python唐诗宋词经典案例

下面是一个使用Python爬虫和文本处理库jieba实现的唐诗宋词经典案例：

1. 爬取唐诗宋词文本数据

import requests

# 爬取唐诗文本
def crawl_tang_poetry():
    url = 'https://raw.githubusercontent.com/Werneror/Poetry/master/poetry_tang.txt'
    response = requests.get(url)
    text = response.text
    return text

# 爬取宋词文本
def crawl_song_ci():
    url = 'https://raw.githubusercontent.com/Werneror/Poetry/master/poetry_song.txt'
    response = requests.get(url)
    text = response.text
    return text

2. 分词并统计词频

import jieba
from collections import Counter

# 分词并统计词频
def word_count(text):
    words = jieba.cut(text)
    counter = Counter(words)
    return counter

# 统计唐诗词频
tang_poetry = crawl_tang_poetry()
tang_counter = word_count(tang_poetry)

# 统计宋词词频
song_ci = crawl_song_ci()
song_counter = word_count(song_ci)

3. 生成词云图

from wordcloud import WordCloud
import matplotlib.pyplot as plt

# 生成唐诗词云图
tang_wordcloud = WordCloud(width=800, height=600, background_color='white', font_path='msyh.ttc').generate_from_frequencies(tang_counter)
plt.imshow(tang_wordcloud)
plt.axis('off')
plt.show()

# 生成宋词词云图
song_wordcloud = WordCloud(width=800, height=600, background_color='white', font_path='msyh.ttc').generate_from_frequencies(song_counter)
plt.imshow(song_wordcloud)
plt.axis('off')
plt.show()

通过以上三步，我们就可以得到唐诗宋词的词云图了。这个案例可以帮助我们学习Python爬虫、文本处理和数据可视化的基础知识。