Revert Interval/IntervalIndex/interval_range.inclusive deprecation

asv_bench/benchmarks/reshape.py

@@ -268,9 +268,7 @@ def setup(self, bins):
         self.datetime_series = pd.Series(
             np.random.randint(N, size=N), dtype="datetime64[ns]"
         )
-        self.interval_bins = pd.IntervalIndex.from_breaks(
-            np.linspace(0, N, bins), "right"
-        )
+        self.interval_bins = pd.IntervalIndex.from_breaks(np.linspace(0, N, bins))
 
     def time_cut_int(self, bins):
         pd.cut(self.int_series, bins)

doc/redirects.csv

@@ -741,11 +741,11 @@ generated/pandas.Index.values,../reference/api/pandas.Index.values
 generated/pandas.Index.view,../reference/api/pandas.Index.view
 generated/pandas.Index.where,../reference/api/pandas.Index.where
 generated/pandas.infer_freq,../reference/api/pandas.infer_freq
-generated/pandas.Interval.inclusive,../reference/api/pandas.Interval.inclusive
+generated/pandas.Interval.closed,../reference/api/pandas.Interval.closed
 generated/pandas.Interval.closed_left,../reference/api/pandas.Interval.closed_left
 generated/pandas.Interval.closed_right,../reference/api/pandas.Interval.closed_right
 generated/pandas.Interval,../reference/api/pandas.Interval
-generated/pandas.IntervalIndex.inclusive,../reference/api/pandas.IntervalIndex.inclusive
+generated/pandas.IntervalIndex.closed,../reference/api/pandas.IntervalIndex.closed
 generated/pandas.IntervalIndex.contains,../reference/api/pandas.IntervalIndex.contains
 generated/pandas.IntervalIndex.from_arrays,../reference/api/pandas.IntervalIndex.from_arrays
 generated/pandas.IntervalIndex.from_breaks,../reference/api/pandas.IntervalIndex.from_breaks
@@ -761,7 +761,6 @@ generated/pandas.IntervalIndex.mid,../reference/api/pandas.IntervalIndex.mid
 generated/pandas.IntervalIndex.overlaps,../reference/api/pandas.IntervalIndex.overlaps
 generated/pandas.IntervalIndex.right,../reference/api/pandas.IntervalIndex.right
 generated/pandas.IntervalIndex.set_closed,../reference/api/pandas.IntervalIndex.set_closed
-generated/pandas.IntervalIndex.set_inclusive,../reference/api/pandas.IntervalIndex.set_inclusive
 generated/pandas.IntervalIndex.to_tuples,../reference/api/pandas.IntervalIndex.to_tuples
 generated/pandas.IntervalIndex.values,../reference/api/pandas.IntervalIndex.values
 generated/pandas.Interval.left,../reference/api/pandas.Interval.left

doc/source/reference/arrays.rst

@@ -303,7 +303,6 @@ Properties
 .. autosummary::
    :toctree: api/
 
-   Interval.inclusive
    Interval.closed
    Interval.closed_left
    Interval.closed_right
@@ -341,7 +340,7 @@ A collection of intervals may be stored in an :class:`arrays.IntervalArray`.
 
       arrays.IntervalArray.left
       arrays.IntervalArray.right
-      arrays.IntervalArray.inclusive
+      arrays.IntervalArray.closed
       arrays.IntervalArray.mid
       arrays.IntervalArray.length
       arrays.IntervalArray.is_empty
@@ -352,7 +351,6 @@ A collection of intervals may be stored in an :class:`arrays.IntervalArray`.
       arrays.IntervalArray.contains
       arrays.IntervalArray.overlaps
       arrays.IntervalArray.set_closed
-      arrays.IntervalArray.set_inclusive
       arrays.IntervalArray.to_tuples
 
 

doc/source/reference/indexing.rst

@@ -242,7 +242,7 @@ IntervalIndex components
    IntervalIndex.left
    IntervalIndex.right
    IntervalIndex.mid
-   IntervalIndex.inclusive
+   IntervalIndex.closed
    IntervalIndex.length
    IntervalIndex.values
    IntervalIndex.is_empty
@@ -251,7 +251,6 @@ IntervalIndex components
    IntervalIndex.get_loc
    IntervalIndex.get_indexer
    IntervalIndex.set_closed
-   IntervalIndex.set_inclusive
    IntervalIndex.contains
    IntervalIndex.overlaps
    IntervalIndex.to_tuples

doc/source/user_guide/advanced.rst

@@ -1020,7 +1020,7 @@ Trying to select an ``Interval`` that is not exactly contained in the ``Interval
 
    In [7]: df.loc[pd.Interval(0.5, 2.5)]
    ---------------------------------------------------------------------------
-   KeyError: Interval(0.5, 2.5, inclusive='right')
+   KeyError: Interval(0.5, 2.5, closed='right')
 
 Selecting all ``Intervals`` that overlap a given ``Interval`` can be performed using the
 :meth:`~IntervalIndex.overlaps` method to create a boolean indexer.
@@ -1082,14 +1082,14 @@ of :ref:`frequency aliases <timeseries.offset_aliases>` with datetime-like inter
 
    pd.interval_range(start=pd.Timedelta("0 days"), periods=3, freq="9H")
 
-Additionally, the ``inclusive`` parameter can be used to specify which side(s) the intervals
-are closed on.  Intervals are closed on the both side by default.
+Additionally, the ``closed`` parameter can be used to specify which side(s) the intervals
+are closed on.  Intervals are closed on the right side by default.
 
 .. ipython:: python
 
-   pd.interval_range(start=0, end=4, inclusive="both")
+   pd.interval_range(start=0, end=4, closed="both")
 
-   pd.interval_range(start=0, end=4, inclusive="neither")
+   pd.interval_range(start=0, end=4, closed="neither")
 
 Specifying ``start``, ``end``, and ``periods`` will generate a range of evenly spaced
 intervals from ``start`` to ``end`` inclusively, with ``periods`` number of elements

doc/source/whatsnew/v0.20.0.rst

@@ -448,7 +448,7 @@ Selecting via a specific interval:
 
 .. ipython:: python
 
-   df.loc[pd.Interval(1.5, 3.0, "right")]
+   df.loc[pd.Interval(1.5, 3.0)]
 
 Selecting via a scalar value that is contained *in* the intervals.
 

doc/source/whatsnew/v0.25.0.rst

@@ -584,18 +584,18 @@ this would previously return ``True`` for any ``Interval`` overlapping an ``Inte
 
 .. code-block:: python
 
-   In [4]: pd.Interval(1, 2, inclusive='neither') in ii
+   In [4]: pd.Interval(1, 2, closed='neither') in ii
    Out[4]: True
 
-   In [5]: pd.Interval(-10, 10, inclusive='both') in ii
+   In [5]: pd.Interval(-10, 10, closed='both') in ii
    Out[5]: True
 
 *New behavior*:
 
 .. ipython:: python
 
-   pd.Interval(1, 2, inclusive='neither') in ii
-   pd.Interval(-10, 10, inclusive='both') in ii
+   pd.Interval(1, 2, closed='neither') in ii
+   pd.Interval(-10, 10, closed='both') in ii
 
 The :meth:`~IntervalIndex.get_loc` method now only returns locations for exact matches to ``Interval`` queries, as opposed to the previous behavior of
 returning locations for overlapping matches.  A ``KeyError`` will be raised if an exact match is not found.
@@ -619,7 +619,7 @@ returning locations for overlapping matches.  A ``KeyError`` will be raised if a
 
    In [7]: ii.get_loc(pd.Interval(2, 6))
    ---------------------------------------------------------------------------
-   KeyError: Interval(2, 6, inclusive='right')
+   KeyError: Interval(2, 6, closed='right')
 
 Likewise, :meth:`~IntervalIndex.get_indexer` and :meth:`~IntervalIndex.get_indexer_non_unique` will also only return locations for exact matches
 to ``Interval`` queries, with ``-1`` denoting that an exact match was not found.
@@ -680,11 +680,11 @@ Similarly, a ``KeyError`` will be raised for non-exact matches instead of return
 
    In [6]: s[pd.Interval(2, 3)]
    ---------------------------------------------------------------------------
-   KeyError: Interval(2, 3, inclusive='right')
+   KeyError: Interval(2, 3, closed='right')
 
    In [7]: s.loc[pd.Interval(2, 3)]
    ---------------------------------------------------------------------------
-   KeyError: Interval(2, 3, inclusive='right')
+   KeyError: Interval(2, 3, closed='right')
 
 The :meth:`~IntervalIndex.overlaps` method can be used to create a boolean indexer that replicates the
 previous behavior of returning overlapping matches.

doc/source/whatsnew/v1.5.0.rst

@@ -823,17 +823,10 @@ Other Deprecations
 - Deprecated :attr:`Timedelta.freq` and :attr:`Timedelta.is_populated` (:issue:`46430`)
 - Deprecated :attr:`Timedelta.delta` (:issue:`46476`)
 - Deprecated passing arguments as positional in :meth:`DataFrame.any` and :meth:`Series.any` (:issue:`44802`)
-- Deprecated the ``closed`` argument in :meth:`interval_range` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
 - Deprecated the methods :meth:`DataFrame.mad`, :meth:`Series.mad`, and the corresponding groupby methods (:issue:`11787`)
 - Deprecated positional arguments to :meth:`Index.join` except for ``other``, use keyword-only arguments instead of positional arguments (:issue:`46518`)
 - Deprecated positional arguments to :meth:`StringMethods.rsplit` and :meth:`StringMethods.split` except for ``pat``, use keyword-only arguments instead of positional arguments (:issue:`47423`)
 - Deprecated indexing on a timezone-naive :class:`DatetimeIndex` using a string representing a timezone-aware datetime (:issue:`46903`, :issue:`36148`)
-- Deprecated the ``closed`` argument in :class:`Interval` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
-- Deprecated the ``closed`` argument in :class:`IntervalIndex` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
-- Deprecated the ``closed`` argument in :class:`IntervalDtype` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
-- Deprecated the ``closed`` argument in :class:`.IntervalArray` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
-- Deprecated :meth:`.IntervalArray.set_closed` and :meth:`.IntervalIndex.set_closed` in favor of ``set_inclusive``; In a future version ``set_closed`` will get removed (:issue:`40245`)
-- Deprecated the ``closed`` argument in :class:`ArrowInterval` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
 - Deprecated allowing ``unit="M"`` or ``unit="Y"`` in :class:`Timestamp` constructor with a non-round float value (:issue:`47267`)
 - Deprecated the ``display.column_space`` global configuration option (:issue:`7576`)
 - Deprecated the argument ``na_sentinel`` in :func:`factorize`, :meth:`Index.factorize`, and :meth:`.ExtensionArray.factorize`; pass ``use_na_sentinel=True`` instead to use the sentinel ``-1`` for NaN values and ``use_na_sentinel=False`` instead of ``na_sentinel=None`` to encode NaN values (:issue:`46910`)

pandas/_libs/interval.pyi

@@ -8,14 +8,13 @@ from typing import (
 import numpy as np
 import numpy.typing as npt
 
-from pandas._libs import lib
 from pandas._typing import (
-    IntervalInclusiveType,
+    IntervalClosedType,
     Timedelta,
     Timestamp,
 )
 
-VALID_INCLUSIVE: frozenset[str]
+VALID_CLOSED: frozenset[str]
 
 _OrderableScalarT = TypeVar("_OrderableScalarT", int, float)
 _OrderableTimesT = TypeVar("_OrderableTimesT", Timestamp, Timedelta)
@@ -50,31 +49,22 @@ class IntervalMixin:
     def open_right(self) -> bool: ...
     @property
     def is_empty(self) -> bool: ...
-    def _check_inclusive_matches(
-        self, other: IntervalMixin, name: str = ...
-    ) -> None: ...
-
-def _warning_interval(
-    inclusive, closed
-) -> tuple[IntervalInclusiveType, lib.NoDefault]: ...
+    def _check_closed_matches(self, other: IntervalMixin, name: str = ...) -> None: ...
 
 class Interval(IntervalMixin, Generic[_OrderableT]):
     @property
     def left(self: Interval[_OrderableT]) -> _OrderableT: ...
     @property
     def right(self: Interval[_OrderableT]) -> _OrderableT: ...
     @property
-    def inclusive(self) -> IntervalInclusiveType: ...
-    @property
-    def closed(self) -> IntervalInclusiveType: ...
+    def closed(self) -> IntervalClosedType: ...
     mid: _MidDescriptor
     length: _LengthDescriptor
     def __init__(
         self,
         left: _OrderableT,
         right: _OrderableT,
-        inclusive: IntervalInclusiveType = ...,
-        closed: IntervalInclusiveType = ...,
+        closed: IntervalClosedType = ...,
     ) -> None: ...
     def __hash__(self) -> int: ...
     @overload
@@ -157,15 +147,15 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     def overlaps(self: Interval[_OrderableT], other: Interval[_OrderableT]) -> bool: ...
 
 def intervals_to_interval_bounds(
-    intervals: np.ndarray, validate_inclusive: bool = ...
-) -> tuple[np.ndarray, np.ndarray, IntervalInclusiveType]: ...
+    intervals: np.ndarray, validate_closed: bool = ...
+) -> tuple[np.ndarray, np.ndarray, str]: ...
 
 class IntervalTree(IntervalMixin):
     def __init__(
         self,
         left: np.ndarray,
         right: np.ndarray,
-        inclusive: IntervalInclusiveType = ...,
+        closed: IntervalClosedType = ...,
         leaf_size: int = ...,
     ) -> None: ...
     @property