一个完整的大作业

一个完整的大作业——新闻

1.选一个自己感兴趣的主题。

2.网络上爬取相关的数据。

3.进行文本分析,生成词云。

4.对文本分析结果解释说明。

5.写一篇完整的博客,附上源代码、数据爬取及分析结果,形成一个可展示的成果。

 

本次大作业选择的主题是新闻,其链接是http://news.sina.com.cn/world/:

 

网络上爬取相关的数据:

import requests
from bs4 import BeautifulSoup

url = 'http://news.sina.com.cn/world/'
res = requests.get(url)
res.encoding = 'UTF-8'

soup = BeautifulSoup(res.text, 'html.parser')


for news in soup.select('.news-item'):
    h2 = news.select('h2')
    if len(h2) > 0:
        time = news.select('.time')[0].text
        title = h2[0].text
        href = h2[0].select('a')[0]['href']
        print(title,time,href)

 

进行文本分析,生成词云:

import requests
from bs4 import BeautifulSoup
from os import path  
from scipy.misc import imread    
import jieba  
import sys  
import matplotlib.pyplot as plt  
from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator    
text = open('D:\\world.txt').read()  
wordlist = jieba.cut(text)     #cut_all = True  
wl_space_split = " ".join(wordlist)  
#print wl_space_split 
d = path.dirname(__file__)  
nana_coloring = imread(path.join(d, "D:\\1.jpg"))  
my_wordcloud = WordCloud( background_color = 'white',    
                            mask = nana_coloring,         
                            max_words = 5000,            
                            stopwords = STOPWORDS,  
                            max_font_size = 80,        
                            random_state = 20,            )  
 # generate word cloud   
text_dict = {   'you': 2993,   'and': 6625,   'in': 2767,   'was': 2525,   'the': 7845,}
my_wordcloud = WordCloud().generate_from_frequencies(text_dict)
#my_wordcloud.generate(text_dict)  
image_colors = ImageColorGenerator(nana_coloring)   
my_wordcloud.recolor(color_func=image_colors)  
plt.imshow(my_wordcloud)    
plt.axis("off")             
plt.show()   
my_wordcloud.to_file(path.join(d, "cloudimg.png"))  

 

生成云图:

 

由词云可以看出,在国际里面,美国特朗普是最大关注点。

posted @ 2017-10-31 22:06  讲道理  阅读(347)  评论(0编辑  收藏  举报