maybe_upcast_putmask: require other to be a scalar

pandas/core/dtypes/cast.py

@@ -232,7 +232,7 @@ def trans(x):
     return result
 
 
-def maybe_upcast_putmask(result, mask, other):
+def maybe_upcast_putmask(result: np.ndarray, mask: np.ndarray, other):
     """
     A safe version of putmask that potentially upcasts the result.
     The result is replaced with the first N elements of other,
@@ -245,8 +245,8 @@ def maybe_upcast_putmask(result, mask, other):
         The destination array. This will be mutated in-place if no upcasting is
         necessary.
     mask : boolean ndarray
-    other : ndarray or scalar
-        The source array or value
+    other : scalar
+        The source value
 
     Returns
     -------
@@ -264,6 +264,10 @@ def maybe_upcast_putmask(result, mask, other):
 
     if not isinstance(result, np.ndarray):
         raise ValueError("The result input must be a ndarray.")
+    if not is_scalar(other):
+        # We _could_ support non-scalar other, but until we have a compelling
+        #  use case, we assume away the possibility.
+        raise ValueError("other must be a scalar")
 
     if mask.any():
         # Two conversions for date-like dtypes that can't be done automatically

pandas/core/nanops.py

@@ -273,6 +273,12 @@ def _get_values(
     fill_value : Any
         fill value used
     """
+
+    # In _get_values is only called from within nanops, and in all cases
+    #  with scalar fill_value.  This guarantee is important for the
+    #  maybe_upcast_putmask call below
+    assert is_scalar(fill_value)
+
     mask = _maybe_get_mask(values, skipna, mask)
 
     if is_datetime64tz_dtype(values):

pandas/tests/dtypes/cast/test_upcast.py

@@ -9,84 +9,63 @@
 
 @pytest.mark.parametrize("result", [Series([10, 11, 12]), [10, 11, 12], (10, 11, 12)])
 def test_upcast_error(result):
-    # GH23823
+    # GH23823 require result arg to be ndarray
     mask = np.array([False, True, False])
     other = np.array([61, 62, 63])
     with pytest.raises(ValueError):
         result, _ = maybe_upcast_putmask(result, mask, other)
 
 
 @pytest.mark.parametrize(
-    "arr, other, exp_changed, expected",
+    "arr, other",
     [
-        (np.arange(1, 6), np.array([61, 62, 63]), False, np.array([1, 61, 3, 62, 63])),
+        (np.arange(1, 6), np.array([61, 62, 63])),
+        (np.arange(1, 6), np.array([61.1, 62.2, 63.3])),
+        (np.arange(10, 15), np.array([61, 62])),
+        (np.arange(10, 15), np.array([61, np.nan])),
         (
-            np.arange(1, 6),
-            np.array([61.1, 62.2, 63.3]),
-            True,
-            np.array([1, 61.1, 3, 62.2, 63.3]),
+            np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]"),
+            np.arange("2018-01-01", "2018-01-04", dtype="datetime64[D]"),
         ),
-        (np.arange(1, 6), np.nan, True, np.array([1, np.nan, 3, np.nan, np.nan])),
-        (np.arange(10, 15), np.array([61, 62]), False, np.array([10, 61, 12, 62, 61])),
         (
-            np.arange(10, 15),
-            np.array([61, np.nan]),
-            True,
-            np.array([10, 61, 12, np.nan, 61]),
+            np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]"),
+            np.arange("2018-01-01", "2018-01-03", dtype="datetime64[D]"),
         ),
     ],
 )
-def test_upcast(arr, other, exp_changed, expected):
+def test_upcast_scalar_other(arr, other):
+    # for now we do not support non-scalar `other`
+    mask = np.array([False, True, False, True, True])
+    with pytest.raises(ValueError, match="other must be a scalar"):
+        maybe_upcast_putmask(arr, mask, other)
+
+
+def test_upcast():
     # GH23823
+    arr = np.arange(1, 6)
     mask = np.array([False, True, False, True, True])
-    result, changed = maybe_upcast_putmask(arr, mask, other)
+    result, changed = maybe_upcast_putmask(arr, mask, other=np.nan)
 
-    assert changed == exp_changed
+    expected = np.array([1, np.nan, 3, np.nan, np.nan])
+    assert changed
     tm.assert_numpy_array_equal(result, expected)
 
 
-@pytest.mark.parametrize(
-    "arr, other, exp_changed, expected",
-    [
-        (
-            np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]"),
-            np.arange("2018-01-01", "2018-01-04", dtype="datetime64[D]"),
-            False,
-            np.array(
-                ["2019-01-01", "2018-01-01", "2019-01-03", "2018-01-02", "2018-01-03"],
-                dtype="datetime64[D]",
-            ),
-        ),
-        (
-            np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]"),
-            np.nan,
-            False,
-            np.array(
-                [
-                    "2019-01-01",
-                    np.datetime64("NaT"),
-                    "2019-01-03",
-                    np.datetime64("NaT"),
-                    np.datetime64("NaT"),
-                ],
-                dtype="datetime64[D]",
-            ),
-        ),
-        (
-            np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]"),
-            np.arange("2018-01-01", "2018-01-03", dtype="datetime64[D]"),
-            False,
-            np.array(
-                ["2019-01-01", "2018-01-01", "2019-01-03", "2018-01-02", "2018-01-01"],
-                dtype="datetime64[D]",
-            ),
-        ),
-    ],
-)
-def test_upcast_datetime(arr, other, exp_changed, expected):
+def test_upcast_datetime():
     # GH23823
+    arr = np.arange("2019-01-01", "2019-01-06", dtype="datetime64[D]")
     mask = np.array([False, True, False, True, True])
-    result, changed = maybe_upcast_putmask(arr, mask, other)
+    result, changed = maybe_upcast_putmask(arr, mask, other=np.nan)
 
-    assert changed == exp_changed
+    expected = np.array(
+        [
+            "2019-01-01",
+            np.datetime64("NaT"),
+            "2019-01-03",
+            np.datetime64("NaT"),
+            np.datetime64("NaT"),
+        ],
+        dtype="datetime64[D]",
+    )
+    assert not changed
     tm.assert_numpy_array_equal(result, expected)