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DOC: Remove all versionchanged / versionadded directives < 1.0.0 (#50057)
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doc/source/user_guide/dsintro.rst

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@@ -712,10 +712,8 @@ The ufunc is applied to the underlying array in a :class:`Series`.
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ser = pd.Series([1, 2, 3, 4])
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np.exp(ser)
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.. versionchanged:: 0.25.0
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When multiple :class:`Series` are passed to a ufunc, they are aligned before
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performing the operation.
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When multiple :class:`Series` are passed to a ufunc, they are aligned before
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performing the operation.
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Like other parts of the library, pandas will automatically align labeled inputs
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as part of a ufunc with multiple inputs. For example, using :meth:`numpy.remainder`

doc/source/user_guide/groupby.rst

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@@ -629,8 +629,6 @@ For a grouped ``DataFrame``, you can rename in a similar manner:
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Named aggregation
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~~~~~~~~~~~~~~~~~
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.. versionadded:: 0.25.0
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To support column-specific aggregation *with control over the output column names*, pandas
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accepts the special syntax in :meth:`DataFrameGroupBy.agg` and :meth:`SeriesGroupBy.agg`, known as "named aggregation", where
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doc/source/user_guide/io.rst

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@@ -294,8 +294,6 @@ cache_dates : boolean, default True
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conversion. May produce significant speed-up when parsing duplicate
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date strings, especially ones with timezone offsets.
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Iteration
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+++++++++
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@@ -3829,8 +3827,6 @@ using the `odfpy <https://pypi.org/project/odfpy/>`__ module. The semantics and
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OpenDocument spreadsheets match what can be done for `Excel files`_ using
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``engine='odf'``.
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The :func:`~pandas.read_excel` method can read OpenDocument spreadsheets
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.. code-block:: python
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SPSS formats
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------------
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.. versionadded:: 0.25.0
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The top-level function :func:`read_spss` can read (but not write) SPSS
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SAV (.sav) and ZSAV (.zsav) format files.
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doc/source/user_guide/reshaping.rst

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@@ -890,8 +890,6 @@ Note to subdivide over multiple columns we can pass in a list to the
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Exploding a list-like column
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----------------------------
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.. versionadded:: 0.25.0
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Sometimes the values in a column are list-like.
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.. ipython:: python

doc/source/user_guide/sparse.rst

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@@ -127,9 +127,6 @@ attributes and methods that are specific to sparse data.
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This accessor is available only on data with ``SparseDtype``, and on the :class:`Series`
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class itself for creating a Series with sparse data from a scipy COO matrix with.
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A ``.sparse`` accessor has been added for :class:`DataFrame` as well.
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See :ref:`api.frame.sparse` for more.
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Use :meth:`DataFrame.sparse.from_spmatrix` to create a :class:`DataFrame` with sparse values from a sparse matrix.
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.. ipython:: python
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from scipy.sparse import csr_matrix

doc/source/user_guide/timeseries.rst

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@@ -647,8 +647,6 @@ We are stopping on the included end-point as it is part of the index:
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dft2 = dft2.swaplevel(0, 1).sort_index()
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dft2.loc[idx[:, "2013-01-05"], :]
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Slicing with string indexing also honors UTC offset.
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.. ipython:: python
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)
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rng_utc.tz
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.. ipython:: python
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# datetime.timezone

pandas/_libs/interval.pyx

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"""
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Indicates if an interval is empty, meaning it contains no points.
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Returns
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-------
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bool or ndarray

pandas/_libs/tslibs/nattype.pyx

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"""
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Convert the Timestamp to a NumPy datetime64 or timedelta64.
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With the default 'dtype', this is an alias method for `NaT.to_datetime64()`.
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The copy parameter is available here only for compatibility. Its value

pandas/_libs/tslibs/timedeltas.pyx

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"""
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Convert the Timedelta to a NumPy timedelta64.
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This is an alias method for `Timedelta.to_timedelta64()`. The dtype and
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copy parameters are available here only for compatibility. Their values
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will not affect the return value.

pandas/_libs/tslibs/timestamps.pyx

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"""
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Convert the Timestamp to a NumPy datetime64.
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This is an alias method for `Timestamp.to_datetime64()`. The dtype and
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copy parameters are available here only for compatibility. Their values
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will not affect the return value.

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