Closed
Description
I didn't directly found an open issue about it, but is there a reason we do not implement interpolation of datetime values (so not in the index)?
Example:
In [14]: s = pd.Series(pd.date_range('2012-01-01', periods=5))
In [16]: s[2] = np.nan
In [17]: s
Out[17]:
0 2012-01-01
1 2012-01-02
2 NaT
3 2012-01-04
4 2012-01-05
dtype: datetime64[ns]
In [18]: s.interpolate()
Out[18]:
0 2012-01-01
1 2012-01-02
2 NaT
3 2012-01-04
4 2012-01-05
dtype: datetime64[ns]
A crude manual work around:
In [20]: s2 = pd.Series(s.values.astype('int64'))
In [21]: s2[s2<0] = np.nan
In [22]: s2
Out[22]:
0 1.325376e+18
1 1.325462e+18
2 NaN
3 1.325635e+18
4 1.325722e+18
dtype: float64
In [23]: pd.to_datetime(s2.interpolate(), unit='ns')
Out[23]:
0 2012-01-01
1 2012-01-02
2 2012-01-03
3 2012-01-04
4 2012-01-05
dtype: datetime64[ns]