Pandas Dataframe Mask based on index

Question

I have the following dataframe:

import pandas as pd
index = pd.date_range(\'2013-1-1\',periods=10,freq=\'15Min\')
data = pd.DataFrame(data=[1,2,3,4,5,6,7,8,9         


        

Answer 1

'start' and 'stop' keywords are deprecated.With pandas >17.1; I had to use the following syntax instead:

data.iloc[data.index.indexer_between_time('1:15', '02:00')]
Out[90]: 
                     value
2013-01-01 01:15:00      6
2013-01-01 01:30:00      7
2013-01-01 01:45:00      8
2013-01-01 02:00:00      9

Answer 2

You can mask using indexer_between_time:

In [11]: data.index.indexer_between_time(start='01:15', end='02:00')
Out[11]: array([5, 6, 7, 8])

In [12]: data.iloc[data.index.indexer_between_time(start='1:15', end='02:00')]
Out[12]:
                     value
2013-01-01 01:15:00      6
2013-01-01 01:30:00      7
2013-01-01 01:45:00      8
2013-01-01 02:00:00      9

As you can see, you access the index by the attribute .index.

Note: indexer_between_time by default both include_start and include_end are True, it also offers a tz argument to compare the time to a different timezone.