Fix graph_objects ignoring the mask of numpy masked arrays

CHANGELOG.md

@@ -24,6 +24,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 - Fix `mpl_to_plotly` conversion of matplotlib contour lines and line collections: close contour rings ending with `Z` codes, support dash styles, convert date x-axes, separate disjoint subpaths with `None` separators, hide line collection traces from the legend by default, and group consecutive same-style lines into single traces [[#5770](https://github.com/plotly/plotly.py/pull/5770)], with thanks to @robertoffmoura for the contribution!
 - Fix `plotly.io.write_images` ignoring `layout.width`/`layout.height` (and the template's) and exporting every figure at the default 700x500 size; it now uses the same width/height priority as `write_image` and `to_image` [[#5784](https://github.com/plotly/plotly.py/pull/5784)], with thanks to @breken-ai for the contribution!
 - Fix color utilities mutating the list of colors passed to them [[#5836](https://github.com/plotly/plotly.py/pull/5836)], with thanks to @Enesuygurs for the contribution!
+- Fix `graph_objects` ignoring the mask of numpy masked arrays passed to data array properties such as `x` and `y` [[#5861](https://github.com/plotly/plotly.py/pull/5861)], with thanks to @LiShuochen for the contribution!
 
 
 ## [7.1.0] - 2026-09-15

_plotly_utils/basevalidators.py

@@ -417,6 +417,17 @@ def validate_coerce(self, v):
         if is_none_or_typed_array_spec(v):
             pass
         elif is_homogeneous_array(v):
+            ma = get_module("numpy.ma", should_load=False)
+            if ma and ma.isMaskedArray(v) and v.dtype.kind in "biufU" and v.mask.any():
+                np = get_module("numpy")
+                # Replace masked values with NaN (numeric arrays) or None (boolean
+                # and string arrays) so that they are treated as missing values
+                if v.dtype.kind in "iu":
+                    v = v.astype("float64")
+                if v.dtype.kind == "f":
+                    v = v.filled(np.nan)
+                else:
+                    v = np.where(v.mask, None, v.data.astype("object"))
             v = copy_to_readonly_numpy_array(v)
         elif is_simple_array(v):
             v = to_scalar_or_list(v)

tests/test_plotly_utils/validators/test_dataarray_validator.py

@@ -42,6 +42,37 @@ def test_validator_acceptance_homogeneous(val, validator):
     assert np.array_equal(validator.present(coerce_val), val)
 
 
+@pytest.mark.parametrize(
+    "val,expected",
+    [
+        (np.ma.array([1, 2, 3], mask=[0, 1, 0]), np.array([1, np.nan, 3])),
+        (
+            np.ma.array([1, 2, 3], mask=[0, 1, 0], dtype="float32"),
+            np.array([1, np.nan, 3], dtype="float32"),
+        ),
+        (np.ma.array([1, 2, 3], mask=True), np.array([np.nan, np.nan, np.nan])),
+        (np.ma.array([1, 2, 3], mask=False), np.array([1, 2, 3])),
+        (
+            np.ma.array([[1, 2], [3, 4]], mask=[[0, 1], [0, 0]]),
+            np.array([[1, np.nan], [3, 4]]),
+        ),
+        (
+            np.ma.array(["a", "b", "c"], mask=[0, 1, 0]),
+            np.array(["a", None, "c"], dtype="object"),
+        ),
+        (
+            np.ma.array([True, False, True], mask=[0, 1, 0]),
+            np.array([True, None, True], dtype="object"),
+        ),
+    ],
+)
+def test_validator_acceptance_masked(val, expected, validator):
+    coerce_val = validator.validate_coerce(val)
+    assert not np.ma.isMaskedArray(coerce_val)
+    assert coerce_val.dtype == expected.dtype
+    np.testing.assert_array_equal(coerce_val, expected)
+
+
 # Rejection
 @pytest.mark.parametrize("val", ["Hello", 23, set(), {}])
 def test_rejection(val, validator):