BUG: Block.iget not wrapping timedelta64/datetime64 (#31666)

Author: jbrockmendel

doc/source/whatsnew/v1.0.1.rst

@@ -24,6 +24,7 @@ Fixed regressions
 - Fixed regression in :meth:`to_datetime` when parsing non-nanosecond resolution datetimes (:issue:`31491`)
 - Fixed regression in :meth:`~DataFrame.to_csv` where specifying an ``na_rep`` might truncate the values written (:issue:`31447`)
 - Fixed regression in :class:`Categorical` construction with ``numpy.str_`` categories (:issue:`31499`)
+- Fixed regression in :meth:`DataFrame.loc` and :meth:`DataFrame.iloc` when selecting a row containing a single ``datetime64`` or ``timedelta64`` column (:issue:`31649`)
 - Fixed regression where setting :attr:`pd.options.display.max_colwidth` was not accepting negative integer. In addition, this behavior has been deprecated in favor of using ``None`` (:issue:`31532`)
 - Fixed regression in objTOJSON.c fix return-type warning (:issue:`31463`)
 - Fixed regression in :meth:`qcut` when passed a nullable integer. (:issue:`31389`)

pandas/core/internals/blocks.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from pandas._libs import NaT, algos as libalgos, lib, tslib, writers
+from pandas._libs import NaT, Timestamp, algos as libalgos, lib, tslib, writers
 from pandas._libs.index import convert_scalar
 import pandas._libs.internals as libinternals
 from pandas._libs.tslibs import Timedelta, conversion
@@ -2158,6 +2158,16 @@ def internal_values(self):
         # Override to return DatetimeArray and TimedeltaArray
         return self.array_values()
 
+    def iget(self, key):
+        # GH#31649 we need to wrap scalars in Timestamp/Timedelta
+        # TODO: this can be removed if we ever have 2D EA
+        result = super().iget(key)
+        if isinstance(result, np.datetime64):
+            result = Timestamp(result)
+        elif isinstance(result, np.timedelta64):
+            result = Timedelta(result)
+        return result
+
 
 class DatetimeBlock(DatetimeLikeBlockMixin, Block):
     __slots__ = ()

pandas/tests/frame/indexing/test_indexing.py

@@ -2165,3 +2165,41 @@ def test_set_reset(self):
 
         df = result.set_index("foo")
         tm.assert_index_equal(df.index, idx)
+
+
+def test_object_casting_indexing_wraps_datetimelike():
+    # GH#31649, check the indexing methods all the way down the stack
+    df = pd.DataFrame(
+        {
+            "A": [1, 2],
+            "B": pd.date_range("2000", periods=2),
+            "C": pd.timedelta_range("1 Day", periods=2),
+        }
+    )
+
+    ser = df.loc[0]
+    assert isinstance(ser.values[1], pd.Timestamp)
+    assert isinstance(ser.values[2], pd.Timedelta)
+
+    ser = df.iloc[0]
+    assert isinstance(ser.values[1], pd.Timestamp)
+    assert isinstance(ser.values[2], pd.Timedelta)
+
+    ser = df.xs(0, axis=0)
+    assert isinstance(ser.values[1], pd.Timestamp)
+    assert isinstance(ser.values[2], pd.Timedelta)
+
+    mgr = df._data
+    arr = mgr.fast_xs(0)
+    assert isinstance(arr[1], pd.Timestamp)
+    assert isinstance(arr[2], pd.Timedelta)
+
+    blk = mgr.blocks[mgr._blknos[1]]
+    assert blk.dtype == "M8[ns]"  # we got the right block
+    val = blk.iget((0, 0))
+    assert isinstance(val, pd.Timestamp)
+
+    blk = mgr.blocks[mgr._blknos[2]]
+    assert blk.dtype == "m8[ns]"  # we got the right block
+    val = blk.iget((0, 0))
+    assert isinstance(val, pd.Timedelta)