goodinfo.py

#! /usr/bin/python
# -*- coding: utf-8 -*-
import re
import urllib2
import csv
import pandas as pd

def GetHtmlcode(ID):
    # Get the webpage's source html code
    source = 'http://goodinfo.tw/StockInfo/StockDetail.asp?STOCK_ID='
    url = source + ID
    #print url

    # Header
    headers = { 'User-Agent' : 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/31.0.1650.63 Safari/537.36',
                'Accept' : 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
                'Accept-Charset' : 'Big5,utf-8;q=0.7,*;q=0.3',
                #'Accept-Encoding' : 'gzip,deflate,sdch',
                'Accept-Language' : 'zh-TW,zh;q=0.8,en-US;q=0.6,en;q=0.4,ja;q=0.2' ,
                'Cache-Control' : 'max-age=0',
                'Connection' : 'keep-alive',
                'Cookie' : '427 bytes were stripped',
                'Host' : 'www.goodinfo.tw',
                'Referer' : url }

    # 連到網頁抓取資料
    req= urllib2.Request(url,"",headers)
    response = urllib2.urlopen(req)
    result = response.read().decode('utf-8')
    #print result
    return result

def main():
    page = GetHtmlcode('2103')
    df=pd.read_html(page)
    df2=pd.DataFrame(df[41])
    print df2

if __name__ == "__main__":
    main()

result

0   獲　利　狀　況      (/)    NaN      NaN    NaN    NaN      NaN       NaN     NaN
1                NaN    NaN      NaN    NaN    NaN      NaN       NaN     NaN
2                年/季  營收(億)  稅後淨利(億)  毛利(%)  營益(%)  稅後淨利(%)    ROE(%)  EPS(元)
3           16Q3(累季)    198     9.31   15.8   7.77     5.25  7.87(年估)    1.13
4               2015    260     5.29     13   5.38     2.31      3.32    0.64
5               2014    319     11.4   12.4   6.09      3.9      6.97    1.38
6               2013    344       15   12.4      6     4.98      10.3     1.9
7               2012    171     25.7   13.6   7.14     15.1      15.6    3.27
8               2011    206     57.4   21.9   16.2     27.9      38.1    8.03
9               2010    153     32.8   17.2   11.4     21.5      26.1    5.05
10              2009    103     23.3   20.7   14.5     22.7      19.4    3.59
11              2008    174     27.7   18.7   13.9     15.9      23.4    4.26
12              2007    132     32.6   17.3   10.7     24.7      29.5    5.02
13              2006    116     20.4     14      8     17.6      20.8    3.14