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UPDATE2: try the following workaround:

compare[pd.Series(compare.index.get_level_values(0).month).isin([5, 6, 7]).values]

UPDATE: test with your index values:

In [56]: i = pd.DatetimeIndex(['2016-01-04 01:40:00', '2016-01-04 02:00:00', '2016-01-04 02:10:00', '2016-01-04 02:30:00', '2016-01-04 02:4
    ...: 0:00'], dtype='datetime64[ns]', name=u'TTimeStamp', freq=None)

In [57]: i
Out[57]: DatetimeIndex(['2016-01-04 01:40:00', '2016-01-04 02:00:00', '2016-01-04 02:10:00', '2016-01-04 02:30:00', '2016-01-04 02:40:00'],
dtype='datetime64[ns]', name='TTimeStamp', freq=None)

In [58]: i.month
Out[58]: Int64Index([1, 1, 1, 1, 1], dtype='int64', name='TTimeStamp')

In [59]: i.month.isin([2,3])
Out[59]: array([False, False, False, False, False], dtype=bool)

In [60]: i.month.isin([1,2,3])
Out[60]: array([ True,  True,  True,  True,  True], dtype=bool)

PS this should work for Pandas version 0.18.1+

PS this should work for Pandas version 0.18.1+