matplotlib做一个豆瓣TOP250导演词云图

好的，以下是实现步骤：

1. 确认需要爬取的数据

我们需要从豆瓣电影TOP250中爬取每个电影的信息，包括导演名称，电影名称和评分。

2. 爬取数据

使用requests和BeautifulSoup库，我们可以从豆瓣电影TOP250的页面中获取电影信息。

import requests
from bs4 import BeautifulSoup

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')
movies = soup.find_all('div', class_='info')

3. 提取导演信息

从每个电影的信息中提取导演名称，我们可以使用正则表达式或BeautifulSoup库来实现。

import re

directors = []
for movie in movies:
    director = movie.find('div', class_='bd').p.text
    director = re.sub('\n.*', '', director).strip()
    directors.append(director)

4. 统计导演出现次数

使用Python中的collections库中的Counter类来统计每个导演出现的次数。

from collections import Counter

director_count = Counter(directors)

5. 生成词云图

使用Python中的wordcloud库来生成词云图。

from wordcloud import WordCloud
import matplotlib.pyplot as plt

wordcloud = WordCloud(font_path='simhei.ttf', background_color='white', max_words=200, width=1200, height=800).generate_from_frequencies(director_count)

plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()

完整代码如下：

import requests
from bs4 import BeautifulSoup
import re
from collections import Counter
from wordcloud import WordCloud
import matplotlib.pyplot as plt

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')
movies = soup.find_all('div', class_='info')

directors = []
for movie in movies:
    director = movie.find('div', class_='bd').p.text
    director = re.sub('\n.*', '', director).strip()
    directors.append(director)

director_count = Counter(directors)

wordcloud = WordCloud(font_path='simhei.ttf', background_color='white', max_words=200, width=1200, height=800).generate_from_frequencies(director_count)

plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()