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DOC: move 'Other API changes' under correct section #34817

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217 changes: 110 additions & 107 deletions doc/source/whatsnew/v1.1.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -297,116 +297,10 @@ Other enhancements

.. ---------------------------------------------------------------------------

Increased minimum versions for dependencies
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Some minimum supported versions of dependencies were updated (:issue:`33718`, :issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
If installed, we now require:

+-----------------+-----------------+----------+---------+
| Package | Minimum Version | Required | Changed |
+=================+=================+==========+=========+
| numpy | 1.15.4 | X | X |
+-----------------+-----------------+----------+---------+
| pytz | 2015.4 | X | |
+-----------------+-----------------+----------+---------+
| python-dateutil | 2.7.3 | X | X |
+-----------------+-----------------+----------+---------+
| bottleneck | 1.2.1 | | |
+-----------------+-----------------+----------+---------+
| numexpr | 2.6.2 | | |
+-----------------+-----------------+----------+---------+
| pytest (dev) | 4.0.2 | | |
+-----------------+-----------------+----------+---------+

For `optional libraries <https://dev.pandas.io/docs/install.html#dependencies>`_ the general recommendation is to use the latest version.
The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+---------+
| Package | Minimum Version | Changed |
+=================+=================+=========+
| beautifulsoup4 | 4.6.0 | |
+-----------------+-----------------+---------+
| fastparquet | 0.3.2 | |
+-----------------+-----------------+---------+
| gcsfs | 0.2.2 | |
+-----------------+-----------------+---------+
| lxml | 3.8.0 | |
+-----------------+-----------------+---------+
| matplotlib | 2.2.2 | |
+-----------------+-----------------+---------+
| numba | 0.46.0 | |
+-----------------+-----------------+---------+
| openpyxl | 2.5.7 | |
+-----------------+-----------------+---------+
| pyarrow | 0.13.0 | |
+-----------------+-----------------+---------+
| pymysql | 0.7.1 | |
+-----------------+-----------------+---------+
| pytables | 3.4.3 | X |
+-----------------+-----------------+---------+
| s3fs | 0.3.0 | |
+-----------------+-----------------+---------+
| scipy | 1.2.0 | X |
+-----------------+-----------------+---------+
| sqlalchemy | 1.1.4 | |
+-----------------+-----------------+---------+
| xarray | 0.8.2 | |
+-----------------+-----------------+---------+
| xlrd | 1.1.0 | |
+-----------------+-----------------+---------+
| xlsxwriter | 0.9.8 | |
+-----------------+-----------------+---------+
| xlwt | 1.2.0 | |
+-----------------+-----------------+---------+
| pandas-gbq | 1.2.0 | X |
+-----------------+-----------------+---------+

See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for more.

Development Changes
^^^^^^^^^^^^^^^^^^^

- The minimum version of Cython is now the most recent bug-fix version (0.29.16) (:issue:`33334`).

.. _whatsnew_110.api.other:

Other API changes
^^^^^^^^^^^^^^^^^

- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``, ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
.. _whatsnew_110.api:

Backwards incompatible API changes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
- :meth:`DataFrame.swaplevels` now raises a ``TypeError`` if the axis is not a :class:`MultiIndex`.
Previously an ``AttributeError`` was raised (:issue:`31126`)
- :meth:`DataFrame.xs` now raises a ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
Previously an ``AttributeError`` was raised (:issue:`33610`)
- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
now raise a ``TypeError`` if a not-accepted keyword argument is passed into it.
Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
- Combining a ``Categorical`` with integer categories and which contains missing values
with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
will now result in a float column instead of an object dtyped column (:issue:`33607`)
- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
(previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)

``MultiIndex.get_indexer`` interprets `method` argument differently
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Expand Down Expand Up @@ -733,6 +627,115 @@ apply and applymap on ``DataFrame`` evaluates first row/column only once

df.apply(func, axis=1)

.. _whatsnew_110.api.other:

Other API changes
^^^^^^^^^^^^^^^^^

- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
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why are you lumping enhancements in here? this is very confusing

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@jorisvandenbossche jorisvandenbossche Jun 16, 2020 •
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Well, this are the entries that were originally (look at the diff above) under "Other API changes".

I fully agree that this is an enhancement, and that should be cleaned-up, see #34801, but here I am just correcting the order of the sections, not actually fixing the bullet points itself as mentioned in the comment above.

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ok fair enough, yeah these should really be separated a more fine grained way

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Yeah, value_counts here should simply be moved to the enhancement section, and we can discuss in #34801 what kind of more fine grained sections we want for the API changes itself.

- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``, ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
- :meth:`DataFrame.swaplevels` now raises a ``TypeError`` if the axis is not a :class:`MultiIndex`.
Previously an ``AttributeError`` was raised (:issue:`31126`)
- :meth:`DataFrame.xs` now raises a ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
Previously an ``AttributeError`` was raised (:issue:`33610`)
- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
now raise a ``TypeError`` if a not-accepted keyword argument is passed into it.
Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
- Combining a ``Categorical`` with integer categories and which contains missing values
with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
will now result in a float column instead of an object dtyped column (:issue:`33607`)
- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
(previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)


Increased minimum versions for dependencies
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Some minimum supported versions of dependencies were updated (:issue:`33718`, :issue:`29766`, :issue:`29723`, pytables >= 3.4.3).
If installed, we now require:

+-----------------+-----------------+----------+---------+
| Package | Minimum Version | Required | Changed |
+=================+=================+==========+=========+
| numpy | 1.15.4 | X | X |
+-----------------+-----------------+----------+---------+
| pytz | 2015.4 | X | |
+-----------------+-----------------+----------+---------+
| python-dateutil | 2.7.3 | X | X |
+-----------------+-----------------+----------+---------+
| bottleneck | 1.2.1 | | |
+-----------------+-----------------+----------+---------+
| numexpr | 2.6.2 | | |
+-----------------+-----------------+----------+---------+
| pytest (dev) | 4.0.2 | | |
+-----------------+-----------------+----------+---------+

For `optional libraries <https://dev.pandas.io/docs/install.html#dependencies>`_ the general recommendation is to use the latest version.
The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+---------+
| Package | Minimum Version | Changed |
+=================+=================+=========+
| beautifulsoup4 | 4.6.0 | |
+-----------------+-----------------+---------+
| fastparquet | 0.3.2 | |
+-----------------+-----------------+---------+
| gcsfs | 0.2.2 | |
+-----------------+-----------------+---------+
| lxml | 3.8.0 | |
+-----------------+-----------------+---------+
| matplotlib | 2.2.2 | |
+-----------------+-----------------+---------+
| numba | 0.46.0 | |
+-----------------+-----------------+---------+
| openpyxl | 2.5.7 | |
+-----------------+-----------------+---------+
| pyarrow | 0.13.0 | |
+-----------------+-----------------+---------+
| pymysql | 0.7.1 | |
+-----------------+-----------------+---------+
| pytables | 3.4.3 | X |
+-----------------+-----------------+---------+
| s3fs | 0.3.0 | |
+-----------------+-----------------+---------+
| scipy | 1.2.0 | X |
+-----------------+-----------------+---------+
| sqlalchemy | 1.1.4 | |
+-----------------+-----------------+---------+
| xarray | 0.8.2 | |
+-----------------+-----------------+---------+
| xlrd | 1.1.0 | |
+-----------------+-----------------+---------+
| xlsxwriter | 0.9.8 | |
+-----------------+-----------------+---------+
| xlwt | 1.2.0 | |
+-----------------+-----------------+---------+
| pandas-gbq | 1.2.0 | X |
+-----------------+-----------------+---------+

See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for more.

Development Changes
^^^^^^^^^^^^^^^^^^^

- The minimum version of Cython is now the most recent bug-fix version (0.29.16) (:issue:`33334`).


.. _whatsnew_110.deprecations:

Expand Down