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DOC: fixup v1.0.1 whatsnew entries #31686

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Feb 5, 2020
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DOC: fixup v1.0.1 whatsnew entries #31686

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5 changes: 4 additions & 1 deletion doc/source/whatsnew/v1.0.1.rst
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Expand Up @@ -20,9 +20,12 @@ Fixed regressions
- Fixed regression in ``DataFrame.__setitem__`` raising an ``AttributeError`` with a :class:`MultiIndex` and a non-monotonic indexer (:issue:`31449`)
- Fixed regression in :class:`Series` multiplication when multiplying a numeric :class:`Series` with >10000 elements with a timedelta-like scalar (:issue:`31457`)
- Fixed regression in ``.groupby()`` aggregations with categorical dtype using Cythonized reduction functions (e.g. ``first``) (:issue:`31450`)
- Fixed regression in :meth:`DataFrame.groupby` whereby taking the minimum or maximum of a column with period dtype would raise a ``TypeError``. (:issue:`31471`)
- Fixed regression in :meth:`GroupBy.apply` if called with a function which returned a non-pandas non-scalar object (e.g. a list or numpy array) (:issue:`31441`)
- Fixed regression in :meth:`DataFrame.groupby` whereby taking the minimum or maximum of a column with period dtype would raise a ``TypeError``. (:issue:`31471`)
- Fixed regression in :meth:`DataFrame.apply` with object dtype and non-reducing function (:issue:`31505`)
- Fixed regression in :meth:`to_datetime` when parsing non-nanosecond resolution datetimes (:issue:`31491`)
- Fixed regression in :meth:`~DataFrame.to_csv` where specifying an ``na_rep`` might truncate the values written (:issue:`31447`)
- Fixed regression in :class:`Categorical` construction with ``numpy.str_`` categories (:issue:`31499`)
- Fixed regression in :meth:`DataFrame.loc` and :meth:`DataFrame.iloc` when selecting a row containing a single ``datetime64`` or ``timedelta64`` column (:issue:`31649`)
- Fixed regression where setting :attr:`pd.options.display.max_colwidth` was not accepting negative integer. In addition, this behavior has been deprecated in favor of using ``None`` (:issue:`31532`)
- Fixed regression in objTOJSON.c fix return-type warning (:issue:`31463`)
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