py数据结构化与保存

1. 将新闻的正文内容保存到文本文件。

content_info['content'] = soup.select('#content')[0].text
    with open('test.txt', 'a', encoding='UTF-8') as story:
        story.write(content_info['content'])

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
  

  def gzcc_content_info(content_url):
      content_info = {}
      resp = requests.get(content_url)
      resp.encoding = 'utf-8'
      soup = BeautifulSoup(resp.text, 'html.parser')
      match_str = {'author': '作者：(.*)s+[审核]?', 'examine': '审核：(.*)s+[来源]?', 'source': '来源：(.*)s+[摄影]?', 
                   'photography': '摄影：(.*)s+[点击]'}
      remarks = soup.select('.show-info')[0].text
      for i in match_str:
          if re.match('.*' + match_str[i], remarks):
              content_info[i] = re.search(match_str[i], remarks).group(1).split("xa0")[0]
          else:
              content_info[i] = "  "
      time = re.search('d{4}-d{2}-d{2}sd{2}:d{2}:d{2}', remarks).group()
      content_info['time'] = datetime.strptime(time, '%Y-%m-%d %H:%M:%S')
      content_info['title'] = soup.select('.show-title')[0].text
      content_info['url'] = content_url
      content_info['clicks'] = gzcc_content_clicks(content_url)
      return content_info

• 一个列表页所有单条新闻汇总-->列表newsls.append(news)
  

  def gzcc_list_page(page_url):
      page_news = []
      res = requests.get(page_url)
      res.encoding = 'utf-8'
      soup = BeautifulSoup(res.text, 'html.parser')
      news_list = soup.select('.news-list')[0]
      news_point = news_list.select('li')
      for i in news_point:
          a = i.select('a')[0]['href']
          page_news.append(gzcc_content_info(a))
      return page_news

• 所有列表页的所有新闻汇总列表newstotal.extend(newsls)
  

  all_news = []
  url = 'http://news.gzcc.cn/html/xiaoyuanxinwen/'
  res = requests.get(url)
  res.encoding = 'utf-8'
  soup = BeautifulSoup(res.text, 'html.parser')
  n = int(soup.select('#pages')[0].select("a")[-2].text)
  all_news.extend(gzcc_list_page(url))
  for i in range(2, n):
      all_news.extend(gzcc_list_page('http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'.format(i)))

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

df = pandas.DataFrame(all_news)

4. 通过df将提取的数据保存到csv或excel 文件。

df.to_excel('news.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
  

  df[['clicks', 'title', 'source']].head(6)

• 提取‘学校综合办’发布的，‘点击次数’超过3000的新闻。
  

  df[(df['clicks'] > 3000) & (df['source'] == '学校综合办')]

• 提取'国际学院'和'学生工作处'发布的新闻。
  

  news_info = ['国际学院', '学生工作处']
  df[df['source'].isin(news_info)]