DEPR: remove is_period, is_datetimetz

doc/source/reference/general_utility_functions.rst

@@ -97,13 +97,11 @@ Scalar introspection
     api.types.is_bool
     api.types.is_categorical
     api.types.is_complex
-    api.types.is_datetimetz
     api.types.is_float
     api.types.is_hashable
     api.types.is_integer
     api.types.is_interval
     api.types.is_number
-    api.types.is_period
     api.types.is_re
     api.types.is_re_compilable
     api.types.is_scalar

doc/source/whatsnew/v1.0.0.rst

@@ -325,6 +325,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - :meth:`DataFrame.to_records` no longer supports the argument "convert_datetime64" (:issue:`18902`)
 - Removed the previously deprecated ``IntervalIndex.from_intervals`` in favor of the :class:`IntervalIndex` constructor (:issue:`19263`)
 - Changed the default value for the "keep_tz" argument in :meth:`DatetimeIndex.to_series` to ``True`` (:issue:`23739`)
+- Removed the previously deprecated :func:`api.types.is_period` and :func:`api.types.is_datetimetz` (:issue:`23917`)
 - Ability to read pickles containing :class:`Categorical` instances created with pre-0.16 version of pandas has been removed (:issue:`27538`)
 - Removed previously deprecated :func:`pandas.tseries.plotting.tsplot` (:issue:`18627`)
 - Removed the previously deprecated ``reduce`` and ``broadcast`` arguments from :meth:`DataFrame.apply` (:issue:`18577`)

pandas/core/dtypes/api.py

@@ -12,7 +12,6 @@
     is_datetime64_dtype,
     is_datetime64_ns_dtype,
     is_datetime64tz_dtype,
-    is_datetimetz,
     is_dict_like,
     is_dtype_equal,
     is_extension_array_dtype,
@@ -32,7 +31,6 @@
     is_number,
     is_numeric_dtype,
     is_object_dtype,
-    is_period,
     is_period_dtype,
     is_re,
     is_re_compilable,

pandas/core/dtypes/common.py

@@ -375,56 +375,6 @@ def is_categorical(arr) -> bool:
     return isinstance(arr, ABCCategorical) or is_categorical_dtype(arr)
 
 
-def is_datetimetz(arr) -> bool:
-    """
-    Check whether an array-like is a datetime array-like with a timezone
-    component in its dtype.
-
-    .. deprecated:: 0.24.0
-
-    Parameters
-    ----------
-    arr : array-like
-        The array-like to check.
-
-    Returns
-    -------
-    boolean
-        Whether or not the array-like is a datetime array-like with a
-        timezone component in its dtype.
-
-    Examples
-    --------
-    >>> is_datetimetz([1, 2, 3])
-    False
-
-    Although the following examples are both DatetimeIndex objects,
-    the first one returns False because it has no timezone component
-    unlike the second one, which returns True.
-
-    >>> is_datetimetz(pd.DatetimeIndex([1, 2, 3]))
-    False
-    >>> is_datetimetz(pd.DatetimeIndex([1, 2, 3], tz="US/Eastern"))
-    True
-
-    The object need not be a DatetimeIndex object. It just needs to have
-    a dtype which has a timezone component.
-
-    >>> dtype = DatetimeTZDtype("ns", tz="US/Eastern")
-    >>> s = pd.Series([], dtype=dtype)
-    >>> is_datetimetz(s)
-    True
-    """
-
-    warnings.warn(
-        "'is_datetimetz' is deprecated and will be removed in a "
-        "future version.  Use 'is_datetime64tz_dtype' instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return is_datetime64tz_dtype(arr)
-
-
 def is_offsetlike(arr_or_obj) -> bool:
     """
     Check if obj or all elements of list-like is DateOffset
@@ -456,43 +406,6 @@ def is_offsetlike(arr_or_obj) -> bool:
     return False
 
 
-def is_period(arr) -> bool:
-    """
-    Check whether an array-like is a periodical index.
-
-    .. deprecated:: 0.24.0
-
-    Parameters
-    ----------
-    arr : array-like
-        The array-like to check.
-
-    Returns
-    -------
-    boolean
-        Whether or not the array-like is a periodical index.
-
-    Examples
-    --------
-    >>> is_period([1, 2, 3])
-    False
-    >>> is_period(pd.Index([1, 2, 3]))
-    False
-    >>> is_period(pd.PeriodIndex(["2017-01-01"], freq="D"))
-    True
-    """
-
-    warnings.warn(
-        "'is_period' is deprecated and will be removed in a future "
-        "version.  Use 'is_period_dtype' or is_period_arraylike' "
-        "instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-
-    return isinstance(arr, ABCPeriodIndex) or is_period_arraylike(arr)
-
-
 def is_datetime64_dtype(arr_or_dtype) -> bool:
     """
     Check whether an array-like or dtype is of the datetime64 dtype.

pandas/tests/api/test_types.py

@@ -50,7 +50,7 @@ class TestTypes(Base):
         "infer_dtype",
         "is_extension_array_dtype",
     ]
-    deprecated = ["is_period", "is_datetimetz", "is_extension_type"]
+    deprecated = ["is_extension_type"]
     dtypes = ["CategoricalDtype", "DatetimeTZDtype", "PeriodDtype", "IntervalDtype"]
 
     def test_types(self):

pandas/tests/dtypes/test_common.py

@@ -207,25 +207,6 @@ def test_is_categorical():
     assert not com.is_categorical([1, 2, 3])
 
 
-def test_is_datetimetz():
-    with tm.assert_produces_warning(FutureWarning):
-        assert not com.is_datetimetz([1, 2, 3])
-        assert not com.is_datetimetz(pd.DatetimeIndex([1, 2, 3]))
-
-        assert com.is_datetimetz(pd.DatetimeIndex([1, 2, 3], tz="US/Eastern"))
-
-        dtype = DatetimeTZDtype("ns", tz="US/Eastern")
-        s = pd.Series([], dtype=dtype)
-        assert com.is_datetimetz(s)
-
-
-def test_is_period_deprecated():
-    with tm.assert_produces_warning(FutureWarning):
-        assert not com.is_period([1, 2, 3])
-        assert not com.is_period(pd.Index([1, 2, 3]))
-        assert com.is_period(pd.PeriodIndex(["2017-01-01"], freq="D"))
-
-
 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

@@ -12,10 +12,8 @@
     is_datetime64_dtype,
     is_datetime64_ns_dtype,
     is_datetime64tz_dtype,
-    is_datetimetz,
     is_dtype_equal,
     is_interval_dtype,
-    is_period,
     is_period_dtype,
     is_string_dtype,
 )
@@ -294,25 +292,15 @@ def test_basic(self):
         assert not is_datetime64tz_dtype(np.dtype("float64"))
         assert not is_datetime64tz_dtype(1.0)
 
-        with tm.assert_produces_warning(FutureWarning):
-            assert is_datetimetz(s)
-            assert is_datetimetz(s.dtype)
-            assert not is_datetimetz(np.dtype("float64"))
-            assert not is_datetimetz(1.0)
-
     def test_dst(self):
 
         dr1 = date_range("2013-01-01", periods=3, tz="US/Eastern")
         s1 = Series(dr1, name="A")
         assert is_datetime64tz_dtype(s1)
-        with tm.assert_produces_warning(FutureWarning):
-            assert is_datetimetz(s1)
 
         dr2 = date_range("2013-08-01", periods=3, tz="US/Eastern")
         s2 = Series(dr2, name="A")
         assert is_datetime64tz_dtype(s2)
-        with tm.assert_produces_warning(FutureWarning):
-            assert is_datetimetz(s2)
         assert s1.dtype == s2.dtype
 
     @pytest.mark.parametrize("tz", ["UTC", "US/Eastern"])
@@ -457,22 +445,14 @@ def test_basic(self):
 
         assert is_period_dtype(pidx.dtype)
         assert is_period_dtype(pidx)
-        with tm.assert_produces_warning(FutureWarning):
-            assert is_period(pidx)
 
         s = Series(pidx, name="A")
 
         assert is_period_dtype(s.dtype)
         assert is_period_dtype(s)
-        with tm.assert_produces_warning(FutureWarning):
-            assert is_period(s)
 
         assert not is_period_dtype(np.dtype("float64"))
         assert not is_period_dtype(1.0)
-        with tm.assert_produces_warning(FutureWarning):
-            assert not is_period(np.dtype("float64"))
-        with tm.assert_produces_warning(FutureWarning):
-            assert not is_period(1.0)
 
     def test_empty(self):
         dt = PeriodDtype()