Description
In [7]: import datetime as dt
In [8]: df = pd.DataFrame([[dt.datetime(2016,1,31,15)], [dt.datetime(2016,2,7,17)]], index=[dt.datetime(2016,1,31,15), dt.datetime(2016,2,7,17)], columns=['timestamp'])
In [10]: df
Out[10]:
timestamp
2016-01-31 15:00:00 2016-01-31 15:00:00
2016-02-07 17:00:00 2016-02-07 17:00:00
In [11]: df.resample('D').first().timestamp
Out[11]:
2016-01-31 2016-01-31 15:00:00
2016-02-01 NaT
2016-02-02 NaT
2016-02-03 NaT
2016-02-04 NaT
2016-02-05 NaT
2016-02-06 NaT
2016-02-07 2016-02-07 17:00:00
Freq: D, Name: timestamp, dtype: datetime64[ns]
In [12]: df.timestamp.resample('D').first()
Out[12]:
2016-01-31 1.454252e+18
2016-02-01 NaN
2016-02-02 NaN
2016-02-03 NaN
2016-02-04 NaN
2016-02-05 NaN
2016-02-06 NaN
2016-02-07 1.454864e+18
Freq: D, Name: timestamp, dtype: float64
Tested it with latest master