[SPARK-38821][PYTHON] Skip nsmall/nlarge nan test under pandas 1.4.[0,1,2] #36356
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Yikun
commented
Apr 26, 2022
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| if not (LooseVersion("1.4.0") <= LooseVersion(pd.__version__) <= LooseVersion("1.4.2")): | ||
| self.assert_eq(psdf.nlargest(5, columns="a"), pdf.nlargest(5, columns="a")) | ||
| self.assert_eq( | ||
| psdf.nlargest(5, columns=["a", "b"]), pdf.nlargest(5, columns=["a", "b"]) | ||
| ) |
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If you still think I need to compare with real results rather than skip, I'd also like to change. We need to change index=np.random.rand(7) to a certain range, and construct a result df.
Because this is only failed with panda 1.4.0~1.4.2, so I thought skip is enough.
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cc @itholic @xinrong-databricks @HyukjinKwon |
HyukjinKwon
approved these changes
Apr 26, 2022
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Merged to master. |
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What changes were proposed in this pull request?
Skip nsmall/nlarge nan test under pandas 1.4.[0,1,2].
Pandas get wrong results when
np.nanin the sorting column since pandas-dev/pandas@16d2f59 (v1.4.0)I confirmed this issue are fixed by:
pandas-dev/pandas@2886388
Why are the changes needed?
No
Does this PR introduce any user-facing change?
No
How was this patch tested?
CI passed