数据结构化与保存

1. 将新闻的正文内容保存到文本文件。

def writeNewsDetail(newid,content):
    f=open(newid+'.txt','a',encoding='utf-8')
    f.write(content)
    f.close()

2. 将新闻数据结构化为字典的列表:

  • 单条新闻的详情-->字典news
  • 一个列表页所有单条新闻汇总-->列表newsls.append(news)
  • 所有列表页的所有新闻汇总列表newstotal.extend(newsls)
    import re
    import requests
    from bs4 import BeautifulSoup
    from datetime import datetime
    def getClickCount(newsUrl):
        newId=re.search("/(d*).html$",newsUrl).group(1)
        clickUrl ="http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80".format(newId)
        resc = requests.get(clickUrl)
        num = re.search(".html('(d*)')",resc.text).group(1)
        return int(num,10)
    def getNewDetail(newsUrl):
        res1 = requests.get(newsUrl)
        res1.encoding = 'utf-8'
        soup1 = BeautifulSoup(res1.text, 'html.parser')
        #标题
        title=soup1.select_one(".show-title").text
        # 正文
        content = soup1.select_one("#content").text
        info = soup1.select_one(".show-info").text
        # 发布时间
        time = datetime.strptime(info.lstrip("发布时间:")[:19], "%Y-%m-%d %H:%M:%S")
        # 作者
        author = info[info.find("作者:"):].split()[0].lstrip("作者:")
        # 来源
        x = info.find("来源:")
        if x >= 0:
            source = info[x:].split()[0].lstrip("来源:")
        else:
            source = ""
        # 摄影
        x = info.find("摄影:")
        if x >= 0:
            shot = info[x:].split()[0].lstrip("摄影:")
        else:
            shot = ""
        return {"title":title,"content":content,"time":time,"author":author,"source":source,"shot":shot,"count":getClickCount(newsUrl)}
    def getnewsls(newslsUrl):
        newsls=[];
        res = requests.get(newslsUrl)
        res.encoding='utf-8'
        soup = BeautifulSoup(res.text, 'html.parser')
        a = soup.select_one(".news-list").select("a")
        for i in a:
            url = i.attrs.get('href')
            newsls.append(getNewDetail(url))
        return newsls
    def getPageNum(newstotalUrl):
        res = requests.get(newstotalUrl)
        res.encoding = 'utf-8'
        soup = BeautifulSoup(res.text, 'html.parser')
        a = soup.select_one("#pages").select("a")[-2]
        return int(a.text,10)
    def getnewstotal(newstotalUrl):
        newstotal=[];
        pageNum=getPageNum(newstotalUrl)
        newstotal.extend(getnewsls(newstotalUrl))
        for i in range(2,pageNum+1):
            newstotal.extend(getnewsls("http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html".format(i)))
        return newstotal
    
    newstotal=getnewstotal("http://news.gzcc.cn/html/xiaoyuanxinwen/")

3. 安装pandas,用pandas.DataFrame(newstotal),创建一个DataFrame对象df.

df = pandas.DataFrame(newsTotal)

4. 通过df将提取的数据保存到csv或excel 文件。

df.to_excel('newsData.xlsx')

5. 用pandas提供的函数和方法进行数据分析:

  • 提取包含点击次数、标题、来源的前6行数据
  • 提取‘学校综合办’发布的,‘点击次数’超过3000的新闻。
  • 提取'国际学院'和'学生工作处'发布的新闻。
      print(df[['click', 'title', 'sources']].head(6))
    
      print(df[(df['click'] > 3000) & (df['sources'] == '学校综合办')])
    
      sou = ['国际学院', '学生工作处']
      print(df[df['sources'].isin(sou)])
原文地址:https://www.cnblogs.com/hehe2333/p/8857334.html