DEPR: to_datetime with integer/float values and format argument#65181
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jbrockmendel wants to merge 4 commits intopandas-dev:mainfrom
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DEPR: to_datetime with integer/float values and format argument#65181jbrockmendel wants to merge 4 commits intopandas-dev:mainfrom
jbrockmendel wants to merge 4 commits intopandas-dev:mainfrom
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Deprecate the implicit str() cast of integer/float values in array_strptime when a format argument is provided. Users should explicitly convert to strings first, e.g. data.astype(str). Also fix internal callers (_assemble_from_unit_mappings and _handle_date_column) to convert numeric data to strings before calling to_datetime with a format, so they don't trigger the deprecation. closes pandas-dev#55663 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace object-dtype pre-conversion with warnings.catch_warnings() to suppress the Pandas4Warning. This has zero performance overhead compared to the pre-deprecation code, since the ensure_object conversion was already happening inside _convert_listlike_datetimes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…path internally Reword the deprecation message in array_strptime to correctly state that integers/floats will be interpreted via the 'unit' keyword in a future version (rather than rejected), and recommend casting to strings explicitly without prescribing .astype(str) (which would mishandle Timestamps in mixed-dtype object arrays). Also replace the warnings.catch_warnings() suppression in the two internal callers (_assemble_from_unit_mappings and _handle_date_column) with explicit string conversion, so they use the future-friendly path directly rather than relying on suppression. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
str()cast of integer/float values inarray_strptimewhen aformatargument is provided toto_datetime. In a future version, passing numeric data withformatwill raise a TypeError._assemble_from_unit_mappingsindatetimes.pyand_handle_date_columninsql.py) to convert numeric data to strings before callingto_datetimewith a format, so they don't trigger the deprecation.pd.to_datetime(data.astype(str), format="%Y%m%d").closes #55663
Test plan
test_to_datetime.pytests pass (including with-W error::Pandas4Warning)test_sql.pytests passtest_stata.py, JSON IO, andDatetimeIndextests unaffected🤖 Generated with Claude Code