O9X3d3d8cfNLlCQ0Md91eQY8eO5XuFotydV2HzFib3MVpZxw4fPixJ6tu3rzw8PJx+/vnPf8oYo+PHj1/0/j777DO98MIL6tGjh5555pl8azp06OC0/NzPIN1+++1aunSpMjMzNXjwYNWqVUtNmjTRwoULHfMePXrU6eIChT3mor6u1uf92LFjyszM1GuvvZbnucgNfrl/PI0bN06vvPKKNm/erK5du6pKlSrq0KFDka+UVdBrc2GP/fv318yZM/XAAw9o5cqV2rJli5KSklStWjWdPXs2z/z5rUejR4/Ws88+q169eunzzz/XN998o6SkJF1//fX5LqOocvssaN3Nzs7WiRMnCl3G6dOnddttt+mbb77RxIkTtX79eiUlJWnJkiWSVKL+1q5dq3379unuu+9WSkqKTp48qZMnT+qee+5RWlqaY506ceKEsrKyLrpO5bK+t728vC7a4+HDh3Xy5EnHZyQv/ElOTnYKBPfdd5/OnTunDz74QJK0cuVKHTp0SPfee6/T8owxCgkJybO8zZs35wkYlStXztOTp6dnnnFPT09JOX8US8V7H1zK85Nr0KBBmjNnjvbv36+77rpLwcHBatWqlRISEi4676OPPqrU1FTNnz9fkjRz5kzVqlVLPXv2vOi8Us7nkXL3F23atNF9992nBQsWaM+ePXr11Vclnd9GjhkzJs/zERcXJ+n88zF16lQNHz5crVq10scff6zNmzcrKSlJXbp0uaT326W6kusCcCVw1TugFDVr1kwrV67UTz/9pJYtW6pKlSr65ptvZIxx+qP6yJEjyszMVNWqVR1jZ86c0aBBg1S/fn0dPnxYDzzwgD799NM895GZmaljx445/cGQnJwsKe8fEReqUqWKDh06lGc894PiF/ZSHFWqVHHc/4WsY7nLf+211wq8mllISEih9/Xjjz9q0KBBioiI0HvvvVfgldZmzZrldDGJCx9bz5491bNnT6Wnp2vz5s2aPHmy+vfvrzp16qh169aqVq2a/vjjj0L7KM7rKilPn5UqVZKbm5sGDRpU4AfB69atKyknGI8ePVqjR4/WyZMntXr1av3jH/9Q586ddeDAAfn6+hbaa0GvTe66curUKS1btkzjx4/XU0895ahJT08vMLjm97y///77Gjx4sCZNmuQ0/tdff13Spbpz+yxo3a1QoYLT0br8rF27VgcPHtT69esdR5EkXdL3Lc2ePVtSzh+sU6dOzff2YcOGqXLlynJzc7voOnUpci/8kN+H46WcIyK5co8qz507V8OGDdPcuXNVo0YNderUyWl5NptNGzZscASRC+U3VhLFeR+UlnvvvVf33nuvzpw5o6+++krjx49X9+7d9dNPPyk8PLzA+SIiItS1a1e9/vrr6tq1qz777DNNmDBBbm5uJe4l92jYd999J+n8dmrcuHHq06dPvvM0aNBAUs77LSYmRm+++abT7QVdRKesc8W6ABQFQQkoRTt27JB0/rKpHTp00OLFi7V06VKn7/h59913Hbfnevjhh/X7779ry5Yt2rt3r/r27atp06bp73//e577mT9/vtMRpwULFkgq/HsyOnTooMmTJ2vbtm1OV7d69913ZbPZ1K5dO0nF+w+tlHOZ2ylTpui7775zOv0ut6dcbdu2VVBQULFOV7lQamqqevfurezsbH3yySeOK0blJ/ePicJ4eXkpOjpaQUFBWrlypbZv367WrVura9eueu6557R27Vq1b98+33mL87rmx9fXV+3atdP27dvVrFkzx39XLyYoKEh9+/bVn3/+qVGjRum333676KWiFy5c6PhCVCnnVJeNGzdq8ODBknJCjzEmzx+/b7/9tuNqi0Vhs9nyLGP58uX6888/FRERUeTlWDVo0EA1a9bUggULNGbMGMfjOHPmjD7++GPHlfCkgtfd3Hms/c2aNatEPZ04cUKffPKJ2rZtq4kTJ+a5/e2339b8+fO1a9cuNWnSRNHR0frwww/14osvlvgfEoXp3r27PvjgA2VlZalVq1YXrb/33ns1fPhwff311/r88881evRopz/4u3fvrpdeekl//vmn7rnnnlLvN1dJ3wcX4+XlddHtl5+fn7p27aqMjAz16tVLu3fvLjQoSdJjjz2mTp06aciQIXJzc9ODDz54SX3m7i+Cg4Ml5azrkZGR+u677/L8w8Eqv/fbzp07tWnTJoWFhTnGirs9d5XLtS4Al4qgBJTQrl27lJmZKSnntIElS5YoISFBvXv3dvzna/DgwXr99dc1ZMgQ/fbbb2ratKm+/vprTZo0SbGxsY7Pwbz99tt6//33NXfuXDVu3FiNGzfWiBEj9OSTT6pt27ZOnyvy9PTUq6++qtOnT+vmm2/Wxo0bNXHiRHXt2lW33nprgf3+/e9/17vvvqtu3brp+eefV3h4uJYvX6433nhDw4cPd3yPR8WKFRUeHq5PP/1UHTp0UOXKlVW1alXVqVMn3+WOGjVKc+bMUbdu3TRx4kSFhIRo/vz5TpfSlnI+U/Laa69pyJAhOn78uPr27avg4GAdPXpU3333nY4ePZrnv6MXGjx4sPbs2aMxY8YoNTU13/PVvby81Lx58wKX8dxzz+mPP/5Qhw4dVKtWLZ08eVIzZsxw+rzKqFGjtGjRIvXs2VNPPfWUWrZsqbNnzyoxMVHdu3dXu3btivy6FmbGjBm69dZbddttt2n48OGqU6eOUlNT9csvv+jzzz93fGasR48eju8xqVatmvbv36/p06crPDxckZGRF72fI0eOqHfv3nrwwQd16tQpjR8/Xt7e3ho3bpyknC9yvf322/Xyyy87XufExETNnj27WEeCunfvrnnz5qlhw4Zq1qyZvv32W7388stFPuWsIBUqVNCUKVM0YMAAde/eXcOGDVN6erpefvllnTx5Ui+99JKjtmnTppJyntshQ4bIw8NDDRo0UJs2bVSpUiU9/PDDGj9+vDw8PDR//nzHf/KLa/78+Tp37pxGjhyZ7z8nqlSpovnz52v27NmaNm2apk6dqltvvVWtWrXSU089pYiICB0+fFifffaZZs2a5XTEpyT+7//+T/Pnz1dsbKwee+wxtWzZUh4eHvrjjz+0bt069ezZ0ynQ9+vXT6NHj1a/fv2Unp6e53LRbdu21UMPPaR7771XW7du1e233y4/Pz8dOnRIX3/9tZo2barhw4dfUs+5ivo+KI6mTZtqyZIlevPNN3XTTTepQoUKatGihR588EH5+Piobdu2ql69upKTkzV58mQFBgY6Pr9YmI4dOyoqKkrr1q1zfM1CUZ08edKxzbLb7dqzZ48mTZokLy8vpyMos2bNUteuXdW5c2cNHTpUNWvW1PHjx7Vnzx5t27ZNH374oaSc99sLL7yg8ePHKzo6Wj/++KOef/551a1b17Ffkoq/PXely7EuAJfMhReSAK5K+V31LjAw0Nxwww1m6tSp5ty5c071x44dMw8//LCpXr26cXd3N+Hh4WbcuHGOup07dxofHx+nK9QZk3Np15tuusnUqVPHnDhxwhiTc9U7Pz8/s3PnThMTE2N8fHxM5cqVzfDhw83p06ed5rde9c4YY/bv32/69+9vqlSpYjw8PEyDBg3Myy+/nOdKSqtXrzbNmzc3Xl5eRlKe5Vj98MMPpmPHjsbb29tUrlzZ3H///Y5LEV94eXBjjElMTDTdunUzlStXNh4eHqZmzZqmW7du5sMPPyz0PqzPeX4/+V3p6kLLli0zXbt2NTVr1jSenp4mODjYxMbGOi4xnevEiRPmscceM7Vr1zYeHh4mODjYdOvWzeky1xd7XS/s+5FHHsm3n3379pn77rvP1KxZ03h4eJhq1aqZNm3amIkTJzpqXn31VdOmTRtTtWpVx6Xh77//fvPbb78V+lhzrxL23nvvmZEjR5pq1aoZLy8vc9tttzldlcoYY/744w9z1113mUqVKpmKFSuaLl26mF27duVZhwq7CtaJEyfM/fffb4KDg42vr6+59dZbzYYNG/Jcoe1i8rs8uDHGLF261LRq1cp4e3sbPz8/06FDB/Pf//43z/zjxo0zNWrUMBUqVHBa/zZu3Ghat25tfH19TbVq1cwDDzxgtm3blueyy0W56t0NN9xggoODTXp6eoE1t9xyi6lataqj5ocffjB33323qVKliuN1HDp0qGN9Kei5zX0dL3wf5fec2u1288orr5jrr7/eeHt7G39/f9OwYUMzbNgw8/PPP+fpr3///kZSnstTX2jOnDmmVatWxs/Pz/j4+JjrrrvODB482Gn9iY6ONo0bN84zb3h4uOnWrVue8fzeD0V5H+Q+D9btRO76cuFrePz4cdO3b18TFBRkbDab4/V85513TLt27UxISIjx9PQ0NWrUMPfcc4/ZuXNngc+BVXx8vOPrIYrKetU7Nzc3U7t2bdO3b1+zffv2PPXfffedueeee0xwcLDx8PAwoaGhpn379uatt95y1KSnp5sxY8aYmjVrGm9vb3PjjTeapUuXmiFDhuTZDhZ3e56rJFe9uxLrAnAl2YzJ55vxAJRJQ4cO1UcffaTTp0+7uhWUcevXr1e7du304Ycf5rk6H4CSadGihWw2m5KSklzdCoArgFPvAAAACpCSkqJdu3Zp2bJl+vbbb/XJJ5+4uiUAVwhBCQAAoADbtm1Tu3btVKVKFY0fP169evVydUsArhBOvQMAAAAAC75wFgAAAAAsCEoAAAAAYEFQAgAAAACLcn8xh+zsbB08eFAVK1Z0fDs7AAAAgGuPMUapqamqUaOGKlQo/JhRuQ9KBw8eVFhYmKvbAAAAAFBGHDhwQLVq1Sq0ptwHpYoVK0rKeTICAgJc3A3gGna7XatWrVKnTp3k4eHh6nYAAC7AvgDI+W60sLAwR0YoTLkPSrmn2wUEBBCUcM2y2+3y9fVVQEAAO0cAuEaxLwDOK8pHcriYAwAAAABYEJQAAAAAwIKgBAAAAAAW5f4zSgAAAMDlZoxRZmamsrKyXN3KNc3NzU3u7u6l8rVABCUAAADgEmRkZOjQoUNKS0tzdSuQ5Ovrq+rVq8vT0/OSlkNQAgAAAEooOztb+/btk5ubm2rUqCFPT89SOZqB4jPGKCMjQ0ePHtW+ffsUGRl50S+VLQxBCQAAACihjIwMZWdnKywsTL6+vq5u55rn4+MjDw8P7d+/XxkZGfL29i7xsriYAwAAAHCJLuXIBUpXab0WvKIAAAAAYEFQAgAAAAALghIAAACAUmWz2bR06dLLsuyYmBiNGjXqsiz7QgQlAAAA4BpUUOBYunQpV+4TQQkAAABAGWC3213dghOCEgAAQDmXlZWlxMREffXVV0pMTFRWVparW7o2nDlT8M+5c0WvPXu2aLWXQXx8vG644QbNmTNHtWvXlr+/v4YPH66srCxNmTJFoaGhCg4O1osvvphn3kOHDqlr167y8fFR3bp19eGHHzpu++2332Sz2bR48WLFxMTI29tb77//vo4dO6Z+/fqpVq1a8vX1VdOmTbVw4cLL8tguhqAEAABQji1ZskQRERHq2LGjpk6dqo4dOyoiIkJLlixxdWvln79/wT933eVcGxxccG3Xrs61derkX3eZ/Prrr/ryyy+1YsUKLVy4UHPmzFG3bt30xx9/KDExUf/85z/1zDPPaPPmzU7zPfvss7rrrrv03XffaeDAgerXr5/27NnjVPPkk09q5MiR2rNnjzp37qxz587ppptu0rJly7Rr1y499NBDGjRokL755pvL9vgKQlACAAAop5YsWaK+ffuqadOm2rBhgxYuXKgNGzaoadOm6tu3L2EJRZKdna05c+YoKipKPXr0ULt27fTjjz9q+vTpatCgge699141aNBA69evd5rv7rvv1gMPPKD69evrhRdeUIsWLfTaa6851YwaNUp9+vRR3bp1VaNGDdWsWVNjxozRDTfcoHr16unRRx9V586dnY5GXSnuV/weAQAAcNllZWXp8ccfV/fu3bV06VJlZWXp2LFjatWqlZYuXapevXppzJgx6tmzp9zc3Fzdbvl0+nTBt1mf8yNHCq61foHqb7+VuKWSqFOnjipWrOiYDgkJkZubm9MXu4aEhOiI5TG0bt06z/SOHTucxlq0aOE0nZWVpZdeekmLFi3Sn3/+qfT0dKWnp8vPz6+UHk3REZQAAADKoQ0bNui3337TwoULVaFCBafPJVWoUEHjxo1TmzZttGHDBsXExLiu0fKsOH/cX67aQgQEBOjUqVN5xk+ePKmAgADHtIeHh9PtNpst37Hs7OyL3qf1anrWAPTqq69q2rRpmj59upo2bSo/Pz+NGjVKGRkZF112aePUOwAAgHLo0KFDkqQmTZrke3vueG4drj0NGzbU1q1b84wnJSWpQYMGl7x862eWNm/erIYNGxY6z4YNG9SzZ08NHDhQ119/verVq6eff/75knspCYISAABAOVS9enVJ0q5du/K9PXc8tw7Xnri4OP3666965JFH9N133+mnn37S66+/rtmzZ+uJJ5645OV/+OGHmjNnjn766SeNHz9eW7Zs0YgRIwqdJyIiQgkJCdq4caP27NmjYcOGKTk5+ZJ7KQmCEgAAQDl02223qU6dOpo0aVKeU6Kys7M1efJk1a1bV7fddpuLOoSr1alTRxs2bNCvv/6qTp066eabb9a8efM0b9483X333Ze8/AkTJuiDDz5Qs2bN9M4772j+/PmKiooqdJ5nn31WN954ozp37qyYmBiFhoaqV69el9xLSdiMMcYl93yFpKSkKDAwUKdOnXI61xK4ltjtdn3xxReKjY3Nc04xAKD8yr3qXffu3fXEE0/ozz//VM2aNfXyyy9r2bJl+uijj9SnTx9Xt3lVO3funPbt26e6devK29vb1e1Ahb8mxckGXMwBAACgnOrTp48++ugjPf7447r99tsd43Xr1iUkARdBUAIAACjH+vTpo549e2rdunX68ssv1bVrV7Vr145LggMXQVACAAAo59zc3BQdHa0zZ84oOjqakAQUARdzAAAAAAALghIAAABwicr59dGuKqX1WhCUAAAAgBLKvZpsWlqaiztBrtzX4lKv9MtnlAAAAIAScnNzU1BQkI4cOSJJ8vX1lc1mc3FX1yZjjNLS0nTkyBEFBQVd8mfxCEoAAADAJQgNDZUkR1iCawUFBTlek0tBUAIAAAAugc1mU/Xq1RUcHCy73e7qdq5pHh4epXZVR4ISAAAAUArc3Ny49Ho5wsUcAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuXBqX4+HjZbDannwu/RdcYo/j4eNWoUUM+Pj6KiYnR7t27XdgxAAAAgGuBy48oNW7cWIcOHXL8fP/9947bpkyZoqlTp2rmzJlKSkpSaGioOnbsqNTUVBd2DAAAAKC8c3lQcnd3V2hoqOOnWrVqknKOJk2fPl1PP/20+vTpoyZNmuidd95RWlqaFixY4OKuAQAAAJRn7q5u4Oeff1aNGjXk5eWlVq1aadKkSapXr5727dun5ORkderUyVHr5eWl6Ohobdy4UcOGDct3eenp6UpPT3dMp6SkSJLsdrvsdvvlfTBAGZW77vMeAIBrF/sCoHjrv0uDUqtWrfTuu++qfv36Onz4sCZOnKg2bdpo9+7dSk5OliSFhIQ4zRMSEqL9+/cXuMzJkydrwoQJecZXrVolX1/f0n0AwFUmISHB1S0AAFyMfQGuZWlpaUWutRljzGXspVjOnDmj6667TmPHjtUtt9yitm3b6uDBg6pevbqj5sEHH9SBAwe0YsWKfJeR3xGlsLAw/fXXXwoICLjsjwEoi+x2uxISEtSxY0d5eHi4uh0AgAuwLwByskHVqlV16tSpi2YDl596dyE/Pz81bdpUP//8s3r16iVJSk5OdgpKR44cyXOU6UJeXl7y8vLKM+7h4cFGAdc83gcAAPYFuJYVZ913+cUcLpSenq49e/aoevXqqlu3rkJDQ50OD2dkZCgxMVFt2rRxYZcAAAAAyjuXHlEaM2aMevToodq1a+vIkSOaOHGiUlJSNGTIENlsNo0aNUqTJk1SZGSkIiMjNWnSJPn6+qp///6ubBsAAABAOefSoPTHH3+oX79++uuvv1StWjXdcsst2rx5s8LDwyVJY8eO1dmzZxUXF6cTJ06oVatWWrVqlSpWrOjKtgEAAACUcy4NSh988EGht9tsNsXHxys+Pv7KNAQAAAAAKmOfUQIAAACAsoCgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYFFmgtLkyZNls9k0atQox5gxRvHx8apRo4Z8fHwUExOj3bt3u65JAAAAANeEMhGUkpKS9O9//1vNmjVzGp8yZYqmTp2qmTNnKikpSaGhoerYsaNSU1Nd1CkAAACAa4HLg9Lp06c1YMAA/ec//1GlSpUc48YYTZ8+XU8//bT69OmjJk2a6J133lFaWpoWLFjgwo4BAAAAlHfurm7gkUceUbdu3XTHHXdo4sSJjvF9+/YpOTlZnTp1cox5eXkpOjpaGzdu1LBhw/JdXnp6utLT0x3TKSkpkiS73S673X6ZHgVQtuWu+7wHAODaxb4AKN7679Kg9MEHH2jbtm1KSkrKc1tycrIkKSQkxGk8JCRE+/fvL3CZkydP1oQJE/KMr1q1Sr6+vpfYMXB1S0hIcHULAAAXY1+Aa1laWlqRa10WlA4cOKDHHntMq1atkre3d4F1NpvNadoYk2fsQuPGjdPo0aMd0ykpKQoLC1OnTp0UEBBw6Y0DVyG73a6EhAR17NhRHh4erm4HAOAC7AuA82ebFYXLgtK3336rI0eO6KabbnKMZWVl6auvvtLMmTP1448/Sso5slS9enVHzZEjR/IcZbqQl5eXvLy88ox7eHiwUcA1j/cBAIB9Aa5lxVn3XXYxhw4dOuj777/Xjh07HD8tWrTQgAEDtGPHDtWrV0+hoaFOh4czMjKUmJioNm3auKptAAAAANcAlx1Rqlixopo0aeI05ufnpypVqjjGR40apUmTJikyMlKRkZGaNGmSfH191b9/f1e0DAAAAOAa4fKr3hVm7NixOnv2rOLi4nTixAm1atVKq1atUsWKFV3dGgAAAIByrEwFpfXr1ztN22w2xcfHKz4+3iX9AAAAALg2ufwLZwEAAACgrCEoAQAAAIAFQQkAAAAALAhKAAAAAGBRpi7mAKD0ZWRk6LXXXtPatWv1yy+/6NFHH5Wnp6er2wIAACjTOKIElGNjx46Vn5+fxowZoy+++EJjxoyRn5+fxo4d6+rWAAAAyjSOKAHl1NixY/Xyyy8rJCREEyZMkJeXl9LT0zV+/Hi9/PLLkqQpU6a4uEsAAICyiSNKQDmUkZGhadOmKSQkRH/88Yfuu+8+VapUSffdd5/++OMPhYSEaNq0acrIyHB1qwAAAGUSQQkoh9544w1lZmZq4sSJcnd3PnDs7u6u559/XpmZmXrjjTdc1CEAAEDZRlACyqFff/1VktS9e/d8b88dz60DAACAM4ISUA5dd911kqRly5ble3vueG4dAAAAnBGUgHIoLi5O7u7ueuaZZ5SZmel0W2Zmpp577jm5u7srLi7ORR0CAACUbQQloBzy9PTU3//+dx0+fFi1atXS22+/rePHj+vtt99WrVq1dPjwYf3973/n+5QAAAAKwOXBgXIq99Lf06ZNczpy5O7urieeeIJLgwMAABSCI0pAOTZlyhSdOXNGr7zyimJjY/XKK6/ozJkzhCQAAICL4IgSUM55enpq5MiRioiIUGxsrDw8PFzdEgAAQJnHESUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYuDQovfnmm2rWrJkCAgIUEBCg1q1b68svv3TcboxRfHy8atSoIR8fH8XExGj37t0u7BgAAADAtcClQalWrVp66aWXtHXrVm3dulXt27dXz549HWFoypQpmjp1qmbOnKmkpCSFhoaqY8eOSk1NdWXbAAAAAMo5lwalHj16KDY2VvXr11f9+vX14osvyt/fX5s3b5YxRtOnT9fTTz+tPn36qEmTJnrnnXeUlpamBQsWuLJtAAAAAOWcu6sbyJWVlaUPP/xQZ86cUevWrbVv3z4lJyerU6dOjhovLy9FR0dr48aNGjZsWL7LSU9PV3p6umM6JSVFkmS322W32y/vgwDKqNx1n/cAAFy72BcAxVv/XR6Uvv/+e7Vu3Vrnzp2Tv7+/PvnkE0VFRWnjxo2SpJCQEKf6kJAQ7d+/v8DlTZ48WRMmTMgzvmrVKvn6+pZu88BVJiEhwdUtAABcjH0BrmVpaWlFrnV5UGrQoIF27NihkydP6uOPP9aQIUOUmJjouN1msznVG2PyjF1o3LhxGj16tGM6JSVFYWFh6tSpkwICAkr/AQBXAbvdroSEBHXs2FEeHh6ubgcA4ALsC4DzZ5sVhcuDkqenpyIiIiRJLVq0UFJSkmbMmKEnn3xSkpScnKzq1as76o8cOZLnKNOFvLy85OXllWfcw8ODjQKuebwPAADsC3AtK866X+a+R8kYo/T0dNWtW1ehoaFOh4czMjKUmJioNm3auLBDAAAAAOWdS48o/eMf/1DXrl0VFham1NRUffDBB1q/fr1WrFghm82mUaNGadKkSYqMjFRkZKQmTZokX19f9e/f35VtAwAAACjnXBqUDh8+rEGDBunQoUMKDAxUs2bNtGLFCnXs2FGSNHbsWJ09e1ZxcXE6ceKEWrVqpVWrVqlixYqubBsAAABAOefSoDR79uxCb7fZbIqPj1d8fPyVaQgAAAAAVAY/owQAAAAArkZQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgUeKg9Ouvv+qZZ55Rv379dOTIEUnSihUrtHv37lJrDgAAAABcoURBKTExUU2bNtU333yjJUuW6PTp05KknTt3avz48aXaIAAAAABcaSUKSk899ZQmTpyohIQEeXp6OsbbtWunTZs2lVpzAAAAAOAKJQpK33//vXr37p1nvFq1ajp27NglNwUAAAAArlSioBQUFKRDhw7lGd++fbtq1qx5yU0BAAAAgCuVKCj1799fTz75pJKTk2Wz2ZSdna3//ve/GjNmjAYPHlzaPQIAAADAFVWioPTiiy+qdu3aqlmzpk6fPq2oqCjdfvvtatOmjZ555pnS7hEAAAAArij34s5gjNHBgwf1n//8Ry+88IK2bdum7OxsNW/eXJGRkZejRwAAAAC4okoUlCIjI7V7925FRkaqXr16l6MvAAAAAHCZYp96V6FCBUVGRnJ1OwAAAADlVok+ozRlyhQ98cQT2rVrV2n3AwAAAAAuV+xT7yRp4MCBSktL0/XXXy9PT0/5+Pg43X78+PFSaQ4AAAAAXKFEQWn69Oml3AYAAAAAlB0lCkpDhgwp7T4AAAAAoMwoUVCSpKysLC1dulR79uyRzWZTVFSU7rzzTrm5uZVmfwAAAABwxZUoKP3yyy+KjY3Vn3/+qQYNGsgYo59++klhYWFavny5rrvuutLuEwAAAACumBJd9W7kyJG67rrrdODAAW3btk3bt2/X77//rrp162rkyJGl3SMAAAAAXFElOqKUmJiozZs3q3Llyo6xKlWq6KWXXlLbtm1LrTkAAAAAcIUSHVHy8vJSampqnvHTp0/L09PzkpsCAAAAAFcqUVDq3r27HnroIX3zzTcyxsgYo82bN+vhhx/WnXfeWdo9AgAAAMAVVaKg9K9//UvXXXedWrduLW9vb3l7e6tt27aKiIjQjBkzSrtHAAAAALiiSvQZpaCgIH366af65ZdftGfPHhljFBUVpYiIiNLuDwAAAACuuBJ/j5IkRUREEI4AAAAAlDslOvWub9++eumll/KMv/zyy7r77rsvuSkAAAAAcKUSBaXExER169Ytz3iXLl301VdfXXJTAAAAAOBKJQpKBV0G3MPDQykpKZfcFAAAAAC4UomCUpMmTbRo0aI84x988IGioqIuuSkAAAAAcKUSXczh2Wef1V133aVff/1V7du3lyStWbNGCxcu1IcffliqDQIAAADAlVaioHTnnXdq6dKlmjRpkj766CP5+PioWbNmWr16taKjo0u7RwAAAAC4okp8efBu3brle0EHAAAAALjalegzSgcOHNAff/zhmN6yZYtGjRqlf//736XWGAAAAAC4SomCUv/+/bVu3TpJUnJysu644w5t2bJF//jHP/T888+XaoMAAAAAcKWVKCjt2rVLLVu2lCQtXrxYTZs21caNG7VgwQLNmzevNPsDAAAAgCuuREHJbrfLy8tLkrR69WrdeeedkqSGDRvq0KFDpdcdAAAAALhAiYJS48aN9dZbb2nDhg1KSEhQly5dJEkHDx5UlSpVSrVBAAAAALjSShSU/vnPf2rWrFmKiYlRv379dP3110uSPvvsM8cpeQAAAABwtSrR5cFjYmL0119/KSUlRZUqVXKMP/TQQ/L19S215gAAAADAFUp0REmS3NzcVKlSJb300ks6efKkJKlOnToKDg4urd4AAAAAwCVKHJRyTZo0ScePHy+NXgAAAACgTLjkoGSMKY0+AAAAAKDMuOSgBAAAAADlTbGCUocOHbRkyRKnsR9++EHh4eGSpL/++kv16tUrve4AAAAAwAWKFZTWrVune+65R+PHj3eMhYWFyc3NTZKUlZWl/fv3l26HAAAAAHCFFfvUuzfffFMzZsxQ7969dfr06cvREwAAAAC4VLGDUs+ePbVp0yb98MMPat26tf73v/9djr4AAAAAwGVKdDGHRo0aacuWLQoLC9PNN9+s1atXl3ZfAAAAAOAyJb7qXWBgoJYvX64HH3xQsbGxmjZtWmn2BQAAAAAu416cYpvNlmf6pZdeUvPmzXX//fdr7dq1pdocAAAAALhCsY4oFfTlsn/729/09ddf6/vvvy+VpgAAAADAlYp1RGndunWqXLlyvrfdcMMN+vbbb7V8+fJSaQwAAAAAXKVYQSk6OrrQ26tUqaLBgwdfUkMAAAAA4GolvpgDAAAAAJRXBCUAAAAAsHBpUJo8ebJuvvlmVaxYUcHBwerVq5d+/PFHpxpjjOLj41WjRg35+PgoJiZGu3fvdlHHAAAAAK4FLg1KiYmJeuSRR7R582YlJCQoMzNTnTp10pkzZxw1U6ZM0dSpUzVz5kwlJSUpNDRUHTt2VGpqqgs7BwAAAFCeFetiDqVtxYoVTtNz585VcHCwvv32W91+++0yxmj69Ol6+umn1adPH0nSO++8o5CQEC1YsEDDhg1zRdsAAAAAyjmXBiWrU6dOSZLjEuT79u1TcnKyOnXq5Kjx8vJSdHS0Nm7cmG9QSk9PV3p6umM6JSVFkmS322W32y9n+0CZlbvu8x4AgGsX+wKgeOt/mQlKxhiNHj1at956q5o0aSJJSk5OliSFhIQ41YaEhGj//v35Lmfy5MmaMGFCnvFVq1bJ19e3lLsGri4JCQmubgEA4GLsC3AtS0tLK3JtmQlKI0aM0M6dO/X111/nuc1mszlNG2PyjOUaN26cRo8e7ZhOSUlRWFiYOnXqpICAgNJtGrhK2O12JSQkqGPHjvLw8HB1OwAAF2BfAJw/26woykRQevTRR/XZZ5/pq6++Uq1atRzjoaGhknKOLFWvXt0xfuTIkTxHmXJ5eXnJy8srz7iHhwcbBVzzeB8AANgX4FpWnHXfpVe9M8ZoxIgRWrJkidauXau6des63V63bl2FhoY6HSLOyMhQYmKi2rRpc6XbBQAAAHCNcOkRpUceeUQLFizQp59+qooVKzo+kxQYGCgfHx/ZbDaNGjVKkyZNUmRkpCIjIzVp0iT5+vqqf//+rmwdAAAAQDnm0qD05ptvSpJiYmKcxufOnauhQ4dKksaOHauzZ88qLi5OJ06cUKtWrbRq1SpVrFjxCncLAAAA4Frh0qBkjLlojc1mU3x8vOLj4y9/QwAAAAAgF39GCQAAAADKIoISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACxcGpS++uor9ejRQzVq1JDNZtPSpUudbjfGKD4+XjVq1JCPj49iYmK0e/du1zQLAAAA4Jrh0qB05swZXX/99Zo5c2a+t0+ZMkVTp07VzJkzlZSUpNDQUHXs2FGpqalXuFMAAAAA1xJ3V955165d1bVr13xvM8Zo+vTpevrpp9WnTx9J0jvvvKOQkBAtWLBAw4YNy3e+9PR0paenO6ZTUlIkSXa7XXa7vZQfAXB1yF33eQ8AwLWLfQFQvPXfpUGpMPv27VNycrI6derkGPPy8lJ0dLQ2btxYYFCaPHmyJkyYkGd81apV8vX1vWz9AleDhIQEV7cAAHAx9gW4lqWlpRW5tswGpeTkZElSSEiI03hISIj2799f4Hzjxo3T6NGjHdMpKSkKCwtTp06dFBAQcHmaBco4u92uhIQEdezYUR4eHq5uBwDgAuwLgPNnmxVFmQ1KuWw2m9O0MSbP2IW8vLzk5eWVZ9zDw4ONAq55vA8AAOwLcC0rzrpfZi8PHhoaKun8kaVcR44cyXOUCQAAAABKU5kNSnXr1lVoaKjTebQZGRlKTExUmzZtXNgZAAAAgPLOpafenT59Wr/88otjet++fdqxY4cqV66s2rVra9SoUZo0aZIiIyMVGRmpSZMmydfXV/3793dh1wAAAADKO5cGpa1bt6pdu3aO6dyLMAwZMkTz5s3T2LFjdfbsWcXFxenEiRNq1aqVVq1apYoVK7qqZQAAAADXAJcGpZiYGBljCrzdZrMpPj5e8fHxV64pAAAAANe8MvsZJQAAAABwFYISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWLi7uoEr5swZyc0t77ibm+Tt7VxXkAoVJB+fktWmpUnG5F9rs0m+viWrPXtWys4uuA8/v5LVnjsnZWWVTq2vb07fkpSeLmVmlk6tj0/O8yxJGRmS3V46td7e59eV4tTa7Tn1BfHyktzdi1+bmZnzXBTE01Py8Ci81m6X27lzOfebW5uVlfPaFcTDI2fZxa3Nzs5Z10qj1t0957mQct4TaWmlU1uc9z3biPxr2UYUv7YsbyPyq2UbcX66vGwj7Ha5WV9/thE5v7ONKH7t1bqNKOx9Z2XKuVOnThlJ5lTO05P3JzbWeQZf3/zrJGOio51rq1YtuLZFC+fa8PCCa6OinGujogquDQ93rm3RouDaqlWda6OjC6719XWujY0tuNa62vTtW3jt6dPna4cMKbz2yJHztXFxhdfu23e+dsyYwmt37TpfO3584bVbtpyvnTKl8Np1687XzpxZeO2yZedr584tvHbx4vO1ixcXXjt37vnaZcsKrc2cMeN87bp1hS93ypTztVu2FF47fvz52l27Cq8dM+Z87b59hdfGxZ2vPXKk8NohQ87Xnj5deG3fvsZJYbVsI3J+2Eac/ynH2wgzc+b5WrYR5xVWe5VtI85Uq2YyMjLO17KNyME2Isc1sI04JRlJ5tSpU+ZiOPUOAAAAACxsxhjj6iYup5SUFAUGBurUwYMKCAjIW3A1HTLPr5ZD5jm/c8i80Fq73a6VK1eqc48e8shdf67WQ+alUVteT6vJr5ZtRM7vbCOKX8s24vx0OdlG2O12rVy1Sp1795ZH7uvMNiLnd7YRxa+9SrcRKSkpCqxRQ6dOnco/G1zg2glKRXgygPLKbrfriy++UGxs7PmdIwDgmsK+ACheNuDUOwAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADA4qoISm+88Ybq1q0rb29v3XTTTdqwYYOrWwIAAABQjpX5oLRo0SKNGjVKTz/9tLZv367bbrtNXbt21e+//+7q1gAAAACUU+6ubuBipk6dqvvvv18PPPCAJGn69OlauXKl3nzzTU2ePDlPfXp6utLT0x3TKSkpkiS73S673X5lmgbKmNx1n/cAAFy72BcAxVv/y3RQysjI0LfffqunnnrKabxTp07auHFjvvNMnjxZEyZMyDO+atUq+fr6XpY+geJISUnRni3rFFDhbLHmS09P1+HDhy/pvlfOm1Ki+UJCQuTl5VXs+Twrh+m6G9qW6D4BoDwr6b5AuvT9QUn3BVLJ9gfsC1CWpKWlFbm2TAelv/76S1lZWQoJCXEaDwkJUXJycr7zjBs3TqNHj3ZMp6SkKCwsTJ06dVJAQMBl7Rcoijlz5sjz+wV6Kqb4wUOhpd9P0ewq0Vzx69JVr88gNWzYsJT7AYCr2yXtC6Sran/AvgBlSe7ZZkVRpoNSLpvN5jRtjMkzlsvLyyvf/3R4eHjIw8PjsvQHFMddd92llTqjT7KK/kaVpLS0M/r11/+V6D6NMTp8+LBCQkIKfO8U5rrr6snX16/Y83V4srGaNm1a7PkAoLwr6b5AKvn+4FL3BVLJ9gfsC1CWFCcPlOmgVLVqVbm5ueU5enTkyJE8R5mAq0XVqlU1YNjoixeWIrvdri+++EKxsbH8wwAAygD2BUDZV6aveufp6ambbrpJCQkJTuMJCQlq06aNi7oCAAAAUN6V6SNKkjR69GgNGjRILVq0UOvWrfXvf/9bv//+ux5++GFXtwYAAACgnCrzQelvf/ubjh07pueff16HDh1SkyZN9MUXXyg8PNzVrQEAAAAop8p8UJKkuLg4xcXFuboNAAAAANeIMv0ZJQAAAABwBYISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALAgKAEAAACABUEJAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAW7q5u4Io5c0Zyc8s77uYmeXs71xWkQgXJx6dktWlpkjH519pskq9vyWrPnpWyswvuw8+vZLXnzklZWaVT6+ub07ckpadLmZmlU+vjk/M8S1JGhmS3l06tt/f5daU4tXZ7Tn1BvLwkd/fi12Zm5jwXBfH0lDw8Cq+12+V27lzO/ebWZmXlvHYF8fDIWXZxa7Ozc9a10qh1d895LqSc90RaWunUFud9zzYi/1q2EcWvLcvbiPxq2Uacny4v2wi7XW7W159tRM7vbCOKX3u1biMKe99ZmXLu1KlTRpI5lfP05P2JjXWewdc3/zrJmOho59qqVQuubdHCuTY8vODaqCjn2qiogmvDw51rW7QouLZqVefa6OiCa319nWtjYwuuta42ffsWXnv69PnaIUMKrz1y5HxtXFzhtfv2na8dM6bw2l27zteOH1947ZYt52unTCm8dt2687UzZxZeu2zZ+dq5cwuvXbz4fO3ixYXXzp17vnbZskJrM2fMOF+7bl3hy50y5Xztli2F144ff752167Ca8eMOV+7b1/htXFx52uPHCm8dsiQ87WnTxde27evcVJYLduInB+2Eed/yvE2wsyceb6WbcR5hdVeZduIM9WqmYyMjPO1bCNysI3IcQ1sI05JRpI5deqUuRhOvQMAAAAAC5sxxri6icspJSVFgYGBOnXwoAICAvIWXE2HzPOr5ZB5zu8cMi+01m63a+XKlerco4c8ctefq/WQeWnUltfTavKrZRuR8zvbiOLXso04P11OthF2u10rV61S59695ZH7OrONyPmdbUTxa6/SbURKSooCa9TQqVOn8s8GF7h2glIRngygvLLb7friiy8UGxt7fucIALimsC8AipcNOPUOAAAAACwISgAAAABgQVACAAAAAAuCEgAAAABYEJQAAAAAwIKgBAAAAAAWBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAs3F3dwOVmjJEkpaSkuLgTwHXsdrvS0tKUkpIiDw8PV7cDAHAB9gXA+UyQmxEKU+6DUmpqqiQpLCzMxZ0AAAAAKAtSU1MVGBhYaI3NFCVOXcWys7N18OBBVaxYUTabzdXtAC6RkpKisLAwHThwQAEBAa5uBwDgAuwLgJwjSampqapRo4YqVCj8U0jl/ohShQoVVKtWLVe3AZQJAQEB7BwB4BrHvgDXuosdScrFxRwAAAAAwIKgBAAAAAAWBCXgGuDl5aXx48fLy8vL1a0AAFyEfQFQPOX+Yg4AAAAAUFwcUQIAAAAAC4ISAAAAAFgQlAAAAADAgqAElLI6depo+vTpl/U+YmJiNGrUqEJrbDabli5deln7AACUX1difwaUZQQllFs2m63Qn6FDh150/ssZNP744w95enqqYcOGl2X5hw4dUteuXS/Lssua3377TTabTTt27HB1KwCQr6FDhzrtg6pUqaIuXbpo586dpX5fF9t/zZs376L7yPXr1yspKUkPPfRQqfcHXC0ISii3Dh065PiZPn26AgICnMZmzJjh0v7mzZune+65R2lpafrvf/9b6ssPDQ3lErAAUIZ06dLFsQ9as2aN3N3d1b179yvex9/+9jen/WHr1q314IMPOo21adNG1apVk6+v7xXvDygrCEoot0JDQx0/gYGBstlsTmMLFizQddddJ09PTzVo0EDvvfeeY946depIknr37i2bzeaY/vXXX9WzZ0+FhITI399fN998s1avXl3s3owxmjt3rgYNGqT+/ftr9uzZeWr++9//Kjo6Wr6+vqpUqZI6d+6sEydOOG7Pzs7W2LFjVblyZYWGhio+Pt5pfut/FP/880/97W9/U6VKlVSlShX17NlTv/32myRp5cqV8vb21smTJ52WMXLkSEVHRzumN27cqNtvv10+Pj4KCwvTyJEjdebMGafnbeLEiRo8eLD8/f0VHh6uTz/9VEePHlXPnj3l7++vpk2bauvWrU73U5TlTpo0Sffdd58qVqyo2rVr69///rfj9rp160qSmjdvLpvNppiYGEnS+vXr1bJlS/n5+SkoKEht27bV/v37C35hAOAy8vLycuyDbrjhBj355JM6cOCAjh496qgpbFstSUlJSerYsaOqVq2qwMBARUdHa9u2bY7bC9p/XcjHx8dpf+jp6SlfX988Y9ZT72w2m2bNmqXu3bvL19dXjRo10qZNm/TLL78oJiZGfn5+at26tX799Ven+/v888910003ydvbW/Xq1dOECROUmZlZKs8pcDkRlHBN+uSTT/TYY4/p8ccf165duzRs2DDde++9WrdunaScHZEkzZ07V4cOHXJMnz59WrGxsVq9erW2b9+uzp07q0ePHvr999+Ldf/r1q1TWlqa7rjjDg0aNEiLFy9Wamqq4/YdO3aoQ4cOaty4sTZt2qSvv/5aPXr0UFZWlqPmnXfekZ+fn7755htNmTJFzz//vBISEvK9v7S0NLVr107+/v766quv9PXXX8vf319dunRRRkaG7rjjDgUFBenjjz92zJOVlaXFixdrwIABkqTvv/9enTt3Vp8+fbRz504tWrRIX3/9tUaMGOF0X9OmTVPbtm21fft2devWTYMGDdLgwYM1cOBAbdu2TRERERo8eLByv8KtqMt99dVX1aJFC23fvl1xcXEaPny49u7dK0nasmWLJGn16tU6dOiQlixZoszMTPXq1UvR0dHauXOnNm3apIceekg2m61YrxUAXA6nT5/W/PnzFRERoSpVqki6+LZaklJTUzVkyBBt2LBBmzdvVmRkpGJjYx37kIL2X6XlhRde0ODBg7Vjxw41bNhQ/fv317BhwzRu3DjHP8Eu3H6vXLlSAwcO1MiRI/XDDz9o1qxZmjdvnl588cVS7Qu4LAxwDZg7d64JDAx0TLdp08Y8+OCDTjV33323iY2NdUxLMp988slFlx0VFWVee+01x3R4eLiZNm1aofP079/fjBo1yjF9/fXXm//85z+O6X79+pm2bdsWOH90dLS59dZbncZuvvlm8+STT+bb/+zZs02DBg1Mdna24/b09HTj4+NjVq5caYwxZuTIkaZ9+/aO21euXGk8PT3N8ePHjTHGDBo0yDz00ENO97lhwwZToUIFc/bsWcdjHzhwoOP2Q4cOGUnm2WefdYxt2rTJSDKHDh0q8XKzs7NNcHCwefPNN40xxuzbt89IMtu3b3fUHDt2zEgy69evL/B5BIArZciQIcbNzc34+fkZPz8/I8lUr17dfPvtt46aomyrrTIzM03FihXN559/7hgr6v4rV3R0tHnsscfyjFv3Z5LMM88845jO3Z7Pnj3bMbZw4ULj7e3tmL7tttvMpEmTnJb73nvvmerVqxe5P8BVOKKEa9KePXvUtm1bp7G2bdtqz549hc535swZjR07VlFRUQoKCpK/v7/27t1brCNKJ0+e1JIlSzRw4EDH2MCBAzVnzhzHdO4RpcI0a9bMabp69eo6cuRIvrXffvutfvnlF1WsWFH+/v7y9/dX5cqVde7cOccpEgMGDND69et18OBBSdL8+fMVGxurSpUqOZYxb948x/z+/v7q3LmzsrOztW/fvnz7CgkJkSQ1bdo0z1huryVZbu5plAU9XkmqXLmyhg4d6jjqN2PGDB06dKjAegC43Nq1a6cdO3Zox44d+uabb9SpUyd17drVcUpwUbbVR44c0cMPP6z69esrMDBQgYGBOn36dLHPbCipomzjz507p5SUFMdjev7555228bmfh0pLS7siPQMl5e7qBgBXsZ6CZYy56GlZTzzxhFauXKlXXnlFERER8vHxUd++fR2nRBTFggULdO7cObVq1crpvrOzs/XDDz8oKipKPj4+F12Oh4dHnseTnZ2db212drZuuukmzZ8/P89t1apVkyS1bNlS1113nT744AMNHz5cn3zyiebOneu0jGHDhmnkyJF5llG7du18+8p9PvMby+21JMu92OPNNXfuXI0cOVIrVqzQokWL9MwzzyghIUG33HJLofMBwOXg5+eniIgIx/RNN92kwMBA/ec//9HEiROLtK0eOnSojh49qunTpys8PFxeXl5q3bp1sfZDl6Ik2/gJEyaoT58+eZbl7e19OVsFLhlBCdekRo0a6euvv9bgwYMdYxs3blSjRo0c0x4eHk6fCZKkDRs2aOjQoerdu7eknHPML/yQbVHMnj1bjz/+eJ7Lk48cOVJz5szRK6+8ombNmmnNmjWaMGFC8R5YAW688UYtWrRIwcHBCggIKLCuf//+mj9/vmrVqqUKFSqoW7duTsvYvXu3006+tHq71OV6enpKUp7XS8q5wEPz5s01btw4tW7dWgsWLCAoASgTbDabKlSooLNnz0oq2rZ6w4YNeuONNxQbGytJOnDggP766y+nmvz2X65y44036scffyz1fQdwJXDqHa5JTzzxhObNm6e33npLP//8s6ZOnaolS5ZozJgxjpo6depozZo1Sk5OdlxtLiIiQkuWLNGOHTv03XffqX///hc9qnGhHTt2aNu2bXrggQfUpEkTp59+/frp3Xffld1u17hx45SUlKS4uDjt3LlTe/fu1ZtvvplnZ1hUAwYMUNWqVdWzZ09t2LBB+/btU2Jioh577DH98ccfTnXbtm3Tiy++qL59+zr9t+/JJ5/Upk2b9Mgjj2jHjh36+eef9dlnn+nRRx8tUU+ludzg4GD5+PhoxYoVOnz4sE6dOqV9+/Zp3Lhx2rRpk/bv369Vq1bpp59+cgrDAHAlpaenKzk5WcnJydqzZ48effRRnT59Wj169JBUtG11RESE3nvvPe3Zs0fffPONBgwYkOcshPz2X67y3HPP6d1331V8fLx2796tPXv2OI7wA2UdQQnXpF69emnGjBl6+eWX1bhxY82aNUtz5851XFZayrnKWkJCgsLCwtS8eXNJOVd0q1Spktq0aaMePXqoc+fOuvHGG4t8v7Nnz1ZUVFS+XzLbq1cvHT9+XJ9//rnq16+vVatW6bvvvlPLli3VunVrffrpp3J3L9lBYF9fX3311VeqXbu2+vTpo0aNGum+++7T2bNnnf5rGRkZqZtvvlk7d+50XO0uV7NmzZSYmKiff/5Zt912m5o3b65nn31W1atXL1FPpblcd3d3/etf/9KsWbNUo0YN9ezZU76+vtq7d6/uuusu1a9fXw899JBGjBihYcOGXVK/AFBSK1asUPXq1VW9enW1atVKSUlJ+vDDDx37nqJsq+fMmaMTJ06oefPmGjRokEaOHKng4GCn+8lv/+UqnTt31rJly5SQkKCbb75Zt9xyi6ZOnarw8HCX9gUUhc2Y/3+NXgAAAACAJI4oAQAAAEAeBCUAAAAAsCAoAQAAAIAFQQkAAAAALAhKAAAAAGBBUAIAAAAAC4ISAAAAAFgQlAAAAADAgqAEALhqxMfH64YbbnB1GwCAawBBCQBwxSQnJ+vRRx9VvXr15OXlpbCwMPXo0UNr1qxxdWsAADhxd3UDAIBrw2+//aa2bdsqKChIU6ZMUbNmzWS327Vy5Uo98sgj2rt3r6tbBADAgSNKAIArIi4uTjabTVu2bFHfvn1Vv359NW7cWKNHj9bmzZslSb///rt69uwpf39/BQQE6J577tHhw4cLXGZMTIxGjRrlNNarVy8NHTrUMV2nTh1NnDhRgwcPlr+/v8LDw/Xpp5/q6NGjjvtq2rSptm7d6phn3rx5CgoK0sqVK9WoUSP5+/urS5cuOnTokKMmKSlJHTt2VNWqVRUYGKjo6Ght27bNqZf4+HjVrl1bXl5eqlGjhkaOHHkJzyAA4EoiKAEALrvjx49rxYoVeuSRR+Tn55fn9qCgIBlj1KtXLx0/flyJiYlKSEjQr7/+qr/97W+XfP/Tpk1T27ZttX37dnXr1k2DBg3S4MGDNXDgQG3btk0REREaPHiwjDGOedLS0vTKK6/ovffe01dffaXff/9dY8aMcdyempqqIUOGaMOGDdq8ebMiIyMVGxur1NRUSdJHH32kadOmadasWfr555+1dOlSNW3a9JIfCwDgyuDUOwDAZffLL7/IGKOGDRsWWLN69Wrt3LlT+/btU1hYmCTpvffeU+PGjZWUlKSbb765xPcfGxurYcOGSZKee+45vfnmm7r55pt19913S5KefPJJtW7dWocPH1ZoaKgkyW6366233tJ1110nSRoxYoSef/55xzLbt2/vdB+zZs1SpUqVlJiYqO7du+v3339XaGio7rjjDnl4eKh27dpq2bJliR8DAODK4ogSAOCyyz1SY7PZCqzZs2ePwsLCHCFJkqKiohQUFKQ9e/Zc0v03a9bM8XtISIgkOR3dyR07cuSIY8zX19cRkiSpevXqTrcfOXJEDz/8sOrXr6/AwEAFBgbq9OnT+v333yVJd999t86ePat69erpwQcf1CeffKLMzMxLehwAgCuHoAQAuOwiIyNls9kKDTzGmHyDVEHjklShQgWn0+WknCNBVh4eHo7fc5eV31h2dna+8+TWXHhfQ4cO1bfffqvp06dr48aN2rFjh6pUqaKMjAxJUlhYmH788Ue9/vrr8vHxUVxcnG6//fZ8+wMAlD0EJQDAZVe5cmV17txZr7/+us6cOZPn9pMnTyoqKkq///67Dhw44Bj/4YcfdOrUKTVq1Cjf5VarVs3pAgtZWVnatWtX6T+AfGzYsEEjR45UbGysGjduLC8vL/31119ONT4+Prrzzjv1r3/9S+vXr9emTZv0/fffX5H+AACXhqAEALgi3njjDWVlZally5b6+OOP9fPPP2vPnj3617/+pdatW+uOO+5Qs2bNNGDAAG3btk1btmzR4MGDFR0drRYtWuS7zPbt22v58uVavny59u7dq7i4OJ08efKKPJ6IiAi999572rNnj7755hsNGDBAPj4+jtvnzZun2bNna9euXfrf//6n9957Tz4+PgoPD78i/QEALg1BCQBwRdStW1fbtm1Tu3bt9Pjjj6tJkybq2LGj1qxZozfffFM2m01Lly5VpUqVdPvtt+uOO+5QvXr1tGjRogKXed9992nIkCGOQFW3bl21a9fuijyeOXPm6MSJE2revLkGDRqkkSNHKjg42HF7UFCQ/vOf/6ht27Zq1qyZ1qxZo88//1xVqlS5Iv0BAC6NzVhP7gYAAACAaxxHlAAAAADAgqAEAAAAABYEJQAAAACwICgBAAAAgAVBCQAAAAAsCEoAAAAAYEFQAgAAAAALghIAAAAAWBCUAAAAAMCCoAQAAAAAFgQlAAAAALD4f/QSEPt52+XSAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers:\n",
      "      total_achievements_zscore  beat_time_zscore\n",
      "3779                  -0.026458         53.460266\n",
      "4990                  37.795502         -0.018705\n",
      "5806                  37.795502         -0.018705\n"
     ]
    }
   ],
   "source": [
    "# Crea el boxplot\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.boxplot([z_scores_achievements, z_scores_beat_time], labels=['Total Achievements', 'Beat Time'])\n",
    "plt.title('Boxplot de Z-scores para Total Achievements y Beat Time')\n",
    "plt.xlabel('Columnas')\n",
    "plt.ylabel('Z-score')\n",
    "plt.grid(True)\n",
    "plt.axhline(y=threshold, color='r', linestyle='--', label='Umbral')\n",
    "plt.axhline(y=-threshold, color='r', linestyle='--')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "\n",
    "print(\"Outliers:\")\n",
    "print(outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_games = df_games.drop(outliers.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Suponiendo que df_games['total_achievements'] es tu columna que deseas normalizar\n",
    "total_achievements = df_games[['total_achievements']].values\n",
    "\n",
    "# Crea un objeto MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "# Aplica el escalado Min-Max\n",
    "df_games['total_achievements'] = scaler.fit_transform(total_achievements)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Suponiendo que df_games['total_achievements'] es tu columna que deseas normalizar\n",
    "total_achievements = df_games[['beat_time']].values\n",
    "\n",
    "# Crea un objeto MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "# Aplica el escalado Min-Max\n",
    "df_games['beat_time'] = scaler.fit_transform(total_achievements)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trainning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "features = df_games[['total_achievements', 'achievement_completed', 'playtime_forever']]\n",
    "target = df_games['beat_time']\t\n",
    "\n",
    "\n",
    "df_games['beat_time'] = pd.to_numeric(df_games['beat_time'], errors='coerce')\n",
    "df_games['total_achievements'] = pd.to_numeric(df_games['total_achievements'], errors='coerce')\n",
    "\n",
    "df_games['achievement_completed'] = pd.to_numeric(df_games['achievement_completed'], errors='coerce')\n",
    "df_games['playtime_forever'] = pd.to_numeric(df_games['playtime_forever'], errors='coerce')\n",
    "\n",
    "# Divide los datos en conjuntos de entrenamiento y prueba\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.3, random_state=42)\n",
    "\n",
    "# Inicializa el modelo de regresión lineal\n",
    "model = LinearRegression()\n",
    "\n",
    "# Entrena el modelo con los datos de entrenamiento\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "# Realiza predicciones en el conjunto de prueba\n",
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 2856 entries, 0 to 5939\n",
      "Data columns (total 3 columns):\n",
      " #   Column                 Non-Null Count  Dtype  \n",
      "---  ------                 --------------  -----  \n",
      " 0   total_achievements     2856 non-null   float64\n",
      " 1   achievement_completed  2856 non-null   int64  \n",
      " 2   playtime_forever       2856 non-null   int64  \n",
      "dtypes: float64(1), int64(2)\n",
      "memory usage: 89.2 KB\n"
     ]
    }
   ],
   "source": [
    "features.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error Cuadrático Medio: 0.0\n"
     ]
    }
   ],
   "source": [
    "# Evalúa el rendimiento del modelo (en este caso, usando el error cuadrático medio)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "print(f'Error Cuadrático Medio: {mse}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_test['playtime_forever'], y_test, color='black', label='Real')\n",
    "plt.scatter(X_test['playtime_forever'], y_pred, color='blue', label='Predicción')\n",
    "plt.xlabel('Beat Time')\n",
    "plt.ylabel('Playtime Forever')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: [0. 0. 0.]\n",
      "Intercept: 0.0\n"
     ]
    }
   ],
   "source": [
    "coefficients = model.coef_\n",
    "intercept = model.intercept_\n",
    "\n",
    "print(\"Coefficients:\", coefficients)\n",
    "print(\"Intercept:\", intercept)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 0.0\n",
      "R-squared: 1.0\n"
     ]
    }
   ],
   "source": [
    "# Make predictions on the test set\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "# Calculate metrics using the test set\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "\n",
    "print(\"Mean Squared Error:\", mse)\n",
    "print(\"R-squared:\", r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}