ENH: use stable sort in value_counts #63158
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rhshadrach
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Nov 23, 2025
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rhshadrach
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Change you Series.value_counts docstring too and add a test - something like
ser = pd.Series(np.random.randint(0, 100, 10000))
result = ser.value_counts()
expected = ser.value_counts(sort=False).sort_values(ascending=False, kind="stable")
tm.assert_series_equal(result, expected)seems to fairly reliably fail without this PR (100000 out of 100000 times). Should set the NumPy random seed in the test.
I don't think this is a breaking change since unstable sorting doesn't guarantee anything about the output order. Would also like another eye on this.
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Thank you for the hint, dc431ca
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value_countsand record it in the docs #63155doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.AGENTS.md.