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DOC: 1.0.4 release notes and date (#34425)
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doc/source/whatsnew/v1.0.4.rst

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.. _whatsnew_104:
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What's new in 1.0.4 (May ??, 2020)
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What's new in 1.0.4 (May 28, 2020)
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------------------------------------
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These are the changes in pandas 1.0.4. See :ref:`release` for a full changelog
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Fixed regressions
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~~~~~~~~~~~~~~~~~
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- Bug where :meth:`Series.isna` and :meth:`DataFrame.isna` would raise for categorical dtype when ``pandas.options.mode.use_inf_as_na`` was set to ``True`` (:issue:`33594`)
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- Bug in :meth:`GroupBy.first` and :meth:`GroupBy.last` where None is not preserved in object dtype (:issue:`32800`)
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- Bug in DataFrame reductions using ``numeric_only=True`` and ExtensionArrays (:issue:`33256`).
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- Fix regression where :meth:`Series.isna` and :meth:`DataFrame.isna` would raise for categorical dtype when ``pandas.options.mode.use_inf_as_na`` was set to ``True`` (:issue:`33594`)
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- Fix regression in :meth:`GroupBy.first` and :meth:`GroupBy.last` where None is not preserved in object dtype (:issue:`32800`)
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- Fix regression in DataFrame reductions using ``numeric_only=True`` and ExtensionArrays (:issue:`33256`).
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- Fix performance regression in ``memory_usage(deep=True)`` for object dtype (:issue:`33012`)
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- Bug where :meth:`Categorical.replace` would replace with ``NaN`` whenever the new value and replacement value were equal (:issue:`33288`)
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- Bug where an ordered :class:`Categorical` containing only ``NaN`` values would raise rather than returning ``NaN`` when taking the minimum or maximum (:issue:`33450`)
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- Bug in :meth:`DataFrameGroupBy.agg` with dictionary input losing ``ExtensionArray`` dtypes (:issue:`32194`)
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- Fix regression where :meth:`Categorical.replace` would replace with ``NaN`` whenever the new value and replacement value were equal (:issue:`33288`)
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- Fix regression where an ordered :class:`Categorical` containing only ``NaN`` values would raise rather than returning ``NaN`` when taking the minimum or maximum (:issue:`33450`)
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- Fix regression in :meth:`DataFrameGroupBy.agg` with dictionary input losing ``ExtensionArray`` dtypes (:issue:`32194`)
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- Fix to preserve the ability to index with the "nearest" method with xarray's CFTimeIndex, an :class:`Index` subclass (`pydata/xarray#3751 <https://github.com/pydata/xarray/issues/3751>`_, :issue:`32905`).
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- Fix regression in :meth:`DataFrame.describe` raising ``TypeError: unhashable type: 'dict'`` (:issue:`32409`)
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- Bug in :meth:`DataFrame.replace` casts columns to ``object`` dtype if items in ``to_replace`` not in values (:issue:`32988`)
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- Bug in :meth:`Series.groupby` would raise ``ValueError`` when grouping by :class:`PeriodIndex` level (:issue:`34010`)
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- Bug in :meth:`GroupBy.rolling.apply` ignores args and kwargs parameters (:issue:`33433`)
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- More informative error message with ``np.min`` or ``np.max`` on unordered :class:`Categorical` (:issue:`33115`)
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- Fixed regression in :meth:`DataFrame.loc` and :meth:`Series.loc` throwing an error when a ``datetime64[ns, tz]`` value is provided (:issue:`32395`)
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- Fix regression in :meth:`DataFrame.replace` casts columns to ``object`` dtype if items in ``to_replace`` not in values (:issue:`32988`)
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- Fix regression in :meth:`Series.groupby` would raise ``ValueError`` when grouping by :class:`PeriodIndex` level (:issue:`34010`)
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- Fix regression in :meth:`GroupBy.rolling.apply` ignores args and kwargs parameters (:issue:`33433`)
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- Fix regression in error message with ``np.min`` or ``np.max`` on unordered :class:`Categorical` (:issue:`33115`)
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- Fix regression in :meth:`DataFrame.loc` and :meth:`Series.loc` throwing an error when a ``datetime64[ns, tz]`` value is provided (:issue:`32395`)
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.. _whatsnew_104.bug_fixes:
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- Bug in :meth:`read_parquet` was raising a ``FileNotFoundError`` when passed an s3 directory path. (:issue:`26388`)
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- Bug in :meth:`~DataFrame.to_parquet` was throwing an ``AttributeError`` when writing a partitioned parquet file to s3 (:issue:`27596`)
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- Bug in :meth:`GroupBy.quantile` causes the quantiles to be shifted when the ``by`` axis contains ``NaN`` (:issue:`33200`, :issue:`33569`)
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Contributors
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~~~~~~~~~~~~

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