ffn

import ffn

#%pylab inline

# download price data from Yahoo! Finance. By default,

# the Adj. Close will be used.

prices = ffn.get('aapl,msft', start='2010-01-01')

# let's compare the relative performance of each stock

# we will rebase here to get a common starting point for both securities

ax = prices.rebase().plot()

# now what do the return distributions look like?

returns = prices.to_returns().dropna()

ax = returns.hist()