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{
"cells": [
{
"cell_type": "markdown",
"id": "29cc0f22",
"metadata": {
"toc": true
},
"source": [
"<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
"<div class=\"toc\"><ul class=\"toc-item\"></ul></div>"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "fd5af781",
"metadata": {},
"outputs": [],
"source": [
"from bs4 import BeautifulSoup\n",
"import requests\n",
"import pandas as pd\n",
"import re\n",
"import fake_useragent\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "b6333adb",
"metadata": {},
"outputs": [],
"source": [
"user = fake_useragent.UserAgent().random"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "db46f2ff",
"metadata": {},
"outputs": [],
"source": [
"posters = []\n",
"titles = []\n",
"sources = []\n",
"descriptions = []\n",
"ganres = []\n",
"filters = []\n",
"\n",
"with open('serials.txt') as file:\n",
" lst = file.read().split('\\n')\n",
"s = 10000\n",
"for url in lst[10000:]:\n",
" headers = {\n",
" 'Accept': '*/*',\n",
" 'User-Agent': user\n",
" }\n",
" req = requests.get(url, headers=headers)\n",
" # req = requests.get(url)\n",
" src = req.text\n",
" s +=1\n",
" print(s)\n",
"\n",
" with open('index.html', 'w', encoding=\"utf-8\") as file:\n",
" file.write(src)\n",
"\n",
" with open('index.html', encoding=\"utf-8\") as file:\n",
" src = file.read()\n",
"\n",
" soup = BeautifulSoup(src, 'lxml')\n",
" # тянем название\n",
" try:\n",
" title = soup.find(class_='text text_bold_giant color_white').text\n",
" title = re.sub(r'\\([^)]*\\)', ' ', title).strip()\n",
" titles.append(title)\n",
" except:\n",
" titles.append(None)\n",
" # тянем постер\n",
" try:\n",
" picture_url = soup.find('meta', itemprop='image')\n",
" picture_url = picture_url['content']\n",
" posters.append(picture_url)\n",
" except:\n",
" posters.append(None)\n",
" # тянем жанры\n",
" ganre = soup.find_all('span', class_='badge__text')\n",
" helper = []\n",
" for i in ganre:\n",
" helper.append(i.text)\n",
" ganres.append(helper)\n",
" # тянем описание\n",
" try:\n",
" description = soup.find('div', class_='p-movie-info__description-text').text\n",
" descriptions.append(description)\n",
" except:\n",
" descriptions.append(None)\n",
" # возраст\n",
" try:\n",
" age_filter = soup.find('span', class_='label_restrict').text\n",
" filters.append(age_filter)\n",
" except:\n",
" filters.append(None)\n",
" # url\n",
" sources.append(url)\n",
" if len(sources) % 1 == 0:\n",
" res = pd.DataFrame({'url':sources,\n",
" 'poster':posters,\n",
" 'title':titles,\n",
" 'ganres':ganres,\n",
" 'description':descriptions,\n",
" 'age_limit':filters})\n",
" print(f'{len(res)} saved')\n",
" res.to_csv('DATA.csv')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "1cbe183b",
"metadata": {},
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: 'DATA1.csv'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m df1 \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;43mDATA1.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;43mUnnamed: 0\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m df2 \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDATA2.csv\u001b[39m\u001b[38;5;124m'\u001b[39m, index_col\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUnnamed: 0\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 3\u001b[0m df3 \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDATA3.csv\u001b[39m\u001b[38;5;124m'\u001b[39m, index_col\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUnnamed: 0\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
"File \u001b[0;32m~/ds_bootcamp/.elbrus2/lib/python3.10/site-packages/pandas/io/parsers/readers.py:948\u001b[0m, in \u001b[0;36mread_csv\u001b[0;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[1;32m 935\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m 936\u001b[0m dialect,\n\u001b[1;32m 937\u001b[0m delimiter,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 944\u001b[0m dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[1;32m 945\u001b[0m )\n\u001b[1;32m 946\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m--> 948\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",
"File \u001b[0;32m~/ds_bootcamp/.elbrus2/lib/python3.10/site-packages/pandas/io/parsers/readers.py:611\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 608\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[1;32m 610\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 611\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[1;32m 613\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[1;32m 614\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
"File \u001b[0;32m~/ds_bootcamp/.elbrus2/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1448\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 1445\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[1;32m 1447\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[0;32m-> 1448\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",
"File \u001b[0;32m~/ds_bootcamp/.elbrus2/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1705\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m 1703\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[1;32m 1704\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[0;32m-> 1705\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[1;32m 1706\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1707\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1708\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[1;32m 1709\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[1;32m 1710\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[1;32m 1711\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[1;32m 1712\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[1;32m 1713\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[1;32m 1714\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1715\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[1;32m 1716\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",
"File \u001b[0;32m~/ds_bootcamp/.elbrus2/lib/python3.10/site-packages/pandas/io/common.py:863\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 858\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[1;32m 859\u001b[0m \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[1;32m 860\u001b[0m \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[1;32m 861\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[1;32m 862\u001b[0m \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[0;32m--> 863\u001b[0m handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m 864\u001b[0m \u001b[43m \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 865\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[1;32m 866\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[1;32m 867\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[1;32m 868\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[1;32m 869\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 870\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 871\u001b[0m \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[1;32m 872\u001b[0m handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'DATA1.csv'"
]
}
],
"source": [
"df1 = pd.read_csv('DATA1.csv', index_col='Unnamed: 0')\n",
"df2 = pd.read_csv('DATA2.csv', index_col='Unnamed: 0')\n",
"df3 = pd.read_csv('DATA3.csv', index_col='Unnamed: 0')\n",
"df4 = pd.read_csv('DATA4.csv', index_col='Unnamed: 0')\n",
"df5 = pd.read_csv('DATA5.csv', index_col='Unnamed: 0')\n",
"df6 = pd.read_csv('DATA6.csv', index_col='Unnamed: 0')\n",
"df7 = pd.read_csv('DATA7.csv', index_col='Unnamed: 0')\n",
"df8 = pd.read_csv('DATA8.csv', index_col='Unnamed: 0')\n",
"df9 = pd.read_csv('DATA9.csv', index_col='Unnamed: 0')\n",
"df10 = pd.read_csv('DATA10.csv', index_col='Unnamed: 0')\n",
"df11 = pd.read_csv('DATA11.csv', index_col='Unnamed: 0')\n",
"df12 = pd.read_csv('DATA12.csv', index_col='Unnamed: 0')\n",
"df13 = pd.read_csv('DATA13.csv', index_col='Unnamed: 0')\n",
"df14 = pd.read_csv('DATA14.csv', index_col='Unnamed: 0')\n",
"df15 = pd.read_csv('DATA15 - с 11880.csv', index_col='Unnamed: 0')\n",
"df16 = pd.read_csv('DATA16.csv', index_col='Unnamed: 0')\n",
"df17 = pd.read_csv('DATA17.csv', index_col='Unnamed: 0')\n",
"df18 = pd.read_csv('DATA18.csv', index_col='Unnamed: 0')\n",
"df19 = pd.read_csv('DATA19.csv', index_col='Unnamed: 0')\n",
"df20 = pd.read_csv('DATA20.csv', index_col='Unnamed: 0')\n",
"df21 = pd.read_csv('DATA21.csv', index_col='Unnamed: 0')\n",
"df22 = pd.read_csv('DATA22.csv', index_col='Unnamed: 0')\n",
"df23 = pd.read_csv('DATA23.csv', index_col='Unnamed: 0')\n",
"df24 = pd.read_csv('DATA24.csv', index_col='Unnamed: 0')\n",
"df25 = pd.read_csv('DATA25.csv', index_col='Unnamed: 0')\n",
"df26 = pd.read_csv('DATA26.csv', index_col='Unnamed: 0')\n",
"df27 = pd.read_csv('DATA27.csv', index_col='Unnamed: 0')\n",
"df28 = pd.read_csv('DATA0-5000.csv', index_col='Unnamed: 0')\n",
"df29 = pd.read_csv('DATA2-8.csv', index_col='Unnamed: 0')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8cda987f",
"metadata": {},
"outputs": [],
"source": [
"data = pd.concat([df1, df2, df3, df4, df5, df6, df7, df8, df9, df10, df11, df12, df13, df14, df15, df16, df17, df18, df19, df20, \\\n",
" df21, df22, df23, df24, df25, df26, df27, df28, df29], axis=0).reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "222e1aef",
"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>url</th>\n",
" <th>poster</th>\n",
" <th>title</th>\n",
" <th>ganres</th>\n",
" <th>description</th>\n",
" <th>age_limit</th>\n",
" <th>Unnamed: 0.1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>14969</th>\n",
" <td>https://kino.mail.ru/series_893084_rusalka/</td>\n",
" <td>https://resizer.mail.ru/p/11575246-90fe-53c0-b...</td>\n",
" <td>Русалка</td>\n",
" <td>['мелодрама']</td>\n",
" <td>Наташа Алпатова (Елена Шилова) — простая девуш...</td>\n",
" <td>12 +</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14970</th>\n",
" <td>https://kino.mail.ru/series_838624_sezon_ohoti/</td>\n",
" <td>https://resizer.mail.ru/p/ca54339b-94e8-5813-a...</td>\n",
" <td>Сезон охоты</td>\n",
" <td>['драма', 'мелодрама', 'комедия', 'для взрослых']</td>\n",
" <td>В центре сюжета — история молодого успешного б...</td>\n",
" <td>18 +</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14971</th>\n",
" <td>https://kino.mail.ru/series_783649_smertelnii_...</td>\n",
" <td>https://resizer.mail.ru/p/767707c0-af9c-588a-a...</td>\n",
" <td>Смертельный танец</td>\n",
" <td>['детектив']</td>\n",
" <td>В родное Заречье возвращается танцовщица Настя...</td>\n",
" <td>16 +</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14972</th>\n",
" <td>https://kino.mail.ru/series_781099_fantom/</td>\n",
" <td>https://resizer.mail.ru/p/07f60bae-b56a-58ea-b...</td>\n",
" <td>Фантом</td>\n",
" <td>['боевик']</td>\n",
" <td>Сериал расскажет о деятельности спецслужб Росс...</td>\n",
" <td>12 +</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14973</th>\n",
" <td>https://kino.mail.ru/series_773279_handerbi/</td>\n",
" <td>https://resizer.mail.ru/p/a5ddec74-e1f8-512d-a...</td>\n",
" <td>Хандерби</td>\n",
" <td>['комедия']</td>\n",
" <td>Сюжет сериала «Хандерби» начинается в 1831 год...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" url \\\n",
"14969 https://kino.mail.ru/series_893084_rusalka/ \n",
"14970 https://kino.mail.ru/series_838624_sezon_ohoti/ \n",
"14971 https://kino.mail.ru/series_783649_smertelnii_... \n",
"14972 https://kino.mail.ru/series_781099_fantom/ \n",
"14973 https://kino.mail.ru/series_773279_handerbi/ \n",
"\n",
" poster title \\\n",
"14969 https://resizer.mail.ru/p/11575246-90fe-53c0-b... Русалка \n",
"14970 https://resizer.mail.ru/p/ca54339b-94e8-5813-a... Сезон охоты \n",
"14971 https://resizer.mail.ru/p/767707c0-af9c-588a-a... Смертельный танец \n",
"14972 https://resizer.mail.ru/p/07f60bae-b56a-58ea-b... Фантом \n",
"14973 https://resizer.mail.ru/p/a5ddec74-e1f8-512d-a... Хандерби \n",
"\n",
" ganres \\\n",
"14969 ['мелодрама'] \n",
"14970 ['драма', 'мелодрама', 'комедия', 'для взрослых'] \n",
"14971 ['детектив'] \n",
"14972 ['боевик'] \n",
"14973 ['комедия'] \n",
"\n",
" description age_limit \\\n",
"14969 Наташа Алпатова (Елена Шилова) — простая девуш... 12 + \n",
"14970 В центре сюжета — история молодого успешного б... 18 + \n",
"14971 В родное Заречье возвращается танцовщица Настя... 16 + \n",
"14972 Сериал расскажет о деятельности спецслужб Росс... 12 + \n",
"14973 Сюжет сериала «Хандерби» начинается в 1831 год... NaN \n",
"\n",
" Unnamed: 0.1 \n",
"14969 NaN \n",
"14970 NaN \n",
"14971 NaN \n",
"14972 NaN \n",
"14973 NaN "
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.tail()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "85c382bb",
"metadata": {},
"outputs": [],
"source": [
"data['title'] = data['title'].apply(lambda x: re.sub(r'\\([^)]*\\)', ' ', x).strip() if isinstance(x, str) else x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fe021810",
"metadata": {},
"outputs": [],
"source": [
"data = data.drop(['Unnamed: 0.1'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f317f7e3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 14973 entries, 0 to 14973\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 url 14973 non-null object\n",
" 1 poster 14785 non-null object\n",
" 2 title 14785 non-null object\n",
" 3 ganres 14973 non-null object\n",
" 4 description 14730 non-null object\n",
" 5 age_limit 13105 non-null object\n",
"dtypes: object(6)\n",
"memory usage: 818.8+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "57f21838",
"metadata": {},
"outputs": [],
"source": [
"data = data.drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "da517ed0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.duplicated().sum()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fcf403cf",
"metadata": {},
"outputs": [],
"source": [
"# data.to_csv('data.csv')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".elbrus2",
"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": "3.10.12"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": true,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": true,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|