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@reidy-p reidy-p commented Jan 6, 2018

On master:

In [2]: pd.DatetimeIndex(['2017-01-01 23:59:59.999999999'])
Out[2]:  DatetimeIndex(['2017-01-01'], dtype='datetime64[ns]', freq=None)

On my branch:

In [3]: pd.DatetimeIndex(['2017-01-01 23:59:59.999999999'])
Out[3]: DatetimeIndex(['2017-01-01 23:59:59.999999999'], dtype='datetime64[ns]', freq=None)

It seems that it's only a problem when the time value was 23:59:59.999999999 or very similar, but I may need to add some more tests to check this further.

@@ -883,6 +883,20 @@ def test_datetimelike_frame(self):
'[10 rows x 2 columns]')
assert repr(df) == expected

def test_datetimeindex_highprecision(self):
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see if you can parametrize this checking each digit of precision

@@ -374,7 +374,8 @@ Conversion
- Bug in :class:`TimedeltaIndex` where division by a ``Series`` would return a ``TimedeltaIndex`` instead of a ``Series`` (issue:`19042`)
- Bug in :class:`Series` with ``dtype='timedelta64[ns]`` where addition or subtraction of ``TimedeltaIndex`` could return a ``Series`` with an incorrect name (issue:`19043`)
- Fixed bug where comparing :class:`DatetimeIndex` failed to raise ``TypeError`` when attempting to compare timezone-aware and timezone-naive datetimelike objects (:issue:`18162`)
-
- Bug in :class:`DatetimeIndex` where the repr was not showing the time values for the end of the day (:issue:`19030`)
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make this more clear

@jreback jreback added Output-Formatting __repr__ of pandas objects, to_string Datetime Datetime data dtype labels Jan 6, 2018
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codecov bot commented Jan 7, 2018

Codecov Report

Merging #19109 into master will increase coverage by 0.02%.
The diff coverage is n/a.

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@@            Coverage Diff             @@
##           master   #19109      +/-   ##
==========================================
+ Coverage   91.51%   91.53%   +0.02%     
==========================================
  Files         148      148              
  Lines       48753    48753              
==========================================
+ Hits        44616    44628      +12     
+ Misses       4137     4125      -12
Flag Coverage Δ
#multiple 89.91% <ø> (+0.02%) ⬆️
#single 41.6% <ø> (ø) ⬆️
Impacted Files Coverage Δ
pandas/io/formats/format.py 96.24% <ø> (ø) ⬆️
pandas/plotting/_converter.py 66.95% <0%> (+1.73%) ⬆️

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@reidy-p reidy-p force-pushed the datetimeindex_repr branch from 338c441 to 055e0ac Compare January 7, 2018 12:25
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pep8speaks commented Jan 7, 2018

Hello @reidy-p! Thanks for updating the PR.

Cheers ! There are no PEP8 issues in this Pull Request. 🍻

Comment last updated on January 07, 2018 at 12:38 Hours UTC

@jreback jreback added this to the 0.23.0 milestone Jan 7, 2018
@jreback jreback merged commit fe66b56 into pandas-dev:master Jan 7, 2018
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jreback commented Jan 7, 2018

thanks @reidy-p

@reidy-p reidy-p deleted the datetimeindex_repr branch January 7, 2018 15:44
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BUG: repr on DTI with high precision is wrong
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