From 5880623a1f64f16a7f5e45af982a6b3d0901a1e2 Mon Sep 17 00:00:00 2001 From: pl9p5shn8 <1911627069@qq.com> Date: Tue, 12 Apr 2022 17:55:02 +0800 Subject: [PATCH] ADD file via upload --- 豆瓣——周英红.ipynb | 136 ++++++++++++++++++++++++++++++++++++ 1 file changed, 136 insertions(+) create mode 100644 豆瓣——周英红.ipynb diff --git a/豆瓣——周英红.ipynb b/豆瓣——周英红.ipynb new file mode 100644 index 0000000..bd24410 --- /dev/null +++ b/豆瓣——周英红.ipynb @@ -0,0 +1,136 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 7, + "id": "8494782a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "爬取成功!!!\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import requests\n", + "from bs4 import BeautifulSoup\n", + "import json\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "page_index = range(0, 250, 25)\n", + "def all_html():\n", + " htmls = []\n", + " for idx in page_index:\n", + " url = f\"https://movie.douban.com/top250?start={idx}&filter=\"\n", + " headers = {\n", + " 'User-Agent': \"Mozilla/5.0 (Windows NT 10.0; Win64; x64)\"\n", + " \" AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.60 Safari/\"\n", + " \"537.36 Edg/100.0.1185.29\"\n", + " }\n", + " # requeat请求及响应\n", + " r = requests.get(url, headers=headers)\n", + " if r.status_code != 200:\n", + " raise Exception(\"error\")\n", + " htmls.append(r.text)\n", + " return htmls\n", + "def parse_single_html(html):\n", + " soup=BeautifulSoup(html,'html.parser')\n", + " article_items=(\n", + " soup.find(\"div\",class_=\"article\").find(\"ol\",class_=\"grid_view\").find_all(\"div\",class_=\"item\"))\n", + " datas=[]\n", + " for article_item in article_items:\n", + " rank=article_item.find(\"div\",class_=\"pic\").find(\"em\").get_text()\n", + " info=article_item.find(\"div\",class_=\"info\")\n", + " title=info.find(\"div\",class_=\"hd\").find(\"span\",class_=\"title\").get_text()\n", + " stars=(info.find(\"div\",class_=\"bd\").find(\"div\",class_=\"star\").find_all(\"span\"))\n", + " rating_star=stars[0][\"class\"][0]\n", + " rating_num=stars[1].get_text()\n", + " comments=stars[3].get_text()\n", + " datas.append({\n", + " \"rank\":rank,\n", + " \"title\":title,\n", + " \"rating_start\":rating_star.replace(\"rating\",\"\"),\n", + " \"rating_num\":rating_num,\n", + " \"comments\":comments.replace(\"人评价\",\"\")\n", + " })\n", + " return datas\n", + "all_datas=[]\n", + "htmls=all_html()\n", + "for html in htmls:\n", + " all_datas.extend(parse_single_html(html))\n", + "df = pd.DataFrame(all_datas)\n", + "df.to_excel(\"豆瓣电影Top250(5).xlsx\")\n", + "print(\"爬取成功!!!\")\n", + "\n", + "data = pd.read_excel('豆瓣电影Top250(5).xlsx')\n", + "plt.rcParams['font.sans-serif']=['SimHei']\n", + "x1=data['rank'][:50]\n", + "y1=data['comments'][:50]\n", + "x2=data['rank'][51:101]\n", + "y2=data['comments'][51:101]\n", + "x3=data['rank'][101:151]\n", + "y3=data['comments'][101:151]\n", + "x4=data['rank'][151:200]\n", + "y4=data['comments'][151:200]\n", + "fig, axes = plt.subplots(2, 2)\n", + "axes[0, 0].scatter(x1,y1,color=\"b\",alpha=0.5)\n", + "axes[0, 0].set_xlabel('1~50作品')\n", + "axes[0, 0].set_ylabel('评论数')\n", + "axes[0, 1].plot(x2, y2,color=\"r\",alpha=0.5)\n", + "axes[0, 1].set_xlabel('51~100作品')\n", + "axes[0, 1].set_ylabel('评论数')\n", + "axes[1, 0].plot(x3, y3,color=\"c\",alpha=0.5)\n", + "axes[1, 0].set_xlabel('101~151作品')\n", + "axes[1, 0].set_ylabel('评论数')\n", + "axes[1, 1].scatter(x4, y4,color=\"g\",alpha=0.5)\n", + "axes[1, 1].set_xlabel('150~201作品')\n", + "axes[1, 1].set_ylabel('评论数')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bda3c2fc", + "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": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}