Fixing for OR operations

Author: Tarun2605

pandas/core/ops/array_ops.py

@@ -462,25 +462,36 @@ def alignOutputWithKleene(left, right, op):
         result = np.zeros_like(res_values, dtype=bool)  # all False, bool dtype
         return result
 
-    if op.__name__ in {"and_", "rand_"}:
+    elif op.__name__ in {"and_", "rand_"}:
         res_values[:] = lvalues & rvalues
-        mask[:] = (
-            (left_mask & rvalues) | (right_mask & lvalues) | (left_mask & right_mask)
-        )
+        mask[:] = False
+
+        # Case 1: True & NA → NA
+        mask[lvalues & right_mask] = True
+        mask[rvalues & left_mask] = True
+
+        # Case 2: False & NA → False (keep False, no NA)
+        # Case 3: NA & NA → NA
+        mask[left_mask & right_mask] = True
 
     # --- OR logic ---
     elif op.__name__ in {"or_", "ror_"}:
         res_values[:] = lvalues | rvalues
-        # Unknown only if both sides are NA
-        mask[:] = left_mask & right_mask
 
-        # Handle cases where NA OR False → False, NA OR True → True
-        # Pandas convention: np.nan | False -> False, np.nan | True -> True
-        res_values[left_mask & ~rvalues] = False
-        res_values[right_mask & ~lvalues] = False
+        # Start fresh mask
+        mask[:] = False
+
+        # Case 1: NA | True → True (keep, no NA)
         res_values[left_mask & rvalues] = True
         res_values[right_mask & lvalues] = True
 
+        # Case 2: NA | False → NA
+        mask[left_mask & ~rvalues] = True
+        mask[right_mask & ~lvalues] = True
+
+        # Case 3: NA | NA → NA
+        mask[left_mask & right_mask] = True
+
     # --- XOR logic ---
     elif op.__name__ in {"xor", "rxor"}:
         res_values[:] = lvalues ^ rvalues

pandas/tests/series/test_logical_ops.py

@@ -46,7 +46,8 @@ def test_logical_operators_bool_dtype_with_empty(self):
         tm.assert_series_equal(res, expected)
 
         res = s_tft | s_empty
-        expected = s_tft.sort_index()
+        # changed the test case output to align with kleene principle
+        expected = Series([True, np.nan, True], index=index).sort_index()
         tm.assert_series_equal(res, expected)
 
     def test_logical_operators_int_dtype_with_int_dtype(self):
@@ -389,7 +390,7 @@ def test_logical_ops_label_based(self, using_infer_string):
         tm.assert_series_equal(result, expected)
 
         result = a | empty
-        expected = Series([True, True, False], list("abc"))
+        expected = Series([True, True, np.nan], list("abc"))
         tm.assert_series_equal(result, expected)
 
         # vs non-matching
@@ -469,10 +470,10 @@ def test_logical_ops_df_compat(self):
         tm.assert_series_equal(s2 & s1, exp)
 
         # True | np.nan => True
-        exp_or1 = Series([True, True, True, False], index=list("ABCD"), name="x")
+        exp_or1 = Series([True, True, True, np.nan], index=list("ABCD"), name="x")
         tm.assert_series_equal(s1 | s2, exp_or1)
         # np.nan | True => True (should be)
-        exp_or = Series([True, True, True, False], index=list("ABCD"), name="x")
+        exp_or = Series([True, True, True, np.nan], index=list("ABCD"), name="x")
         tm.assert_series_equal(s2 | s1, exp_or)
 
         # DataFrame doesn't fill nan with False