DOC: remove versionadded/changed:: 0.24 (#41851)

pandas-dev · Jun 8, 2021 · 9936902 · 9936902
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diff --git a/doc/source/development/extending.rst b/doc/source/development/extending.rst
@@ -106,8 +106,6 @@ extension array for IP Address data, this might be ``ipaddress.IPv4Address``.
 
 See the `extension dtype source`_ for interface definition.
 
-.. versionadded:: 0.24.0
-
 :class:`pandas.api.extension.ExtensionDtype` can be registered to pandas to allow creation via a string dtype name.
 This allows one to instantiate ``Series`` and ``.astype()`` with a registered string name, for
 example ``'category'`` is a registered string accessor for the ``CategoricalDtype``.
@@ -141,8 +139,6 @@ and comments contain guidance for properly implementing the interface.
 :class:`~pandas.api.extensions.ExtensionArray` operator support
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. versionadded:: 0.24.0
-
 By default, there are no operators defined for the class :class:`~pandas.api.extensions.ExtensionArray`.
 There are two approaches for providing operator support for your ExtensionArray:
 

diff --git a/doc/source/user_guide/advanced.rst b/doc/source/user_guide/advanced.rst
@@ -40,11 +40,6 @@ analysis.
 
 See the :ref:`cookbook<cookbook.multi_index>` for some advanced strategies.
 
-.. versionchanged:: 0.24.0
-
-   :attr:`MultiIndex.labels` has been renamed to :attr:`MultiIndex.codes`
-   and :attr:`MultiIndex.set_labels` to :attr:`MultiIndex.set_codes`.
-
 Creating a MultiIndex (hierarchical index) object
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -87,8 +82,6 @@ You can also construct a ``MultiIndex`` from a ``DataFrame`` directly, using
 the method :meth:`MultiIndex.from_frame`. This is a complementary method to
 :meth:`MultiIndex.to_frame`.
 
-.. versionadded:: 0.24.0
-
 .. ipython:: python
 
    df = pd.DataFrame(

diff --git a/doc/source/user_guide/basics.rst b/doc/source/user_guide/basics.rst
@@ -1490,8 +1490,6 @@ for altering the ``Series.name`` attribute.
 
 .. _basics.rename_axis:
 
-.. versionadded:: 0.24.0
-
 The methods :meth:`DataFrame.rename_axis` and :meth:`Series.rename_axis`
 allow specific names of a ``MultiIndex`` to be changed (as opposed to the
 labels).

diff --git a/doc/source/user_guide/computation.rst b/doc/source/user_guide/computation.rst
@@ -141,8 +141,6 @@ Like ``cov``, ``corr`` also supports the optional ``min_periods`` keyword:
    frame.corr(min_periods=12)
 
 
-.. versionadded:: 0.24.0
-
 The ``method`` argument can also be a callable for a generic correlation
 calculation. In this case, it should be a single function
 that produces a single value from two ndarray inputs. Suppose we wanted to

diff --git a/doc/source/user_guide/groupby.rst b/doc/source/user_guide/groupby.rst
@@ -125,8 +125,6 @@ We could naturally group by either the ``A`` or ``B`` columns, or both:
    grouped = df.groupby("A")
    grouped = df.groupby(["A", "B"])
 
-.. versionadded:: 0.24
-
 If we also have a MultiIndex on columns ``A`` and ``B``, we can group by all
 but the specified columns
 

diff --git a/doc/source/user_guide/integer_na.rst b/doc/source/user_guide/integer_na.rst
@@ -8,8 +8,6 @@
 Nullable integer data type
 **************************
 
-.. versionadded:: 0.24.0
-
 .. note::
 
    IntegerArray is currently experimental. Its API or implementation may

diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
@@ -297,7 +297,6 @@ compression : {``'infer'``, ``'gzip'``, ``'bz2'``, ``'zip'``, ``'xz'``, ``None``
   create a reproducible gzip archive:
   ``compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}``.
 
-  .. versionchanged:: 0.24.0 'infer' option added and set to default.
   .. versionchanged:: 1.1.0 dict option extended to support ``gzip`` and ``bz2``.
   .. versionchanged:: 1.2.0 Previous versions forwarded dict entries for 'gzip' to ``gzip.open``.
 thousands : str, default ``None``
@@ -2714,8 +2713,6 @@ table CSS classes. Note that these classes are *appended* to the existing
 The ``render_links`` argument provides the ability to add hyperlinks to cells
 that contain URLs.
 
-.. versionadded:: 0.24
-
 .. ipython:: python
 
    url_df = pd.DataFrame(
@@ -3590,8 +3587,6 @@ indices to be parsed.
 
 Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``.
 
-.. versionadded:: 0.24
-
 If ``usecols`` is a list of strings, it is assumed that each string corresponds
 to a column name provided either by the user in ``names`` or inferred from the
 document header row(s). Those strings define which columns will be parsed:
@@ -3602,8 +3597,6 @@ document header row(s). Those strings define which columns will be parsed:
 
 Element order is ignored, so ``usecols=['baz', 'joe']`` is the same as ``['joe', 'baz']``.
 
-.. versionadded:: 0.24
-
 If ``usecols`` is callable, the callable function will be evaluated against
 the column names, returning names where the callable function evaluates to ``True``.
 
@@ -4260,9 +4253,6 @@ everything in the sub-store and **below**, so be *careful*.
 You can walk through the group hierarchy using the ``walk`` method which
 will yield a tuple for each group key along with the relative keys of its contents.
 
-.. versionadded:: 0.24.0
-
-
 .. ipython:: python
 
    for (path, subgroups, subkeys) in store.walk():
@@ -5439,8 +5429,6 @@ underlying engine's default behavior.
 Partitioning Parquet files
 ''''''''''''''''''''''''''
 
-.. versionadded:: 0.24.0
-
 Parquet supports partitioning of data based on the values of one or more columns.
 
 .. ipython:: python
@@ -5668,8 +5656,6 @@ will convert the data to UTC.
 Insertion method
 ++++++++++++++++
 
-.. versionadded:: 0.24.0
-
 The parameter ``method`` controls the SQL insertion clause used.
 Possible values are:
 

diff --git a/doc/source/user_guide/sparse.rst b/doc/source/user_guide/sparse.rst
@@ -114,8 +114,6 @@ in many places
 Sparse accessor
 ---------------
 
-.. versionadded:: 0.24.0
-
 pandas provides a ``.sparse`` accessor, similar to ``.str`` for string data, ``.cat``
 for categorical data, and ``.dt`` for datetime-like data. This namespace provides
 attributes and methods that are specific to sparse data.

diff --git a/pandas/_libs/interval.pyx b/pandas/_libs/interval.pyx
@@ -449,8 +449,6 @@ cdef class Interval(IntervalMixin):
         endpoints. Intervals that only have an open endpoint in common do not
         overlap.
 
-        .. versionadded:: 0.24.0
-
         Parameters
         ----------
         other : Interval

diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
@@ -1063,8 +1063,6 @@ def is_list_like(obj: object, allow_sets: bool = True) -> bool:
     allow_sets : bool, default True
         If this parameter is False, sets will not be considered list-like.
 
-        .. versionadded:: 0.24.0
-
     Returns
     -------
     bool

diff --git a/pandas/_libs/tslibs/nattype.pyx b/pandas/_libs/tslibs/nattype.pyx
@@ -744,7 +744,6 @@ class NaTType(_NaT):
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -759,8 +758,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         a new Timestamp rounded to the given resolution of `freq`
@@ -822,7 +819,6 @@ timedelta}, default 'raise'
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -837,8 +833,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Raises
         ------
         ValueError if the freq cannot be converted.
@@ -896,7 +890,6 @@ timedelta}, default 'raise'
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -911,8 +904,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Raises
         ------
         ValueError if the freq cannot be converted.
@@ -1041,8 +1032,6 @@ default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         localized : Timestamp

diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
@@ -1378,7 +1378,6 @@ class Timestamp(_Timestamp):
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -1393,8 +1392,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         a new Timestamp rounded to the given resolution of `freq`
@@ -1458,7 +1455,6 @@ timedelta}, default 'raise'
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -1473,8 +1469,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Raises
         ------
         ValueError if the freq cannot be converted.
@@ -1532,7 +1526,6 @@ timedelta}, default 'raise'
             * 'NaT' will return NaT for an ambiguous time.
             * 'raise' will raise an AmbiguousTimeError for an ambiguous time.
 
-            .. versionadded:: 0.24.0
         nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', \
 timedelta}, default 'raise'
             A nonexistent time does not exist in a particular timezone
@@ -1547,8 +1540,6 @@ timedelta}, default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Raises
         ------
         ValueError if the freq cannot be converted.
@@ -1669,8 +1660,6 @@ default 'raise'
             * 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         localized : Timestamp

diff --git a/pandas/_libs/tslibs/tzconversion.pyx b/pandas/_libs/tslibs/tzconversion.pyx
@@ -110,8 +110,6 @@ def tz_localize_to_utc(ndarray[int64_t] vals, tzinfo tz, object ambiguous=None,
 timedelta-like}
         How to handle non-existent times when converting wall times to UTC
 
-        .. versionadded:: 0.24.0
-
     Returns
     -------
     localized : ndarray[int64_t]

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
@@ -938,8 +938,6 @@ def mode(values, dropna: bool = True) -> Series:
     dropna : bool, default True
         Don't consider counts of NaN/NaT.
 
-        .. versionadded:: 0.24.0
-
     Returns
     -------
     mode : Series

diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
@@ -251,8 +251,6 @@ def _from_sequence_of_strings(
         """
         Construct a new ExtensionArray from a sequence of strings.
 
-        .. versionadded:: 0.24.0
-
         Parameters
         ----------
         strings : Sequence
@@ -755,8 +753,6 @@ def shift(self, periods: int = 1, fill_value: object = None) -> ExtensionArray:
         Newly introduced missing values are filled with
         ``self.dtype.na_value``.
 
-        .. versionadded:: 0.24.0
-
         Parameters
         ----------
         periods : int, default 1
@@ -767,8 +763,6 @@ def shift(self, periods: int = 1, fill_value: object = None) -> ExtensionArray:
             The scalar value to use for newly introduced missing values.
             The default is ``self.dtype.na_value``.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         ExtensionArray
@@ -817,8 +811,6 @@ def searchsorted(self, value, side="left", sorter=None):
         """
         Find indices where elements should be inserted to maintain order.
 
-        .. versionadded:: 0.24.0
-
         Find the indices into a sorted array `self` (a) such that, if the
         corresponding elements in `value` were inserted before the indices,
         the order of `self` would be preserved.

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
@@ -653,11 +653,6 @@ def from_codes(
             If :class:`CategoricalDtype`, cannot be used together with
             `categories` or `ordered`.
 
-            .. versionadded:: 0.24.0
-
-               When `dtype` is provided, neither `categories` nor `ordered`
-               should be provided.
-
         Returns
         -------
         Categorical
@@ -2170,8 +2165,6 @@ def mode(self, dropna=True):
         dropna : bool, default True
             Don't consider counts of NaN/NaT.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         modes : `Categorical` (sorted)

diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
@@ -1596,8 +1596,6 @@ def strftime(self, date_format: str) -> np.ndarray:
         - 'raise' will raise an AmbiguousTimeError if there are ambiguous
           times.
 
-        .. versionadded:: 0.24.0
-
     nonexistent : 'shift_forward', 'shift_backward', 'NaT', timedelta, default 'raise'
         A nonexistent time does not exist in a particular timezone
         where clocks moved forward due to DST.
@@ -1611,8 +1609,6 @@ def strftime(self, date_format: str) -> np.ndarray:
         - 'raise' will raise an NonExistentTimeError if there are
           nonexistent times.
 
-        .. versionadded:: 0.24.0
-
     Returns
     -------
     DatetimeIndex, TimedeltaIndex, or Series

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
@@ -151,8 +151,6 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
     """
     Pandas ExtensionArray for tz-naive or tz-aware datetime data.
 
-    .. versionadded:: 0.24.0
-
     .. warning::
 
        DatetimeArray is currently experimental, and its API may change
@@ -910,8 +908,6 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise") -> DatetimeArr
             - 'raise' will raise an NonExistentTimeError if there are
               nonexistent times.
 
-            .. versionadded:: 0.24.0
-
         Returns
         -------
         Same type as self