Time series in pandas

In [9]:

    

import numpy as np
import pandas as pd
%matplotlib inline


    

In [10]:

    

rng = pd.date_range('1/1/2011', periods=72, freq='H')


    

In [11]:

    

rng.dtype


    

    
Out[11]:





dtype('<M8[ns]')

In [20]:

    

delta = pd.Series(np.random.randn(len(rng)), index=rng)


    

In [23]:

    

delta.head()


    

    
Out[23]:





2011-01-01 00:00:00   -1.065152
2011-01-01 01:00:00   -0.462886
2011-01-01 02:00:00   -1.004773
2011-01-01 03:00:00    1.521123
2011-01-01 04:00:00    1.756298
Freq: H, dtype: float64

In [21]:

    

ts = delta.cumsum()


    

In [24]:

    

ts.head()


    

    
Out[24]:





2011-01-01 00:00:00   -1.065152
2011-01-01 01:00:00   -1.528037
2011-01-01 02:00:00   -2.532810
2011-01-01 03:00:00   -1.011687
2011-01-01 04:00:00    0.744611
Freq: H, dtype: float64

In [22]:

    

ts.plot()


    

    
Out[22]:





<matplotlib.axes._subplots.AxesSubplot at 0x7ff96432f828>






    

In [25]:

    

conv = ts.asfreq('45Min', method='pad')


    

In [26]:

    

conv.head()


    

    
Out[26]:





2011-01-01 00:00:00   -1.065152
2011-01-01 00:45:00   -1.065152
2011-01-01 01:30:00   -1.528037
2011-01-01 02:15:00   -2.532810
2011-01-01 03:00:00   -1.011687
Freq: 45T, dtype: float64