diff --git a/doc/source/user_guide/duplicates.rst b/doc/source/user_guide/duplicates.rst index 7894789846ce8..9aef38d868374 100644 --- a/doc/source/user_guide/duplicates.rst +++ b/doc/source/user_guide/duplicates.rst @@ -109,8 +109,6 @@ with the same label. Disallowing Duplicate Labels ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -.. versionadded:: 1.2.0 - As noted above, handling duplicates is an important feature when reading in raw data. That said, you may want to avoid introducing duplicates as part of a data processing pipeline (from methods like :meth:`pandas.concat`, diff --git a/doc/source/user_guide/groupby.rst b/doc/source/user_guide/groupby.rst index 4ec34db6ed959..552f6a0699340 100644 --- a/doc/source/user_guide/groupby.rst +++ b/doc/source/user_guide/groupby.rst @@ -1264,8 +1264,6 @@ with Numba accelerated routines -------------------------- -.. versionadded:: 1.1 - If `Numba `__ is installed as an optional dependency, the ``transform`` and ``aggregate`` methods support ``engine='numba'`` and ``engine_kwargs`` arguments. See :ref:`enhancing performance with Numba ` for general usage of the arguments diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst index 3f59ad2faae08..972fe9d05df09 100644 --- a/doc/source/user_guide/io.rst +++ b/doc/source/user_guide/io.rst @@ -158,12 +158,6 @@ dtype : Type name or dict of column -> type, default ``None`` and not interpret dtype. If converters are specified, they will be applied INSTEAD of dtype conversion. - .. versionadded:: 1.5.0 - - Support for defaultdict was added. Specify a defaultdict as input where - the default determines the dtype of the columns which are not explicitly - listed. - dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames Which dtype_backend to use, e.g. whether a DataFrame should have NumPy arrays, nullable dtypes are used for all dtypes that have a nullable @@ -177,12 +171,8 @@ dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFram engine : {``'c'``, ``'python'``, ``'pyarrow'``} Parser engine to use. The C and pyarrow engines are faster, while the python engine is currently more feature-complete. Multithreading is currently only supported by - the pyarrow engine. - - .. versionadded:: 1.4.0 - - The "pyarrow" engine was added as an *experimental* engine, and some features - are unsupported, or may not work correctly, with this engine. + the pyarrow engine.The "pyarrow" engine was added as an *experimental* engine, + and some features are unsupported, or may not work correctly, with this engine. converters : dict, default ``None`` Dict of functions for converting values in certain columns. Keys can either be integers or column labels. @@ -357,8 +347,6 @@ on_bad_lines : {{'error', 'warn', 'skip'}}, default 'error' - 'warn', print a warning when a bad line is encountered and skip that line. - 'skip', skip bad lines without raising or warning when they are encountered. - .. versionadded:: 1.3.0 - .. _io.dtypes: Specifying column data types @@ -937,8 +925,6 @@ DD/MM/YYYY instead. For convenience, a ``dayfirst`` keyword is provided: Writing CSVs to binary file objects +++++++++++++++++++++++++++++++++++ -.. versionadded:: 1.2.0 - ``df.to_csv(..., mode="wb")`` allows writing a CSV to a file object opened binary mode. In most cases, it is not necessary to specify ``mode`` as pandas will auto-detect whether the file object is @@ -1124,8 +1110,6 @@ You can elect to skip bad lines: data = "a,b,c\n1,2,3\n4,5,6,7\n8,9,10" pd.read_csv(StringIO(data), on_bad_lines="skip") -.. versionadded:: 1.4.0 - Or pass a callable function to handle the bad line if ``engine="python"``. The bad line will be a list of strings that was split by the ``sep``: @@ -1553,8 +1537,6 @@ functions - the following example shows reading a CSV file: df = pd.read_csv("https://download.bls.gov/pub/time.series/cu/cu.item", sep="\t") -.. versionadded:: 1.3.0 - A custom header can be sent alongside HTTP(s) requests by passing a dictionary of header key value mappings to the ``storage_options`` keyword argument as shown below: @@ -1606,8 +1588,6 @@ More sample configurations and documentation can be found at `S3Fs documentation If you do *not* have S3 credentials, you can still access public data by specifying an anonymous connection, such as -.. versionadded:: 1.2.0 - .. code-block:: python pd.read_csv( @@ -2541,8 +2521,6 @@ Links can be extracted from cells along with the text using ``extract_links="all df[("GitHub", None)] df[("GitHub", None)].str[1] -.. versionadded:: 1.5.0 - .. _io.html: Writing to HTML files @@ -2732,8 +2710,6 @@ parse HTML tables in the top-level pandas io function ``read_html``. LaTeX ----- -.. versionadded:: 1.3.0 - Currently there are no methods to read from LaTeX, only output methods. Writing to LaTeX files @@ -2772,8 +2748,6 @@ XML Reading XML ''''''''''' -.. versionadded:: 1.3.0 - The top-level :func:`~pandas.io.xml.read_xml` function can accept an XML string/file/URL and will parse nodes and attributes into a pandas ``DataFrame``. @@ -3099,8 +3073,6 @@ supports parsing such sizeable files using `lxml's iterparse`_ and `etree's iter which are memory-efficient methods to iterate through an XML tree and extract specific elements and attributes. without holding entire tree in memory. -.. versionadded:: 1.5.0 - .. _`lxml's iterparse`: https://lxml.de/3.2/parsing.html#iterparse-and-iterwalk .. _`etree's iterparse`: https://docs.python.org/3/library/xml.etree.elementtree.html#xml.etree.ElementTree.iterparse @@ -3139,8 +3111,6 @@ of reading in Wikipedia's very large (12 GB+) latest article data dump. Writing XML ''''''''''' -.. versionadded:: 1.3.0 - ``DataFrame`` objects have an instance method ``to_xml`` which renders the contents of the ``DataFrame`` as an XML document. diff --git a/doc/source/user_guide/reshaping.rst b/doc/source/user_guide/reshaping.rst index bc5a2d5ed5735..30dac01fa5985 100644 --- a/doc/source/user_guide/reshaping.rst +++ b/doc/source/user_guide/reshaping.rst @@ -478,8 +478,6 @@ The values can be cast to a different type using the ``dtype`` argument. pd.get_dummies(df, dtype=np.float32).dtypes -.. versionadded:: 1.5.0 - :func:`~pandas.from_dummies` converts the output of :func:`~pandas.get_dummies` back into a :class:`Series` of categorical values from indicator values. diff --git a/doc/source/user_guide/text.rst b/doc/source/user_guide/text.rst index 11d5ab86e76ef..ee284c85fdc88 100644 --- a/doc/source/user_guide/text.rst +++ b/doc/source/user_guide/text.rst @@ -335,8 +335,6 @@ regular expression object will raise a ``ValueError``. ``removeprefix`` and ``removesuffix`` have the same effect as ``str.removeprefix`` and ``str.removesuffix`` added in `Python 3.9 `__: -.. versionadded:: 1.4.0 - .. ipython:: python s = pd.Series(["str_foo", "str_bar", "no_prefix"]) diff --git a/doc/source/user_guide/timeseries.rst b/doc/source/user_guide/timeseries.rst index 6a66c30cffbf0..72b40982abb0c 100644 --- a/doc/source/user_guide/timeseries.rst +++ b/doc/source/user_guide/timeseries.rst @@ -1964,8 +1964,6 @@ Note the use of ``'start'`` for ``origin`` on the last example. In that case, `` Backward resample ~~~~~~~~~~~~~~~~~ -.. versionadded:: 1.3.0 - Instead of adjusting the beginning of bins, sometimes we need to fix the end of the bins to make a backward resample with a given ``freq``. The backward resample sets ``closed`` to ``'right'`` by default since the last value should be considered as the edge point for the last bin. We can set ``origin`` to ``'end'``. The value for a specific ``Timestamp`` index stands for the resample result from the current ``Timestamp`` minus ``freq`` to the current ``Timestamp`` with a right close. diff --git a/doc/source/user_guide/visualization.rst b/doc/source/user_guide/visualization.rst index 4b5cdca23103c..3687ca7448f34 100644 --- a/doc/source/user_guide/visualization.rst +++ b/doc/source/user_guide/visualization.rst @@ -649,8 +649,6 @@ each point: If a categorical column is passed to ``c``, then a discrete colorbar will be produced: -.. versionadded:: 1.3.0 - .. ipython:: python @savefig scatter_plot_categorical.png diff --git a/doc/source/user_guide/window.rst b/doc/source/user_guide/window.rst index 5b27442c80bb8..22eb1d4c026cf 100644 --- a/doc/source/user_guide/window.rst +++ b/doc/source/user_guide/window.rst @@ -76,9 +76,6 @@ which will first group the data by the specified keys and then perform a windowi `__ is used to compute the rolling sums to preserve accuracy as much as possible. - -.. versionadded:: 1.3.0 - Some windowing operations also support the ``method='table'`` option in the constructor which performs the windowing operation over an entire :class:`DataFrame` instead of a single column at a time. This can provide a useful performance benefit for a :class:`DataFrame` with many columns @@ -100,8 +97,6 @@ be calculated with :meth:`~Rolling.apply` by specifying a separate column of wei df = pd.DataFrame([[1, 2, 0.6], [2, 3, 0.4], [3, 4, 0.2], [4, 5, 0.7]]) df.rolling(2, method="table", min_periods=0).apply(weighted_mean, raw=True, engine="numba") # noqa: E501 -.. versionadded:: 1.3 - Some windowing operations also support an ``online`` method after constructing a windowing object which returns a new object that supports passing in new :class:`DataFrame` or :class:`Series` objects to continue the windowing calculation with the new values (i.e. online calculations). @@ -182,8 +177,6 @@ By default the labels are set to the right edge of the window, but a This can also be applied to datetime-like indices. -.. versionadded:: 1.3.0 - .. ipython:: python df = pd.DataFrame( @@ -363,11 +356,8 @@ Numba will be applied in potentially two routines: The ``engine_kwargs`` argument is a dictionary of keyword arguments that will be passed into the `numba.jit decorator `__. These keyword arguments will be applied to *both* the passed function (if a standard Python function) -and the apply for loop over each window. - -.. versionadded:: 1.3.0 - -``mean``, ``median``, ``max``, ``min``, and ``sum`` also support the ``engine`` and ``engine_kwargs`` arguments. +and the apply for loop over each window. ``mean``, ``median``, ``max``, ``min``, and ``sum`` +also support the ``engine`` and ``engine_kwargs`` arguments. .. _window.cov_corr: diff --git a/pandas/_testing/asserters.py b/pandas/_testing/asserters.py index 3f95997bb84f4..160c362d0dbc1 100644 --- a/pandas/_testing/asserters.py +++ b/pandas/_testing/asserters.py @@ -931,14 +931,10 @@ def assert_series_equal( assertion message. check_index : bool, default True Whether to check index equivalence. If False, then compare only values. - - .. versionadded:: 1.3.0 check_like : bool, default False If True, ignore the order of the index. Must be False if check_index is False. Note: same labels must be with the same data. - .. versionadded:: 1.5.0 - See Also -------- testing.assert_index_equal : Check that two Indexes are equal. diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py index b977e998b82a4..6bc3e04f576ec 100644 --- a/pandas/core/algorithms.py +++ b/pandas/core/algorithms.py @@ -698,8 +698,7 @@ def factorize( NaN values will be encoded as non-negative integers and will not drop the NaN from the uniques of the values. - .. versionadded:: 1.5.0 - {size_hint}\ + {size_hint} Returns ------- @@ -731,7 +730,7 @@ def factorize( ``pd.factorize(values)``. The results are identical for methods like :meth:`Series.factorize`. - >>> codes, uniques = pd.factorize(np.array(['b', 'b', 'a', 'c', 'b'], dtype="O")) + >>> codes, uniques = pd.factorize(np.array(["b", "b", "a", "c", "b"], dtype="O")) >>> codes array([0, 0, 1, 2, 0]) >>> uniques @@ -740,8 +739,9 @@ def factorize( With ``sort=True``, the `uniques` will be sorted, and `codes` will be shuffled so that the relationship is the maintained. - >>> codes, uniques = pd.factorize(np.array(['b', 'b', 'a', 'c', 'b'], dtype="O"), - ... sort=True) + >>> codes, uniques = pd.factorize( + ... np.array(["b", "b", "a", "c", "b"], dtype="O"), sort=True + ... ) >>> codes array([1, 1, 0, 2, 1]) >>> uniques @@ -751,7 +751,7 @@ def factorize( the `codes` with the sentinel value ``-1`` and missing values are not included in `uniques`. - >>> codes, uniques = pd.factorize(np.array(['b', None, 'a', 'c', 'b'], dtype="O")) + >>> codes, uniques = pd.factorize(np.array(["b", None, "a", "c", "b"], dtype="O")) >>> codes array([ 0, -1, 1, 2, 0]) >>> uniques @@ -761,7 +761,7 @@ def factorize( NumPy arrays). When factorizing pandas objects, the type of `uniques` will differ. For Categoricals, a `Categorical` is returned. - >>> cat = pd.Categorical(['a', 'a', 'c'], categories=['a', 'b', 'c']) + >>> cat = pd.Categorical(["a", "a", "c"], categories=["a", "b", "c"]) >>> codes, uniques = pd.factorize(cat) >>> codes array([0, 0, 1]) @@ -775,7 +775,7 @@ def factorize( For all other pandas objects, an Index of the appropriate type is returned. - >>> cat = pd.Series(['a', 'a', 'c']) + >>> cat = pd.Series(["a", "a", "c"]) >>> codes, uniques = pd.factorize(cat) >>> codes array([0, 0, 1]) diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py index e091ecf18668d..c4c892258b025 100644 --- a/pandas/core/arrays/base.py +++ b/pandas/core/arrays/base.py @@ -1574,8 +1574,6 @@ def factorize( NaN values will be encoded as non-negative integers and will not drop the NaN from the uniques of the values. - .. versionadded:: 1.5.0 - Returns ------- codes : ndarray diff --git a/pandas/core/common.py b/pandas/core/common.py index 72b15b6e1bf4e..4f1c8d1800c00 100644 --- a/pandas/core/common.py +++ b/pandas/core/common.py @@ -639,8 +639,6 @@ def fill_missing_names(names: Sequence[Hashable | None]) -> list[Hashable]: """ If a name is missing then replace it by level_n, where n is the count - .. versionadded:: 1.4.0 - Parameters ---------- names : list-like diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 68ea6795d47dd..3a91621dd8f62 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -1843,9 +1843,7 @@ def from_dict( (default). Otherwise if the keys should be rows, pass 'index'. If 'tight', assume a dict with keys ['index', 'columns', 'data', 'index_names', 'column_names']. - - .. versionadded:: 1.4.0 - 'tight' as an allowed value for the ``orient`` argument + 'tight' as an allowed value for the ``orient`` argument dtype : dtype, default None Data type to force after DataFrame construction, otherwise infer. @@ -2084,9 +2082,7 @@ def to_dict( - 'records' : list like [{column -> value}, ... , {column -> value}] - 'index' : dict like {index -> {column -> value}} - - .. versionadded:: 1.4.0 - 'tight' as an allowed value for the ``orient`` argument + 'tight' as an allowed value for the ``orient`` argument into : class, default dict The collections.abc.MutableMapping subclass used for all Mappings @@ -2680,8 +2676,6 @@ def to_stata( to labels as values. Labels for a single variable must be 32,000 characters or smaller. - .. versionadded:: 1.4.0 - Raises ------ NotImplementedError @@ -3088,8 +3082,6 @@ def to_orc( """ Write a DataFrame to the Optimized Row Columnar (ORC) format. - .. versionadded:: 1.5.0 - Parameters ---------- path : str, file-like object or None, default None @@ -3463,8 +3455,6 @@ def to_xml( """ Render a DataFrame to an XML document. - .. versionadded:: 1.3.0 - Parameters ---------- path_or_buffer : str, path object, file-like object, or None, default None @@ -6522,16 +6512,11 @@ def reset_index( levels are named. If None then the index name is repeated. allow_duplicates : bool, optional, default lib.no_default Allow duplicate column labels to be created. - - .. versionadded:: 1.5.0 - names : int, str or 1-dimensional list, default None Using the given string, rename the DataFrame column which contains the index data. If the DataFrame has a MultiIndex, this has to be a list with length equal to the number of levels. - .. versionadded:: 1.5.0 - Returns ------- DataFrame or None @@ -7709,8 +7694,6 @@ def value_counts( dropna : bool, default True Do not include counts of rows that contain NA values. - .. versionadded:: 1.3.0 - Returns ------- Series @@ -9846,9 +9829,6 @@ def pivot( sort : bool, default True Specifies if the result should be sorted. - - .. versionadded:: 1.3.0 - **kwargs : dict Optional keyword arguments to pass to ``aggfunc``. @@ -10202,9 +10182,6 @@ def explode( be str or tuple, and all specified columns their list-like data on same row of the frame must have matching length. - .. versionadded:: 1.3.0 - Multi-column explode - ignore_index : bool, default False If True, the resulting index will be labeled 0, 1, …, n - 1. @@ -10820,8 +10797,6 @@ def apply( ``by_row=False`` (backward compatible). If False, the funcs will be passed the whole Series at once. - .. versionadded:: 2.1.0 - engine : decorator or {'python', 'numba'}, optional Choose the execution engine to use. If not provided the function will be executed by the regular Python interpreter. @@ -11236,8 +11211,6 @@ def join( * "many_to_one" or "m:1": check if join keys are unique in right dataset. * "many_to_many" or "m:m": allowed, but does not result in checks. - .. versionadded:: 1.5.0 - Returns ------- DataFrame @@ -11626,8 +11599,6 @@ def corr( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 The default value of ``numeric_only`` is now ``False``. @@ -11753,8 +11724,6 @@ def cov( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 The default value of ``numeric_only`` is now ``False``. @@ -11893,8 +11862,6 @@ def corrwith( min_periods : int, optional Minimum number of observations needed to have a valid result. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 The default value of ``numeric_only`` is now ``False``. @@ -13414,8 +13381,6 @@ def idxmin( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - Returns ------- Series @@ -13519,8 +13484,6 @@ def idxmax( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - Returns ------- Series diff --git a/pandas/core/generic.py b/pandas/core/generic.py index b542ca1f431c3..1b66deb6ed696 100644 --- a/pandas/core/generic.py +++ b/pandas/core/generic.py @@ -2151,7 +2151,6 @@ def _repr_data_resource_(self): @doc( klass="object", storage_options=_shared_docs["storage_options"], - storage_options_versionadded="1.2.0", encoding_parameter="", verbose_parameter="", extra_parameters=textwrap.dedent( @@ -2237,8 +2236,6 @@ def to_excel( Specifies the one-based bottommost row and rightmost column that is to be frozen. {storage_options} - - .. versionadded:: {storage_options_versionadded} {extra_parameters} See Also -------- @@ -2878,8 +2875,6 @@ def to_sql( `sqlite3 `__ or `SQLAlchemy `__. - .. versionadded:: 1.4.0 - Raises ------ ValueError @@ -5859,19 +5854,12 @@ def sample( If int, array-like, or BitGenerator, seed for random number generator. If np.random.RandomState or np.random.Generator, use as given. Default ``None`` results in sampling with the current state of np.random. - - .. versionchanged:: 1.4.0 - - np.random.Generator objects now accepted - axis : {0 or 'index', 1 or 'columns', None}, default None Axis to sample. Accepts axis number or name. Default is stat axis for given data type. For `Series` this parameter is unused and defaults to `None`. ignore_index : bool, default False If True, the resulting index will be labeled 0, 1, …, n - 1. - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -8967,8 +8955,6 @@ def resample( - 'end': `origin` is the last value of the timeseries - 'end_day': `origin` is the ceiling midnight of the last day - .. versionadded:: 1.3.0 - .. note:: Only takes effect for Tick-frequencies (i.e. fixed frequencies like @@ -8980,12 +8966,6 @@ def resample( Whether to include the group keys in the result index when using ``.apply()`` on the resampled object. - .. versionadded:: 1.5.0 - - Not specifying ``group_keys`` will retain values-dependent behavior - from pandas 1.4 and earlier (see :ref:`pandas 1.5.0 Release notes - ` for examples). - .. versionchanged:: 2.0.0 ``group_keys`` now defaults to ``False``. diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py index d279594617235..a61c7736bf33a 100644 --- a/pandas/core/groupby/generic.py +++ b/pandas/core/groupby/generic.py @@ -889,8 +889,6 @@ def value_counts( """ Return a Series or DataFrame containing counts of unique rows. - .. versionadded:: 1.4.0 - Parameters ---------- normalize : bool, default False @@ -2606,8 +2604,6 @@ def idxmax( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - Returns ------- DataFrame @@ -2680,8 +2676,6 @@ def idxmin( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - Returns ------- DataFrame @@ -2752,8 +2746,6 @@ def value_counts( """ Return a Series or DataFrame containing counts of unique rows. - .. versionadded:: 1.4.0 - Parameters ---------- subset : list-like, optional @@ -3329,8 +3321,6 @@ def corrwith( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 The default value of ``numeric_only`` is now ``False``. diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py index 910268ebdfb8a..c365fc8a9fbde 100644 --- a/pandas/core/groupby/groupby.py +++ b/pandas/core/groupby/groupby.py @@ -2195,8 +2195,6 @@ def mean( * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2204,8 +2202,6 @@ def mean( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` - .. versionadded:: 1.4.0 - Returns ------- pandas.Series or pandas.DataFrame @@ -2397,8 +2393,6 @@ def std( * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2406,13 +2400,9 @@ def std( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` - .. versionadded:: 1.4.0 - numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. @@ -2515,8 +2505,6 @@ def var( * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2524,13 +2512,9 @@ def var( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` - .. versionadded:: 1.4.0 - numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. @@ -2746,8 +2730,6 @@ def sem( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. @@ -4400,8 +4382,6 @@ def quantile( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py index a45ce1f385e4d..70e3d45a02305 100644 --- a/pandas/core/groupby/grouper.py +++ b/pandas/core/groupby/grouper.py @@ -113,8 +113,6 @@ class Grouper: - 'end': `origin` is the last value of the timeseries - 'end_day': `origin` is the ceiling midnight of the last day - .. versionadded:: 1.3.0 - offset : Timedelta or str, default is None An offset timedelta added to the origin. diff --git a/pandas/core/indexers/objects.py b/pandas/core/indexers/objects.py index 2c2413c74f2fa..6fa973c1599c5 100644 --- a/pandas/core/indexers/objects.py +++ b/pandas/core/indexers/objects.py @@ -94,7 +94,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -134,7 +133,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -189,7 +187,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -316,7 +313,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -422,7 +418,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -509,7 +504,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -599,7 +593,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API @@ -681,7 +674,6 @@ def get_window_bounds( closed passed from the top level rolling API step : int, default None step passed from the top level rolling API - .. versionadded:: 1.5 win_type : str, default None win_type passed from the top level rolling API diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py index 6451e55f7fc4d..ba475989e547d 100644 --- a/pandas/core/indexes/datetimes.py +++ b/pandas/core/indexes/datetimes.py @@ -892,8 +892,6 @@ def date_range( Name of the resulting DatetimeIndex. inclusive : {"both", "neither", "left", "right"}, default "both" Include boundaries; Whether to set each bound as closed or open. - - .. versionadded:: 1.4.0 unit : {'s', 'ms', 'us', 'ns'}, default 'ns' Specify the desired resolution of the result. @@ -1094,8 +1092,6 @@ def bdate_range( are passed. inclusive : {"both", "neither", "left", "right"}, default "both" Include boundaries; Whether to set each bound as closed or open. - - .. versionadded:: 1.4.0 **kwargs For compatibility. Has no effect on the result. diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py index 1cc1928136da1..43e6469e078f0 100644 --- a/pandas/core/indexes/multi.py +++ b/pandas/core/indexes/multi.py @@ -1900,8 +1900,6 @@ def to_frame( allow_duplicates : bool, optional default False Allow duplicate column labels to be created. - .. versionadded:: 1.5.0 - Returns ------- DataFrame diff --git a/pandas/core/methods/to_dict.py b/pandas/core/methods/to_dict.py index 75003675dc173..1c9ca5f4d0d3c 100644 --- a/pandas/core/methods/to_dict.py +++ b/pandas/core/methods/to_dict.py @@ -126,9 +126,6 @@ def to_dict( [{column -> value}, ... , {column -> value}] - 'index' : dict like {index -> {column -> value}} - .. versionadded:: 1.4.0 - 'tight' as an allowed value for the ``orient`` argument - into : class, default dict The collections.abc.MutableMapping subclass used for all Mappings in the return value. Can be the actual class or an empty diff --git a/pandas/core/resample.py b/pandas/core/resample.py index 2694b581a6707..e7207a9ed0c21 100644 --- a/pandas/core/resample.py +++ b/pandas/core/resample.py @@ -1545,8 +1545,6 @@ def std( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. @@ -1604,8 +1602,6 @@ def var( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. @@ -1670,8 +1666,6 @@ def sem( numeric_only : bool, default False Include only `float`, `int` or `boolean` data. - .. versionadded:: 1.5.0 - .. versionchanged:: 2.0.0 numeric_only now defaults to ``False``. diff --git a/pandas/core/reshape/encoding.py b/pandas/core/reshape/encoding.py index 5c5fed272b925..b761bcec0c584 100644 --- a/pandas/core/reshape/encoding.py +++ b/pandas/core/reshape/encoding.py @@ -377,8 +377,6 @@ def from_dummies( Inverts the operation performed by :func:`~pandas.get_dummies`. - .. versionadded:: 1.5.0 - Parameters ---------- data : DataFrame diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py index 04c584c226aed..eb64ce8d98118 100644 --- a/pandas/core/reshape/pivot.py +++ b/pandas/core/reshape/pivot.py @@ -124,13 +124,9 @@ def pivot_table( sort : bool, default True Specifies if the result should be sorted. - .. versionadded:: 1.3.0 - **kwargs : dict Optional keyword arguments to pass to ``aggfunc``. - .. versionadded:: 3.0.0 - Returns ------- DataFrame diff --git a/pandas/core/series.py b/pandas/core/series.py index fe71a3ab91933..d4dc74786d7a0 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -1307,8 +1307,6 @@ def reset_index( allow_duplicates : bool, default False Allow duplicate column labels to be created. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame or None @@ -3031,8 +3029,6 @@ def compare( result_names : tuple, default ('self', 'other') Set the dataframes names in the comparison. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -5656,8 +5652,6 @@ def info( This method prints information about a Series including the index dtype, non-NA values and memory usage. - .. versionadded:: 1.4.0 - Parameters ---------- verbose : bool, optional diff --git a/pandas/core/shared_docs.py b/pandas/core/shared_docs.py index bf30c215596f2..4544729112444 100644 --- a/pandas/core/shared_docs.py +++ b/pandas/core/shared_docs.py @@ -79,8 +79,6 @@ result_names : tuple, default ('self', 'other') Set the dataframes names in the comparison. - - .. versionadded:: 1.5.0 """ _shared_docs["groupby"] = """ @@ -338,9 +336,7 @@ As an example, the following could be passed for faster compression and to create a reproducible gzip archive: ``compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}``. - - .. versionadded:: 1.5.0 - Added support for `.tar` files.""" + Added support for `.tar` files.""" _shared_docs["decompression_options"] = """compression : str or dict, default 'infer' For on-the-fly decompression of on-disk data. If 'infer' and '%s' is @@ -358,9 +354,7 @@ As an example, the following could be passed for Zstandard decompression using a custom compression dictionary: ``compression={'method': 'zstd', 'dict_data': my_compression_dict}``. - - .. versionadded:: 1.5.0 - Added support for `.tar` files.""" + Added support for `.tar` files.""" _shared_docs["replace"] = """ Replace values given in `to_replace` with `value`. diff --git a/pandas/core/strings/accessor.py b/pandas/core/strings/accessor.py index ff3a17e4d2d5b..3ed022a337057 100644 --- a/pandas/core/strings/accessor.py +++ b/pandas/core/strings/accessor.py @@ -848,8 +848,6 @@ def cat( - If ``None`` and `pat` length is 1, treats `pat` as a literal string. - If ``None`` and `pat` length is not 1, treats `pat` as a regular expression. - Cannot be set to False if `pat` is a compiled regex - - .. versionadded:: 1.4.0 """, "raises_split": """ Raises diff --git a/pandas/core/window/doc.py b/pandas/core/window/doc.py index 6dbc52a99e70c..716ab9b5a9f23 100644 --- a/pandas/core/window/doc.py +++ b/pandas/core/window/doc.py @@ -35,9 +35,7 @@ def create_section_header(header: str) -> str: kwargs_numeric_only = dedent( """ numeric_only : bool, default False - Include only float, int, boolean columns. - - .. versionadded:: 1.5.0\n + Include only float, int, boolean columns.\n """ ).replace("\n", "", 1) @@ -148,27 +146,19 @@ def create_section_header(header: str) -> str: ) -def window_agg_numba_parameters(version: str = "1.3") -> str: - return ( - dedent( - """ +def window_agg_numba_parameters() -> str: + return dedent( + """ engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: {version}.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` and ``parallel`` dictionary keys. The values must either be ``True`` or ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` - - .. versionadded:: {version}.0\n """ - ) - .replace("\n", "", 1) - .replace("{version}", version) ) diff --git a/pandas/core/window/ewm.py b/pandas/core/window/ewm.py index 1ea05e24d0db5..0d6eb230714c0 100644 --- a/pandas/core/window/ewm.py +++ b/pandas/core/window/ewm.py @@ -215,8 +215,6 @@ class ExponentialMovingWindow(BaseWindow): If 1-D array like, a sequence with the same shape as the observations. method : str {'single', 'table'}, default 'single' - .. versionadded:: 1.4.0 - Execute the rolling operation per single column or row (``'single'``) or over the entire object (``'table'``). @@ -426,8 +424,6 @@ def online( Return an ``OnlineExponentialMovingWindow`` object to calculate exponentially moving window aggregations in an online method. - .. versionadded:: 1.3.0 - Parameters ---------- engine: str, default ``'numba'`` diff --git a/pandas/core/window/expanding.py b/pandas/core/window/expanding.py index 2527a5dd508d8..2ef0b4676b06d 100644 --- a/pandas/core/window/expanding.py +++ b/pandas/core/window/expanding.py @@ -57,8 +57,6 @@ class Expanding(RollingAndExpandingMixin): This argument is only implemented when specifying ``engine='numba'`` in the method call. - .. versionadded:: 1.3.0 - Returns ------- pandas.api.typing.Expanding @@ -215,8 +213,6 @@ def count(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -436,16 +432,12 @@ def sum( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -453,8 +445,6 @@ def sum( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -502,16 +492,12 @@ def max( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -519,8 +505,6 @@ def max( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -568,16 +552,12 @@ def min( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -585,8 +565,6 @@ def min( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -634,16 +612,12 @@ def mean( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -651,8 +625,6 @@ def mean( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -700,16 +672,12 @@ def median( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -717,8 +685,6 @@ def median( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -771,16 +737,12 @@ def std( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -788,8 +750,6 @@ def std( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.4.0 - Returns ------- Series or DataFrame @@ -850,16 +810,12 @@ def var( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -867,8 +823,6 @@ def var( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}`` - .. versionadded:: 1.4.0 - Returns ------- Series or DataFrame @@ -923,8 +877,6 @@ def sem(self, ddof: int = 1, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -963,8 +915,6 @@ def skew(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1004,8 +954,6 @@ def kurt(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1054,8 +1002,6 @@ def first(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1091,8 +1037,6 @@ def last(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1149,8 +1093,6 @@ def quantile( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1191,8 +1133,6 @@ def rank( """ Calculate the expanding rank. - .. versionadded:: 1.4.0 - Parameters ---------- method : {'average', 'min', 'max'}, default 'average' @@ -1210,8 +1150,6 @@ def rank( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1275,8 +1213,6 @@ def nunique( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1333,8 +1269,6 @@ def cov( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -1394,8 +1328,6 @@ def corr( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py index e6f84941f6b1a..5519f4d3bd7cc 100644 --- a/pandas/core/window/rolling.py +++ b/pandas/core/window/rolling.py @@ -934,12 +934,8 @@ class Window(BaseWindow): ``[::step]``. ``window`` must be an integer. Using a step argument other than None or 1 will produce a result with a different shape than the input. - .. versionadded:: 1.5.0 - method : str {'single', 'table'}, default 'single' - .. versionadded:: 1.3.0 - Execute the rolling operation per single column or row (``'single'``) or over the entire object (``'table'``). @@ -1307,8 +1303,6 @@ def sum(self, numeric_only: bool = False, **kwargs): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - **kwargs Keyword arguments to configure the ``SciPy`` weighted window type. @@ -1367,8 +1361,6 @@ def mean(self, numeric_only: bool = False, **kwargs): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - **kwargs Keyword arguments to configure the ``SciPy`` weighted window type. @@ -1428,9 +1420,6 @@ def var(self, ddof: int = 1, numeric_only: bool = False, **kwargs): is ``N - ddof``, where ``N`` represents the number of elements. numeric_only : bool, default False Include only float, int, boolean columns. - - .. versionadded:: 1.5.0 - **kwargs Keyword arguments to configure the ``SciPy`` weighted window type. @@ -1483,9 +1472,6 @@ def std(self, ddof: int = 1, numeric_only: bool = False, **kwargs): is ``N - ddof``, where ``N`` represents the number of elements. numeric_only : bool, default False Include only float, int, boolean columns. - - .. versionadded:: 1.5.0 - **kwargs Keyword arguments to configure the ``SciPy`` weighted window type. @@ -2137,8 +2123,6 @@ def count(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -2374,16 +2358,12 @@ def sum( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2391,8 +2371,6 @@ def sum( ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -2479,8 +2457,6 @@ def max( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - *args : iterable, optional Positional arguments passed into ``func``. @@ -2490,8 +2466,6 @@ def max( * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2501,8 +2475,6 @@ def max( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.3.0 - **kwargs : mapping, optional A dictionary of keyword arguments passed into ``func``. @@ -2554,16 +2526,12 @@ def min( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2573,8 +2541,6 @@ def min( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -2626,16 +2592,12 @@ def mean( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2645,8 +2607,6 @@ def mean( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -2705,16 +2665,12 @@ def median( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.3.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2724,8 +2680,6 @@ def median( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.3.0 - Returns ------- Series or DataFrame @@ -2782,16 +2736,12 @@ def std( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2801,8 +2751,6 @@ def std( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.4.0 - Returns ------- Series or DataFrame @@ -2862,16 +2810,12 @@ def var( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - engine : str, default None * ``'cython'`` : Runs the operation through C-extensions from cython. * ``'numba'`` : Runs the operation through JIT compiled code from numba. * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba`` - .. versionadded:: 1.4.0 - engine_kwargs : dict, default None * For ``'cython'`` engine, there are no accepted ``engine_kwargs`` * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil`` @@ -2881,8 +2825,6 @@ def var( The default ``engine_kwargs`` for the ``'numba'`` engine is ``{'nopython': True, 'nogil': False, 'parallel': False}``. - .. versionadded:: 1.4.0 - Returns ------- Series or DataFrame @@ -2932,8 +2874,6 @@ def skew(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -2979,8 +2919,6 @@ def sem(self, ddof: int = 1, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3022,8 +2960,6 @@ def kurt(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3072,8 +3008,6 @@ def first(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3109,8 +3043,6 @@ def last(self, numeric_only: bool = False): numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3168,8 +3100,6 @@ def quantile( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3215,8 +3145,6 @@ def rank( """ Calculate the rolling rank. - .. versionadded:: 1.4.0 - Parameters ---------- method : {'average', 'min', 'max'}, default 'average' @@ -3236,8 +3164,6 @@ def rank( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3301,8 +3227,6 @@ def nunique( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3364,8 +3288,6 @@ def cov( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame @@ -3427,8 +3349,6 @@ def corr( numeric_only : bool, default False Include only float, int, boolean columns. - .. versionadded:: 1.5.0 - Returns ------- Series or DataFrame diff --git a/pandas/io/excel/_base.py b/pandas/io/excel/_base.py index 48028c54a1773..0732ba87de30c 100644 --- a/pandas/io/excel/_base.py +++ b/pandas/io/excel/_base.py @@ -259,9 +259,6 @@ Note that this parameter is only necessary for columns stored as TEXT in Excel, any numeric columns will automatically be parsed, regardless of display format.(e.g. use ',' for European data). - - .. versionadded:: 1.4.0 - comment : str, default None Comments out remainder of line. Pass a character or characters to this argument to indicate comments in the input file. Any data between the @@ -997,12 +994,6 @@ class ExcelWriter(Generic[_WorkbookT]): * overlay: Write contents to the existing sheet without first removing, but possibly over top of, the existing contents. - .. versionadded:: 1.3.0 - - .. versionchanged:: 1.4.0 - - Added ``overlay`` option - engine_kwargs : dict, optional Keyword arguments to be passed into the engine. These will be passed to the following functions of the respective engines: @@ -1012,8 +1003,6 @@ class ExcelWriter(Generic[_WorkbookT]): * openpyxl (append mode): ``openpyxl.load_workbook(file, **engine_kwargs)`` * odf: ``odf.opendocument.OpenDocumentSpreadsheet(**engine_kwargs)`` - .. versionadded:: 1.3.0 - See Also -------- read_excel : Read an Excel sheet values (xlsx) file into DataFrame. @@ -1500,25 +1489,20 @@ class ExcelFile: - ``calamine`` supports Excel (.xls, .xlsx, .xlsm, .xlsb) and OpenDocument (.ods) file formats. - .. versionchanged:: 1.2.0 - - The engine `xlrd `_ - now only supports old-style ``.xls`` files. - When ``engine=None``, the following logic will be - used to determine the engine: - - - If ``path_or_buffer`` is an OpenDocument format (.odf, .ods, .odt), - then `odf `_ will be used. - - Otherwise if ``path_or_buffer`` is an xls format, - ``xlrd`` will be used. - - Otherwise if ``path_or_buffer`` is in xlsb format, - `pyxlsb `_ will be used. - - .. versionadded:: 1.3.0 - - - Otherwise if `openpyxl `_ is installed, - then ``openpyxl`` will be used. - - Otherwise if ``xlrd >= 2.0`` is installed, a ``ValueError`` will be raised. + The engine `xlrd `_ + now only supports old-style ``.xls`` files. + When ``engine=None``, the following logic will be + used to determine the engine: + + - If ``path_or_buffer`` is an OpenDocument format (.odf, .ods, .odt), + then `odf `_ will be used. + - Otherwise if ``path_or_buffer`` is an xls format, + ``xlrd`` will be used. + - Otherwise if ``path_or_buffer`` is in xlsb format, + `pyxlsb `_ will be used. + - Otherwise if `openpyxl `_ is installed, + then ``openpyxl`` will be used. + - Otherwise if ``xlrd >= 2.0`` is installed, a ``ValueError`` will be raised. .. warning:: diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py index d72b6cd89b940..cd1810a96d49e 100644 --- a/pandas/io/formats/format.py +++ b/pandas/io/formats/format.py @@ -358,8 +358,6 @@ def get_dataframe_repr_params() -> dict[str, Any]: Supplying these parameters to DataFrame.to_string is equivalent to calling ``repr(DataFrame)``. This is useful if you want to adjust the repr output. - .. versionadded:: 1.4.0 - Example ------- >>> import pandas as pd @@ -391,8 +389,6 @@ def get_series_repr_params() -> dict[str, Any]: Supplying these parameters to Series.to_string is equivalent to calling ``repr(series)``. This is useful if you want to adjust the series repr output. - .. versionadded:: 1.4.0 - Example ------- >>> import pandas as pd diff --git a/pandas/io/formats/info.py b/pandas/io/formats/info.py index dac523898092a..fdad275714009 100644 --- a/pandas/io/formats/info.py +++ b/pandas/io/formats/info.py @@ -155,7 +155,6 @@ "show_counts_sub": show_counts_sub, "examples_sub": frame_examples_sub, "see_also_sub": frame_see_also_sub, - "version_added_sub": "", } @@ -240,7 +239,6 @@ "show_counts_sub": show_counts_sub, "examples_sub": series_examples_sub, "see_also_sub": series_see_also_sub, - "version_added_sub": "\n.. versionadded:: 1.4.0\n", } @@ -250,7 +248,6 @@ This method prints information about a {klass} including the index dtype{type_sub}, non-NA values and memory usage. - {version_added_sub}\ Parameters ---------- diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py index 9bf497af77855..592f67ca06d9b 100644 --- a/pandas/io/formats/style.py +++ b/pandas/io/formats/style.py @@ -157,15 +157,9 @@ class Styler(StylerRenderer): decimal : str, optional Character used as decimal separator for floats, complex and integers. If not given uses ``pandas.options.styler.format.decimal``. - - .. versionadded:: 1.3.0 - thousands : str, optional, default None Character used as thousands separator for floats, complex and integers. If not given uses ``pandas.options.styler.format.thousands``. - - .. versionadded:: 1.3.0 - escape : str, optional Use 'html' to replace the characters ``&``, ``<``, ``>``, ``'``, and ``"`` in cell display string with HTML-safe sequences. @@ -177,14 +171,10 @@ class Styler(StylerRenderer): which either are surrounded by two characters ``$`` or start with the character ``\(`` and end with ``\)``. If not given uses ``pandas.options.styler.format.escape``. - - .. versionadded:: 1.3.0 formatter : str, callable, dict, optional Object to define how values are displayed. See ``Styler.format``. If not given uses ``pandas.options.styler.format.formatter``. - .. versionadded:: 1.4.0 - Attributes ---------- index : data.index Index @@ -304,8 +294,6 @@ def concat(self, other: Styler) -> Styler: """ Append another Styler to combine the output into a single table. - .. versionadded:: 1.5.0 - Parameters ---------- other : Styler @@ -440,8 +428,6 @@ def set_tooltips( These string based tooltips are only applicable to ```` HTML elements, and cannot be used for column or index headers. - .. versionadded:: 1.3.0 - Parameters ---------- ttips : DataFrame @@ -686,8 +672,6 @@ def to_latex( r""" Write Styler to a file, buffer or string in LaTeX format. - .. versionadded:: 1.3.0 - Parameters ---------- buf : str, path object, file-like object, or None, default None @@ -734,8 +718,6 @@ def to_latex( table. - `"skip-last;index"`: as above with lines extending only the width of the index entries. - - .. versionadded:: 1.4.0 label : str, optional The LaTeX label included as: \\label{