GH1488 Add overload for DataFrame.max when axis is None #1490
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cmp0xff
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Nov 15, 2025
cmp0xff
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Nov 16, 2025
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Thank you for adding mean, min, median. I think we just need to relax the type testing.
| skipna: _bool | None = True, | ||
| numeric_only: _bool = False, | ||
| **kwargs: Any, | ||
| ) -> Scalar: ... |
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We can probably further restrict to _OrderableT from pandas-stubs/_libs/intervals.pyi, instead of just Scalar. But this can be done in a separate PR.
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Is it a type that can be returned? I thought it was more of a generic for Interval or something like that. I have left it for later.
tests/test_frame.py
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| df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]}) | ||
| check(assert_type(df.mean(), pd.Series), pd.Series) | ||
| check(assert_type(df.mean(axis=0), pd.Series), pd.Series) | ||
| check(assert_type(df.mean(axis=None), Scalar), np.float64) |
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I think we usually just test for the more generic np.floating unless there is a reason to test for the specific np.float64.
Suggested change
| check(assert_type(df.mean(axis=None), Scalar), np.float64) | |
| check(assert_type(df.mean(axis=None), Scalar), np.floating) |
tests/test_frame.py
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| df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]}) | ||
| check(assert_type(df.median(), pd.Series), pd.Series) | ||
| check(assert_type(df.median(axis=0), pd.Series), pd.Series) | ||
| check(assert_type(df.median(axis=None), Scalar), np.float64) |
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Suggested change
| check(assert_type(df.median(axis=None), Scalar), np.float64) | |
| check(assert_type(df.median(axis=None), Scalar), np.floating) |
tests/test_frame.py
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| df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]}) | ||
| check(assert_type(df.min(), pd.Series), pd.Series) | ||
| check(assert_type(df.min(axis=0), pd.Series), pd.Series) | ||
| check(assert_type(df.min(axis=None), Scalar), np.int64) |
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Suggested change
| check(assert_type(df.min(axis=None), Scalar), np.int64) | |
| check(assert_type(df.min(axis=None), Scalar), np.integer) |
tests/test_frame.py
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| df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]}) | ||
| check(assert_type(df.max(), pd.Series), pd.Series) | ||
| check(assert_type(df.max(axis=0), pd.Series), pd.Series) | ||
| check(assert_type(df.max(axis=None), Scalar), np.int64) |
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Suggested change
| check(assert_type(df.max(axis=None), Scalar), np.int64) | |
| check(assert_type(df.max(axis=None), Scalar), np.integer) |
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DataFrame.maxneeds the same overloads asDataFrame.anyhas #1488assert_type()to assert the type of any return value