資料結構化與儲存

2022-01-13 04:18:24 字數 3787 閱讀 2033

1. 將新聞的正文內容儲存到文字檔案。

soup = beautifulsoup(res.text,'


html.parser')


content =soup.select('


.show-content


')[0].text


f=open('


news.txt


','w


',encoding='


utf-8')


f.write(content)


f.close()
2. 將新聞資料結構化為字典的列表:

3. 安裝pandas，用pandas.dataframe(newstotal)，建立乙個dataframe物件df.

4. 通過df將提取的資料儲存到csv或excel 檔案。

5. 用pandas提供的函式和方法進行資料分析：

import


requests


import


reimport


pandas


import


openpyxl


from bs4 import


beautifulsoup


from datetime import


datetime


homepage='


'#newsurl=''


res = requests.get(homepage) #


返回response物件


res.encoding='


utf-8


'soup = beautifulsoup(res.text,'


html.parser')


newscount=int(soup.select('


.a1')[0].text.split('條'


)[0])


newspages = newscount // 10 + 1allnews=


alllistnews=


defget_new_click_count(click_url):


res =requests.get(click_url)


res.encoding = '


utf-8


'soup = beautifulsoup(res.text, '


html.parser


').text


return soup.split("


('#hits').html


")[1].lstrip("


('").rstrip("


');"


)def


get_all_news(newurl):


dictionary={}


res =requests.get(newurl)


res.encoding = '


utf-8


'soup = beautifulsoup(res.text, '


html.parser')


newlist=soup.select('


.news-list


')[0].select('li'


)    


for newitem in


newlist:


title = newitem.select('


.news-list-title


')[0].text


describe = newitem.select('


.news-list-description


')[0].text


newurl=newitem.a.attrs['


href']


newcontenturl = re.search('


(\d\.html)


', newurl).group(1)


newcontenturl2 = newcontenturl.rstrip('


.html')


click_url='


'+newcontenturl2+'


&modelid=80


'newclicktimes=get_new_click_count(click_url)


defget_new_click_content(newurl):


res =requests.get(newurl)


res.encoding = '


utf-8


'soup = beautifulsoup(res.text, '


html.parser')


distributetime = soup.select('


.show-info


')[0].text.split()[0].lstrip('')


author = soup.select('


.show-info


')[0].text.split()[2].lstrip('')


trial = soup.select('


.show-info


')[0].text.split()[3].lstrip('')


orgin = soup.select('


.show-info


')[0].text.split()[4].lstrip('')


photograph = soup.select('


.show-info


')[0].text.split()[5].lstrip('


攝影：'


)            


return


distributetime,author,trial,orgin,photograph


dictionary[


'distributetime


']=get_new_click_content(newurl)[0]


dictionary[


'author


'] = get_new_click_content(newurl)[1]


dictionary[


'trial


'] = get_new_click_content(newurl)[2]


dictionary[


'orgin


'] = get_new_click_content(newurl)[3]


dictionary[


'photograph


'] = get_new_click_content(newurl)[4]


dictionary[


'title


'] =title


dictionary[


'describe


'] =describe


return


allnews


for i in range(2,6):


page='


{}.html


'.format(i)


alllistnews.extend(get_all_news(page))


df =pandas.dataframe(alllistnews)


print


(df)


df.to_excel(


'text.xlsx')


print(df.head(6))


super=df[(df['


clickcount


']>2000)&(df['


source


']=='


學校綜合辦')]


print(super)


截圖如下：
				
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