DEPR: is_categorical (#49253)

Author: jbrockmendel

doc/redirects.csv

@@ -101,7 +101,6 @@ generated/pandas.api.types.infer_dtype,../reference/api/pandas.api.types.infer_d
 generated/pandas.api.types.is_bool_dtype,../reference/api/pandas.api.types.is_bool_dtype
 generated/pandas.api.types.is_bool,../reference/api/pandas.api.types.is_bool
 generated/pandas.api.types.is_categorical_dtype,../reference/api/pandas.api.types.is_categorical_dtype
-generated/pandas.api.types.is_categorical,../reference/api/pandas.api.types.is_categorical
 generated/pandas.api.types.is_complex_dtype,../reference/api/pandas.api.types.is_complex_dtype
 generated/pandas.api.types.is_complex,../reference/api/pandas.api.types.is_complex
 generated/pandas.api.types.is_datetime64_any_dtype,../reference/api/pandas.api.types.is_datetime64_any_dtype

doc/source/reference/arrays.rst

@@ -659,7 +659,6 @@ Scalar introspection
    :toctree: api/
 
     api.types.is_bool
-    api.types.is_categorical
     api.types.is_complex
     api.types.is_float
     api.types.is_hashable

doc/source/whatsnew/v2.0.0.rst

@@ -164,6 +164,7 @@ Removal of prior version deprecations/changes
 - Removed deprecated :meth:`CategoricalIndex.take_nd` (:issue:`30702`)
 - Removed deprecated :meth:`Index.is_type_compatible` (:issue:`42113`)
 - Removed deprecated :meth:`Index.is_mixed`, check ``index.inferred_type`` directly instead (:issue:`32922`)
+- Removed deprecated :func:`pandas.api.types.is_categorical`; use :func:`pandas.api.types.is_categorical_dtype` instead  (:issue:`33385`)
 - Removed deprecated :meth:`Index.asi8` (:issue:`37877`)
 - Enforced deprecation disallowing passing a timezone-aware :class:`Timestamp` and ``dtype="datetime64[ns]"`` to :class:`Series` or :class:`DataFrame` constructors (:issue:`41555`)
 - Enforced deprecation disallowing passing a sequence of timezone-aware values and ``dtype="datetime64[ns]"`` to to :class:`Series` or :class:`DataFrame` constructors (:issue:`41555`)

pandas/conftest.py

@@ -153,7 +153,6 @@ def pytest_collection_modifyitems(items, config) -> None:
         # Deprecations where the docstring will emit a warning
         ("DataFrame.append", "The frame.append method is deprecated"),
         ("Series.append", "The series.append method is deprecated"),
-        ("dtypes.common.is_categorical", "is_categorical is deprecated"),
         # Docstring divides by zero to show behavior difference
         ("missing.mask_zero_div_zero", "divide by zero encountered"),
         # Docstring demonstrates the call raises a warning

pandas/core/dtypes/api.py

@@ -2,7 +2,6 @@
     is_array_like,
     is_bool,
     is_bool_dtype,
-    is_categorical,
     is_categorical_dtype,
     is_complex,
     is_complex_dtype,
@@ -45,7 +44,6 @@
     "is_array_like",
     "is_bool",
     "is_bool_dtype",
-    "is_categorical",
     "is_categorical_dtype",
     "is_complex",
     "is_complex_dtype",

pandas/core/dtypes/common.py

@@ -7,7 +7,6 @@
     Any,
     Callable,
 )
-import warnings
 
 import numpy as np
 
@@ -22,7 +21,6 @@
     ArrayLike,
     DtypeObj,
 )
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.base import _registry as registry
 from pandas.core.dtypes.dtypes import (
@@ -32,10 +30,7 @@
     IntervalDtype,
     PeriodDtype,
 )
-from pandas.core.dtypes.generic import (
-    ABCCategorical,
-    ABCIndex,
-)
+from pandas.core.dtypes.generic import ABCIndex
 from pandas.core.dtypes.inference import (
     is_array_like,
     is_bool,
@@ -275,47 +270,6 @@ def is_scipy_sparse(arr) -> bool:
     return _is_scipy_sparse(arr)
 
 
-def is_categorical(arr) -> bool:
-    """
-    Check whether an array-like is a Categorical instance.
-
-    .. deprecated:: 1.1.0
-        Use ``is_categorical_dtype`` instead.
-
-    Parameters
-    ----------
-    arr : array-like
-        The array-like to check.
-
-    Returns
-    -------
-    boolean
-        Whether or not the array-like is of a Categorical instance.
-
-    Examples
-    --------
-    >>> is_categorical([1, 2, 3])
-    False
-
-    Categoricals, Series Categoricals, and CategoricalIndex will return True.
-
-    >>> cat = pd.Categorical([1, 2, 3])
-    >>> is_categorical(cat)
-    True
-    >>> is_categorical(pd.Series(cat))
-    True
-    >>> is_categorical(pd.CategoricalIndex([1, 2, 3]))
-    True
-    """
-    warnings.warn(
-        "is_categorical is deprecated and will be removed in a future version. "
-        "Use is_categorical_dtype instead.",
-        FutureWarning,
-        stacklevel=find_stack_level(),
-    )
-    return isinstance(arr, ABCCategorical) or is_categorical_dtype(arr)
-
-
 def is_datetime64_dtype(arr_or_dtype) -> bool:
     """
     Check whether an array-like or dtype is of the datetime64 dtype.
@@ -1772,7 +1726,6 @@ def is_all_strings(value: ArrayLike) -> bool:
     "is_array_like",
     "is_bool",
     "is_bool_dtype",
-    "is_categorical",
     "is_categorical_dtype",
     "is_complex",
     "is_complex_dtype",

pandas/tests/api/test_types.py

@@ -10,7 +10,6 @@ class TestTypes(Base):
     allowed = [
         "is_bool",
         "is_bool_dtype",
-        "is_categorical",
         "is_categorical_dtype",
         "is_complex",
         "is_complex_dtype",

pandas/tests/dtypes/test_common.py

@@ -208,22 +208,6 @@ def test_is_scipy_sparse():
     assert not com.is_scipy_sparse(SparseArray([1, 2, 3]))
 
 
-def test_is_categorical():
-    cat = pd.Categorical([1, 2, 3])
-    with tm.assert_produces_warning(FutureWarning):
-        assert com.is_categorical(cat)
-        assert com.is_categorical(pd.Series(cat))
-        assert com.is_categorical(pd.CategoricalIndex([1, 2, 3]))
-
-        assert not com.is_categorical([1, 2, 3])
-
-
-def test_is_categorical_deprecation():
-    # GH#33385
-    with tm.assert_produces_warning(FutureWarning):
-        com.is_categorical([1, 2, 3])
-
-
 def test_is_datetime64_dtype():
     assert not com.is_datetime64_dtype(object)
     assert not com.is_datetime64_dtype([1, 2, 3])

pandas/tests/dtypes/test_dtypes.py

@@ -9,7 +9,6 @@
 from pandas.core.dtypes.base import _registry as registry
 from pandas.core.dtypes.common import (
     is_bool_dtype,
-    is_categorical,
     is_categorical_dtype,
     is_datetime64_any_dtype,
     is_datetime64_dtype,
@@ -179,13 +178,6 @@ def test_basic(self, dtype):
         assert is_categorical_dtype(s)
         assert not is_categorical_dtype(np.dtype("float64"))
 
-        with tm.assert_produces_warning(FutureWarning):
-            # GH#33385 deprecated
-            assert is_categorical(s.dtype)
-            assert is_categorical(s)
-            assert not is_categorical(np.dtype("float64"))
-            assert not is_categorical(1.0)
-
     def test_tuple_categories(self):
         categories = [(1, "a"), (2, "b"), (3, "c")]
         result = CategoricalDtype(categories)