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Merged
merged 2 commits into from
Jun 1, 2017
Merged

BUG: Fixed pd.unique on array of tuples #16543

merged 2 commits into from
Jun 1, 2017

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@TomAugspurger
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@TomAugspurger TomAugspurger commented May 30, 2017

Closes #16519
@TomAugspurger TomAugspurger added Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Blocker Blocking issue or pull request for an upcoming release Needs Backport labels May 30, 2017
@TomAugspurger TomAugspurger added this to the 0.20.2 milestone May 30, 2017
jreback
jreback approved these changes May 30, 2017
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lgtm.
doc/source/whatsnew/v0.20.2.txt Outdated
- Bug in using ``pathlib.Path`` or ``py.path.local`` objects with io functions (:issue:`16291`)
- Bug in ``DataFrame.update()`` with ``overwrite=False`` and ``NaN values`` (:issue:`15593`)

- Bug in :func:`pd.unique` on an array of tuples (:issue:`16519`)
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@jreback jreback May 30, 2017

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I think has to be :func:`unique` ?
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@TomAugspurger TomAugspurger May 31, 2017

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You're correct.
pandas/tests/test_algos.py
np.array([False, False, False]))

@pytest.mark.parametrize('arr, unique', [
([(0, 0), (0, 1), (1, 0), (1, 1), (0, 0), (0, 1), (1, 0), (1, 1)],
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also add an example of this in pd.unique itself.
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chris-b1 commented May 30, 2017

I think you could back out this change from #16434

https://github.com/TomAugspurger/pandas/blob/35da5b9e60993b722760d52dc8dcc0a14129748e/pandas/core/algorithms.py#L391
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jreback commented May 30, 2017

I with agree @chris-b1 comment, yes that looks right.
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codecov bot commented May 30, 2017

Codecov Report

Merging #16543 into master will not change coverage.
The diff coverage is 100%.

Impacted file tree graph

@@ Coverage Diff @@ ## master #16543 +/- ## ======================================= Coverage 90.79% 90.79% ======================================= Files 161 161 Lines 51063 51063 ======================================= Hits 46365 46365 Misses 4698 4698
Flag Coverage Δ
#multiple 88.63% <100%> (ø) ⬆️
#single 40.15% <0%> (ø) ⬆️
Impacted Files Coverage Δ
pandas/core/algorithms.py 94.41% <100%> (ø) ⬆️

Continue to review full report at Codecov.

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codecov bot commented May 30, 2017 •
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Codecov Report

Merging #16543 into master will not change coverage.
The diff coverage is 100%.

Impacted file tree graph

@@ Coverage Diff @@ ## master #16543 +/- ## ======================================= Coverage 90.79% 90.79% ======================================= Files 161 161 Lines 51063 51063 ======================================= Hits 46365 46365 Misses 4698 4698
Flag Coverage Δ
#multiple 88.63% <100%> (ø) ⬆️
#single 40.15% <0%> (ø) ⬆️
Impacted Files Coverage Δ
pandas/core/algorithms.py 94.41% <100%> (ø) ⬆️

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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codecov bot commented May 30, 2017 •
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Codecov Report

Merging #16543 into master will not change coverage.
The diff coverage is 100%.

Impacted file tree graph

@@ Coverage Diff @@ ## master #16543 +/- ## ======================================= Coverage 90.75% 90.75% ======================================= Files 161 161 Lines 51074 51074 ======================================= Hits 46353 46353 Misses 4721 4721
Flag Coverage Δ
#multiple 88.59% <100%> (ø) ⬆️
#single 40.16% <0%> (ø) ⬆️
Impacted Files Coverage Δ
pandas/core/algorithms.py 94.41% <100%> (ø) ⬆️

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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@TomAugspurger
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TomAugspurger commented May 31, 2017

I think you could back out this change from #16434

The regression test from #16434 fails if I revert the change. The difference being

(Pdb++) values # this is with the fix reverted array([[1, 'a']], dtype=object) (Pdb++) lib.list_to_object_array(list([(1, 'a')])) # this is the fix from 16434 array([(1, 'a')], dtype=object)

So an array of lists vs. an array of tuples. Is that correct?
@jreback
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jreback commented May 31, 2017

you may just need to call
_ensure_arraylike there instead of the isinstance check
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TomAugspurger commented May 31, 2017 •
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Using _ensure_arraylike failed on an empty array pd.Series([1, 2]).isin([]) since it's a float instead of object dtype, so the hashing fails later on. I can handle that case if you want, or just leave the isinstance checks. Not sure which is cleaner really.
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jreback commented May 31, 2017

@TomAugspurger added a commit. should fix up I think.
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jreback commented May 31, 2017

@TomAugspurger looks this broke it. ok just revert my commit and merge your changes. This is a very touchy area. I we are doing the right things in the tests, but just tricky to get exactly right.
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jreback commented May 31, 2017

@TomAugspurger rebased to remove my commit.
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TomAugspurger commented May 31, 2017

@jreback are you able to restart appveyor jobs? One of the network tests failed on the first job.
@jreback jreback merged commit 9d7afa7 into pandas-dev:master Jun 1, 2017
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jreback commented Jun 1, 2017

thanks!
TomAugspurger added a commit to TomAugspurger/pandas that referenced this pull request Jun 1, 2017
@TomAugspurger
BUG: Fixed pd.unique on array of tuples (pandas-dev#16543)
8da0e93 
(cherry picked from commit 9d7afa7)
TomAugspurger added a commit that referenced this pull request Jun 4, 2017
@TomAugspurger
BUG: Fixed pd.unique on array of tuples (#16543)
544fb11 
(cherry picked from commit 9d7afa7)
@TomAugspurger TomAugspurger deleted the unique-tuples branch June 4, 2017 20:29
@chris-b1 chris-b1 mentioned this pull request Jun 8, 2017
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Kiv pushed a commit to Kiv/pandas that referenced this pull request Jun 11, 2017
@TomAugspurger @Kiv
BUG: Fixed pd.unique on array of tuples (pandas-dev#16543)
98ed54d
stangirala pushed a commit to stangirala/pandas that referenced this pull request Jun 11, 2017
@TomAugspurger @stangirala
BUG: Fixed pd.unique on array of tuples (pandas-dev#16543)
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Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Blocker Blocking issue or pull request for an upcoming release

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@TomAugspurger @chris-b1 @jreback