一个完整的大作业--‘’数据观”官方网站数据爬取

2021-05-15 16:29

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标签:atp   res   ati   end   .com   open   print   主题   panda   

1.选一个自己感兴趣的主题。

‘’数据观”官方网站数据爬取,网页网址为‘http://www.cbdio.com/node_2568.htm’

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2.网络上爬取相关的数据。

import requests
from bs4 import BeautifulSoup

url = http://www.cbdio.com/node_2568.htm res = requests.get(url) res.encoding = utf-8 soup = BeautifulSoup(res.text, html.parser) for items in soup.select(li): if len(items.select(.cb-media-title))>0: title=items.select(.cb-media-title)[0].text#标题 url1=items.select(a)[0][href] url2=http://www.cbdio.com/{}.format(url1)#链接
resd=requests.get(url2) resd.encoding=utf-8 soupd=BeautifulSoup(resd.text,html.parser) source=soupd.select(.cb-article-info)[0].text.strip()#来源 content=soupd.select(.cb-article)[0].text#内容 print("################################################################################") print(标题:,title,\t链接:,url2,source)

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3.进行文本分析,生成词云。

url=http://www.cbdio.com/node_2568.htm
res = requests.get(url)
res.encoding = utf-8
soup = BeautifulSoup(res.text, html.parser)
contentls=[]
for item in soup.select(li):
    if len(item.select(.cb-media-title))>0:
        url1=item.select(a)[0][href]
        url2=http://www.cbdio.com/{}.format(url1)
        resd=requests.get(url2)
        resd.encoding=utf-8
        soupd=BeautifulSoup(resd.text,html.parser)
        cont=soupd.select(.cb-article)[0].text#内容
        contentls.append(cont)
print(contentls)
words=jieba.lcut(content)
ls=[]
counts={}
for word in words:
    ls.append(word)
    if len(word)==1:
        continue
    else:
        counts[word]=counts.get(word,0)+1

items = list(counts.items())
items.sort(key = lambda x:x[1], reverse = True)
for i in range(10):
    word , count = items[i]
    print ("{:2}".format(word,count))


#词云制作
from wordcloud import WordCloud
import matplotlib.pyplot as plt

cy = WordCloud(font_path=msyh.ttc).generate(content)
plt.imshow(cy, interpolation=bilinear)
plt.axis("off")
plt.show()

 

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4.对文本分析结果解释说明。

通过以上数据显示,该中国大数据官网主要的话题是数据以及交易 和政府、企业、专家等。

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。

import requests
from bs4 import BeautifulSoup


def getTheContent(url1):
    res = requests.get(url1)
    res.encoding = utf-8
    soup = BeautifulSoup(res.text, html.parser)
    item={}
    item[title]=soup.select(.cb-article-title)[0].text#标题
    item[url]=url1#链接
    resd=requests.get(item[url])
    resd.encoding=utf-8
    soupd=BeautifulSoup(resd.text,html.parser)
    item[source]=soupd.select(.cb-article-info)[0].text.strip()#来源
    item[content]=soupd.select(.cb-article)[0].text#内容
    return(item)

def getOnePage(pageurl):
    res = requests.get(pageurl)
    res.encoding = utf-8
    soup = BeautifulSoup(res.text, html.parser)
    itemls=[]
    for item in soup.select(li):
        if len(item.select(.cb-media-title))>0:
            url1=item.select(a)[0][href]
            url2=http://www.cbdio.com/{}.format(url1)
            itemls.append(getTheContent(url2))
    return(itemls)



  
#结巴词频统计
import jieba

url=http://www.cbdio.com/node_2568.htm
res = requests.get(url)
res.encoding = utf-8
soup = BeautifulSoup(res.text, html.parser)
contentls=[]
for item in soup.select(li):
    if len(item.select(.cb-media-title))>0:
        url1=item.select(a)[0][href]
        url2=http://www.cbdio.com/{}.format(url1)
        resd=requests.get(url2)
        resd.encoding=utf-8
        soupd=BeautifulSoup(resd.text,html.parser)
        cont=soupd.select(.cb-article)[0].text#内容
        contentls.append(cont)
print(contentls)


##for each in contentls:
##    f = open("1.txt", ‘r‘, ‘utf-8‘)
##    f.write(each)
####    print(each)
##    f.close()
##    print(‘#‘)
##fo=open(‘1.txt‘,‘r‘)
##content=fo.read()
##
content=str(contentls)

words=jieba.lcut(content)
ls=[]
counts={}
for word in words:
    ls.append(word)
    if len(word)==1:
        continue
    else:
        counts[word]=counts.get(word,0)+1

items = list(counts.items())
items.sort(key = lambda x:x[1], reverse = True)
for i in range(10):
    word , count = items[i]
    print ("{:2}".format(word,count))


#词云制作
from wordcloud import WordCloud
import matplotlib.pyplot as plt

cy = WordCloud(font_path=msyh.ttc).generate(content)
plt.imshow(cy, interpolation=bilinear)
plt.axis("off")
plt.show()



#excel导出、数据库存储
import re
import pandas
import sqlite3

itemtotal=[]
for i in range(2,3):
    listurl=http://www.cbdio.com/node_2568.htm
    itemtotal.extend(getOnePage(listurl))
df =pandas.DataFrame(itemtotal)
df.to_excel(BigDataItems.xlsx)
with sqlite3.connect(BigDataItems.sqlite) as db:
    df.to_sql(BigDataItems,con=db)
    print(输出成功!!)

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一个完整的大作业--‘’数据观”官方网站数据爬取

标签:atp   res   ati   end   .com   open   print   主题   panda   

原文地址:http://www.cnblogs.com/huanglinxin/p/7732885.html


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