pandas-dev · jreback · Sep 13, 2020 · Sep 13, 2020 · Sep 13, 2020
diff --git a/doc/source/development/extending.rst b/doc/source/development/extending.rst
@@ -73,8 +73,6 @@ applies only to certain dtypes.
 Extension types
 ---------------
 
-.. versionadded:: 0.23.0
-
 .. warning::
 
    The :class:`pandas.api.extensions.ExtensionDtype` and :class:`pandas.api.extensions.ExtensionArray` APIs are new and

diff --git a/doc/source/getting_started/install.rst b/doc/source/getting_started/install.rst
@@ -301,8 +301,6 @@ Optional dependencies for parsing HTML
 One of the following combinations of libraries is needed to use the
 top-level :func:`~pandas.read_html` function:
 
-.. versionchanged:: 0.23.0
-
 * `BeautifulSoup4`_ and `html5lib`_
 * `BeautifulSoup4`_ and `lxml`_
 * `BeautifulSoup4`_ and `html5lib`_ and `lxml`_

diff --git a/doc/source/user_guide/advanced.rst b/doc/source/user_guide/advanced.rst
@@ -1065,8 +1065,6 @@ are closed on.  Intervals are closed on the right side by default.
 
    pd.interval_range(start=0, end=4, closed='neither')
 
-.. versionadded:: 0.23.0
-
 Specifying ``start``, ``end``, and ``periods`` will generate a range of evenly spaced
 intervals from ``start`` to ``end`` inclusively, with ``periods`` number of elements
 in the resulting ``IntervalIndex``:

diff --git a/doc/source/user_guide/basics.rst b/doc/source/user_guide/basics.rst
@@ -1877,8 +1877,6 @@ different columns.
 By indexes and values
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.23.0
-
 Strings passed as the ``by`` parameter to :meth:`DataFrame.sort_values` may
 refer to either columns or index level names.
 

diff --git a/doc/source/user_guide/categorical.rst b/doc/source/user_guide/categorical.rst
@@ -112,8 +112,6 @@ only labels present in a given column are categories:
     df['B']
 
 
-.. versionadded:: 0.23.0
-
 Analogously, all columns in an existing ``DataFrame`` can be batch converted using :meth:`DataFrame.astype`:
 
 .. ipython:: python

diff --git a/doc/source/user_guide/dsintro.rst b/doc/source/user_guide/dsintro.rst
@@ -597,8 +597,6 @@ to be inserted (for example, a ``Series`` or NumPy array), or a function
 of one argument to be called on the ``DataFrame``. A *copy* of the original
 DataFrame is returned, with the new values inserted.
 
-.. versionchanged:: 0.23.0
-
 Starting with Python 3.6 the order of ``**kwargs`` is preserved. This allows
 for *dependent* assignment, where an expression later in ``**kwargs`` can refer
 to a column created earlier in the same :meth:`~DataFrame.assign`.

diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
@@ -2360,8 +2360,6 @@ A few notes on the generated table schema:
       then ``level_<i>`` is used.
 
 
-.. versionadded:: 0.23.0
-
 ``read_json`` also accepts ``orient='table'`` as an argument. This allows for
 the preservation of metadata such as dtypes and index names in a
 round-trippable manner.

diff --git a/doc/source/user_guide/merging.rst b/doc/source/user_guide/merging.rst
@@ -175,8 +175,6 @@ behavior:
 
 .. warning::
 
-   .. versionchanged:: 0.23.0
-
    The default behavior with ``join='outer'`` is to sort the other axis
    (columns in this case). In a future version of pandas, the default will
    be to not sort. We specified ``sort=False`` to opt in to the new
@@ -1198,8 +1196,6 @@ done using the following code.
 Merging on a combination of columns and index levels
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.23
-
 Strings passed as the ``on``, ``left_on``, and ``right_on`` parameters
 may refer to either column names or index level names.  This enables merging
 ``DataFrame`` instances on a combination of index levels and columns without

diff --git a/doc/source/user_guide/missing_data.rst b/doc/source/user_guide/missing_data.rst
@@ -336,10 +336,6 @@ examined :ref:`in the API <api.dataframe.missing>`.
 Interpolation
 ~~~~~~~~~~~~~
 
-.. versionadded:: 0.23.0
-
-  The ``limit_area`` keyword argument was added.
-
 Both Series and DataFrame objects have :meth:`~DataFrame.interpolate`
 that, by default, performs linear interpolation at missing data points.
 
@@ -507,8 +503,8 @@ By default, ``NaN`` values are filled in a ``forward`` direction. Use
    ser.interpolate(limit_direction='both')
 
 By default, ``NaN`` values are filled whether they are inside (surrounded by)
-existing valid values, or outside existing valid values. Introduced in v0.23
-the ``limit_area`` parameter restricts filling to either inside or outside values.
+existing valid values, or outside existing valid values. The ``limit_area``
+parameter restricts filling to either inside or outside values.
 
 .. ipython:: python
 

diff --git a/doc/source/user_guide/reshaping.rst b/doc/source/user_guide/reshaping.rst
@@ -679,8 +679,6 @@ To choose another dtype, use the ``dtype`` argument:
 
     pd.get_dummies(df, dtype=bool).dtypes
 
-.. versionadded:: 0.23.0
-
 
 .. _reshaping.factorize:
 

diff --git a/doc/source/user_guide/text.rst b/doc/source/user_guide/text.rst
@@ -282,8 +282,6 @@ following code will cause trouble because of the regular expression meaning of
    # We need to escape the special character (for >1 len patterns)
    dollars.str.replace(r'-\$', '-')
 
-.. versionadded:: 0.23.0
-
 If you do want literal replacement of a string (equivalent to
 :meth:`str.replace`), you can set the optional ``regex`` parameter to
 ``False``, rather than escaping each character. In this case both ``pat``
@@ -390,8 +388,6 @@ Missing values on either side will result in missing values in the result as wel
 Concatenating a Series and something array-like into a Series
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. versionadded:: 0.23.0
-
 The parameter ``others`` can also be two-dimensional. In this case, the number or rows must match the lengths of the calling ``Series`` (or ``Index``).
 
 .. ipython:: python
@@ -404,8 +400,6 @@ The parameter ``others`` can also be two-dimensional. In this case, the number o
 Concatenating a Series and an indexed object into a Series, with alignment
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. versionadded:: 0.23.0
-
 For concatenation with a ``Series`` or ``DataFrame``, it is possible to align the indexes before concatenation by setting
 the ``join``-keyword.
 

diff --git a/doc/source/user_guide/timedeltas.rst b/doc/source/user_guide/timedeltas.rst
@@ -53,10 +53,6 @@ You can construct a ``Timedelta`` scalar through various arguments:
    pd.Timedelta('P0DT0H1M0S')
    pd.Timedelta('P0DT0H0M0.000000123S')
 
-.. versionadded:: 0.23.0
-
-   Added constructor for `ISO 8601 Duration`_ strings
-
 :ref:`DateOffsets<timeseries.offsets>` (``Day, Hour, Minute, Second, Milli, Micro, Nano``) can also be used in construction.
 
 .. ipython:: python
@@ -387,8 +383,6 @@ The ``freq`` parameter can passed a variety of :ref:`frequency aliases <timeseri
    pd.timedelta_range(start='1 days', periods=5, freq='2D5H')
 
 
-.. versionadded:: 0.23.0
-
 Specifying ``start``, ``end``, and ``periods`` will generate a range of evenly spaced
 timedeltas from ``start`` to ``end`` inclusively, with ``periods`` number of elements
 in the resulting ``TimedeltaIndex``:

diff --git a/doc/source/user_guide/timeseries.rst b/doc/source/user_guide/timeseries.rst
@@ -461,8 +461,6 @@ of those specified will not be generated:
 
    pd.bdate_range(start=start, periods=20)
 
-.. versionadded:: 0.23.0
-
 Specifying ``start``, ``end``, and ``periods`` will generate a range of evenly spaced
 dates from ``start`` to ``end`` inclusively, with ``periods`` number of elements in the
 resulting ``DatetimeIndex``:
@@ -643,8 +641,6 @@ Slicing with string indexing also honors UTC offset.
 Slice vs. exact match
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. versionchanged:: 0.20.0
-
 The same string used as an indexing parameter can be treated either as a slice or as an exact match depending on the resolution of the index. If the string is less accurate than the index, it will be treated as a slice, otherwise as an exact match.
 
 Consider a ``Series`` object with a minute resolution index:

diff --git a/pandas/_libs/tslibs/nattype.pyx b/pandas/_libs/tslibs/nattype.pyx
@@ -392,9 +392,7 @@ class NaTType(_NaT):
 
         Returns
         -------
-        month_name : string
-
-        .. versionadded:: 0.23.0
+        string
         """,
     )
     day_name = _make_nan_func(
@@ -409,9 +407,7 @@ class NaTType(_NaT):
 
         Returns
         -------
-        day_name : string
-
-        .. versionadded:: 0.23.0
+        string
         """,
     )
     # _nat_methods

diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
@@ -503,9 +503,7 @@ cdef class _Timestamp(ABCTimestamp):
 
         Returns
         -------
-        day_name : string
-
-        .. versionadded:: 0.23.0
+        string
         """
         return self._get_date_name_field("day_name", locale)
 
@@ -520,9 +518,7 @@ cdef class _Timestamp(ABCTimestamp):
 
         Returns
         -------
-        month_name : string
-
-        .. versionadded:: 0.23.0
+        string
         """
         return self._get_date_name_field("month_name", locale)
 
@@ -783,7 +779,6 @@ class Timestamp(_Timestamp):
     year, month, day : int
     hour, minute, second, microsecond : int, optional, default 0
     nanosecond : int, optional, default 0
-        .. versionadded:: 0.23.0
     tzinfo : datetime.tzinfo, optional, default None
     fold : {0, 1}, default None, keyword-only
         Due to daylight saving time, one wall clock time can occur twice

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
@@ -1524,8 +1524,6 @@ def take(arr, indices, axis: int = 0, allow_fill: bool = False, fill_value=None)
     """
     Take elements from an array.
 
-    .. versionadded:: 0.23.0
-
     Parameters
     ----------
     arr : sequence

diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
@@ -46,8 +46,6 @@ class ExtensionArray:
     with a custom type and will not attempt to coerce them to objects. They
     may be stored directly inside a :class:`DataFrame` or :class:`Series`.
 
-    .. versionadded:: 0.23.0
-
     Attributes
     ----------
     dtype

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
@@ -838,8 +838,6 @@ def rename_categories(self, new_categories, inplace=False):
             * callable : a callable that is called on all items in the old
               categories and whose return values comprise the new categories.
 
-            .. versionadded:: 0.23.0.
-
         inplace : bool, default False
             Whether or not to rename the categories inplace or return a copy of
             this categorical with renamed categories.

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
@@ -1148,8 +1148,6 @@ def month_name(self, locale=None):
         """
         Return the month names of the DateTimeIndex with specified locale.
 
-        .. versionadded:: 0.23.0
-
         Parameters
         ----------
         locale : str, optional
@@ -1183,8 +1181,6 @@ def day_name(self, locale=None):
         """
         Return the day names of the DateTimeIndex with specified locale.
 
-        .. versionadded:: 0.23.0
-
         Parameters
         ----------
         locale : str, optional

diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
@@ -71,8 +71,6 @@
     neither.
 dtype : dtype or None, default None
     If None, dtype will be inferred.
-
-    .. versionadded:: 0.23.0
 copy : bool, default False
     Copy the input data.
 %(name)s\
@@ -279,8 +277,6 @@ def _from_factorized(cls, values, original):
     dtype : dtype or None, default None
         If None, dtype will be inferred.
 
-        .. versionadded:: 0.23.0
-
     Returns
     -------
     %(klass)s
@@ -335,8 +331,6 @@ def from_breaks(cls, breaks, closed="right", copy=False, dtype=None):
         dtype : dtype, optional
             If None, dtype will be inferred.
 
-            .. versionadded:: 0.23.0
-
         Returns
         -------
         %(klass)s
@@ -407,8 +401,6 @@ def from_arrays(cls, left, right, closed="right", copy=False, dtype=None):
     dtype : dtype or None, default None
         If None, dtype will be inferred.
 
-        .. versionadded:: 0.23.0
-
     Returns
     -------
     %(klass)s
@@ -1167,8 +1159,6 @@ def __arrow_array__(self, type=None):
             Returns NA as a tuple if True, ``(nan, nan)``, or just as the NA
             value itself if False, ``nan``.
 
-            .. versionadded:: 0.23.0
-
         Returns
         -------
         tuples: %(return_type)s

diff --git a/pandas/core/dtypes/base.py b/pandas/core/dtypes/base.py
@@ -19,8 +19,6 @@ class ExtensionDtype:
     """
     A custom data type, to be paired with an ExtensionArray.
 
-    .. versionadded:: 0.23.0
-
     See Also
     --------
     extensions.register_extension_dtype
-Original file line number
+Diff line change
@@ Expand Up / @@ -112,8 +112,6 @@ only labels present in a given column are categories: @@
         df['B']
-    .. versionadded:: 0.23.0
     Analogously, all columns in an existing ``DataFrame`` can be batch converted using :meth:`DataFrame.astype`:
     .. ipython:: python
@@ Expand Down @@
Original file line number	Diff line number	Diff line change
Expand Up		@@ -679,8 +679,6 @@ To choose another dtype, use the ``dtype`` argument:

		pd.get_dummies(df, dtype=bool).dtypes

		.. versionadded:: 0.23.0


		.. _reshaping.factorize:

Expand Down