DEPR: dropping nuisance columns in DataFrame reductions #41480
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jreback
requested changes
May 17, 2021
pandas/core/frame.py
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| @@ -9800,6 +9800,21 @@ def _get_data() -> DataFrame: | |||
| # Even if we are object dtype, follow numpy and return | |||
| # float64, see test_apply_funcs_over_empty | |||
| out = out.astype(np.float64) | |||
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| if numeric_only is None and out.shape[0] != df.shape[1]: | |||
| # columns have been dropped | |||
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can you add the issue number here and below (this PR number is fine),
jreback
added
Deprecate
This was referenced May 17, 2021
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added a whatsnew subsection. this is actually just the first half of the note im about to push for #41475. the smart money says ive made a mess of the rst conventions regarding |
jreback
reviewed
May 17, 2021
doc/source/whatsnew/v1.3.0.rst
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| Deprecated Dropping Nuisance Columns in DataFrame Reductions and DataFrameGroupBy Operations | ||
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
| When calling a reduction (.min, .max, .sum, ...) on a :class:`DataFrame` with |
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Suggested change
| When calling a reduction (.min, .max, .sum, ...) on a :class:`DataFrame` with | |
| The default of calling a reduction (.min, .max, .sum, ...) on a :class:`DataFrame` with | |
| ``numeric_only=None`` will silently ignore and drop from the result nuiscance columns, e.g. a string column in a .mean() reduction. |
jreback
reviewed
May 17, 2021
doc/source/whatsnew/v1.3.0.rst
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| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
| When calling a reduction (.min, .max, .sum, ...) on a :class:`DataFrame` with | ||
| ``numeric_only=None`` (the default, columns on which the reduction raises ``TypeError`` | ||
| are silently ignored and dropped from the result. This behavior is deprecated. |
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Start a new paragraph with 'This behavior is deprecated'
jreback
reviewed
May 17, 2021
jreback
approved these changes
May 21, 2021
jreback
approved these changes
May 21, 2021
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ping |
JulianWgs
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Jul 3, 2021
zhengruifeng
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Aug 21, 2023
…0 and enabling tests ### What changes were proposed in this pull request? This PR proposes to match the behavior with pandas 2.0.0 and above for stat functions, such as `sum`, `quantile`, `prod`, etc. See pandas-dev/pandas#41480 and pandas-dev/pandas#47500 for more detail. ### Why are the changes needed? To match the behavior to latest pandas. ### Does this PR introduce _any_ user-facing change? Yes, the behaviors for stat funcs are now matched with pandas 2.0.0 and above. ### How was this patch tested? Enabling & updating the existing UTs. Closes #42526 from itholic/pandas_stat. Authored-by: itholic <haejoon.lee@databricks.com> Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
valentinp17
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Aug 24, 2023
…0 and enabling tests ### What changes were proposed in this pull request? This PR proposes to match the behavior with pandas 2.0.0 and above for stat functions, such as `sum`, `quantile`, `prod`, etc. See pandas-dev/pandas#41480 and pandas-dev/pandas#47500 for more detail. ### Why are the changes needed? To match the behavior to latest pandas. ### Does this PR introduce _any_ user-facing change? Yes, the behaviors for stat funcs are now matched with pandas 2.0.0 and above. ### How was this patch tested? Enabling & updating the existing UTs. Closes apache#42526 from itholic/pandas_stat. Authored-by: itholic <haejoon.lee@databricks.com> Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
ragnarok56
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Mar 2, 2024
…0 and enabling tests ### What changes were proposed in this pull request? This PR proposes to match the behavior with pandas 2.0.0 and above for stat functions, such as `sum`, `quantile`, `prod`, etc. See pandas-dev/pandas#41480 and pandas-dev/pandas#47500 for more detail. ### Why are the changes needed? To match the behavior to latest pandas. ### Does this PR introduce _any_ user-facing change? Yes, the behaviors for stat funcs are now matched with pandas 2.0.0 and above. ### How was this patch tested? Enabling & updating the existing UTs. Closes apache#42526 from itholic/pandas_stat. Authored-by: itholic <haejoon.lee@databricks.com> Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
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