DEPR: Index methods, to_time, Categorical constructor

asv_bench/benchmarks/index_cached_properties.py

@@ -70,6 +70,3 @@ def time_engine(self, index_type):
 
     def time_inferred_type(self, index_type):
         self.idx.inferred_type
-
-    def time_is_all_dates(self, index_type):
-        self.idx.is_all_dates

doc/redirects.csv

@@ -661,7 +661,6 @@ generated/pandas.Index.identical,../reference/api/pandas.Index.identical
 generated/pandas.Index.inferred_type,../reference/api/pandas.Index.inferred_type
 generated/pandas.Index.insert,../reference/api/pandas.Index.insert
 generated/pandas.Index.intersection,../reference/api/pandas.Index.intersection
-generated/pandas.Index.is_all_dates,../reference/api/pandas.Index.is_all_dates
 generated/pandas.Index.is_boolean,../reference/api/pandas.Index.is_boolean
 generated/pandas.Index.is_categorical,../reference/api/pandas.Index.is_categorical
 generated/pandas.Index.is_floating,../reference/api/pandas.Index.is_floating
@@ -671,7 +670,6 @@ generated/pandas.Index.is_integer,../reference/api/pandas.Index.is_integer
 generated/pandas.Index.is_interval,../reference/api/pandas.Index.is_interval
 generated/pandas.Index.is_lexsorted_for_tuple,../reference/api/pandas.Index.is_lexsorted_for_tuple
 generated/pandas.Index.is_monotonic_decreasing,../reference/api/pandas.Index.is_monotonic_decreasing
-generated/pandas.Index.is_monotonic,../reference/api/pandas.Index.is_monotonic
 generated/pandas.Index.is_monotonic_increasing,../reference/api/pandas.Index.is_monotonic_increasing
 generated/pandas.Index.isna,../reference/api/pandas.Index.isna
 generated/pandas.Index.isnull,../reference/api/pandas.Index.isnull
@@ -1068,7 +1066,6 @@ generated/pandas.Series.interpolate,../reference/api/pandas.Series.interpolate
 generated/pandas.Series.is_copy,../reference/api/pandas.Series.is_copy
 generated/pandas.Series.isin,../reference/api/pandas.Series.isin
 generated/pandas.Series.is_monotonic_decreasing,../reference/api/pandas.Series.is_monotonic_decreasing
-generated/pandas.Series.is_monotonic,../reference/api/pandas.Series.is_monotonic
 generated/pandas.Series.is_monotonic_increasing,../reference/api/pandas.Series.is_monotonic_increasing
 generated/pandas.Series.isna,../reference/api/pandas.Series.isna
 generated/pandas.Series.isnull,../reference/api/pandas.Series.isnull

doc/source/reference/indexing.rst

@@ -25,15 +25,13 @@ Properties
    :toctree: api/
 
    Index.values
-   Index.is_monotonic
    Index.is_monotonic_increasing
    Index.is_monotonic_decreasing
    Index.is_unique
    Index.has_duplicates
    Index.hasnans
    Index.dtype
    Index.inferred_type
-   Index.is_all_dates
    Index.shape
    Index.name
    Index.names

doc/source/reference/series.rst

@@ -167,7 +167,6 @@ Computations / descriptive stats
    Series.unique
    Series.nunique
    Series.is_unique
-   Series.is_monotonic
    Series.is_monotonic_increasing
    Series.is_monotonic_decreasing
    Series.value_counts

doc/source/whatsnew/v2.0.0.rst

@@ -159,6 +159,7 @@ Deprecations
 Removal of prior version deprecations/changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 - Removed deprecated module ``pandas.core.index`` (:issue:`30193`)
+- Removed deprecated alias ``pandas.core.tools.datetimes.to_time``, import the function directly from ``pandas.core.tools.times`` instead (:issue:`34145`)
 - Removed deprecated :meth:`Categorical.to_dense`, use ``np.asarray(cat)`` instead (:issue:`32639`)
 - Removed deprecated :meth:`Categorical.take_nd` (:issue:`27745`)
 - Removed deprecated :meth:`Categorical.mode`, use ``Series(cat).mode()`` instead (:issue:`45033`)
@@ -182,6 +183,8 @@ Removal of prior version deprecations/changes
 - Removed deprecated :meth:`.Styler.render` (:issue:`49397`)
 - Removed deprecated argument ``null_color`` in :meth:`.Styler.highlight_null` (:issue:`49397`)
 - Removed deprecated ``null_counts`` argument in :meth:`DataFrame.info`. Use ``show_counts`` instead (:issue:`37999`)
+- Removed deprecated :meth:`Index.is_monotonic`, and :meth:`Series.is_monotonic`; use ``obj.is_monotonic_increasing`` instead (:issue:`45422`)
+- Removed deprecated :meth:`Index.is_all_dates` (:issue:`36697`)
 - 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`)
 - Enforced deprecation disallowing unit-less "datetime64" dtype in :meth:`Series.astype` and :meth:`DataFrame.astype` (:issue:`47844`)
@@ -245,6 +248,8 @@ Removal of prior version deprecations/changes
 - Disallow passing non-keyword arguments to :meth:`DataFrame.replace`, :meth:`Series.replace` except for ``to_replace`` and ``value`` (:issue:`47587`)
 - Disallow passing non-keyword arguments to :meth:`DataFrame.sort_values` except for ``by`` (:issue:`41505`)
 - Disallow passing non-keyword arguments to :meth:`Series.sort_values` (:issue:`41505`)
+- Disallowed constructing :class:`Categorical` with scalar ``data`` (:issue:`38433`)
+- Disallowed constructing :class:`CategoricalIndex` without passing ``data`` (:issue:`38944`)
 - Removed :meth:`.Rolling.validate`, :meth:`.Expanding.validate`, and :meth:`.ExponentialMovingWindow.validate` (:issue:`43665`)
 - Removed :attr:`Rolling.win_type` returning ``"freq"`` (:issue:`38963`)
 - Removed :attr:`Rolling.is_datetimelike` (:issue:`38963`)
@@ -286,6 +291,8 @@ Removal of prior version deprecations/changes
 - Changed behavior of empty data passed into :class:`Series`; the default dtype will be ``object`` instead of ``float64`` (:issue:`29405`)
 - Changed the behavior of :func:`to_datetime` with argument "now" with ``utc=False`` to match ``Timestamp("now")`` (:issue:`18705`)
 - Changed behavior of :meth:`SparseArray.astype` when given a dtype that is not explicitly ``SparseDtype``, cast to the exact requested dtype rather than silently using a ``SparseDtype`` instead (:issue:`34457`)
+- Changed behavior of :meth:`Index.ravel` to return a view on the original :class:`Index` instead of a ``np.ndarray`` (:issue:`36900`)
+- Changed behavior of :meth:`Index.to_frame` with explicit ``name=None`` to use ``None`` for the column name instead of the index's name or default ``0`` (:issue:`45523`)
 - Changed behavior of :class:`DataFrame` constructor given floating-point ``data`` and an integer ``dtype``, when the data cannot be cast losslessly, the floating point dtype is retained, matching :class:`Series` behavior (:issue:`41170`)
 - Changed behavior of :class:`DataFrame` constructor when passed a ``dtype`` (other than int) that the data cannot be cast to; it now raises instead of silently ignoring the dtype (:issue:`41733`)
 - Changed the behavior of :class:`Series` constructor, it will no longer infer a datetime64 or timedelta64 dtype from string entries (:issue:`41731`)

pandas/core/arrays/categorical.py

@@ -15,7 +15,6 @@
     cast,
     overload,
 )
-from warnings import warn
 
 import numpy as np
 
@@ -40,7 +39,6 @@
     type_t,
 )
 from pandas.compat.numpy import function as nv
-from pandas.util._exceptions import find_stack_level
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -384,13 +382,7 @@ def __init__(
 
         if not is_list_like(values):
             # GH#38433
-            warn(
-                "Allowing scalars in the Categorical constructor is deprecated "
-                "and will raise in a future version.  Use `[value]` instead",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            values = [values]
+            raise TypeError("Categorical input must be list-like")
 
         # null_mask indicates missing values we want to exclude from inference.
         # This means: only missing values in list-likes (not arrays/ndframes).

pandas/core/base.py

@@ -17,7 +17,6 @@
     final,
     overload,
 )
-import warnings
 
 import numpy as np
 
@@ -38,7 +37,6 @@
     cache_readonly,
     doc,
 )
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
@@ -1056,27 +1054,6 @@ def is_unique(self) -> bool:
         """
         return self.nunique(dropna=False) == len(self)
 
-    @property
-    def is_monotonic(self) -> bool:
-        """
-        Return boolean if values in the object are monotonically increasing.
-
-        .. deprecated:: 1.5.0
-            is_monotonic is deprecated and will be removed in a future version.
-            Use is_monotonic_increasing instead.
-
-        Returns
-        -------
-        bool
-        """
-        warnings.warn(
-            "is_monotonic is deprecated and will be removed in a future version. "
-            "Use is_monotonic_increasing instead.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-        return self.is_monotonic_increasing
-
     @property
     def is_monotonic_increasing(self) -> bool:
         """

pandas/core/indexes/base.py

@@ -941,34 +941,19 @@ def dtype(self) -> DtypeObj:
         return self._data.dtype
 
     @final
-    def ravel(self, order: str_t = "C"):
+    def ravel(self, order: str_t = "C") -> Index:
         """
-        Return an ndarray of the flattened values of the underlying data.
+        Return a view on self.
 
         Returns
         -------
-        numpy.ndarray
-            Flattened array.
+        Index
 
         See Also
         --------
         numpy.ndarray.ravel : Return a flattened array.
         """
-        warnings.warn(
-            "Index.ravel returning ndarray is deprecated; in a future version "
-            "this will return a view on self.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-        if needs_i8_conversion(self.dtype):
-            # Item "ndarray[Any, Any]" of "Union[ExtensionArray, ndarray[Any, Any]]"
-            # has no attribute "_ndarray"
-            values = self._data._ndarray  # type: ignore[union-attr]
-        elif is_interval_dtype(self.dtype):
-            values = np.asarray(self._data)
-        else:
-            values = self._get_engine_target()
-        return values.ravel(order=order)
+        return self[:]
 
     def view(self, cls=None):
 
@@ -1555,7 +1540,7 @@ def to_frame(
         index : bool, default True
             Set the index of the returned DataFrame as the original Index.
 
-        name : object, default None
+        name : object, defaults to index.name
             The passed name should substitute for the index name (if it has
             one).
 
@@ -1597,17 +1582,6 @@ def to_frame(
         """
         from pandas import DataFrame
 
-        if name is None:
-            warnings.warn(
-                "Explicitly passing `name=None` currently preserves the Index's name "
-                "or uses a default name of 0. This behaviour is deprecated, and in "
-                "the future `None` will be used as the name of the resulting "
-                "DataFrame column.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            name = lib.no_default
-
         if name is lib.no_default:
             name = self._get_level_names()
         result = DataFrame({name: self._values.copy()})
@@ -2200,24 +2174,6 @@ def _can_hold_na(self) -> bool:
             return False
         return True
 
-    @final
-    @property
-    def is_monotonic(self) -> bool:
-        """
-        Alias for is_monotonic_increasing.
-
-        .. deprecated:: 1.5.0
-            is_monotonic is deprecated and will be removed in a future version.
-            Use is_monotonic_increasing instead.
-        """
-        warnings.warn(
-            "is_monotonic is deprecated and will be removed in a future version. "
-            "Use is_monotonic_increasing instead.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-        return self.is_monotonic_increasing
-
     @property
     def is_monotonic_increasing(self) -> bool:
         """
@@ -2629,20 +2585,6 @@ def _is_all_dates(self) -> bool:
             return False
         return is_datetime_array(ensure_object(self._values))
 
-    @cache_readonly
-    @final
-    def is_all_dates(self) -> bool:
-        """
-        Whether or not the index values only consist of dates.
-        """
-        warnings.warn(
-            "Index.is_all_dates is deprecated, will be removed in a future version. "
-            "check index.inferred_type instead.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-        return self._is_all_dates
-
     @final
     @cache_readonly
     def _is_multi(self) -> bool:

pandas/core/indexes/category.py

@@ -216,18 +216,8 @@ def __new__(
 
         name = maybe_extract_name(name, data, cls)
 
-        if data is None:
-            # GH#38944
-            warnings.warn(
-                "Constructing a CategoricalIndex without passing data is "
-                "deprecated and will raise in a future version. "
-                "Use CategoricalIndex([], ...) instead.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            data = []
-
         if is_scalar(data):
+            # GH#38944 include None here, which pre-2.0 subbed in []
             cls._raise_scalar_data_error(data)
 
         data = Categorical(

pandas/core/indexes/multi.py

@@ -1738,17 +1738,6 @@ def to_frame(
         """
         from pandas import DataFrame
 
-        if name is None:
-            warnings.warn(
-                "Explicitly passing `name=None` currently preserves the Index's name "
-                "or uses a default name of 0. This behaviour is deprecated, and in "
-                "the future `None` will be used as the name of the resulting "
-                "DataFrame column.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-            name = lib.no_default
-
         if name is not lib.no_default:
             if not is_list_like(name):
                 raise TypeError("'name' must be a list / sequence of column names.")

pandas/core/tools/datetimes.py

@@ -15,7 +15,6 @@
     cast,
     overload,
 )
-import warnings
 
 import numpy as np
 
@@ -42,7 +41,6 @@
     Timezone,
     npt,
 )
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     ensure_object,
@@ -1294,27 +1292,8 @@ def calc_with_mask(carg, mask):
     return None
 
 
-def to_time(
-    arg,
-    format=None,
-    infer_time_format: bool = False,
-    errors: DateTimeErrorChoices = "raise",
-):
-    # GH#34145
-    warnings.warn(
-        "`to_time` has been moved, should be imported from pandas.core.tools.times. "
-        "This alias will be removed in a future version.",
-        FutureWarning,
-        stacklevel=find_stack_level(),
-    )
-    from pandas.core.tools.times import to_time
-
-    return to_time(arg, format, infer_time_format, errors)
-
-
 __all__ = [
     "DateParseError",
     "should_cache",
     "to_datetime",
-    "to_time",
 ]

pandas/tests/arrays/categorical/test_constructors.py

@@ -33,9 +33,9 @@
 
 
 class TestCategoricalConstructors:
-    def test_categorical_scalar_deprecated(self):
+    def test_categorical_disallows_scalar(self):
         # GH#38433
-        with tm.assert_produces_warning(FutureWarning):
+        with pytest.raises(TypeError, match="Categorical input must be list-like"):
             Categorical("A", categories=["A", "B"])
 
     def test_categorical_1d_only(self):
@@ -220,13 +220,6 @@ def test_constructor(self):
         assert len(cat.codes) == 1
         assert cat.codes[0] == 0
 
-        with tm.assert_produces_warning(FutureWarning):
-            # GH#38433
-            cat = Categorical(1)
-        assert len(cat.categories) == 1
-        assert cat.categories[0] == 1
-        assert len(cat.codes) == 1
-        assert cat.codes[0] == 0
         # two arrays
         #  - when the first is an integer dtype and the second is not
         #  - when the resulting codes are all -1/NaN

pandas/tests/indexes/categorical/test_category.py

@@ -38,11 +38,6 @@ def test_can_hold_identifiers(self):
         key = idx[0]
         assert idx._can_hold_identifiers_and_holds_name(key) is True
 
-    def test_pickle_compat_construction(self):
-        # Once the deprecation is enforced, we can use the parent class's test
-        with tm.assert_produces_warning(FutureWarning, match="without passing data"):
-            self._index_cls()
-
     def test_insert(self, simple_index):
 
         ci = simple_index