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bug in Series.replace with timezone-aware datetime columns #11792

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multiloc opened this issue Dec 7, 2015 · 2 comments

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commented Dec 7, 2015

Seeing the following behavior in 0.17.1 with the patch from #11715 applied (would raise without the patch):

In [29]: ser = pd.Series([pd.NaT, pd.Timestamp('2015/01/01', tz='UTC')])

# works
In [30]: ser.replace(pd.NaT, pd.Timestamp.min)
Out[30]: 
0    1677-09-22 00:12:43.145225
1     2015-01-01 00:00:00+00:00
dtype: object

# doesn't work
In [31]: ser.replace([np.nan, pd.NaT], pd.Timestamp.min)
Out[31]: 
0                         NaT
1   2015-01-01 00:00:00+00:00
dtype: datetime64[ns, UTC]

# works without timezone-aware datetimes
In [32]: ser = pd.Series([pd.NaT, pd.Timestamp('2015/01/01')])
In [33]: ser.replace([np.nan, pd.NaT], pd.Timestamp.min)
Out[33]: 
0   1677-09-22 00:12:43.145225
1   2015-01-01 00:00:00.000000
dtype: datetime64[ns]
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commented Dec 9, 2015

yep, looks like a buggie! (thanks for the multiple reports BTW). interested in a pull-request to fix?

@jreback jreback added this to the Next Major Release milestone Dec 9, 2015

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commented Dec 10, 2015

sure, I'll look into it over the weekend

@mroeschke mroeschke referenced this issue Jun 23, 2018

Merged

TST: Clean old timezone issues PT2 #21612

10 of 10 tasks complete

@jreback jreback modified the milestones: Next Major Release, 0.24.0 Jun 25, 2018

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