DOC: Remove versionadded/changed for 1.1.0 (#52905)

* DOC: Remove versionadded/changed for 1.1.0

* Update contributing_codebase.rst

* Remove double line break

* Fix

Author: phofl

doc/source/development/contributing_codebase.rst

@@ -959,9 +959,9 @@ directive is used. The sphinx syntax for that is:
 
 .. code-block:: rst
 
-  .. versionadded:: 1.1.0
+    .. versionadded:: 2.1.0
 
-This will put the text *New in version 1.1.0* wherever you put the sphinx
+This will put the text *New in version 2.1.0* 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

@@ -686,8 +686,6 @@ of a 1D array of values. It can also be used as a function on regular arrays:
    s.value_counts()
    pd.value_counts(data)
 
-.. versionadded:: 1.1.0
-
 The :meth:`~DataFrame.value_counts` method can be used to count combinations across multiple columns.
 By default all columns are used but a subset can be selected using the ``subset`` argument.
 
@@ -1812,8 +1810,6 @@ used to sort a pandas object by its index levels.
 
 .. _basics.sort_index_key:
 
-.. versionadded:: 1.1.0
-
 Sorting by index also supports a ``key`` parameter that takes a callable
 function to apply to the index being sorted. For ``MultiIndex`` objects,
 the key is applied per-level to the levels specified by ``level``.
@@ -1867,8 +1863,6 @@ argument:
 
 .. _basics.sort_value_key:
 
-.. versionadded:: 1.1.0
-
 Sorting also supports a ``key`` parameter that takes a callable function
 to apply to the values being sorted.
 

doc/source/user_guide/boolean.rst

@@ -24,8 +24,6 @@ Indexing with NA values
 
 pandas allows indexing with ``NA`` values in a boolean array, which are treated as ``False``.
 
-.. versionchanged:: 1.0.2
-
 .. ipython:: python
    :okexcept:
 

doc/source/user_guide/dsintro.rst

@@ -413,8 +413,6 @@ first ``namedtuple``, a ``ValueError`` is raised.
 From a list of dataclasses
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 1.1.0
-
 Data Classes as introduced in `PEP557 <https://www.python.org/dev/peps/pep-0557>`__,
 can be passed into the DataFrame constructor.
 Passing a list of dataclasses is equivalent to passing a list of dictionaries.

doc/source/user_guide/groupby.rst

@@ -218,8 +218,6 @@ For example, the groups created by ``groupby()`` below are in the order they app
 
 .. _groupby.dropna:
 
-.. versionadded:: 1.1.0
-
 GroupBy dropna
 ^^^^^^^^^^^^^^
 

doc/source/user_guide/indexing.rst

@@ -371,8 +371,6 @@ For getting values with a boolean array:
 
 NA values in a boolean array propagate as ``False``:
 
-.. versionchanged:: 1.0.2
-
 .. ipython:: python
 
    mask = pd.array([True, False, True, False, pd.NA, False], dtype="boolean")

doc/source/user_guide/io.rst

@@ -335,7 +335,6 @@ compression : {``'infer'``, ``'gzip'``, ``'bz2'``, ``'zip'``, ``'xz'``, ``'zstd'
   create a reproducible gzip archive:
   ``compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}``.
 
-  .. 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``
   Thousands separator.
@@ -3890,8 +3889,6 @@ The :func:`~pandas.read_excel` method can read OpenDocument spreadsheets
    # Returns a DataFrame
    pd.read_excel("path_to_file.ods", engine="odf")
 
-.. versionadded:: 1.1.0
-
 Similarly, the :func:`~pandas.to_excel` method can write OpenDocument spreadsheets
 
 .. code-block:: python

doc/source/user_guide/reshaping.rst

@@ -298,8 +298,6 @@ For instance,
 
 When transforming a DataFrame using :func:`~pandas.melt`, the index will be ignored. The original index values can be kept around by setting the ``ignore_index`` parameter to ``False`` (default is ``True``). This will however duplicate them.
 
-.. versionadded:: 1.1.0
-
 .. ipython:: python
 
    index = pd.MultiIndex.from_tuples([("person", "A"), ("person", "B")])

doc/source/user_guide/text.rst

@@ -62,8 +62,6 @@ Or ``astype`` after the ``Series`` or ``DataFrame`` is created
    s.astype("string")
 
 
-.. versionchanged:: 1.1.0
-
 You can also use :class:`StringDtype`/``"string"`` as the dtype on non-string data and
 it will be converted to ``string`` dtype:
 
@@ -666,8 +664,6 @@ Or whether elements match a pattern:
        dtype="string",
    ).str.match(pattern)
 
-.. versionadded:: 1.1.0
-
 .. ipython:: python
 
    pd.Series(

doc/source/user_guide/timeseries.rst

@@ -822,8 +822,6 @@ Furthermore, if you have a ``Series`` with datetimelike values, then you can
 access these properties via the ``.dt`` accessor, as detailed in the section
 on :ref:`.dt accessors<basics.dt_accessors>`.
 
-.. versionadded:: 1.1.0
-
 You may obtain the year, week and day components of the ISO year from the ISO 8601 standard:
 
 .. ipython:: python
@@ -1870,8 +1868,6 @@ See :ref:`groupby.iterating-label` or :class:`Resampler.__iter__` for more.
 Use ``origin`` or ``offset`` to adjust the start of the bins
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 1.1.0
-
 The bins of the grouping are adjusted based on the beginning of the day of the time series starting point. This works well with frequencies that are multiples of a day (like ``30D``) or that divide a day evenly (like ``90s`` or ``1min``). This can create inconsistencies with some frequencies that do not meet this criteria. To change this behavior you can specify a fixed Timestamp with the argument ``origin``.
 
 For example:
@@ -2117,8 +2113,6 @@ PeriodIndex partial string indexing
 
 PeriodIndex now supports partial string slicing with non-monotonic indexes.
 
-.. versionadded:: 1.1.0
-
 You can pass in dates and strings to ``Series`` and ``DataFrame`` with ``PeriodIndex``, in the same manner as ``DatetimeIndex``. For details, refer to :ref:`DatetimeIndex Partial String Indexing <timeseries.partialindexing>`.
 
 .. ipython:: python
@@ -2491,8 +2485,6 @@ To remove time zone information, use ``tz_localize(None)`` or ``tz_convert(None)
 Fold
 ~~~~
 
-.. versionadded:: 1.1.0
-
 For ambiguous times, pandas supports explicitly specifying the keyword-only fold argument.
 Due to daylight saving time, one wall clock time can occur twice when shifting
 from summer to winter time; fold describes whether the datetime-like corresponds

doc/source/user_guide/visualization.rst

@@ -1209,8 +1209,6 @@ shown by default.
 Controlling the labels
 ~~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 1.1.0
-
 You may set the ``xlabel`` and ``ylabel`` arguments to give the plot custom labels
 for x and y axis. By default, pandas will pick up index name as xlabel, while leaving
 it empty for ylabel.

doc/source/user_guide/window.rst

@@ -237,8 +237,6 @@ from present information back to past information. This allows the rolling windo
 Custom window rolling
 ~~~~~~~~~~~~~~~~~~~~~
 
-.. versionadded:: 1.0
-
 In addition to accepting an integer or offset as a ``window`` argument, ``rolling`` also accepts
 a ``BaseIndexer`` subclass that allows a user to define a custom method for calculating window bounds.
 The ``BaseIndexer`` subclass will need to define a ``get_window_bounds`` method that returns
@@ -358,8 +356,6 @@ the windows are cast as :class:`Series` objects (``raw=False``) or ndarray objec
 Numba engine
 ~~~~~~~~~~~~
 
-.. versionadded:: 1.0
-
 Additionally, :meth:`~Rolling.apply` can leverage `Numba <https://numba.pydata.org/>`__
 if installed as an optional dependency. The apply aggregation can be executed using Numba by specifying
 ``engine='numba'`` and ``engine_kwargs`` arguments (``raw`` must also be set to ``True``).
@@ -593,8 +589,6 @@ and **alpha** to the EW functions:
   one half.
 * **Alpha** specifies the smoothing factor directly.
 
-.. versionadded:: 1.1.0
-
 You can also specify ``halflife`` in terms of a timedelta convertible unit to specify the amount of
 time it takes for an observation to decay to half its value when also specifying a sequence
 of ``times``.

pandas/_libs/testing.pyx

@@ -59,12 +59,8 @@ cpdef assert_almost_equal(a, b,
     b : object
     rtol : float, default 1e-5
         Relative tolerance.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance.
-
-        .. versionadded:: 1.1.0
     check_dtype: bool, default True
         check dtype if both a and b are np.ndarray.
     obj : str, default None
@@ -80,8 +76,6 @@ cpdef assert_almost_equal(a, b,
         Specify shared index values of objects being compared, internally used
         to show appropriate assertion message.
 
-        .. versionadded:: 1.1.0
-
     """
     cdef:
         double diff = 0.0

pandas/_libs/tslibs/timestamps.pyx

@@ -1302,8 +1302,6 @@ class Timestamp(_Timestamp):
         datetime-like corresponds  to the first (0) or the second time (1)
         the wall clock hits the ambiguous time.
 
-        .. versionadded:: 1.1.0
-
     Notes
     -----
     There are essentially three calling conventions for the constructor. The

pandas/_testing/asserters.py

@@ -85,12 +85,8 @@ def assert_almost_equal(
         equivalent when doing type checking.
     rtol : float, default 1e-5
         Relative tolerance.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance.
-
-        .. versionadded:: 1.1.0
     """
     if isinstance(left, Index):
         assert_index_equal(
@@ -217,12 +213,8 @@ def assert_index_equal(
         .. versionadded:: 1.2.0
     rtol : float, default 1e-5
         Relative tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     obj : str, default 'Index'
         Specify object name being compared, internally used to show appropriate
         assertion message.
@@ -711,12 +703,8 @@ def assert_extension_array_equal(
         Whether to compare number exactly.
     rtol : float, default 1e-5
         Relative tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     obj : str, default 'ExtensionArray'
         Specify object name being compared, internally used to show appropriate
         assertion message.
@@ -842,25 +830,17 @@ def assert_series_equal(
         Whether to compare internal Categorical exactly.
     check_category_order : bool, default True
         Whether to compare category order of internal Categoricals.
-
-        .. versionadded:: 1.0.2
     check_freq : bool, default True
         Whether to check the `freq` attribute on a DatetimeIndex or TimedeltaIndex.
-
-        .. versionadded:: 1.1.0
     check_flags : bool, default True
         Whether to check the `flags` attribute.
 
         .. versionadded:: 1.2.0
 
     rtol : float, default 1e-5
         Relative tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     obj : str, default 'Series'
         Specify object name being compared, internally used to show appropriate
         assertion message.
@@ -1111,18 +1091,12 @@ def assert_frame_equal(
         (same as in columns) - same labels must be with the same data.
     check_freq : bool, default True
         Whether to check the `freq` attribute on a DatetimeIndex or TimedeltaIndex.
-
-        .. versionadded:: 1.1.0
     check_flags : bool, default True
         Whether to check the `flags` attribute.
     rtol : float, default 1e-5
         Relative tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     atol : float, default 1e-8
         Absolute tolerance. Only used when check_exact is False.
-
-        .. versionadded:: 1.1.0
     obj : str, default 'DataFrame'
         Specify object name being compared, internally used to show appropriate
         assertion message.

pandas/core/arrays/datetimes.py

@@ -1350,8 +1350,6 @@ def isocalendar(self) -> DataFrame:
         """
         Calculate year, week, and day according to the ISO 8601 standard.
 
-        .. versionadded:: 1.1.0
-
         Returns
         -------
         DataFrame

pandas/core/common.py

@@ -439,11 +439,6 @@ def random_state(state: RandomState | None = None):
         If receives `None`, returns np.random.
         If receives anything else, raises an informative ValueError.
 
-        .. versionchanged:: 1.1.0
-
-            array-like and BitGenerator object now passed to np.random.RandomState()
-            as seed
-
         Default None.
 
     Returns