BUG: pd.array with non-nano

pandas-dev · Apr 23, 2023 · adea1d3 · adea1d3
1 parent c58fa84
commit adea1d3
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Showing 3 changed files with 36 additions and 37 deletions.
diff --git a/doc/source/whatsnew/v2.1.0.rst b/doc/source/whatsnew/v2.1.0.rst
@@ -323,6 +323,7 @@ Conversion
 - Bug in :meth:`ArrowDtype.numpy_dtype` returning nanosecond units for non-nanosecond ``pyarrow.timestamp`` and ``pyarrow.duration`` types (:issue:`51800`)
 - Bug in :meth:`DataFrame.__repr__` incorrectly raising a ``TypeError`` when the dtype of a column is ``np.record`` (:issue:`48526`)
 - Bug in :meth:`DataFrame.info` raising  ``ValueError`` when ``use_numba`` is set (:issue:`51922`)
+- Bug in :func:`array`  when given a ``datetime64`` or ``timedelta64`` dtype with unit of "s", "us", or "ms" returning :class:`PandasArray` instead of :class:`DatetimeArray` or :class:`TimedeltaArray` (:issue:`??`)
 -
 
 Strings

diff --git a/pandas/core/construction.py b/pandas/core/construction.py
@@ -19,7 +19,11 @@
 from numpy import ma
 
 from pandas._libs import lib
-from pandas._libs.tslibs.period import Period
+from pandas._libs.tslibs import (
+    Period,
+    get_unit_from_dtype,
+    is_supported_unit,
+)
 from pandas._typing import (
     AnyArrayLike,
     ArrayLike,
@@ -28,10 +32,7 @@
     T,
 )
 
-from pandas.core.dtypes.base import (
-    ExtensionDtype,
-    _registry as registry,
-)
+from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.cast import (
     construct_1d_arraylike_from_scalar,
     construct_1d_object_array_from_listlike,
@@ -42,12 +43,10 @@
     maybe_promote,
 )
 from pandas.core.dtypes.common import (
-    is_datetime64_ns_dtype,
     is_dtype_equal,
-    is_extension_array_dtype,
     is_list_like,
     is_object_dtype,
-    is_timedelta64_ns_dtype,
+    pandas_dtype,
 )
 from pandas.core.dtypes.dtypes import PandasDtype
 from pandas.core.dtypes.generic import (
@@ -310,8 +309,8 @@ def array(
     data = extract_array(data, extract_numpy=True)
 
     # this returns None for not-found dtypes.
-    if isinstance(dtype, str):
-        dtype = registry.find(dtype) or dtype
+    if dtype is not None:
+        dtype = pandas_dtype(dtype)
 
     if isinstance(data, ExtensionArray) and (
         dtype is None or is_dtype_equal(dtype, data.dtype)
@@ -321,8 +320,8 @@ def array(
             return data.copy()
         return data
 
-    if is_extension_array_dtype(dtype):
-        cls = cast(ExtensionDtype, dtype).construct_array_type()
+    if isinstance(dtype, ExtensionDtype):
+        cls = dtype.construct_array_type()
         return cls._from_sequence(data, dtype=dtype, copy=copy)
 
     if dtype is None:
@@ -365,12 +364,22 @@ def array(
             return BooleanArray._from_sequence(data, copy=copy)
 
     # Pandas overrides NumPy for
-    #   1. datetime64[ns]
-    #   2. timedelta64[ns]
+    #   1. datetime64[ns,us,ms,s]
+    #   2. timedelta64[ns,us,ms,s]
     # so that a DatetimeArray is returned.
-    if is_datetime64_ns_dtype(dtype):
+    if (
+        lib.is_np_dtype(dtype, "M")
+        # error: Argument 1 to "py_get_unit_from_dtype" has incompatible type
+        # "Optional[dtype[Any]]"; expected "dtype[Any]"
+        and is_supported_unit(get_unit_from_dtype(dtype))  # type: ignore[arg-type]
+    ):
         return DatetimeArray._from_sequence(data, dtype=dtype, copy=copy)
-    elif is_timedelta64_ns_dtype(dtype):
+    if (
+        lib.is_np_dtype(dtype, "m")
+        # error: Argument 1 to "py_get_unit_from_dtype" has incompatible type
+        # "Optional[dtype[Any]]"; expected "dtype[Any]"
+        and is_supported_unit(get_unit_from_dtype(dtype))  # type: ignore[arg-type]
+    ):
         return TimedeltaArray._from_sequence(data, dtype=dtype, copy=copy)
 
     return PandasArray._from_sequence(data, dtype=dtype, copy=copy)

diff --git a/pandas/tests/arrays/test_array.py b/pandas/tests/arrays/test_array.py
@@ -5,8 +5,6 @@
 import pytest
 import pytz
 
-from pandas.core.dtypes.base import _registry as registry
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.api.extensions import register_extension_dtype
@@ -80,6 +78,11 @@
             np.dtype("datetime64[ns]"),
             DatetimeArray._from_sequence(np.array([1, 2], dtype="datetime64[ns]")),
         ),
+        (
+            [1, 2],
+            np.dtype("datetime64[s]"),
+            DatetimeArray._from_sequence(np.array([1, 2], dtype="datetime64[s]")),
+        ),
         (
             np.array([1, 2], dtype="datetime64[ns]"),
             None,
@@ -119,6 +122,11 @@
             np.dtype("timedelta64[ns]"),
             TimedeltaArray._from_sequence(["1H", "2H"]),
         ),
+        (
+            np.array([1, 2], dtype="m8[s]"),
+            np.dtype("timedelta64[s]"),
+            TimedeltaArray._from_sequence(np.array([1, 2], dtype="m8[s]")),
+        ),
         (
             pd.TimedeltaIndex(["1H", "2H"]),
             None,
@@ -404,25 +412,6 @@ def test_array_unboxes(index_or_series):
     tm.assert_equal(result, expected)
 
 
-@pytest.fixture
-def registry_without_decimal():
-    """Fixture yielding 'registry' with no DecimalDtype entries"""
-    idx = registry.dtypes.index(DecimalDtype)
-    registry.dtypes.pop(idx)
-    yield
-    registry.dtypes.append(DecimalDtype)
-
-
-def test_array_not_registered(registry_without_decimal):
-    # check we aren't on it
-    assert registry.find("decimal") is None
-    data = [decimal.Decimal("1"), decimal.Decimal("2")]
-
-    result = pd.array(data, dtype=DecimalDtype)
-    expected = DecimalArray._from_sequence(data)
-    tm.assert_equal(result, expected)
-
-
 def test_array_to_numpy_na():
     # GH#40638
     arr = pd.array([pd.NA, 1], dtype="string")