ENH: DTI/TDI as_unit

doc/source/reference/indexing.rst

@@ -385,6 +385,7 @@ Conversion
 .. autosummary::
    :toctree: api/
 
+   DatetimeIndex.as_unit
    DatetimeIndex.to_period
    DatetimeIndex.to_pydatetime
    DatetimeIndex.to_series
@@ -423,6 +424,7 @@ Conversion
 .. autosummary::
    :toctree: api/
 
+   TimedeltaIndex.as_unit
    TimedeltaIndex.to_pytimedelta
    TimedeltaIndex.to_series
    TimedeltaIndex.round

doc/source/whatsnew/v2.0.0.rst

@@ -108,6 +108,7 @@ Other enhancements
 - :meth:`DataFrame.plot.hist` now recognizes ``xlabel`` and ``ylabel`` arguments (:issue:`49793`)
 - Improved error message in :func:`to_datetime` for non-ISO8601 formats, informing users about the position of the first error (:issue:`50361`)
 - Improved error message when trying to align :class:`DataFrame` objects (for example, in :func:`DataFrame.compare`) to clarify that "identically labelled" refers to both index and columns (:issue:`50083`)
+- Added :meth:`DatetimeIndex.as_unit` and :meth:`TimedeltaIndex.as_unit` to convert to different resolutions; supported resolutions are "s", "ms", "us", and "ns" (:issue:`??`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/indexes/datetimelike.py

@@ -396,6 +396,14 @@ class DatetimeTimedeltaMixin(DatetimeIndexOpsMixin):
 
     _join_precedence = 10
 
+    @property
+    def unit(self) -> str:
+        return self._data.unit
+
+    def as_unit(self: _TDT, unit: str) -> _TDT:
+        arr = self._data.as_unit(unit)
+        return type(self)._simple_new(arr, name=self.name)
+
     def _with_freq(self, freq):
         arr = self._data._with_freq(freq)
         return type(self)._simple_new(arr, name=self._name)

pandas/tests/indexes/datetimes/methods/test_snap.py

@@ -7,13 +7,6 @@
 import pandas._testing as tm
 
 
-def astype_non_nano(dti_nano, unit):
-    # TODO(2.0): remove once DTI supports as_unit
-    dta = dti_nano._data.as_unit(unit)
-    dti = DatetimeIndex(dta, name=dti_nano.name)
-    return dti
-
-
 @pytest.mark.parametrize("tz", [None, "Asia/Shanghai", "Europe/Berlin"])
 @pytest.mark.parametrize("name", [None, "my_dti"])
 @pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])
@@ -32,12 +25,12 @@ def test_dti_snap(name, tz, unit):
         tz=tz,
         freq="D",
     )
-    dti = astype_non_nano(dti, unit)
+    dti = dti.as_unit(unit)
 
     result = dti.snap(freq="W-MON")
     expected = date_range("12/31/2001", "1/7/2002", name=name, tz=tz, freq="w-mon")
     expected = expected.repeat([3, 4])
-    expected = astype_non_nano(expected, unit)
+    expected = expected.as_unit(unit)
     tm.assert_index_equal(result, expected)
     assert result.tz == expected.tz
     assert result.freq is None
@@ -47,7 +40,7 @@ def test_dti_snap(name, tz, unit):
 
     expected = date_range("1/1/2002", "1/7/2002", name=name, tz=tz, freq="b")
     expected = expected.repeat([1, 1, 1, 2, 2])
-    expected = astype_non_nano(expected, unit)
+    expected = expected.as_unit(unit)
     tm.assert_index_equal(result, expected)
     assert result.tz == expected.tz
     assert result.freq is None

pandas/tests/series/test_constructors.py

@@ -1587,9 +1587,8 @@ def test_convert_non_ns(self):
         ser = Series(arr)
         assert ser.dtype == arr.dtype
 
-        tdi = timedelta_range("00:00:01", periods=3, freq="s")
-        tda = tdi._data.as_unit("s")
-        expected = Series(tda)
+        tdi = timedelta_range("00:00:01", periods=3, freq="s").as_unit("s")
+        expected = Series(tdi)
         assert expected.dtype == arr.dtype
         tm.assert_series_equal(ser, expected)