豆瓣电影top250可视化代码

以下是豆瓣电影Top250的可视化代码示例：

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

# 获取豆瓣电影Top250的URL
url = 'https://movie.douban.com/top250'

# 获取网页HTML代码
response = requests.get(url)
html = response.content.decode('utf-8')

# 使用BeautifulSoup解析HTML代码
soup = BeautifulSoup(html, 'html.parser')

# 获取电影名称、评分和评价数
movies = soup.find_all('div', {'class': 'info'})
names = [movie.find('span', {'class': 'title'}).get_text() for movie in movies]
scores = [float(movie.find('span', {'class': 'rating_num'}).get_text()) for movie in movies]
comments = [int(movie.find('div', {'class': 'star'}).find_all('span')[3].get_text().replace('人评价', '')) for movie in movies]

# 将数据存储到Pandas DataFrame
df = pd.DataFrame({'Name': names, 'Score': scores, 'Comment': comments})

# 绘制散点图
plt.scatter(df['Comment'], df['Score'], alpha=0.5)
plt.xlabel('Number of Comments')
plt.ylabel('Score')
plt.title('Douban Top250 Movies')
plt.show()

这段代码将获取豆瓣电影Top250页面的HTML代码，并使用BeautifulSoup解析数据。然后，将电影名称、评分和评论数存储到Pandas DataFrame中，并绘制散点图以可视化数据。