REGR: resampling DataFrame with DateTimeIndex with empty groups and uint8, uint16 or uint32 columns incorrectly raising RuntimeError

doc/source/whatsnew/v1.3.5.rst

@@ -16,6 +16,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :meth:`Series.equals` when comparing floats with dtype object to None (:issue:`44190`)
 - Fixed regression in :func:`merge_asof` raising error when array was supplied as join key (:issue:`42844`)
+- Fixed regression when resampling :class:`DataFrame` with :class:`DateTimeIndex` with empty groups and ``uint8``, ``uint16`` or ``uint32`` columns incorrectly raising ``RuntimeError`` (:issue:`43329`)
 - Fixed regression in creating a :class:`DataFrame` from a timezone-aware :class:`Timestamp` scalar near a Daylight Savings Time transition (:issue:`42505`)
 - Fixed performance regression in :func:`read_csv` (:issue:`44106`)
 - Fixed regression in :meth:`Series.duplicated` and :meth:`Series.drop_duplicates` when Series has :class:`Categorical` dtype with boolean categories (:issue:`44351`)

pandas/core/groupby/ops.py

@@ -500,9 +500,10 @@ def _call_cython_op(
         elif is_bool_dtype(dtype):
             values = values.astype("int64")
         elif is_integer_dtype(dtype):
-            # e.g. uint8 -> uint64, int16 -> int64
-            dtype_str = dtype.kind + "8"
-            values = values.astype(dtype_str, copy=False)
+            # GH#43329 If the dtype is explicitly of type uint64 the type is not
+            # changed to prevent overflow.
+            if dtype != np.uint64:
+                values = values.astype(np.int64, copy=False)
         elif is_numeric:
             if not is_complex_dtype(dtype):
                 values = ensure_float64(values)

pandas/tests/resample/test_datetime_index.py

@@ -1828,3 +1828,27 @@ def test_resample_aggregate_functions_min_count(func):
         index=DatetimeIndex(["2020-03-31"], dtype="datetime64[ns]", freq="Q-DEC"),
     )
     tm.assert_series_equal(result, expected)
+
+
+def test_resample_unsigned_int(any_unsigned_int_numpy_dtype):
+    # gh-43329
+    df = DataFrame(
+        index=date_range(start="2000-01-01", end="2000-01-03 23", freq="12H"),
+        columns=["x"],
+        data=[0, 1, 0] * 2,
+        dtype=any_unsigned_int_numpy_dtype,
+    )
+    df = df.loc[(df.index < "2000-01-02") | (df.index > "2000-01-03"), :]
+
+    if any_unsigned_int_numpy_dtype == "uint64":
+        with pytest.raises(RuntimeError, match="empty group with uint64_t"):
+            result = df.resample("D").max()
+    else:
+        result = df.resample("D").max()
+
+        expected = DataFrame(
+            [1, np.nan, 0],
+            columns=["x"],
+            index=date_range(start="2000-01-01", end="2000-01-03 23", freq="D"),
+        )
+        tm.assert_frame_equal(result, expected)