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{
"cell_type": "code",
"execution_count": 110,
"id": "f939b9bd-d446-4af6-8035-5f31787811da",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Rank': 'Рейтинг игры в списке', 'Image Link': 'Ссылка на изображение игры', 'Title': 'Название игры', 'Current': 'Текущее количество игроков', '24h Peak': 'Максимальное количество игроков за последние 24 часа', 'All-Time Peak': 'Максимальное количество игроков за все время', 'Genre': 'Жанр игры'}\n"
]
},
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" .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>Rank</th>\n",
" <th>Title</th>\n",
" <th>Current</th>\n",
" <th>24h Peak</th>\n",
" <th>All-Time Peak</th>\n",
" <th>Genre</th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>Counter-Strike 2</td>\n",
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" <td>Dota 2</td>\n",
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" <td>PUBG: BATTLEGROUNDS</td>\n",
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" <td>35151</td>\n",
" <td>Grand Strategy</td>\n",
" </tr>\n",
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" <td>100</td>\n",
" <td>Victoria 3</td>\n",
" <td>15609</td>\n",
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" <td>70100</td>\n",
" <td>Unknown</td>\n",
" </tr>\n",
" </tbody>\n",
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"text/plain": [
" Rank Title Current 24h Peak All-Time Peak \\\n",
"0 1 Counter-Strike 2 1015721 1276702 1818773 \n",
"1 2 Dota 2 702487 805624 1295114 \n",
"2 3 Banana 409758 428540 917272 \n",
"3 4 PUBG: BATTLEGROUNDS 371000 688475 3257248 \n",
"4 5 ELDEN RING 294359 319707 953426 \n",
".. ... ... ... ... ... \n",
"95 96 Soundpad 16028 17064 21920 \n",
"96 97 Supermarket Simulator 15817 15875 51363 \n",
"97 98 V Rising 15803 16275 150645 \n",
"98 99 Squad 15729 19288 35151 \n",
"99 100 Victoria 3 15609 17598 70100 \n",
"\n",
" Genre \n",
"0 First-person Shooter \n",
"1 MOBA (Multiplayer Online Battle Arena) \n",
"2 Unknown \n",
"3 Battle Royale \n",
"4 Action RPG \n",
".. ... \n",
"95 Simulation / Tycoon \n",
"96 Vampire / Open world \n",
"97 Tactical Shooter \n",
"98 Grand Strategy \n",
"99 Unknown \n",
"\n",
"[100 rows x 6 columns]"
]
},
"execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"df = pd.read_csv('sample-dataset-a-b-modules.csv')\n",
"data_description = {\n",
" 'Rank': 'Рейтинг игры в списке',\n",
" 'Image Link': 'Ссылка на изображение игры',\n",
" 'Title': 'Название игры',\n",
" 'Current': 'Текущее количество игроков',\n",
" '24h Peak': 'Максимальное количество игроков за последние 24 часа',\n",
" 'All-Time Peak': 'Максимальное количество игроков за все время',\n",
" 'Genre': 'Жанр игры'\n",
"}\n",
"print(data_description)\n",
"df\n",
"\n",
"#Удаление столбцов\n",
"df = df.drop(columns = ['Image Link'])\n",
"\n",
"#ДЛЯ СТОЛБЦА \"All-Time Peak\"\n",
"# 1. Заменяем запятые на точки (для десятичных разделителей)\n",
"df['All-Time Peak'] = df['All-Time Peak'].str.replace(',', '', regex=False) # Убираем запятые как разделители тысяч\n",
"\n",
"# 2. Преобразуем строку в вещественное число, заменяя ошибки на NaN\n",
"df['All-Time Peak'] = pd.to_numeric(df['All-Time Peak'], errors='coerce')\n",
"\n",
"\n",
"#ДЛЯ СТОЛБЦА \"24h Peak\"\n",
"# 1. Заменяем запятые на точки (для десятичных разделителей)\n",
"df['24h Peak'] = df['24h Peak'].str.replace(',', '', regex=False) # Убираем запятые как разделители тысяч\n",
"\n",
"# 2. Преобразуем строку в вещественное число, заменяя ошибки на NaN\n",
"df['24h Peak'] = pd.to_numeric(df['24h Peak'], errors='coerce')\n",
"\n",
"\n",
"#ДЛЯ СТОЛБЦА \"Current\"\n",
"# 1. Заменяем запятые на точки (для десятичных разделителей)\n",
"df['Current'] = df['Current'].str.replace(',', '', regex=False) # Убираем запятые как разделители тысяч\n",
"\n",
"# 2. Преобразуем строку в вещественное число, заменяя ошибки на NaN\n",
"df['Current'] = pd.to_numeric(df['Current'], errors='coerce')\n",
"#df['All-Time Peak'] = df['All-Time Peak'].fillna(0).astype(int)\n",
"\n",
"#ДЛЯ СТОЛБЦА \"Rank\"\n",
"df['Rank'] = df['Rank'].fillna(0).astype(int)\n",
"\n",
"df.to_csv('1 sample-dataset-a-b-modules.csv')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 112,
"id": "77314f8e-ad83-449b-b4f9-1a3611aef75d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Количество дубликатов в данных: 0\n",
"Количество дубликатов после удаления: 0\n"
]
}
],
"source": [
"# Проверка на дубликаты\n",
"duplicates = df.duplicated().sum()\n",
"print(f\"Количество дубликатов в данных: {duplicates}\")\n",
"\n",
"# Удаление дубликатов\n",
"df_cleaned = df.drop_duplicates()\n",
"\n",
"# Проверяем снова количество дубликатов после удаления\n",
"duplicates_after = df_cleaned.duplicated().sum()\n",
"print(f\"Количество дубликатов после удаления: {duplicates_after}\")"
]
},
{
"cell_type": "code",
"execution_count": 114,
"id": "d1ec44e1-c01f-4d09-8fa9-01bbdd5bce12",
"metadata": {},
"outputs": [
{
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" <td>Simulation / Tycoon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>97</td>\n",
" <td>Supermarket Simulator</td>\n",
" <td>15817</td>\n",
" <td>15875</td>\n",
" <td>51363</td>\n",
" <td>Vampire / Open world</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97</th>\n",
" <td>98</td>\n",
" <td>V Rising</td>\n",
" <td>15803</td>\n",
" <td>16275</td>\n",
" <td>150645</td>\n",
" <td>Tactical Shooter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98</th>\n",
" <td>99</td>\n",
" <td>Squad</td>\n",
" <td>15729</td>\n",
" <td>19288</td>\n",
" <td>35151</td>\n",
" <td>Grand Strategy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>100</td>\n",
" <td>Victoria 3</td>\n",
" <td>15609</td>\n",
" <td>17598</td>\n",
" <td>70100</td>\n",
" <td>Unknown</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>100 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" Rank Title Current 24h Peak All-Time Peak \\\n",
"0 1 Counter-Strike 2 1015721 1276702 1818773 \n",
"1 2 Dota 2 702487 805624 1295114 \n",
"2 3 Banana 409758 428540 917272 \n",
"3 4 PUBG: BATTLEGROUNDS 371000 688475 3257248 \n",
"4 5 ELDEN RING 294359 319707 953426 \n",
".. ... ... ... ... ... \n",
"95 96 Soundpad 16028 17064 21920 \n",
"96 97 Supermarket Simulator 15817 15875 51363 \n",
"97 98 V Rising 15803 16275 150645 \n",
"98 99 Squad 15729 19288 35151 \n",
"99 100 Victoria 3 15609 17598 70100 \n",
"\n",
" Genre \n",
"0 First-person Shooter \n",
"1 MOBA (Multiplayer Online Battle Arena) \n",
"2 Unknown \n",
"3 Battle Royale \n",
"4 Action RPG \n",
".. ... \n",
"95 Simulation / Tycoon \n",
"96 Vampire / Open world \n",
"97 Tactical Shooter \n",
"98 Grand Strategy \n",
"99 Unknown \n",
"\n",
"[100 rows x 6 columns]"
]
},
"execution_count": 114,
"metadata": {},
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],
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"df"
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"source": [
"#КОМАНДЫ\n",
"\n",
"#df['All-Time Peak'] = pd.to_numeric(df['All-Time Peak'], errors='coerce').astype('Int64')\n",
"\n",
"\n",
"\n",
"## Заменяем запятые на точки\n",
"#df['All-Time Peak'] = df['All-Time Peak'].str.replace(',', '.', regex=False)\n",
"\n",
"# Преобразуем тип данных в вещественные числа\n",
"##df['All-Time Peak'] = df['All-Time Peak'].astype(float)\n",
"\n",
"## Преобразуем строку в вещественное число, заменяя ошибки на NaN\n",
"#df['All-Time Peak'] = pd.to_numeric(df['All-Time Peak'], errors='coerce')\n",
"\n",
"## Проверим результат\n",
"#print(df)"
]
},
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],
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"display_name": "Python [conda env:base] *",
"language": "python",
"name": "conda-base-py"
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