DEPR: unit keyword in TimedeltaIndex

doc/source/whatsnew/v2.2.0.rst

@@ -297,6 +297,7 @@ Other Deprecations
 - Deprecated the ``errors="ignore"`` option in :func:`to_datetime`, :func:`to_timedelta`, and :func:`to_numeric`; explicitly catch exceptions instead (:issue:`54467`)
 - Deprecated the ``fastpath`` keyword in the :class:`Series` constructor (:issue:`20110`)
 - Deprecated the ``ordinal`` keyword in :class:`PeriodIndex`, use :meth:`PeriodIndex.from_ordinals` instead (:issue:`55960`)
+- Deprecated the ``unit`` keyword in :class:`TimedeltaIndex` construction, use :func:`to_timedelta` instead (:issue:`55499`)
 - Deprecated the extension test classes ``BaseNoReduceTests``, ``BaseBooleanReduceTests``, and ``BaseNumericReduceTests``, use ``BaseReduceTests`` instead (:issue:`54663`)
 - Deprecated the option ``mode.data_manager`` and the ``ArrayManager``; only the ``BlockManager`` will be available in future versions (:issue:`55043`)
 - Deprecated the previous implementation of :class:`DataFrame.stack`; specify ``future_stack=True`` to adopt the future version (:issue:`53515`)

pandas/core/indexes/timedeltas.py

@@ -64,6 +64,10 @@ class TimedeltaIndex(DatetimeTimedeltaMixin):
         Optional timedelta-like data to construct index with.
     unit : {'D', 'h', 'm', 's', 'ms', 'us', 'ns'}, optional
         The unit of ``data``.
+
+        .. deprecated:: 2.2.0
+         Use ``pd.to_timedelta`` instead.
+
     freq : str or pandas offset object, optional
         One of pandas date offset strings or corresponding objects. The string
         ``'infer'`` can be passed in order to set the frequency of the index as
@@ -114,13 +118,9 @@ class TimedeltaIndex(DatetimeTimedeltaMixin):
     TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
                    dtype='timedelta64[ns]', freq=None)
 
-    >>> pd.TimedeltaIndex([1, 2, 4, 8], unit='D')
-    TimedeltaIndex(['1 days', '2 days', '4 days', '8 days'],
-                   dtype='timedelta64[ns]', freq=None)
-
     We can also let pandas infer the frequency when possible.
 
-    >>> pd.TimedeltaIndex(range(5), unit='D', freq='infer')
+    >>> pd.TimedeltaIndex(np.arange(5) * 24 * 3600 * 1e9, freq='infer')
     TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
                    dtype='timedelta64[ns]', freq='D')
     """
@@ -150,7 +150,7 @@ def _resolution_obj(self) -> Resolution | None:  # type: ignore[override]
     def __new__(
         cls,
         data=None,
-        unit=None,
+        unit=lib.no_default,
         freq=lib.no_default,
         closed=lib.no_default,
         dtype=None,
@@ -166,6 +166,18 @@ def __new__(
                 stacklevel=find_stack_level(),
             )
 
+        if unit is not lib.no_default:
+            # GH#55499
+            warnings.warn(
+                f"The 'unit' keyword in {cls.__name__} construction is "
+                "deprecated and will be removed in a future version. "
+                "Use pd.to_timedelta instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        else:
+            unit = None
+
         name = maybe_extract_name(name, data, cls)
 
         if is_scalar(data):

pandas/core/tools/timedeltas.py

@@ -279,5 +279,5 @@ def _convert_listlike(
 
     from pandas import TimedeltaIndex
 
-    value = TimedeltaIndex(td64arr, unit="ns", name=name)
+    value = TimedeltaIndex(td64arr, name=name)
     return value

pandas/tests/arrays/test_datetimelike.py

@@ -217,7 +217,7 @@ def test_concat_same_type(self, arr1d):
 
         result = arr._concat_same_type([arr[:-1], arr[1:], arr])
         arr2 = arr.astype(object)
-        expected = self.index_cls(np.concatenate([arr2[:-1], arr2[1:], arr2]), None)
+        expected = self.index_cls(np.concatenate([arr2[:-1], arr2[1:], arr2]))
 
         tm.assert_index_equal(self.index_cls(result), expected)
 
@@ -1247,7 +1247,7 @@ def test_to_numpy_extra(arr):
     "values",
     [
         pd.to_datetime(["2020-01-01", "2020-02-01"]),
-        TimedeltaIndex([1, 2], unit="D"),
+        pd.to_timedelta([1, 2], unit="D"),
         PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
     ],
 )
@@ -1278,7 +1278,7 @@ def test_searchsorted_datetimelike_with_listlike(values, klass, as_index):
     "values",
     [
         pd.to_datetime(["2020-01-01", "2020-02-01"]),
-        TimedeltaIndex([1, 2], unit="D"),
+        pd.to_timedelta([1, 2], unit="D"),
         PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
     ],
 )

pandas/tests/indexes/test_datetimelike.py

@@ -165,5 +165,5 @@ def test_diff(self, unit):
         # GH 55080
         dti = pd.to_datetime([10, 20, 30], unit=unit).as_unit(unit)
         result = dti.diff(1)
-        expected = pd.TimedeltaIndex([pd.NaT, 10, 10], unit=unit).as_unit(unit)
+        expected = pd.to_timedelta([pd.NaT, 10, 10], unit=unit).as_unit(unit)
         tm.assert_index_equal(result, expected)

pandas/tests/indexes/timedeltas/test_constructors.py

@@ -39,8 +39,10 @@ def test_array_of_dt64_nat_raises(self):
     @pytest.mark.parametrize("unit", ["Y", "y", "M"])
     def test_unit_m_y_raises(self, unit):
         msg = "Units 'M', 'Y', and 'y' are no longer supported"
+        depr_msg = "The 'unit' keyword in TimedeltaIndex construction is deprecated"
         with pytest.raises(ValueError, match=msg):
-            TimedeltaIndex([1, 3, 7], unit)
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                TimedeltaIndex([1, 3, 7], unit)
 
     def test_int64_nocopy(self):
         # GH#23539 check that a copy isn't made when we pass int64 data
@@ -120,7 +122,7 @@ def test_float64_ns_rounded(self):
 
     def test_float64_unit_conversion(self):
         # GH#23539
-        tdi = TimedeltaIndex([1.5, 2.25], unit="D")
+        tdi = to_timedelta([1.5, 2.25], unit="D")
         expected = TimedeltaIndex([Timedelta(days=1.5), Timedelta(days=2.25)])
         tm.assert_index_equal(tdi, expected)
 
@@ -133,6 +135,9 @@ def test_construction_base_constructor(self):
         tm.assert_index_equal(pd.Index(arr), TimedeltaIndex(arr))
         tm.assert_index_equal(pd.Index(np.array(arr)), TimedeltaIndex(np.array(arr)))
 
+    @pytest.mark.filterwarnings(
+        "ignore:The 'unit' keyword in TimedeltaIndex construction:FutureWarning"
+    )
     def test_constructor(self):
         expected = TimedeltaIndex(
             [
@@ -157,15 +162,18 @@ def test_constructor(self):
         expected = TimedeltaIndex(
             ["0 days 00:00:00", "0 days 00:00:01", "0 days 00:00:02"]
         )
-        tm.assert_index_equal(TimedeltaIndex(range(3), unit="s"), expected)
+        result = TimedeltaIndex(range(3), unit="s")
+        tm.assert_index_equal(result, expected)
         expected = TimedeltaIndex(
             ["0 days 00:00:00", "0 days 00:00:05", "0 days 00:00:09"]
         )
-        tm.assert_index_equal(TimedeltaIndex([0, 5, 9], unit="s"), expected)
+        result = TimedeltaIndex([0, 5, 9], unit="s")
+        tm.assert_index_equal(result, expected)
         expected = TimedeltaIndex(
             ["0 days 00:00:00.400", "0 days 00:00:00.450", "0 days 00:00:01.200"]
         )
-        tm.assert_index_equal(TimedeltaIndex([400, 450, 1200], unit="ms"), expected)
+        result = TimedeltaIndex([400, 450, 1200], unit="ms")
+        tm.assert_index_equal(result, expected)
 
     def test_constructor_iso(self):
         # GH #21877

pandas/tests/indexes/timedeltas/test_scalar_compat.py

@@ -100,7 +100,7 @@ def test_round(self):
         t1 = timedelta_range("1 days", periods=3, freq="1 min 2 s 3 us")
         t2 = -1 * t1
         t1a = timedelta_range("1 days", periods=3, freq="1 min 2 s")
-        t1c = TimedeltaIndex([1, 1, 1], unit="D")
+        t1c = TimedeltaIndex(np.array([1, 1, 1], "m8[D]")).as_unit("ns")
 
         # note that negative times round DOWN! so don't give whole numbers
         for freq, s1, s2 in [
@@ -122,7 +122,7 @@ def test_round(self):
             ),
             ("12min", t1c, TimedeltaIndex(["-1 days", "-1 days", "-1 days"])),
             ("h", t1c, TimedeltaIndex(["-1 days", "-1 days", "-1 days"])),
-            ("d", t1c, TimedeltaIndex([-1, -1, -1], unit="D")),
+            ("d", t1c, -1 * t1c),
         ]:
             r1 = t1.round(freq)
             tm.assert_index_equal(r1, s1)

pandas/tests/reductions/test_stat_reductions.py

@@ -68,7 +68,8 @@ def test_period_mean(self, box, freq):
 
     @pytest.mark.parametrize("box", [Series, pd.Index, TimedeltaArray])
     def test_td64_mean(self, box):
-        tdi = pd.TimedeltaIndex([0, 3, -2, -7, 1, 2, -1, 3, 5, -2, 4], unit="D")
+        m8values = np.array([0, 3, -2, -7, 1, 2, -1, 3, 5, -2, 4], "m8[D]")
+        tdi = pd.TimedeltaIndex(m8values).as_unit("ns")
 
         tdarr = tdi._data
         obj = box(tdarr, copy=False)

pandas/tests/resample/test_timedelta.py

@@ -98,9 +98,12 @@ def test_resample_categorical_data_with_timedeltaindex():
     df = DataFrame({"Group_obj": "A"}, index=pd.to_timedelta(list(range(20)), unit="s"))
     df["Group"] = df["Group_obj"].astype("category")
     result = df.resample("10s").agg(lambda x: (x.value_counts().index[0]))
+    exp_tdi = pd.TimedeltaIndex(np.array([0, 10], dtype="m8[s]"), freq="10s").as_unit(
+        "ns"
+    )
     expected = DataFrame(
         {"Group_obj": ["A", "A"], "Group": ["A", "A"]},
-        index=pd.TimedeltaIndex([0, 10], unit="s", freq="10s"),
+        index=exp_tdi,
     )
     expected = expected.reindex(["Group_obj", "Group"], axis=1)
     expected["Group"] = expected["Group_obj"].astype("category")

pandas/tests/scalar/timedelta/test_constructors.py

@@ -144,7 +144,8 @@ def test_unit_parser(self, unit, np_unit, wrapper):
         if (unit, np_unit) in (("u", "us"), ("U", "us"), ("n", "ns"), ("N", "ns")):
             warn = FutureWarning
         else:
-            warn = None
+            warn = FutureWarning
+            msg = "The 'unit' keyword in TimedeltaIndex construction is deprecated"
         with tm.assert_produces_warning(warn, match=msg):
             result = to_timedelta(wrapper(range(5)), unit=unit)
             tm.assert_index_equal(result, expected)