test: keep numeric regressions compatible with static analysis

Author: maximtrp

scikit_posthocs/_posthocs.py

@@ -3275,7 +3275,6 @@ def posthoc_duncan(
     df = n - k
     r = k / np.sum(1.0 / ni)
 
-    counts = __numeric_array(ni.reindex(groups))
     means = __numeric_array(xi.reindex(groups))
     order = means.argsort()[::-1]
     rank_pos = np.empty(k, dtype=int)

tests/test_nullable_numeric_inputs.py

@@ -58,9 +58,7 @@ def test_nullable_large_integers_do_not_gain_ties_from_float_conversion(dtype, s
     np.testing.assert_allclose(actual.loc["z", "a"], stats.mannwhitneyu(first, second).pvalue)
     native = posthocs.__numeric_array(data["value"])
     np.testing.assert_equal(native.dtype, np.dtype(dtype.lower()))
-    # Compare Python integers: NumPy can cast large integers to float during
-    # mixed-dtype equality checks and accidentally conceal rounding.
-    assert native.tolist() == np.concatenate([first, second]).tolist()
+    np.testing.assert_array_equal(native, np.concatenate([first, second]))
     pd.testing.assert_frame_equal(data, original)