diff --git a/tests/pdarrayclass_test.py b/tests/pdarrayclass_test.py
index 76351b17bc..bc04445df5 100644
--- a/tests/pdarrayclass_test.py
+++ b/tests/pdarrayclass_test.py
@@ -23,35 +23,40 @@
 class TestPdarrayClass:
 
     @pytest.mark.skip_if_max_rank_less_than(2)
-    def test_reshape(self):
-        a = ak.arange(4)
+    @pytest.mark.parametrize("dtype", DTYPES)
+    def test_reshape(self, dtype):
+        a = ak.arange(4, dtype=dtype)
         r = a.reshape((2, 2))
         assert r.shape == (2, 2)
         assert isinstance(r, ak.pdarray)
 
-    def test_shape(self):
-        a = ak.arange(4)
-        np_a = np.arange(4)
+    @pytest.mark.parametrize("dtype", list(set(DTYPES) - set(["bool"])))
+    def test_shape(self, dtype):
+        a = ak.arange(4, dtype=dtype)
+        np_a = np.arange(4, dtype=dtype)
         assert isinstance(a.shape, tuple)
         assert a.shape == np_a.shape
 
     @pytest.mark.skip_if_max_rank_less_than(2)
-    def test_shape_multidim(self):
-        a = ak.arange(4).reshape((2, 2))
-        np_a = np.arange(4).reshape((2, 2))
+    @pytest.mark.parametrize("dtype", list(set(DTYPES) - set(["bool"])))
+    def test_shape_multidim(self, dtype):
+        a = ak.arange(4, dtype=dtype).reshape((2, 2))
+        np_a = np.arange(4, dtype=dtype).reshape((2, 2))
         assert isinstance(a.shape, tuple)
         assert a.shape == np_a.shape
 
     @pytest.mark.parametrize("size", pytest.prob_size)
-    def test_flatten(self, size):
-        a = ak.arange(size)
+    @pytest.mark.parametrize("dtype", DTYPES)
+    def test_flatten(self, size, dtype):
+        a = ak.arange(size, dtype=dtype)
         ak_assert_equal(a.flatten(), a)
 
     @pytest.mark.skip_if_max_rank_less_than(3)
+    @pytest.mark.parametrize("dtype", DTYPES)
     @pytest.mark.parametrize("size", pytest.prob_size)
-    def test_flatten(self, size):
+    def test_flatten_multidim(self, size, dtype):
         size = size - (size % 4)
-        a = ak.arange(size)
+        a = ak.arange(size, dtype=dtype)
         b = a.reshape((2, 2, size / 4))
         ak_assert_equal(b.flatten(), a)
 
@@ -114,12 +119,13 @@ def test_is_locally_sorted_multi_locale(self, size):
         assert not is_sorted(a)
 
     @pytest.mark.skip_if_max_rank_less_than(3)
+    @pytest.mark.skip_if_nl_greater_than(2)
     @pytest.mark.parametrize("dtype", DTYPES)
     @pytest.mark.parametrize("axis", [None, 0, 1, (0, 2), (0, 1, 2)])
     def test_is_locally_sorted_multidim(self, dtype, axis):
         from arkouda.pdarrayclass import is_locally_sorted
 
-        a = ak.array(ak.randint(0, 100, (5, 7, 4), dtype=ak.int64, seed=SEED))
+        a = ak.array(ak.randint(0, 100, (10, 10, 10), dtype=ak.int64, seed=SEED))
         sorted = is_locally_sorted(a, axis=axis)
         if isinstance(sorted, np.bool_):
             assert not sorted