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In [23]:

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

alsea = pd.io.data.get_data_yahoo('ALSEA.MX', 
                                 start=datetime.datetime(2006, 10, 1), 
                                 end=datetime.datetime(2014, 1, 1))
alsea.head()



In [24]:

    
alsea['diff'] = alsea.Open - alsea.Close
alsea.head()



In [25]:

    
close_px = alsea['Adj Close']
mavg = pd.rolling_mean(close_px, 40)
mavg[-10:]









    Out[25]:





Date
2013-12-19    39.61425
2013-12-20    39.62600
2013-12-23    39.62425
2013-12-24    39.62900
2013-12-25    39.63650
2013-12-26    39.62975
2013-12-27    39.60325
2013-12-30    39.60750
2013-12-31    39.62775
2014-01-01    39.66675
dtype: float64



In [26]:

    
rets = close_px / close_px.shift(1) - 1
rets.head()









    Out[26]:





Date
2006-10-02         NaN
2006-10-03   -0.000956
2006-10-04    0.003828
2006-10-05    0.023832
2006-10-06    0.028864
Name: Adj Close, dtype: float64



In [ ]:

    
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rc('figure', figsize=(8, 7))

close_px.plot(label='ALSEA')
mavg.plot(label='mavg')
plt.legend()
plt.show()



In [ ]:

	Open	High	Low	Close	Volume	Adj Close
Date
2006-10-02	45.25	46.00	45.11	46.00	197100	10.46
2006-10-03	46.00	46.00	45.95	45.98	59100	10.45
2006-10-04	46.00	46.22	45.98	46.14	992100	10.49
2006-10-05	46.10	47.35	46.09	47.25	661100	10.74
2006-10-06	47.25	49.00	47.25	48.60	668100	11.05

	Open	High	Low	Close	Volume	Adj Close	diff
Date
2006-10-02	45.25	46.00	45.11	46.00	197100	10.46	-0.75
2006-10-03	46.00	46.00	45.95	45.98	59100	10.45	0.02
2006-10-04	46.00	46.22	45.98	46.14	992100	10.49	-0.14
2006-10-05	46.10	47.35	46.09	47.25	661100	10.74	-1.15
2006-10-06	47.25	49.00	47.25	48.60	668100	11.05	-1.35