BUG: respect freq=None in DTA constructor (#47296)

* BUG: respect freq=None in DTA constructor

* GH ref

* mypy fixu[

Author: jbrockmendel

doc/source/whatsnew/v1.5.0.rst

@@ -737,6 +737,7 @@ Datetimelike
 - Bug in :meth:`DatetimeIndex.tz_localize` localizing to UTC failing to make a copy of the underlying data (:issue:`46460`)
 - Bug in :meth:`DatetimeIndex.resolution` incorrectly returning "day" instead of "nanosecond" for nanosecond-resolution indexes (:issue:`46903`)
 - Bug in :class:`Timestamp` with an integer or float value and ``unit="Y"`` or ``unit="M"`` giving slightly-wrong results (:issue:`47266`)
+- Bug in :class:`DatetimeArray` construction when passed another :class:`DatetimeArray` and ``freq=None`` incorrectly inferring the freq from the given array (:issue:`47296`)
 -
 
 Timedelta

pandas/core/arrays/datetimes.py

@@ -9,6 +9,7 @@
 from typing import (
     TYPE_CHECKING,
     Literal,
+    cast,
 )
 import warnings
 
@@ -256,15 +257,26 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
     _freq = None
 
     def __init__(
-        self, values, dtype=DT64NS_DTYPE, freq=None, copy: bool = False
+        self, values, dtype=DT64NS_DTYPE, freq=lib.no_default, copy: bool = False
     ) -> None:
         values = extract_array(values, extract_numpy=True)
         if isinstance(values, IntegerArray):
             values = values.to_numpy("int64", na_value=iNaT)
 
         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 explicit_none:
+                # don't inherit from values
+                pass
+            elif freq is None:
+                freq = values.freq
+            elif freq and values.freq:
+                freq = to_offset(freq)
+                freq, _ = dtl.validate_inferred_freq(freq, values.freq, False)
+
             # validation
             dtz = getattr(dtype, "tz", None)
             if dtz and values.tz is None:
@@ -279,14 +291,13 @@ def __init__(
             elif values.tz:
                 dtype = values.dtype
 
-            if freq is None:
-                freq = values.freq
             values = values._ndarray
 
         if not isinstance(values, np.ndarray):
             raise ValueError(
-                f"Unexpected type '{type(values).__name__}'. 'values' must be "
-                "a DatetimeArray, ndarray, or Series or Index containing one of those."
+                f"Unexpected type '{type(values).__name__}'. 'values' must be a "
+                f"{type(self).__name__}, ndarray, or Series or Index "
+                "containing one of those."
             )
         if values.ndim not in [1, 2]:
             raise ValueError("Only 1-dimensional input arrays are supported.")
@@ -297,31 +308,19 @@ def __init__(
             #  nanosecond UTC (or tz-naive) unix timestamps
             values = values.view(DT64NS_DTYPE)
 
-        if values.dtype != DT64NS_DTYPE:
-            raise ValueError(
-                "The dtype of 'values' is incorrect. Must be 'datetime64[ns]'. "
-                f"Got {values.dtype} instead."
-            )
-
+        _validate_dt64_dtype(values.dtype)
         dtype = _validate_dt64_dtype(dtype)
 
         if freq == "infer":
             raise ValueError(
-                "Frequency inference not allowed in DatetimeArray.__init__. "
+                f"Frequency inference not allowed in {type(self).__name__}.__init__. "
                 "Use 'pd.array()' instead."
             )
 
         if copy:
             values = values.copy()
         if freq:
             freq = to_offset(freq)
-        if getattr(dtype, "tz", None):
-            # https://github.com/pandas-dev/pandas/issues/18595
-            # Ensure that we have a standard timezone for pytz objects.
-            # Without this, things like adding an array of timedeltas and
-            # a  tz-aware Timestamp (with a tz specific to its datetime) will
-            # be incorrect(ish?) for the array as a whole
-            dtype = DatetimeTZDtype(tz=timezones.tz_standardize(dtype.tz))
 
         NDArrayBacked.__init__(self, values=values, dtype=dtype)
         self._freq = freq
@@ -2394,6 +2393,16 @@ def _validate_dt64_dtype(dtype):
                 f"Unexpected value for 'dtype': '{dtype}'. "
                 "Must be 'datetime64[ns]' or DatetimeTZDtype'."
             )
+
+        if getattr(dtype, "tz", None):
+            # https://github.com/pandas-dev/pandas/issues/18595
+            # Ensure that we have a standard timezone for pytz objects.
+            # Without this, things like adding an array of timedeltas and
+            # a  tz-aware Timestamp (with a tz specific to its datetime) will
+            # be incorrect(ish?) for the array as a whole
+            dtype = cast(DatetimeTZDtype, dtype)
+            dtype = DatetimeTZDtype(tz=timezones.tz_standardize(dtype.tz))
+
     return dtype
 
 

pandas/core/arrays/timedeltas.py

@@ -186,21 +186,22 @@ def __init__(
 
         if isinstance(values, type(self)):
             if explicit_none:
-                # dont inherit from values
+                # don't inherit from values
                 pass
             elif freq is None:
                 freq = values.freq
             elif freq and values.freq:
                 freq = to_offset(freq)
                 freq, _ = dtl.validate_inferred_freq(freq, values.freq, False)
+
             values = values._ndarray
 
         if not isinstance(values, np.ndarray):
-            msg = (
+            raise ValueError(
                 f"Unexpected type '{type(values).__name__}'. 'values' must be a "
-                "TimedeltaArray, ndarray, or Series or Index containing one of those."
+                f"{type(self).__name__}, ndarray, or Series or Index "
+                "containing one of those."
             )
-            raise ValueError(msg)
         if values.ndim not in [1, 2]:
             raise ValueError("Only 1-dimensional input arrays are supported.")
 
@@ -214,11 +215,10 @@ def __init__(
         dtype = _validate_td64_dtype(dtype)
 
         if freq == "infer":
-            msg = (
-                "Frequency inference not allowed in TimedeltaArray.__init__. "
+            raise ValueError(
+                f"Frequency inference not allowed in {type(self).__name__}.__init__. "
                 "Use 'pd.array()' instead."
             )
-            raise ValueError(msg)
 
         if copy:
             values = values.copy()

pandas/tests/arrays/datetimes/test_constructors.py

@@ -87,9 +87,8 @@ def test_non_array_raises(self):
     def test_bool_dtype_raises(self):
         arr = np.array([1, 2, 3], dtype="bool")
 
-        with pytest.raises(
-            ValueError, match="The dtype of 'values' is incorrect.*bool"
-        ):
+        msg = "Unexpected value for 'dtype': 'bool'. Must be"
+        with pytest.raises(ValueError, match=msg):
             DatetimeArray(arr)
 
         msg = r"dtype bool cannot be converted to datetime64\[ns\]"

pandas/tests/indexes/datetimes/test_constructors.py

@@ -925,6 +925,9 @@ def test_explicit_none_freq(self):
         result = DatetimeIndex(rng._data, freq=None)
         assert result.freq is None
 
+        dta = DatetimeArray(rng, freq=None)
+        assert dta.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

@@ -263,6 +263,9 @@ def test_explicit_none_freq(self):
         result = TimedeltaIndex(tdi._data, freq=None)
         assert result.freq is None
 
+        tda = TimedeltaArray(tdi, freq=None)
+        assert tda.freq is None
+
     def test_from_categorical(self):
         tdi = timedelta_range(1, periods=5)