1.选一个自己感兴趣的主题。
2.用python 编写爬虫程序，从网络上爬取相关主题的数据。
3.对爬了的数据进行文本分析，生成词云。
4.对文本分析结果进行解释说明。
5.写一篇完整的博客，描述上述实现过程、遇到的问题及解决办法、数据分析思想及结论。
6.最后提交爬取的全部数据、爬虫及数据分析源代码。
我所爬取的是校园新闻信息还有多玩LOL新闻版块的新闻
完成作业遇到的问题：
词云wordcloud的安装.
主要是不会怎么借助词云导出。
爬取校园新闻信息并且生成词云
import requests
import string
import re
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud,STOPWORDS,ImageColorGenerator
from datetime import datetime
newsurl='http://news.gzcc.cn/html/xiaoyuanxinwen/'
res = requests.get(newsurl) #返回response对象
res.encoding='utf-8'
from bs4 import BeautifulSoup
soup = BeautifulSoup(res.text,'html.parser')
def getKeynews(content):
content = ''.join(re.findall('[\u4e00-\u9fa5]', content)) # 通过正则表达式选取中文字符数组，拼接为无标点字符内容
# 去掉重复的字符生成集合
newSet = set(jieba._lcut(content)) #划分内容
newDict = {} #定义字典
for i in newSet:
newDict[i] = content.count(i)
deleteList, keynews = [], []
for i in newDict.keys():
if len(i) < 2:
deleteList.append(i) #去掉单音无意义字符
for i in deleteList:
del newDict[i]
dictList = list(newDict.items())
dictList.sort(key=lambda item: item[1], reverse=True) # 排序
for dict in dictList:
keynews.append(dict[0])
return keynews
def writeFilekeynews(keywords):
f = open('Filekeynews', 'a', encoding='utf-8')
for word in keywords:
f.write(" "+word)
f.close()
def writeNewsDetail(content):
f=open('gzccNews.txt','a',encoding='utf-8')
f.write("\n" + content)
f.close()
def getNewsDetail(newsUrl):
resd = requests.get(newsUrl)
resd.encoding = 'utf-8'
soupd = BeautifulSoup(resd.text, 'html.parser')
content=soupd.select('.show-content')[0].text.strip()
writeNewsDetail(content)
keynews = getKeynews(content)
writeFilekeynews(keynews)
# def getWordCloud():
# keynewsTowordcloud = open('keyword.txt', 'r', encoding='utf-8').read()
# print(keynewsTowordcloud)
# backgroud_Image = plt.imread('bg.jpg')
# wc = WordCloud(background_color='white', # 设置背景颜色
# mask=backgroud_Image, # 设置背景图片
# stopwords=STOPWORDS,
# max_words=80, # 设置最大现实的字数
# font_path='C:\Windows\Fonts\AdobeKaitiStd-Regular.otf', # 设置字体格式，如不设置显示不了中文
# max_font_size=80, # 设置字体最大值
# random_state=30, # 设置有多少种随机生成状态，即有多少种配色方案
# )
# wc.generate(keynewsTowordcloud)
# image_colors = ImageColorGenerator(backgroud_Image)
# wc.recolor(color_func=image_colors)
# plt.imshow(wc)
# plt.axis('off')
# plt.show()
def getListPage(listPageUrl):
res=requests.get(listPageUrl)
res.encoding='utf-8'
soup=BeautifulSoup(res.text,'html.parser')
for news in soup.select('li'):
if len(news.select('.news-list-title'))>0:
a=news.select('a')[0].attrs['href']
getNewsDetail(a)
firstPage='http://news.gzcc.cn/html/xiaoyuanxinwen/'
getListPage(firstPage)
for i in range(2,3):
listpageUrl='http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'.format(i)
f=open('keyword.txt','r').read()
wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2,font_path='C:\Windows\Fonts\AdobeKaitiStd-Regular.otf').generate(f)
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wordcloud.to_file('111.png')
爬取多玩LOL新闻版块
# -*- coding : UTF-8 -*- import requests import string import re import jieba import matplotlib.pyplot as plt from wordcloud import WordCloud,STOPWORDS,ImageColorGenerator from datetime import datetime from bs4 import BeautifulSoup # def getKeynews(content): # content = ''.join(re.findall('[\u4e00-\u9fa5]', content)) # 通过正则表达式选取中文字符数组，拼接为无标点字符内容 # # 去掉重复的字符生成集合 # newSet = set(jieba._lcut(content)) #划分内容 # newDict = {} #定义字典 # for i in newSet: # newDict[i] = content.count(i) # deleteList, keynews = [], [] # for i in newDict.keys(): # if len(i) < 2: # deleteList.append(i) #去掉单音无意义字符 # for i in deleteList: # del newDict[i] # dictList = list(newDict.items()) # dictList.sort(key=lambda item: item[1], reverse=True) # 排序 # for dict in dictList: # keynews.append(dict[0]) # return keynews # def writeFilekeynews(keywords): # f = open('Filekeynews6', 'a', encoding='utf-8') # for word in keywords: # f.write(" "+word) # f.close() # def writeNewsDetail(content): # f=open('duowanNews.txt','a',encoding='utf-8') # f.write("\n" + content) # f.close() # def getNewsDetail(newsUrl): # resd = requests.get(newsUrl) # resd.encoding = 'utf-8' # soupd = BeautifulSoup(resd.text, 'html.parser') # content=soupd.select('.show-content')[0].text.strip() # writeNewsDetail(content) # keynews = getKeynews(content) # writeFilekeynews(keynews) # firstPage='http://lol.duowan.com/tag/172578469745.html' # for i in range(2,3): # listpageUrl='http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'.format(i) # f=open('keyword.txt','r').read() # wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2,font_path='C:\Windows\Fonts\AdobeKaitiStd-Regular.otf').generate(f) # plt.imshow(wordcloud) # plt.axis("off") # plt.show() # wordcloud.to_file('111.png') # f=open('keyword2.txt','r').read() # wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2,font_path='C:\Windows\Fonts\AdobeKaitiStd-Regular.otf').generate(f) # plt.imshow(wordcloud) # plt.axis("off") # plt.show() def write_news_to_document(filename, content): f = open(filename, 'w', encoding='utf-8') for detail in content: f.write(detail['content']) f.close() # 将得到的关键词写入文件 def write_keywords_to_document(filename, keywords): f = open(filename, 'w', encoding='utf-8') for word in keywords: f.write(' ' + word) f.close() # 通过jieba分词得到关键词 def get_keywords(filename): f = open(filename, 'r', encoding='utf-8') content = f.read() f.close() word_set = set(jieba.lcut(''.join(re.findall("[\u4e00-\u9fa5_a-zA-Z0-9]", content)))) # 通过正则表达式选取中文,字母及数字字符数组，拼接为无标点字符内容,再转换为字符集合 word_dict = {} delete_list = [] keywords = [] for a in word_set: word_dict[a] = content.count(a) # 生成词云字典 for j in word_dict.keys(): if len(j) < 2: delete_list.append(j) # 生成单字无意义字符列表 for k in delete_list: del word_dict[k] # 在词云字典中删除无意义字符 dict_list = list(word_dict.items()) dict_list.sort(key=lambda item: item[1], reverse=True) for dict in dict_list: keywords.append(dict[0]) print(keywords) write_keywords_to_document("NewsKeyword.txt", keywords) # 获取详细新闻内容 # def get_news_detail(news_url): # res_d = requests.get(news_url) # res_d.encoding = 'gbk' # soup_d = BeautifulSoup(res_d.text, 'html.parser') # content = '' # for p in range(0, len(soup_d.select(".text"))): # content += soup_d.select('.text')[p].text + '\n' # detail = {'content': content} # return detail def get_news_detail(news_url): res_d = requests.get(news_url) res_d.encoding = 'UTF-8' soup_d = BeautifulSoup(res_d.text, 'html.parser') content = '' for i in range(3, 15): content += (soup_d.select('p')[i].text)+ '\n' detail = {'content': content} return detail # 获取新闻列表 def get_news_list(list_url): res = requests.get(list_url) res.encoding = 'utf-8' soup = BeautifulSoup(res.text, 'html.parser') page_detail = [] for newsList in soup.select('.m-list')[0].select('li'): a = newsList.select('a')[0].attrs['href'] b = 'http://lol.duowan.com/' + a news_detail = get_news_detail(b) page_detail.append(news_detail) return page_detail #主函数 url = "http://lol.duowan.com/tag/172578469745.html" Page_detail = get_news_list(url) print(Page_detail) write_news_to_document("News.txt", Page_detail) for i in range(2, 9): news_url = "http://lol.duowan.com/tag/172578469745_{}.html".format(i) Page_detail = get_news_list(url) write_news_to_document("News.txt", Page_detail) get_keywords("News.txt") f=open('NewsKeyword.txt','r').read() wordcloud=WordCloud(background_color="white",width=1000,height=860,margin=2,font_path='C:\Windows\Fonts\AdobeKaitiStd-Regular.otf').generate(f) plt.imshow(wordcloud) plt.axis("off") plt.show() wordcloud.to_file('777.png')
爬取这段的时候是LOL的MSI季中赛决赛结束后夺冠，可以看出RNG战队的UZI、Letme、Karsa、Ming、Xiaohu、Mlxg这几名选手的热度都很高，然后由于UZI、Letme、Karsa，这三名选手的表脸都很亮眼，所以词频数很高。