[SPARK-52528][PS] Enable divide-by-zero for numeric mod with ANSI enabled

python/pyspark/pandas/data_type_ops/num_ops.py

@@ -96,9 +96,15 @@ def mod(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
         _sanitize_list_like(right)
         if not is_valid_operand_for_numeric_arithmetic(right):
             raise TypeError("Modulo can not be applied to given types.")
+        spark_session = left._internal.spark_frame.sparkSession
 
         def mod(left: PySparkColumn, right: Any) -> PySparkColumn:
-            return ((left % right) + right) % right
+            if is_ansi_mode_enabled(spark_session):
+                return F.when(F.lit(right == 0), F.lit(None)).otherwise(
+                    ((left % right) + right) % right
+                )
+            else:
+                return ((left % right) + right) % right
 
         right = transform_boolean_operand_to_numeric(right, spark_type=left.spark.data_type)
         return column_op(mod)(left, right)

python/pyspark/pandas/tests/computation/test_binary_ops.py

@@ -225,6 +225,7 @@ def test_binary_operator_mod(self):
         psdf = ps.from_pandas(pdf)
 
         self.assert_eq(psdf["a"] % psdf["b"], pdf["a"] % pdf["b"])
+        self.assert_eq(psdf["a"] % 0, pdf["a"] % 0)
 
         # Negative
         psdf = ps.DataFrame({"a": ["x"], "b": [1]})

python/pyspark/pandas/tests/series/test_stat.py

@@ -443,7 +443,6 @@ def test_rdivmod(self):
         self.assert_eq(krdiv, prdiv)
         self.assert_eq(krmod, prmod)
 
-    @unittest.skipIf(is_ansi_mode_test, ansi_mode_not_supported_message)
     def test_mod(self):
         pser = pd.Series([100, None, -300, None, 500, -700], name="Koalas")
         psser = ps.from_pandas(pser)

python/pyspark/pandas/tests/test_numpy_compat.py

@@ -132,7 +132,6 @@ def test_np_spark_compat_series(self):
         finally:
             reset_option("compute.ops_on_diff_frames")
 
-    @unittest.skipIf(is_ansi_mode_test, ansi_mode_not_supported_message)
     def test_np_spark_compat_frame(self):
         from pyspark.pandas.numpy_compat import unary_np_spark_mappings, binary_np_spark_mappings