用python写一段代码，爬取豆瓣电影信息，进行简单的数据分析并可视化展示

下面是一个使用Python爬取豆瓣电影信息、进行简单数据分析和可视化展示的示例代码：

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

# 爬取电影信息
def get_movie_info():
    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'}
    movie_info = []
    for i in range(0, 250, 25):
        params = {
            'start': str(i),
            'filter': ''
        }
        response = requests.get(url, headers=headers, params=params)
        soup = BeautifulSoup(response.text, 'html.parser')
        movies = soup.find_all('div', class_='item')
        for movie in movies:
            name = movie.find('span', class_='title').text
            rating_num = movie.find('span', class_='rating_num').text
            comment_num = movie.find('div', class_='star').find_all('span')[-1].text[:-3]
            movie_info.append((name, float(rating_num), int(comment_num)))
    return movie_info

# 进行数据分析
def data_analysis(movie_info):
    df = pd.DataFrame(movie_info, columns=['name', 'rating_num', 'comment_num'])
    df['rating_num'].plot(kind='hist', bins=20)
    plt.title('Rating Distribution')
    plt.xlabel('Rating')
    plt.ylabel('Frequency')
    plt.show()
    df.plot(kind='scatter', x='rating_num', y='comment_num')
    plt.title('Rating vs. Comment')
    plt.xlabel('Rating')
    plt.ylabel('Comment')
    plt.show()

if __name__ == '__main__':
    movie_info = get_movie_info()
    data_analysis(movie_info)

该代码使用requests和BeautifulSoup库爬取豆瓣电影Top250的电影信息，包括电影名称、评分和评论数，并将其存储在一个列表中。随后使用pandas和matplotlib库进行数据分析和可视化展示，分别展示了电影评分的分布和评分与评论数之间的关系。