BUG: dropna() on single column timezone-aware values (#13407) #20422
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@@ Coverage Diff @@
## master #20422 +/- ##
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- Coverage 91.85% 91.82% -0.03%
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Files 152 152
Lines 49231 49232 +1
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- Hits 45220 45209 -11
- Misses 4011 4023 +12
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Hello @JQGoh! Thanks for updating the PR. Cheers ! There are no PEP8 issues in this Pull Request. 🍻 Comment last updated on March 25, 2018 at 14:23 Hours UTC |
JQGoh
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@TomAugspurger In case this could be of your interest. I recall that my first commit passed all the CI tests. However, the current failure is related to the new change in pandas/tests/extension/json/test_json.py |
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Sorry about that. Fixed on master. If you fetch master and merge it into your branch things should pass. You can also fixup that pep8 issue. |
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@TomAugspurger Thank you for the revisions. I have fixed the PEP8 issues as well, please help to review the changes if possible. |
jreback
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pandas/tests/frame/test_missing.py
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| @@ -183,6 +186,27 @@ def test_dropna_multiple_axes(self): | |||
| inp.dropna(how='all', axis=(0, 1), inplace=True) | |||
| assert_frame_equal(inp, expected) | |||
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| def test_dropna_tz_aware_datetime(self): | |||
| # GH13407 | |||
| # Example reported by GH13407 | |||
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can you remove this second coment
pandas/tests/frame/test_missing.py
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| assert_frame_equal(result, expected) | ||
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| # Ex2 | ||
| df2 = DataFrame({'Time': [dt1, None, np.nan, dt2]}) |
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name this df, and use result and expected here
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@jreback Thank you for your suggestions. Done. |
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thanks for the patch @JQGoh nice to have an older issue closed! |
git diff upstream/master -u -- "*.py" | flake8 --diffAs mentioned by the title of #13407, DataFrame.values not a 2D-array when constructed from timezone-aware datetimes. Hence,
notna(frame.values)raisesValueErorr: 'axis' entry is out of boundsbecause user tries to applydropnaon a 1D-array.I mainly include the example mentioned by the original author of #13407. Let me know if further test examples are required for this issue. Thanks.
Edit: I add additional test example to demonstrate the dropping of np.nan and None from the Series having timezone-ware datetimes.