diff --git a/tests/test_regrid/test_reduce.py b/tests/test_regrid/test_reduce.py
index 058e04a46..7d81f7547 100644
--- a/tests/test_regrid/test_reduce.py
+++ b/tests/test_regrid/test_reduce.py
@@ -12,10 +12,8 @@ def forward_args():
 
 
 def reverse_args():
-    values = np.flip(np.array([0.0, 1.0, 2.0, np.nan]))
-    weights = np.array([0.5, 0.5, 0.5, 0.5])
-    work = np.empty_like(weights)
-    return values, weights, work
+    values, weights, work = forward_args()
+    return np.flip(values), weights, work
 
 
 @pytest.mark.parametrize("args", [forward_args(), reverse_args()])
diff --git a/xugrid/regrid/nanpercentile.py b/xugrid/regrid/nanpercentile.py
index 07a0ced4c..1163c3612 100644
--- a/xugrid/regrid/nanpercentile.py
+++ b/xugrid/regrid/nanpercentile.py
@@ -1,5 +1,5 @@
 """
-Numba percentile methods allocate continuosly on the heap.
+Numba percentile methods allocate continuously on the heap.
 
 This has significant overhead when calling the reduction method millions of
 times -- as happens when regridding.
diff --git a/xugrid/regrid/regridder.py b/xugrid/regrid/regridder.py
index 9b06ee735..bb587ec30 100644
--- a/xugrid/regrid/regridder.py
+++ b/xugrid/regrid/regridder.py
@@ -467,10 +467,16 @@ class OverlapRegridder(BaseOverlapRegridder):
 
     Examples
     --------
+    Create an OverlapRegridder to regrid with mean:
+
+    >>> regridder = OverlapRegridder(source_grid, target_grid, method="mean")
+    >>> regridder.regrid(source_data)
+
     Setup a custom percentile method and apply it:
 
     >>> p33_3 = OverlapRegridder.create_percentile_method(33.3)
-    >>> regridder = OverlapRegridder(source, target, method=p33_3)
+    >>> regridder = OverlapRegridder(source_grid, target_grid, method=p33_3)
+    >>> regridder.regrid(source_data)
     """
 
     _JIT_FUNCTIONS = {