In [58]:
import pandas.io.data as pdweb
import datetime

In [ ]:
prices = pdweb.get_data_yahoo(['RAX','MSFT','GOOGL'], 
                               start=datetime.datetime(2014, 1, 1), 
                               end=datetime.datetime(2015, 1, 1))['Adj Close']
prices.head()

In [ ]:
volume = pdweb.get_data_yahoo(['RAX','MSFT','GOOGL'], 
                               start=datetime.datetime(2014, 1, 1), 
                               end=datetime.datetime(2015, 1, 1))['Volume']

In [ ]:
volume.head()

In [55]:
#Lets get the return
rets = prices.pct_change()

In [56]:
#Get the correlation of the stocks
corr = rets.corr

In [57]:
#Lets see the prices over time to get a very rough idea of the correlation between the stock prices
prices.plot()


Out[57]:
<matplotlib.axes._subplots.AxesSubplot at 0x12082eef0>

In [ ]: