I am trying to set center=True in pandas rolling function, for a time-series:
import pandas as pd
series = pd.Series(1, index = pd.date_range('2014-01-01', '2014-04-01', freq = 'D'))
series.rolling('7D', min_periods=1, center=True, closed='left')
But output is:
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
<ipython-input-6-6b30c16a2d12> in <module>()
1 import pandas as pd
2 series = pd.Series(1, index = pd.date_range('2014-01-01', '2014-04-01', freq = 'D'))
----> 3 series.rolling('7D', min_periods=1, center=True, closed='left')
~\Anaconda3\lib\site-packages\pandas\core\generic.py in rolling(self, window, min_periods, freq, center, win_type, on, axis, closed)
6193 min_periods=min_periods, freq=freq,
6194 center=center, win_type=win_type,
-> 6195 on=on, axis=axis, closed=closed)
6196
6197 cls.rolling = rolling
~\Anaconda3\lib\site-packages\pandas\core\window.py in rolling(obj, win_type, **kwds)
2050 return Window(obj, win_type=win_type, **kwds)
2051
-> 2052 return Rolling(obj, **kwds)
2053
2054
~\Anaconda3\lib\site-packages\pandas\core\window.py in __init__(self, obj, window, min_periods, freq, center, win_type, axis, on, closed, **kwargs)
84 self.win_freq = None
85 self.axis = obj._get_axis_number(axis) if axis is not None else None
---> 86 self.validate()
87
88 @property
~\Anaconda3\lib\site-packages\pandas\core\window.py in validate(self)
1090 # we don't allow center
1091 if self.center:
-> 1092 raise NotImplementedError("center is not implemented "
1093 "for datetimelike and offset "
1094 "based windows")
NotImplementedError: center is not implemented for datetimelike and offset based windows
Expected output is the one generated by:
import pandas as pd
series = pd.Series(1, index = pd.date_range('2014-01-01', '2014-04-01', freq = 'D'))
series.rolling(7, min_periods=1, center=True).sum().head(10)
2014-01-01 4.0
2014-01-02 5.0
2014-01-03 6.0
2014-01-04 7.0
2014-01-05 7.0
2014-01-06 7.0
2014-01-07 7.0
2014-01-08 7.0
2014-01-09 7.0
2014-01-10 7.0
Freq: D, dtype: float64
But using datetime like offsets, since it simplifies part of my other code (not posted here).
Is there any alternative solution?
Thanks
From pandas version 1.3 this is * directly possible with pandas.
* Or will be (the work is merged, but 1.3 is not yet released as of today; I tested the lines below against the pandas main branch).
import pandas as pd
series = pd.Series(1, index = pd.date_range('2014-01-01', '2014-04-01', freq = 'D'))
series.rolling(7, min_periods=1, center=True).sum().head(10)
Output is as expected:
2014-01-01 4.0
2014-01-02 5.0
2014-01-03 6.0
2014-01-04 7.0
2014-01-05 7.0
2014-01-06 7.0
2014-01-07 7.0
2014-01-08 7.0
2014-01-09 7.0
2014-01-10 7.0
Freq: D, dtype: float64