CI: Fix expected for 32-bit platform (#34135)

Closes #34130

Author: TomAugspurger

pandas/tests/test_algos.py

@@ -331,25 +331,25 @@ def test_factorize_na_sentinel(self, sort, na_sentinel, data, uniques):
             (
                 ["a", None, "b", "a"],
                 True,
-                np.array([0, -1, 1, 0], dtype=np.int64),
+                np.array([0, -1, 1, 0], dtype=np.dtype("intp")),
                 np.array(["a", "b"], dtype=object),
             ),
             (
                 ["a", np.nan, "b", "a"],
                 True,
-                np.array([0, -1, 1, 0], dtype=np.int64),
+                np.array([0, -1, 1, 0], dtype=np.dtype("intp")),
                 np.array(["a", "b"], dtype=object),
             ),
             (
                 ["a", None, "b", "a"],
                 False,
-                np.array([0, 2, 1, 0], dtype=np.int64),
+                np.array([0, 2, 1, 0], dtype=np.dtype("intp")),
                 np.array(["a", "b", np.nan], dtype=object),
             ),
             (
                 ["a", np.nan, "b", "a"],
                 False,
-                np.array([0, 2, 1, 0], dtype=np.int64),
+                np.array([0, 2, 1, 0], dtype=np.dtype("intp")),
                 np.array(["a", "b", np.nan], dtype=object),
             ),
         ],
@@ -368,25 +368,25 @@ def test_object_factorize_dropna(
             (
                 [1, None, 1, 2],
                 True,
-                np.array([0, -1, 0, 1], dtype=np.int64),
+                np.array([0, -1, 0, 1], dtype=np.dtype("intp")),
                 np.array([1, 2], dtype="O"),
             ),
             (
                 [1, np.nan, 1, 2],
                 True,
-                np.array([0, -1, 0, 1], dtype=np.int64),
+                np.array([0, -1, 0, 1], dtype=np.dtype("intp")),
                 np.array([1, 2], dtype=np.float64),
             ),
             (
                 [1, None, 1, 2],
                 False,
-                np.array([0, 2, 0, 1], dtype=np.int64),
+                np.array([0, 2, 0, 1], dtype=np.dtype("intp")),
                 np.array([1, 2, np.nan], dtype="O"),
             ),
             (
                 [1, np.nan, 1, 2],
                 False,
-                np.array([0, 2, 0, 1], dtype=np.int64),
+                np.array([0, 2, 0, 1], dtype=np.dtype("intp")),
                 np.array([1, 2, np.nan], dtype=np.float64),
             ),
         ],