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%matplotlib


    

In [1]:

    

import numpy as np
import pandas as pd
import pandas.io.data as web
goog = web.DataReader('GOOG', data_source='yahoo', start='3/14/2009', end='4/14/2009')
goog.tail()
goog['Log_Ret'] = np.log(goog['Close'] / goog['Close'].shift(1))
goog['Volatility'] = pd.rolling_std(goog['Log_Ret'], window=252) * np.sqrt(252)
goog[['Close','Volatility']].plot(subplots=True, color='blue', figsize=(8,6))


    

    
Out[1]:





array([<matplotlib.axes.AxesSubplot object at 0x7f28c0af7a90>,
       <matplotlib.axes.AxesSubplot object at 0x7f28c0624750>], dtype=object)