TST: fix fixture for numpy dtypes #23983
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Hello @h-vetinari! Thanks for updating the PR.
Comment last updated on November 29, 2018 at 06:43 Hours UTC |
jreback
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Nov 28, 2018
| def test_drop_duplicates(any_numpy_dtype, keep, expected): | ||
| tc = Series([1, 0, 3, 5, 3, 0, 4], dtype=np.dtype(any_numpy_dtype)) | ||
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| if tc.dtype == 'bool': |
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i would just skip if bool here
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pandas/conftest.py
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| @@ -386,8 +386,16 @@ def tz_aware_fixture(request): | |||
| COMPLEX_DTYPES = [complex, "complex64", "complex128"] | |||
| STRING_DTYPES = [str, 'str', 'U'] | |||
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| DATETIMEDELTA_DTYPES = ['datetime64[ns]', 'M8[ns]', | |||
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separate these out, these should not be grouped together
Codecov Report
@@ Coverage Diff @@
## master #23983 +/- ##
==========================================
- Coverage 92.31% 92.3% -0.01%
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Files 161 161
Lines 51513 51551 +38
==========================================
+ Hits 47554 47585 +31
- Misses 3959 3966 +7
Continue to review full report at Codecov.
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lgtm. ping on green. |
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@jreback |
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thanks |
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git diff upstream/master -u -- "*.py" | flake8 --diffThis was one of the things I stumbled over while working on #23982. There's a fixture for all_numpy_dtypes that got introduced in #21899, but it's a lie - it doesn't cover (nearly) all numpy dtypes. It's currently only used in one test, and so I've adapted it here to be able to actually test all numpy dtypes.