Modified whasnew v1.1.0.rst

Author: Santhosh18

doc/source/whatsnew/v1.1.0.rst

@@ -748,43 +748,6 @@ Using :meth:`DataFrame.explode` and :meth:`Series.explode` would always return a
     B    int64
     dtype: object
 
-.. _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 a :func:`pandas.api.indexers.NonFixedVariableWindowIndexer` class to support ``rolling`` operations with non-fixed offsets (:issue:`34994`)
-- 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
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^