import pandas
import pandas_datareader.data as web
all_data = { ticker: web.get_data_yahoo(ticker) for ticker in ['AAPL', 'IBM', 'MSFT', 'GOOG']}
print(all_data.keys()) # dict_keys(['MSFT', 'IBM', 'AAPL', 'GOOG'])
print(all_data['MSFT'].keys()) # Index(['Open', 'High', 'Low', 'Close', 'Volume', 'Adj Close'], dtype='object')
price = pandas.DataFrame({ticker: data['Adj Close'] for ticker, data in all_data.items()})
print(price.head())
volume = pandas.DataFrame({ticker: data['Volume'] for ticker, data in all_data.items()})
print(volume.tail())
returns = price.pct_change() # change in percentage
print(returns.head())
# correlation
print(returns.MSFT.corr(returns.IBM)) # 0.49532932971
print(returns.MSFT.corr(returns.AAPL)) # 0.389551383559
# covariance
print(returns.MSFT.cov(returns.IBM)) # 8.50115754064e-05
print(returns.MSFT.cov(returns.AAPL)) # 9.15254855961e-05