CODEWITHSUNDEEP
pythonjsonweb-scrapingstock
Elif Y
Elif Y

Reputation: 251

Scraping data table from Chinese stock website using Python

I am trying to scrape part of the data from a Chinese website. The website I want to scrape is: http://data.10jqka.com.cn/market/yybzjsl/HTZQGFYXGSCDSJLZQYYB

I want to get the whole data table below:

enter image description here

There are 86 pages. The code below does not succeed. Can someone give me a hand?

import urllib2, pandas,json

baseurl="http://data.10jqka.com.cn/interface/market/yybzjsl/desc/%s/20/"
def getdata(pgnum):
    cururl = baseurl % str(pgnum)
    ##print cururl
    cn=urllib2.urlopen(cururl)
    jstbl=json.load(cn,encoding='gbk')['data']
    return pandas.read_html('<table>'+jstbl+'</table>')[0]

dataout=pandas.DataFrame()
for pgnum in range(86):
    print pgnum
    totaltry=0
    while True:
        try:
            curdata=getdata(pgnum+1)
            curdata['pgnum']=pgnum+1
            break
        except:
            totaltry+=1
            print 'failed: %s' % totaltry
    dataout=dataout.append(curdata, ignore_index=True)

dataout.to_csv('~/Desktop/dataout.csv')

Upvotes: 0

Views: 1366

Answers (2)

timlukins
timlukins

Reputation: 2724

I would suggest using Beautiful Soup to do the scraping.

UPDATE: something like this (but I would recommend looking at the BS4 documentation for how to really use it)...

import urllib
from bs4 import BeautifulSoup, SoupStrainer

baseurl="http://data.10jqka.com.cn/market/yybzjsl/HTZQGFYXGSCDSJLZQYYB"
page = urllib.urlopen(baseurl) 
getonly = SoupStrainer('table')
table = BeautifulSoup(page, parse_only=getonly)

for row in table("tr"):
  text = ''.join(row.findAll(text=True))
  data = text.strip()
  print data

Gets you:

...    
2015-02-04
吴通通讯
日换手率达20%的证券
10.02%
买入
3489.00
1084.38
7.43%
通信设备
2015-02-03
赢时胜
日换手率达20%的证券
5.57%
卖出
1065.53
646.77
6.07%
计算机应用
2015-01-30
京天利
日涨幅偏离值达7%的证券
10.00%
买入
2363.95
1698.03
13.68%
计算机应用

Upvotes: 1

Mikhail Kashkin
Mikhail Kashkin

Reputation: 1538

There is few python frameworks for web scraping. Take a look into Scrapy and Grab. Both have online documentation and tutorials.

Upvotes: 2

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