diff --git a/python/pyspark/sql/tests/connect/test_parity_dataframe.py b/python/pyspark/sql/tests/connect/test_parity_dataframe.py
index 01c565429965..ea1eb23fd4f6 100644
--- a/python/pyspark/sql/tests/connect/test_parity_dataframe.py
+++ b/python/pyspark/sql/tests/connect/test_parity_dataframe.py
@@ -85,10 +85,6 @@ def test_extended_hint_types(self):
     def test_fillna(self):
         super().test_fillna()
 
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_freqItems(self):
-        super().test_freqItems()
-
     @unittest.skip("Fails in Spark Connect, should enable.")
     def test_generic_hints(self):
         super().test_generic_hints()
@@ -97,10 +93,6 @@ def test_generic_hints(self):
     def test_help_command(self):
         super().test_help_command()
 
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_input_files(self):
-        super().test_input_files()
-
     @unittest.skip("Fails in Spark Connect, should enable.")
     def test_invalid_join_method(self):
         super().test_invalid_join_method()
@@ -193,10 +185,6 @@ def test_to_pandas_from_null_dataframe(self):
     def test_to_pandas_on_cross_join(self):
         super().test_to_pandas_on_cross_join()
 
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_to_pandas_required_pandas_not_found(self):
-        super().test_to_pandas_required_pandas_not_found()
-
     @unittest.skip("Fails in Spark Connect, should enable.")
     def test_to_pandas_with_duplicated_column_names(self):
         super().test_to_pandas_with_duplicated_column_names()
diff --git a/python/pyspark/sql/tests/test_dataframe.py b/python/pyspark/sql/tests/test_dataframe.py
index a9011ec1f953..bb87393b362e 100644
--- a/python/pyspark/sql/tests/test_dataframe.py
+++ b/python/pyspark/sql/tests/test_dataframe.py
@@ -74,7 +74,7 @@ def test_duplicated_column_names(self):
 
     def test_freqItems(self):
         vals = [Row(a=1, b=-2.0) if i % 2 == 0 else Row(a=i, b=i * 1.0) for i in range(100)]
-        df = self.sc.parallelize(vals).toDF()
+        df = self.spark.createDataFrame(vals)
         items = df.stat.freqItems(("a", "b"), 0.4).collect()[0]
         self.assertTrue(1 in items[0])
         self.assertTrue(-2.0 in items[1])