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In [2]:

    
import pandas as pd
import pandas.io.data as web
import datetime









    



/home/harish/anaconda2/lib/python2.7/site-packages/pandas/io/data.py:35: FutureWarning: 
The pandas.io.data module is moved to a separate package (pandas-datareader) and will be removed from pandas in a future version.
After installing the pandas-datareader package (https://github.com/pydata/pandas-datareader), you can change the import ``from pandas.io import data, wb`` to ``from pandas_datareader import data, wb``.
  FutureWarning)



In [3]:

    
start = datetime.datetime(2016,1,1)
end = datetime.date.today()



In [4]:

    
google = web.DataReader("GOOGL", "yahoo", start, end)



In [5]:

    
type(google)









    Out[5]:





pandas.core.frame.DataFrame



In [6]:

    
google.head()



In [7]:

    
import matplotlib.pyplot as plt
%matplotlib inline
%pylab inline
pylab.rcParams['figure.figsize'] = (15, 9)









    



Populating the interactive namespace from numpy and matplotlib



In [8]:

    
google["Adj Close"].plot(grid = True)









    Out[8]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fee98738850>



In [9]:

    
amazon = web.DataReader("AMZN", "yahoo", start, end)
facebook = web.DataReader("FB", "yahoo", start, end)



In [10]:

    
stocks = pd.DataFrame({"GOOGL": google["Adj Close"],
                      "AMZN": amazon["Adj Close"],
                      "FB": facebook["Adj Close"]})



In [11]:

    
stocks.head()



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stocks.plot(grid = True)









    Out[12]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fee963aa350>



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stocks.plot(secondary_y = ["FB"], grid = True)









    Out[13]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fee9625d590>



In [14]:

    
stocks_return = stocks.apply(lambda x: x / x[0])
stocks_return.head()



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stocks_return.plot(grid = True).axhline(y = 1, color="black", lw=2)









    Out[15]:





<matplotlib.lines.Line2D at 0x7fee96064c90>



In [20]:

    
# BHARTIARTL.NS
airtel = web.DataReader("BHARTIARTL.NS", "yahoo", start, end)



In [21]:

    
airtel.head()



In [ ]:

	Open	High	Low	Close	Volume	Adj Close
Date
2016-01-04	762.200012	762.200012	747.539978	759.440002	3369100	759.440002
2016-01-05	764.099976	769.200012	755.650024	761.530029	2260800	761.530029
2016-01-06	750.369995	765.729980	748.000000	759.330017	2410300	759.330017
2016-01-07	746.489990	755.309998	735.280029	741.000000	3156600	741.000000
2016-01-08	747.799988	750.119995	728.919983	730.909973	2375300	730.909973

	AMZN	FB	GOOGL
Date
2016-01-04	636.989990	102.220001	759.440002
2016-01-05	633.789978	102.730003	761.530029
2016-01-06	632.650024	102.970001	759.330017
2016-01-07	607.940002	97.919998	741.000000
2016-01-08	607.049988	97.330002	730.909973

	AMZN	FB	GOOGL
Date
2016-01-04	1.000000	1.000000	1.000000
2016-01-05	0.994976	1.004989	1.002752
2016-01-06	0.993187	1.007337	0.999855
2016-01-07	0.954395	0.957934	0.975719
2016-01-08	0.952998	0.952162	0.962433

	Open	High	Low	Close	Volume	Adj Close
Date
2016-01-01	339.95	344.00	337.65	340.50	1250200	339.163
2016-01-04	338.00	338.95	321.00	326.80	3152700	325.517
2016-01-05	327.00	328.75	321.00	323.45	2118900	322.180
2016-01-06	325.90	332.50	319.65	322.20	2414100	320.935
2016-01-07	320.90	325.80	316.60	322.35	2825700	321.085