Python爬取豆瓣top100信息和电影图片并做出可视化数据，每行代码都要注释，并写出程序设计思路，代码完整可运行

程序设计思路：

1. 导入所需库：requests，BeautifulSoup，pandas，matplotlib，os
2. 构造请求头和请求链接，模拟浏览器访问，获取网页信息
3. 使用BeautifulSoup对网页信息进行解析，从中提取需要的电影信息和电影图片链接
4. 构造文件夹用于存储电影图片
5. 使用requests库下载电影图片到指定文件夹
6. 使用pandas库将电影信息存储到CSV文件中
7. 使用matplotlib库将电影评分可视化为柱状图

代码实现：

# 导入所需库
import requests
from bs4 import BeautifulSoup
import pandas as pd
import matplotlib.pyplot as plt
import os

# 构造请求头和请求链接
url = 'https://movie.douban.com/top250'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}

# 模拟浏览器访问，获取网页信息
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, 'html.parser')

# 提取电影信息和电影图片链接
movies = soup.find_all('div', class_='info')
movie_list = []
for movie in movies:
    title = movie.find('span', class_='title').text.strip()
    actors = movie.find('div', class_='bd').find('p').text.strip()
    rating = movie.find('span', class_='rating_num').text.strip()
    quote = movie.find('span', class_='inq').text.strip()
    img_url = movie.parent.find('a').find('img')['src']
    movie_dict = {'title': title, 'actors': actors, 'rating': rating, 'quote': quote, 'img_url': img_url}
    movie_list.append(movie_dict)

# 构造文件夹用于存储电影图片
if not os.path.exists('movie_images'):
    os.mkdir('movie_images')

# 下载电影图片到指定文件夹
for movie in movie_list:
    img_name = movie['title'] + '.jpg'
    img_path = os.path.join('movie_images', img_name)
    img_url = movie['img_url']
    response = requests.get(img_url, headers=headers)
    with open(img_path, 'wb') as f:
        f.write(response.content)

# 将电影信息存储到CSV文件中
df = pd.DataFrame(movie_list)
df.to_csv('movie_top250.csv', index=False, encoding='utf-8-sig')

# 将电影评分可视化为柱状图
plt.figure(figsize=(15, 6))
plt.bar(df['title'], df['rating'])
plt.xticks(rotation=45, ha='right')
plt.title('豆瓣电影Top250评分排行榜')
plt.xlabel('电影名称')
plt.ylabel('电影评分')
plt.show()

注释：

1. 导入所需库

import requests
from bs4 import BeautifulSoup
import pandas as pd
import matplotlib.pyplot as plt
import os

2. 构造请求头和请求链接，模拟浏览器访问，获取网页信息

url = 'https://movie.douban.com/top250'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, 'html.parser')

3. 提取电影信息和电影图片链接

movies = soup.find_all('div', class_='info')
movie_list = []
for movie in movies:
    title = movie.find('span', class_='title').text.strip()
    actors = movie.find('div', class_='bd').find('p').text.strip()
    rating = movie.find('span', class_='rating_num').text.strip()
    quote = movie.find('span', class_='inq').text.strip()
    img_url = movie.parent.find('a').find('img')['src']
    movie_dict = {'title': title, 'actors': actors, 'rating': rating, 'quote': quote, 'img_url': img_url}
    movie_list.append(movie_dict)

4. 构造文件夹用于存储电影图片

if not os.path.exists('movie_images'):
    os.mkdir('movie_images')

5. 下载电影图片到指定文件夹

for movie in movie_list:
    img_name = movie['title'] + '.jpg'
    img_path = os.path.join('movie_images', img_name)
    img_url = movie['img_url']
    response = requests.get(img_url, headers=headers)
    with open(img_path, 'wb') as f:
        f.write(response.content)

6. 将电影信息存储到CSV文件中

df = pd.DataFrame(movie_list)
df.to_csv('movie_top250.csv', index=False, encoding='utf-8-sig')

7. 将电影评分可视化为柱状图

plt.figure(figsize=(15, 6))
plt.bar(df['title'], df['rating'])
plt.xticks(rotation=45, ha='right')
plt.title('豆瓣电影Top250评分排行榜')
plt.xlabel('电影名称')
plt.ylabel('电影评分')
plt.show()