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In [1]: Series(['2011-01-01', np.nan]).apply(pd.to_datetime) Out[1]: 0 2011-01-01 00:00:00 1 NaT dtype: datetime64[ns] In [2]: Series(['00:00:01', np.nan]).apply(pd.to_timedelta) AssertionError: Invalid type for timedelta scalar: <type 'float'>
May not be a trivial fix. So far I have seen that inserting np.nan and pd.tslib.iNaT into the result turns the dtype to object, which is no good.
The text was updated successfully, but these errors were encountered:
That said, if this can be squeezed into 0.13, I'm willing to rush to get it done.
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hmm though has done this oh well
it's easy just change this routine
coerce_scalar_to_timedelta_type(
in tseries/time delta
just need a isnull check and return tslib.iNaT (it will work now if u pass NaT)
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May not be a trivial fix. So far I have seen that inserting np.nan and pd.tslib.iNaT into the result turns the dtype to object, which is no good.
The text was updated successfully, but these errors were encountered: