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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"source": [
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"Загрузка данных в DataFrame"
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"Загрузка данных в DataFrame \"Список форбс\"\n",
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"\n",
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"О рейтинге\n",
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"The World's Billionaires (\"Миллиардеры мира\") - ежегодный рейтинг самых богатых миллиардеров мира, составляемый и публикуемый в марте американским деловым журналом Forbes. Общее состояние каждого человека, включенного в список, оценивается в долларах США на основе его документально подтвержденных активов, а также с учетом долгов и других факторов. Этот рейтинг представляет собой список самых богатых людей, зарегистрированных по документам, за исключением тех, чье благосостояние не может быть полностью установлено.\n",
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"\n",
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"Методология Forbes\n",
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"Каждый год Forbes нанимает команду из более чем 50 репортеров из разных стран, чтобы отслеживать деятельность самых богатых людей мира, а иногда и групп или семей, которые делятся богатством. Предварительные опросы рассылаются тем, кто может попасть в список. \n",
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"\n",
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"По данным Forbes, они получили ответы трех типов: одни люди пытаются преувеличить свое богатство, другие сотрудничают, но не раскрывают деталей, а третьи отказываются отвечать на любые вопросы. \n",
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"Затем тщательно изучаются деловые сделки и оценивается стоимость ценных активов – земли, домов, транспортных средств, произведений искусства и т.д. – сделаны.\n",
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"\n",
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"Для проверки данных и уточнения оценки активов отдельных лиц проводятся собеседования. И, наконец, котировки акций, обращающихся на бирже, оцениваются по рыночным ценам примерно за месяц до публикации. \n",
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"Частные компании оцениваются в соответствии с преобладающим соотношением цены к продажам или цены к прибыли. \n",
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"Известные долги вычитаются из активов, чтобы получить окончательную оценку предполагаемого состояния человека в долларах США. \n",
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"Поскольку цены на акции быстро колеблются, истинное состояние человека и его рейтинг на момент публикации могут отличаться от того, в котором он находился на момент составления списка."
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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"name": "stderr",
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"name": "stdout",
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"output_type": "stream",
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"output_type": "stream",
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"text": [
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"text": [
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"<>:3: SyntaxWarning: invalid escape sequence '\\c'\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"<>:3: SyntaxWarning: invalid escape sequence '\\c'\n",
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"Index: 2600 entries, Automotive to Food & Beverage \n",
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"C:\\Users\\New\\AppData\\Local\\Temp\\ipykernel_9568\\2466488670.py:3: SyntaxWarning: invalid escape sequence '\\c'\n",
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"Data columns (total 6 columns):\n",
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" df = pd.read_csv(\"static\\csv\\Forbes Billionaires.csv\", index_col=\"PassengerId\")\n",
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" # Column Non-Null Count Dtype \n",
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"C:\\Users\\New\\AppData\\Local\\Temp\\ipykernel_9568\\2466488670.py:3: SyntaxWarning: invalid escape sequence '\\c'\n",
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"--- ------ -------------- ----- \n",
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" df = pd.read_csv(\"static\\csv\\Forbes Billionaires.csv\", index_col=\"PassengerId\")\n"
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" 0 Rank 2600 non-null int64 \n",
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" 1 Name 2600 non-null object \n",
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" 2 Networth 2600 non-null float64\n",
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" 3 Age 2600 non-null int64 \n",
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" 4 Country 2600 non-null object \n",
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" 5 Source 2600 non-null object \n",
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"dtypes: float64(1), int64(2), object(3)\n",
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"memory usage: 142.2+ KB\n",
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"(2600, 6)\n"
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{
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{
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"ename": "FileNotFoundError",
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"data": {
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"evalue": "[Errno 2] No such file or directory: 'static\\\\csv\\\\Forbes Billionaires.csv'",
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"text/html": [
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"output_type": "error",
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"<div>\n",
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"traceback": [
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"<style scoped>\n",
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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" .dataframe tbody tr th:only-of-type {\n",
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"\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
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" vertical-align: middle;\n",
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"Cell \u001b[1;32mIn[2], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstatic\u001b[39;49m\u001b[38;5;124;43m\\\u001b[39;49m\u001b[38;5;124;43mcsv\u001b[39;49m\u001b[38;5;124;43m\\\u001b[39;49m\u001b[38;5;124;43mForbes Billionaires.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPassengerId\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 5\u001b[0m df\u001b[38;5;241m.\u001b[39minfo()\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28mprint\u001b[39m(df\u001b[38;5;241m.\u001b[39mshape)\n",
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" }\n",
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"File \u001b[1;32md:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1026\u001b[0m, in \u001b[0;36mread_csv\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[0;32m 1013\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[0;32m 1014\u001b[0m dialect,\n\u001b[0;32m 1015\u001b[0m delimiter,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1022\u001b[0m dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[0;32m 1023\u001b[0m )\n\u001b[0;32m 1024\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[1;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
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"\n",
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"File \u001b[1;32md:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:620\u001b[0m, in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m 617\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[0;32m 619\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[1;32m--> 620\u001b[0m parser \u001b[38;5;241m=\u001b[39m \u001b[43mTextFileReader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 622\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[0;32m 623\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
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" .dataframe tbody tr th {\n",
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"File \u001b[1;32md:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1620\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m 1617\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m 1619\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \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-> 1620\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
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" vertical-align: top;\n",
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"File \u001b[1;32md:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1880\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[1;34m(self, f, engine)\u001b[0m\n\u001b[0;32m 1878\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode:\n\u001b[0;32m 1879\u001b[0m mode \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m-> 1880\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1881\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1882\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1883\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1884\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1885\u001b[0m \u001b[43m \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1886\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1887\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1888\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1889\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1890\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \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[0;32m 1891\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n",
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"File \u001b[1;32md:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\pandas\\io\\common.py:873\u001b[0m, in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m 868\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m 869\u001b[0m \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[0;32m 870\u001b[0m \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[0;32m 871\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[0;32m 872\u001b[0m \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[1;32m--> 873\u001b[0m handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[0;32m 874\u001b[0m \u001b[43m \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 875\u001b[0m \u001b[43m \u001b[49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 876\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 877\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 878\u001b[0m \u001b[43m \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 879\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 880\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 881\u001b[0m \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[0;32m 882\u001b[0m handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
|
"\n",
|
||||||
"\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'static\\\\csv\\\\Forbes Billionaires.csv'"
|
" .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>Name</th>\n",
|
||||||
|
" <th>Networth</th>\n",
|
||||||
|
" <th>Age</th>\n",
|
||||||
|
" <th>Country</th>\n",
|
||||||
|
" <th>Source</th>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Industry</th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" </thead>\n",
|
||||||
|
" <tbody>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Automotive</th>\n",
|
||||||
|
" <td>1</td>\n",
|
||||||
|
" <td>Elon Musk</td>\n",
|
||||||
|
" <td>219.0</td>\n",
|
||||||
|
" <td>50</td>\n",
|
||||||
|
" <td>United States</td>\n",
|
||||||
|
" <td>Tesla, SpaceX</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Technology</th>\n",
|
||||||
|
" <td>2</td>\n",
|
||||||
|
" <td>Jeff Bezos</td>\n",
|
||||||
|
" <td>171.0</td>\n",
|
||||||
|
" <td>58</td>\n",
|
||||||
|
" <td>United States</td>\n",
|
||||||
|
" <td>Amazon</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Fashion & Retail</th>\n",
|
||||||
|
" <td>3</td>\n",
|
||||||
|
" <td>Bernard Arnault & family</td>\n",
|
||||||
|
" <td>158.0</td>\n",
|
||||||
|
" <td>73</td>\n",
|
||||||
|
" <td>France</td>\n",
|
||||||
|
" <td>LVMH</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Technology</th>\n",
|
||||||
|
" <td>4</td>\n",
|
||||||
|
" <td>Bill Gates</td>\n",
|
||||||
|
" <td>129.0</td>\n",
|
||||||
|
" <td>66</td>\n",
|
||||||
|
" <td>United States</td>\n",
|
||||||
|
" <td>Microsoft</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>Finance & Investments</th>\n",
|
||||||
|
" <td>5</td>\n",
|
||||||
|
" <td>Warren Buffett</td>\n",
|
||||||
|
" <td>118.0</td>\n",
|
||||||
|
" <td>91</td>\n",
|
||||||
|
" <td>United States</td>\n",
|
||||||
|
" <td>Berkshire Hathaway</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" </tbody>\n",
|
||||||
|
"</table>\n",
|
||||||
|
"</div>"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
" Rank Name Networth Age \\\n",
|
||||||
|
"Industry \n",
|
||||||
|
"Automotive 1 Elon Musk 219.0 50 \n",
|
||||||
|
"Technology 2 Jeff Bezos 171.0 58 \n",
|
||||||
|
"Fashion & Retail 3 Bernard Arnault & family 158.0 73 \n",
|
||||||
|
"Technology 4 Bill Gates 129.0 66 \n",
|
||||||
|
"Finance & Investments 5 Warren Buffett 118.0 91 \n",
|
||||||
|
"\n",
|
||||||
|
" Country Source \n",
|
||||||
|
"Industry \n",
|
||||||
|
"Automotive United States Tesla, SpaceX \n",
|
||||||
|
"Technology United States Amazon \n",
|
||||||
|
"Fashion & Retail France LVMH \n",
|
||||||
|
"Technology United States Microsoft \n",
|
||||||
|
"Finance & Investments United States Berkshire Hathaway "
|
||||||
]
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 3,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"import pandas as pd\n",
|
"import pandas as pd\n",
|
||||||
"\n",
|
"\n",
|
||||||
"df = pd.read_csv(\"static\\csv\\Forbes Billionaires.csv\", index_col=\"PassengerId\")\n",
|
"df = pd.read_csv(\"..//..//static//csv//Forbes Billionaires.csv\", index_col=\"Industry\")\n",
|
||||||
"\n",
|
"\n",
|
||||||
"df.info()\n",
|
"df.info()\n",
|
||||||
"\n",
|
"\n",
|
||||||
Loading…
Reference in New Issue
Block a user