pandas 提取股票价格

# -*- coding: utf-8 -*-
"""
Created on Fri Apr  7 20:03:39 2017

@author: 罗干
同济大学土木大楼B406
"""

import pandas_datareader.data as web

import numpy as np

import pandas as pd

goog=web.DataReader('GOOG',data_source='google',start='3/14/2017',end='4/14/2017')

outputfile='../go.xls'

goog.to_excel(outputfile)

Out[67]: 
              Open    High     Low   Close   Volume
Date                                               
2017-03-14  843.64  847.24  840.80  845.62   780198
2017-03-15  847.59  848.63  840.77  847.20  1381474
2017-03-16  849.03  850.85  846.13  848.78   977560
2017-03-17  851.61  853.40  847.11  852.12  1716471
2017-03-20  850.01  850.22  845.15  848.40  1231521
2017-03-21  851.40  853.50  829.02  830.46  2463484
2017-03-22  831.91  835.55  827.18  829.59  1401465
2017-03-23  821.00  822.57  812.26  817.58  3487056
2017-03-24  820.08  821.93  808.89  814.43  1981006
2017-03-27  806.95  821.63  803.37  819.51  1894990
2017-03-28  820.41  825.99  814.03  820.92  1620542
2017-03-29  825.00  832.76  822.38  831.41  1786321
2017-03-30  833.50  833.68  829.00  831.50  1055339
2017-03-31  828.97  831.64  827.39  829.56  1401893
2017-04-03  829.22  840.85  829.22  838.55  1671503
2017-04-04  831.36  835.18  829.04  834.57  1045363
2017-04-05  835.51  842.45  830.72  831.41  1555328
2017-04-06  832.40  836.39  826.46  827.88  1254433