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* troubleshoot azure * troubleshoot locale build
…ns.py (pandas-dev#32927) Co-authored-by: MomIsBestFriend <>
) * [pandas-dev#30914] Make a code check which bans imports of fixtures in tests * using indices fixture instead of duplicative index fixture * calling 'indices' fixture as 'index' * Revert "calling 'indices' fixture as 'index'" This reverts commit 1eba26d. * using string_index fixture instead of @pytest.mark.parametrize(indices, [string], indirect=True) * Revert "using string_index fixture instead of @pytest.mark.parametrize(indices, [string], indirect=True)" This reverts commit 2a3e611.
Co-authored-by: MomIsBestFriend <>
pandas-dev#33140) Co-authored-by: Matt Roeschke <[email protected]>
…_init__.py (pandas-dev#33142) * CLN: Remove unused import * Removed `noqa` comment Co-authored-by: MomIsBestFriend <>
* CLN: Nitpicks * Restarting CI as it failed to fetch a URL Co-authored-by: MomIsBestFriend <>
…dev#33220) * Add function to get_iso_calendar - This function reproduces what `datetime.date.isocalendar` returns - Refactor get_week_of_year to use get_iso_calendar internally * Add fields function to build isocalendar array - Returns a structured numpy array with year, week, and day corresponding to the ISO 8601 calendar * Add isocalendar property to DatetimeArray - Add corresponding access properties in accessors - This calculates the year, week, and day components according to the ISO 8601 calendar and returns them in a data frame. - It is analogous to Timestamp.isocalendar and datetime.date.isocalendar * Fix dt tests to handle DataFrame output * Update what’s new for isocalendar * Add columns explicitly when creating DataFrame * Set fill value to a tuple of nan - Older versions of numpy otherwise throw an error: ``` TypeError: a bytes-like object is required, not 'float' ``` * Define return of iso_calendar as ctypedef * Use to_datetime instead of dtype=“datetime64[D]” * Fix doc string to be in row format * Improve readability of ccalendar test * Return Int64 dataframe when NaT present * Clean up example to use a single Series * Always return an Int64 data frame * Return UInt32 per calendar ops standard * Add timeseries documentation Co-authored-by: Jeff Reback <[email protected]>
…ndas-dev#33399 (pandas-dev#33470) * DOC: timezone conversion example added to pandas.Series.astype doc pandas-dev#33399 * DOC: fixed the whitespace issue flagged in pep8 checks pandas-dev#33399 * DOC: added text in comments to commentary in example #333999 * DOC: added a more generic behavior statement as suggested. pandas-dev#33399 * DOC: removed unwanted commentary statement as per suggestion pandas-dev#33399 Co-authored-by: Venkatesh Datta <[email protected]>
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff