BUG: constructors (pandas-dev#49875)

Author: jbrockmendel

doc/source/whatsnew/v2.0.0.rst

@@ -624,6 +624,8 @@ Categorical
 ^^^^^^^^^^^
 - Bug in :meth:`Categorical.set_categories` losing dtype information (:issue:`48812`)
 - Bug in :meth:`DataFrame.groupby` and :meth:`Series.groupby` would reorder categories when used as a grouper (:issue:`48749`)
+- Bug in :class:`Categorical` constructor when constructing from a :class:`Categorical` object and ``dtype="category"`` losing ordered-ness (:issue:`49309`)
+-
 
 Datetimelike
 ^^^^^^^^^^^^
@@ -752,6 +754,8 @@ Reshaping
 - Bug in :meth:`DataFrame.pivot_table` raising ``ValueError`` with parameter ``margins=True`` when result is an empty :class:`DataFrame` (:issue:`49240`)
 - Clarified error message in :func:`merge` when passing invalid ``validate`` option (:issue:`49417`)
 - Bug in :meth:`DataFrame.explode` raising ``ValueError`` on multiple columns with ``NaN`` values or empty lists (:issue:`46084`)
+- Bug in :meth:`DataFrame.transpose` with ``IntervalDtype`` column with ``timedelta64[ns]`` endpoints (:issue:`44917`)
+-
 
 Sparse
 ^^^^^^

pandas/core/arrays/datetimes.py

@@ -2059,6 +2059,7 @@ def _sequence_to_dt64ns(
             new_unit = npy_unit_to_abbrev(new_reso)
             new_dtype = np.dtype(f"M8[{new_unit}]")
             data = astype_overflowsafe(data, dtype=new_dtype, copy=False)
+            data_unit = get_unit_from_dtype(new_dtype)
             copy = False
 
         if data.dtype.byteorder == ">":

pandas/core/dtypes/dtypes.py

@@ -278,6 +278,10 @@ def _from_values_or_dtype(
             # The dtype argument takes precedence over values.dtype (if any)
             if isinstance(dtype, str):
                 if dtype == "category":
+                    if ordered is None and cls.is_dtype(values):
+                        # GH#49309 preserve orderedness
+                        ordered = values.dtype.ordered
+
                     dtype = CategoricalDtype(categories, ordered)
                 else:
                     raise ValueError(f"Unknown dtype {repr(dtype)}")

pandas/tests/arrays/categorical/test_constructors.py

@@ -33,6 +33,13 @@
 
 
 class TestCategoricalConstructors:
+    def test_categorical_from_cat_and_dtype_str_preserve_ordered(self):
+        # GH#49309 we should preserve orderedness in `res`
+        cat = Categorical([3, 1], categories=[3, 2, 1], ordered=True)
+
+        res = Categorical(cat, dtype="category")
+        assert res.dtype.ordered
+
     def test_categorical_disallows_scalar(self):
         # GH#38433
         with pytest.raises(TypeError, match="Categorical input must be list-like"):

pandas/tests/frame/methods/test_transpose.py

@@ -6,12 +6,25 @@
 from pandas import (
     DataFrame,
     DatetimeIndex,
+    IntervalIndex,
     date_range,
+    timedelta_range,
 )
 import pandas._testing as tm
 
 
 class TestTranspose:
+    def test_transpose_td64_intervals(self):
+        # GH#44917
+        tdi = timedelta_range("0 Days", "3 Days")
+        ii = IntervalIndex.from_breaks(tdi)
+        ii = ii.insert(-1, np.nan)
+        df = DataFrame(ii)
+
+        result = df.T
+        expected = DataFrame({i: ii[i : i + 1] for i in range(len(ii))})
+        tm.assert_frame_equal(result, expected)
+
     def test_transpose_empty_preserves_datetimeindex(self):
         # GH#41382
         df = DataFrame(index=DatetimeIndex([]))

pandas/tests/indexes/datetimes/test_constructors.py

@@ -37,6 +37,14 @@
 
 
 class TestDatetimeIndex:
+    def test_from_dt64_unsupported_unit(self):
+        # GH#49292
+        val = np.datetime64(1, "D")
+        result = DatetimeIndex([val], tz="US/Pacific")
+
+        expected = DatetimeIndex([val.astype("M8[s]")], tz="US/Pacific")
+        tm.assert_index_equal(result, expected)
+
     def test_explicit_tz_none(self):
         # GH#48659
         dti = date_range("2016-01-01", periods=10, tz="UTC")

pandas/tests/series/test_constructors.py

@@ -53,6 +53,12 @@
 
 
 class TestSeriesConstructors:
+    def test_from_na_value_and_interval_of_datetime_dtype(self):
+        # GH#41805
+        ser = Series([None], dtype="interval[datetime64[ns]]")
+        assert ser.isna().all()
+        assert ser.dtype == "interval[datetime64[ns], right]"
+
     def test_infer_with_date_and_datetime(self):
         # GH#49341 pre-2.0 we inferred datetime-and-date to datetime64, which
         #  was inconsistent with Index behavior