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danfrankj opened this issue Oct 31, 2014 · 1 comment · Fixed by #8695
Closed

datetime operations on NaT produce dangerous results #8689

danfrankj opened this issue Oct 31, 2014 · 1 comment · Fixed by #8695
Labels
Bug Datetime Datetime data dtype Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate
Milestone
0.15.1

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@danfrankj
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In [189]: ser = pd.Series([np.datetime64('nat')])

In [190]: ser
Out[190]: 
0   NaT
dtype: datetime64[ns]

In [191]: ser.dt.hour
Out[191]: 
0   -1
dtype: int64

While -1 is not a valid hour it is a very valid integer and could (has) caused hard to track bugs.
@jreback
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jreback commented Oct 31, 2014

hmm this is not tested ATM
(as indexes only recently started allowing NaT ; that is how .dt is implemented )

marking as a bug

if u would like to take a shot at fixing lmk

@jreback jreback added Bug Datetime Datetime data dtype Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate labels Oct 31, 2014
@jreback jreback added this to the 0.15.1 milestone Oct 31, 2014
@jreback jreback mentioned this issue Oct 31, 2014
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Bug Datetime Datetime data dtype Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate
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Milestone
0.15.1
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API/BUG: return np.nan rather than -1 for invalid datetime accessors values (GH8689) jreback/pandas
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@danfrankj @jreback