DOC/CLN: remove versionadded/changed:: 0.21

doc/source/development/contributing.rst

@@ -791,7 +791,7 @@ the ``pandas.util._decorators.deprecate``:
 
     from pandas.util._decorators import deprecate
 
-    deprecate('old_func', 'new_func', '0.21.0')
+    deprecate('old_func', 'new_func', '1.1.0')
 
 Otherwise, you need to do it manually:
 
@@ -803,7 +803,7 @@ Otherwise, you need to do it manually:
     def old_func():
         """Summary of the function.
 
-        .. deprecated:: 0.21.0
+        .. deprecated:: 1.1.0
            Use new_func instead.
         """
         warnings.warn('Use new_func instead.', FutureWarning, stacklevel=2)
@@ -1354,9 +1354,9 @@ directive is used. The sphinx syntax for that is:
 
 .. code-block:: rst
 
-  .. versionadded:: 0.21.0
+  .. versionadded:: 1.1.0
 
-This will put the text *New in version 0.21.0* wherever you put the sphinx
+This will put the text *New in version 1.1.0* wherever you put the sphinx
 directive. This should also be put in the docstring when adding a new function
 or method (`example <https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/frame.py#L1495>`__)
 or a new keyword argument (`example <https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/generic.py#L568>`__).

doc/source/user_guide/basics.rst

@@ -1224,8 +1224,6 @@ following can be done:
 This means that the reindexed Series's index is the same Python object as the
 DataFrame's index.
 
-.. versionadded:: 0.21.0
-
 :meth:`DataFrame.reindex` also supports an "axis-style" calling convention,
 where you specify a single ``labels`` argument and the ``axis`` it applies to.
 
@@ -1435,8 +1433,6 @@ Series can also be used:
 If the mapping doesn't include a column/index label, it isn't renamed. Note that
 extra labels in the mapping don't throw an error.
 
-.. versionadded:: 0.21.0
-
 :meth:`DataFrame.rename` also supports an "axis-style" calling convention, where
 you specify a single ``mapper`` and the ``axis`` to apply that mapping to.
 

doc/source/user_guide/categorical.rst

@@ -211,8 +211,6 @@ To get back to the original ``Series`` or NumPy array, use
 CategoricalDtype
 ----------------
 
-.. versionchanged:: 0.21.0
-
 A categorical's type is fully described by
 
 1. ``categories``: a sequence of unique values and no missing values

doc/source/user_guide/groupby.rst

@@ -1327,8 +1327,6 @@ See the :ref:`visualization documentation<visualization.box>` for more.
 Piping function calls
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.21.0
-
 Similar to the functionality provided by ``DataFrame`` and ``Series``, functions
 that take ``GroupBy`` objects can be chained together using a ``pipe`` method to
 allow for a cleaner, more readable syntax. To read about ``.pipe`` in general terms,

doc/source/user_guide/io.rst

@@ -461,8 +461,6 @@ specification:
 
    pd.read_csv(StringIO(data), dtype={'col1': 'category'}).dtypes
 
-.. versionadded:: 0.21.0
-
 Specifying ``dtype='category'`` will result in an unordered ``Categorical``
 whose ``categories`` are the unique values observed in the data. For more
 control on the categories and order, create a
@@ -2171,8 +2169,6 @@ Line delimited json
 pandas is able to read and write line-delimited json files that are common in data processing pipelines
 using Hadoop or Spark.
 
-.. versionadded:: 0.21.0
-
 For line-delimited json files, pandas can also return an iterator which reads in ``chunksize`` lines at a time. This can be useful for large files or to read from a stream.
 
 .. ipython:: python
@@ -4646,8 +4642,6 @@ Read from a feather file.
 Parquet
 -------
 
-.. versionadded:: 0.21.0
-
 `Apache Parquet <https://parquet.apache.org/>`__ provides a partitioned binary columnar serialization for data frames. It is designed to
 make reading and writing data frames efficient, and to make sharing data across data analysis
 languages easy. Parquet can use a variety of compression techniques to shrink the file size as much as possible

doc/source/user_guide/merging.rst

@@ -573,8 +573,6 @@ all standard database join operations between ``DataFrame`` or named ``Series``
       dataset.
     * "many_to_many" or "m:m": allowed, but does not result in checks.
 
-  .. versionadded:: 0.21.0
-
 .. note::
 
    Support for specifying index levels as the ``on``, ``left_on``, and
@@ -773,8 +771,6 @@ Here is another example with duplicate join keys in DataFrames:
 Checking for duplicate keys
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 0.21.0
-
 Users can use the ``validate`` argument to automatically check whether there
 are unexpected duplicates in their merge keys. Key uniqueness is checked before
 merge operations and so should protect against memory overflows. Checking key

pandas/_libs/lib.pyx

@@ -1197,8 +1197,6 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
     skipna : bool, default True
         Ignore NaN values when inferring the type.
 
-        .. versionadded:: 0.21.0
-
     Returns
     -------
     str

pandas/core/arrays/categorical.py

@@ -242,8 +242,6 @@ class Categorical(ExtensionArray, PandasObject):
     dtype : CategoricalDtype
         An instance of ``CategoricalDtype`` to use for this categorical.
 
-        .. versionadded:: 0.21.0
-
     Attributes
     ----------
     categories : Index
@@ -257,8 +255,6 @@ class Categorical(ExtensionArray, PandasObject):
         The instance of ``CategoricalDtype`` storing the ``categories``
         and ``ordered``.
 
-        .. versionadded:: 0.21.0
-
     Methods
     -------
     from_codes
@@ -876,8 +872,6 @@ def rename_categories(self, new_categories, inplace=False):
               are passed through and extra categories in the mapping are
               ignored.
 
-            .. versionadded:: 0.21.0.
-
             * callable : a callable that is called on all items in the old
               categories and whose return values comprise the new categories.
 
@@ -1306,7 +1300,6 @@ def __setstate__(self, state):
         if not isinstance(state, dict):
             raise Exception("invalid pickle state")
 
-        # compat with pre 0.21.0 CategoricalDtype change
         if "_dtype" not in state:
             state["_dtype"] = CategoricalDtype(state["_categories"], state["_ordered"])
 

pandas/core/common.py

@@ -357,8 +357,6 @@ def standardize_mapping(into):
     """
     Helper function to standardize a supplied mapping.
 
-    .. versionadded:: 0.21.0
-
     Parameters
     ----------
     into : instance or subclass of collections.abc.Mapping

pandas/core/dtypes/dtypes.py

@@ -189,8 +189,6 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
     """
     Type for categorical data with the categories and orderedness.
 
-    .. versionchanged:: 0.21.0
-
     Parameters
     ----------
     categories : sequence, optional

pandas/core/frame.py

@@ -245,8 +245,6 @@
       dataset.
     * "many_to_many" or "m:m": allowed, but does not result in checks.
 
-    .. versionadded:: 0.21.0
-
 Returns
 -------
 DataFrame
@@ -1339,8 +1337,6 @@ def to_dict(self, orient="dict", into=dict):
             instance of the mapping type you want.  If you want a
             collections.defaultdict, you must pass it initialized.
 
-            .. versionadded:: 0.21.0
-
         Returns
         -------
         dict, list or collections.abc.Mapping
@@ -2118,8 +2114,6 @@ def to_parquet(
         """
         Write a DataFrame to the binary parquet format.
 
-        .. versionadded:: 0.21.0
-
         This function writes the dataframe as a `parquet file
         <https://parquet.apache.org/>`_. You can choose different parquet
         backends, and have the option of compression. See
@@ -3749,13 +3743,9 @@ def drop(
         index : single label or list-like
             Alternative to specifying axis (``labels, axis=0``
             is equivalent to ``index=labels``).
-
-            .. versionadded:: 0.21.0
         columns : single label or list-like
             Alternative to specifying axis (``labels, axis=1``
             is equivalent to ``columns=labels``).
-
-            .. versionadded:: 0.21.0
         level : int or level name, optional
             For MultiIndex, level from which the labels will be removed.
         inplace : bool, default False

pandas/core/generic.py

@@ -526,13 +526,6 @@ def set_axis(self, labels, axis: Axis = 0, inplace: bool = False):
         Indexes for%(extended_summary_sub)s row labels can be changed by assigning
         a list-like or Index.
 
-        .. versionchanged:: 0.21.0
-
-           The signature is now `labels` and `axis`, consistent with
-           the rest of pandas API. Previously, the `axis` and `labels`
-           arguments were respectively the first and second positional
-           arguments.
-
         Parameters
         ----------
         labels : list-like, Index
@@ -1178,8 +1171,6 @@ def _set_axis_name(self, name, axis=0, inplace=False):
         inplace : bool, default False
             If `True`, do operation inplace and return None.
 
-            .. versionadded:: 0.21.0
-
         Returns
         -------
         Series, DataFrame, or None
@@ -2146,7 +2137,6 @@ def to_json(
             only used when the first argument is a filename. By default, the
             compression is inferred from the filename.
 
-            .. versionadded:: 0.21.0
             .. versionchanged:: 0.24.0
                'infer' option added and set to default
         index : bool, default True
@@ -2663,7 +2653,6 @@ def to_pickle(
             parameter is equivalent to setting its value to HIGHEST_PROTOCOL.
 
             .. [1] https://docs.python.org/3/library/pickle.html.
-            .. versionadded:: 0.21.0.
 
         See Also
         --------
@@ -3794,8 +3783,6 @@ def reindex_like(
             the same size as the index and its dtype must exactly match the
             index's type.
 
-            .. versionadded:: 0.21.0 (list-like tolerance)
-
         Returns
         -------
         Series or DataFrame
@@ -4235,8 +4222,6 @@ def reindex(self: FrameOrSeries, *args, **kwargs) -> FrameOrSeries:
             the same size as the index and its dtype must exactly match the
             index's type.
 
-            .. versionadded:: 0.21.0 (list-like tolerance)
-
         Returns
         -------
         %(klass)s with changed index.
@@ -5750,8 +5735,6 @@ def infer_objects(self: FrameOrSeries) -> FrameOrSeries:
         columns unchanged. The inference rules are the
         same as during normal Series/DataFrame construction.
 
-        .. versionadded:: 0.21.0
-
         Returns
         -------
         converted : same type as input object
@@ -7287,8 +7270,6 @@ def clip(
             Align object with lower and upper along the given axis.
         inplace : bool, default False
             Whether to perform the operation in place on the data.
-
-            .. versionadded:: 0.21.0
         *args, **kwargs
             Additional keywords have no effect but might be accepted
             for compatibility with numpy.

pandas/core/indexes/base.py

@@ -2836,8 +2836,6 @@ def get_loc(self, key, method=None, tolerance=None):
             the index at the matching location most satisfy the equation
             ``abs(index[loc] - key) <= tolerance``.
 
-            .. versionadded:: 0.21.0 (list-like tolerance)
-
         Returns
         -------
         loc : int if unique index, slice if monotonic index, else mask
@@ -2909,8 +2907,6 @@ def get_loc(self, key, method=None, tolerance=None):
             the same size as the index and its dtype must exactly match the
             index's type.
 
-            .. versionadded:: 0.21.0 (list-like tolerance)
-
         Returns
         -------
         indexer : ndarray of int

pandas/core/indexes/category.py

@@ -91,8 +91,6 @@ class CategoricalIndex(ExtensionIndex, accessor.PandasDelegate):
     dtype : CategoricalDtype or "category", optional
         If :class:`CategoricalDtype`, cannot be used together with
         `categories` or `ordered`.
-
-        .. versionadded:: 0.21.0
     copy : bool, default False
         Make a copy of input ndarray.
     name : object, optional

pandas/core/indexes/datetimes.py

@@ -1014,16 +1014,10 @@ def bdate_range(
         Weekmask of valid business days, passed to ``numpy.busdaycalendar``,
         only used when custom frequency strings are passed.  The default
         value None is equivalent to 'Mon Tue Wed Thu Fri'.
-
-        .. versionadded:: 0.21.0
-
     holidays : list-like or None, default None
         Dates to exclude from the set of valid business days, passed to
         ``numpy.busdaycalendar``, only used when custom frequency strings
         are passed.
-
-        .. versionadded:: 0.21.0
-
     closed : str, default None
         Make the interval closed with respect to the given frequency to
         the 'left', 'right', or both sides (None).

pandas/core/resample.py

@@ -467,8 +467,6 @@ def nearest(self, limit=None):
         limit : int, optional
             Limit of how many values to fill.
 
-            .. versionadded:: 0.21.0
-
         Returns
         -------
         Series or DataFrame

pandas/core/reshape/pivot.py

@@ -500,9 +500,6 @@ def crosstab(
     margins_name : str, default 'All'
         Name of the row/column that will contain the totals
         when margins is True.
-
-        .. versionadded:: 0.21.0
-
     dropna : bool, default True
         Do not include columns whose entries are all NaN.
     normalize : bool, {'all', 'index', 'columns'}, or {0,1}, default False

pandas/core/series.py

@@ -1509,8 +1509,6 @@ def to_dict(self, into=dict):
             instance of the mapping type you want.  If you want a
             collections.defaultdict, you must pass it initialized.
 
-            .. versionadded:: 0.21.0
-
         Returns
         -------
         collections.abc.Mapping
@@ -4067,12 +4065,8 @@ def drop(
         index : single label or list-like
             Redundant for application on Series, but 'index' can be used instead
             of 'labels'.
-
-            .. versionadded:: 0.21.0
         columns : single label or list-like
             No change is made to the Series; use 'index' or 'labels' instead.
-
-            .. versionadded:: 0.21.0
         level : int or level name, optional
             For MultiIndex, level for which the labels will be removed.
         inplace : bool, default False

pandas/io/formats/style.py

@@ -765,8 +765,6 @@ def where(
         Updates the HTML representation with a style which is
         selected in accordance with the return value of a function.
 
-        .. versionadded:: 0.21.0
-
         Parameters
         ----------
         cond : callable

pandas/io/html.py

@@ -1057,8 +1057,6 @@ def read_html(
     the header, otherwise the function attempts to find the header within
     the body (by putting rows with only ``<th>`` elements into the header).
 
-        .. versionadded:: 0.21.0
-
     Similar to :func:`~read_csv` the `header` argument is applied
     **after** `skiprows` is applied.