BUG: .describe() doesn't work for EAs #61707 #61760
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Signed-off-by: ianlv <[email protected]>
* DEPR: object inference in to_stata * Whatsnew * Fix broken test * alphabetize
…as-dev#61767) Revert "ENH: Allow third-party packages to register IO engines (pandas-dev#61642)" This reverts commit 9dcce63.
…61705) Co-authored-by: Simon Hawkins <[email protected]> Co-authored-by: jbrockmendel <[email protected]>
…) to 2.3 whatsnew notes (pandas-dev#61795) Co-authored-by: Simon Hawkins <[email protected]>
…1771) Co-authored-by: Joris Van den Bossche <[email protected]>
* CLN: remove and udpate for outdated _item_cache * CLN: remove outdated _item_cache in comment * CLN: rollback unittest unralted to _item_cache
* PERF: avoid object-dtype path in ArrowEA._explode * typo fixup
pandas-dev#61773) * BUG: Decimal(NaN) incorrectly allowed in ArrowEA constructor with timestamp type * GH ref * BUG: ArrowEA constructor with timestamp type * mypy fixup * mypy fixup
…1785) * REF: remove unreachable, stronger typing in parsers.pyx * mypy fixup
* [pre-commit.ci] pre-commit autoupdate updates: - [github.com/astral-sh/ruff-pre-commit: v0.11.12 → v0.12.2](astral-sh/ruff-pre-commit@v0.11.12...v0.12.2) - [github.com/MarcoGorelli/cython-lint: v0.16.6 → v0.16.7](MarcoGorelli/cython-lint@v0.16.6...v0.16.7) - [github.com/pre-commit/mirrors-clang-format: v20.1.5 → v20.1.7](pre-commit/mirrors-clang-format@v20.1.5...v20.1.7) - [github.com/trim21/pre-commit-mirror-meson: v1.8.1 → v1.8.2](trim21/pre-commit-mirror-meson@v1.8.1...v1.8.2) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Rename method * ignore PLW0177 * Noqa test --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Matthew Roeschke <[email protected]>
* Bump numpy * Bump numpy * Bump tzdata * ignore pytables usage, update xfail condition
…_csv (pandas-dev#61650) * feature pandas-dev#49580: support new-style float_format string in to_csv feat(to_csv): support new-style float_format strings using str.format Detect and process new-style format strings (e.g., "{:,.2f}") in the float_format parameter of to_csv. - Check if float_format is a string and matches new-style pattern - Convert it to a callable (e.g., lambda x: float_format.format(x)) - Ensure compatibility with NaN values and mixed data types - Improves formatting output for floats when exporting to CSV Example: df = pd.DataFrame([1234.56789, 9876.54321]) df.to_csv(float_format="{:,.2f}") # now outputs formatted values like 1,234.57 Co-authored-by: Pedro Santos <[email protected]> * update benchmark test * fixed pre commit * fixed offsets.pyx * fixed tests to windows * Update pandas/io/formats/format.py Co-authored-by: Matthew Roeschke <[email protected]> * Update pandas/io/formats/format.py Co-authored-by: Matthew Roeschke <[email protected]> * Update pandas/io/formats/format.py Co-authored-by: Matthew Roeschke <[email protected]> * updated v3.0.0.rst and fixed tm.assert_produces_warning * fixed test_new_style_with_mixed_types_in_column added match to assert_produces_warning * Update doc/source/whatsnew/v3.0.0.rst (removed reference to this PR) Co-authored-by: Simon Hawkins <[email protected]> * fixed pre-commit * removed tm.assert_produces_warning * fixed space * fixed pre-commit --------- Co-authored-by: Pedro Santos <[email protected]> Co-authored-by: Matthew Roeschke <[email protected]> Co-authored-by: Simon Hawkins <[email protected]>
…andas-dev#61727) * TST: update expecteds for using_string_dtype to fix xfails * Update to_dict_of_blocks test to hardcode object dtype * Comment * Split test, update expected, targeted xfails * Update json test * revert commented-out
* DOC: Update link to pytz documentation * Update the pytz link per the suggestion
…ment (pandas-dev#61827) * DOC: Correct error message in AbstractMethodError for methodtype argument * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
fix(doc): rm excessive backtick
…e' and 'Docs' properly (pandas-dev#61836) * DOC: Update README.md to proper link to issues related to Docs * DOC: Update README.md to proper link to issues related to 'good first issue'
…row/fastparquet engine keyword) (pandas-dev#61877)
…ar error (pandas-dev#61855) Co-authored-by: Khemkaran <[email protected]>
| def test_describe_multiple_dtypes(self): | ||
| """ | ||
| GH61707: describe() doesn't work on EAs which generate | ||
| statistics with multiple dtypes. |
There was a problem hiding this comment.
nitpick can this be a comment instead of a docstring
| @@ -215,6 +216,14 @@ def reorder_columns(ldesc: Sequence[Series]) -> list[Hashable]: | |||
| return names | |||
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| def has_multiple_internal_dtypes(d: list[Any]) -> bool: | |||
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i think this can be inlined since it is only used once
| @@ -251,6 +260,10 @@ def describe_numeric_1d(series: Series, percentiles: Sequence[float]) -> Series: | |||
| import pyarrow as pa | |||
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| dtype = ArrowDtype(pa.float64()) | |||
| elif has_multiple_internal_dtypes(d): | |||
| # GH61707: describe() doesn't work on EAs | |||
| # with multiple internal dtypes, so return object dtype | |||
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is the relevant characteristic "multiple internal dtypes" or "entries that cant be cast to Float64"?
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This PR fixes a bug where Series.describe() fails on certain
ExtensionArraydtypes such aspint[kg], due to attempting to cast the result toFloat64Dtype. This is because some of the produced statistics are not castable to float, which raises errors like DimensionalityError.We now avoid forcing a Float64Dtype return dtype when the EA’s scalar values cannot be safely cast. Instead:
If the EA produces outputs with mixed dtypes, the result is returned with
dtype=None.