ENH: allow passing freq=None to DatetimeIndex/TimedeltaIndex (pandas-dev#33635)

Author: jbrockmendel

pandas/core/arrays/datetimelike.py

@@ -1796,6 +1796,7 @@ def maybe_infer_freq(freq):
     -------
     freq : {DateOffset, None}
     freq_infer : bool
+        Whether we should inherit the freq of passed data.
     """
     freq_infer = False
     if not isinstance(freq, DateOffset):

pandas/core/arrays/datetimes.py

@@ -302,11 +302,13 @@ def _from_sequence(
         dtype=None,
         copy=False,
         tz=None,
-        freq=None,
+        freq=lib.no_default,
         dayfirst=False,
         yearfirst=False,
         ambiguous="raise",
     ):
+        explicit_none = freq is None
+        freq = freq if freq is not lib.no_default else None
 
         freq, freq_infer = dtl.maybe_infer_freq(freq)
 
@@ -321,6 +323,8 @@ def _from_sequence(
         )
 
         freq, freq_infer = dtl.validate_inferred_freq(freq, inferred_freq, freq_infer)
+        if explicit_none:
+            freq = None
 
         dtype = tz_to_dtype(tz)
         result = cls._simple_new(subarr, freq=freq, dtype=dtype)

pandas/core/arrays/timedeltas.py

@@ -141,13 +141,18 @@ def dtype(self):
     # ----------------------------------------------------------------
     # Constructors
 
-    def __init__(self, values, dtype=TD64NS_DTYPE, freq=None, copy=False):
+    def __init__(self, values, dtype=TD64NS_DTYPE, freq=lib.no_default, copy=False):
         values = extract_array(values)
 
         inferred_freq = getattr(values, "_freq", None)
+        explicit_none = freq is None
+        freq = freq if freq is not lib.no_default else None
 
         if isinstance(values, type(self)):
-            if freq is None:
+            if explicit_none:
+                # dont inherit from values
+                pass
+            elif freq is None:
                 freq = values.freq
             elif freq and values.freq:
                 freq = to_offset(freq)
@@ -206,13 +211,21 @@ def _simple_new(cls, values, freq=None, dtype=TD64NS_DTYPE):
         return result
 
     @classmethod
-    def _from_sequence(cls, data, dtype=TD64NS_DTYPE, copy=False, freq=None, unit=None):
+    def _from_sequence(
+        cls, data, dtype=TD64NS_DTYPE, copy=False, freq=lib.no_default, unit=None
+    ):
         if dtype:
             _validate_td64_dtype(dtype)
+
+        explicit_none = freq is None
+        freq = freq if freq is not lib.no_default else None
+
         freq, freq_infer = dtl.maybe_infer_freq(freq)
 
         data, inferred_freq = sequence_to_td64ns(data, copy=copy, unit=unit)
         freq, freq_infer = dtl.validate_inferred_freq(freq, inferred_freq, freq_infer)
+        if explicit_none:
+            freq = None
 
         result = cls._simple_new(data, freq=freq)
 

pandas/core/indexes/datetimes.py

@@ -224,7 +224,7 @@ class DatetimeIndex(DatetimeTimedeltaMixin):
     def __new__(
         cls,
         data=None,
-        freq=None,
+        freq=lib.no_default,
         tz=None,
         normalize=False,
         closed=None,

pandas/core/indexes/timedeltas.py

@@ -1,6 +1,6 @@
 """ implement the TimedeltaIndex """
 
-from pandas._libs import NaT, Timedelta, index as libindex
+from pandas._libs import NaT, Timedelta, index as libindex, lib
 from pandas._typing import DtypeObj, Label
 from pandas.util._decorators import doc
 
@@ -121,7 +121,7 @@ def __new__(
         cls,
         data=None,
         unit=None,
-        freq=None,
+        freq=lib.no_default,
         closed=None,
         dtype=TD64NS_DTYPE,
         copy=False,
@@ -141,12 +141,12 @@ def __new__(
                 "represent unambiguous timedelta values durations."
             )
 
-        if isinstance(data, TimedeltaArray) and freq is None:
+        if isinstance(data, TimedeltaArray) and freq is lib.no_default:
             if copy:
                 data = data.copy()
             return cls._simple_new(data, name=name)
 
-        if isinstance(data, TimedeltaIndex) and freq is None and name is None:
+        if isinstance(data, TimedeltaIndex) and freq is lib.no_default and name is None:
             if copy:
                 return data.copy()
             else:
@@ -340,6 +340,6 @@ def timedelta_range(
     if freq is None and com.any_none(periods, start, end):
         freq = "D"
 
-    freq, freq_infer = dtl.maybe_infer_freq(freq)
+    freq, _ = dtl.maybe_infer_freq(freq)
     tdarr = TimedeltaArray._generate_range(start, end, periods, freq, closed=closed)
     return TimedeltaIndex._simple_new(tdarr, name=name)

pandas/tests/indexes/datetimes/test_constructors.py

@@ -816,6 +816,16 @@ def test_dti_constructor_preserve_dti_freq(self):
         rng2 = DatetimeIndex(rng)
         assert rng.freq == rng2.freq
 
+    def test_explicit_none_freq(self):
+        # Explicitly passing freq=None is respected
+        rng = date_range("1/1/2000", "1/2/2000", freq="5min")
+
+        result = DatetimeIndex(rng, freq=None)
+        assert result.freq is None
+
+        result = DatetimeIndex(rng._data, freq=None)
+        assert result.freq is None
+
     def test_dti_constructor_years_only(self, tz_naive_fixture):
         tz = tz_naive_fixture
         # GH 6961

pandas/tests/indexes/timedeltas/test_constructors.py

@@ -227,3 +227,14 @@ def test_constructor_wrong_precision_raises(self):
         msg = r"dtype timedelta64\[us\] cannot be converted to timedelta64\[ns\]"
         with pytest.raises(ValueError, match=msg):
             pd.TimedeltaIndex(["2000"], dtype="timedelta64[us]")
+
+    def test_explicit_none_freq(self):
+        # Explicitly passing freq=None is respected
+        tdi = timedelta_range(1, periods=5)
+        assert tdi.freq is not None
+
+        result = TimedeltaIndex(tdi, freq=None)
+        assert result.freq is None
+
+        result = TimedeltaIndex(tdi._data, freq=None)
+        assert result.freq is None