diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 0c861e8b0d427..ef35b73332572 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -6168,10 +6168,6 @@ def mapInPandas(
         |  1| 21|
         +---+---+
 
-        Notes
-        -----
-        This API is experimental
-
         See Also
         --------
         pyspark.sql.functions.pandas_udf
@@ -6245,10 +6241,6 @@ def mapInArrow(
         |  1| 21|
         +---+---+
 
-        Notes
-        -----
-        This API is unstable, and for developers.
-
         See Also
         --------
         pyspark.sql.functions.pandas_udf
diff --git a/python/pyspark/sql/pandas/group_ops.py b/python/pyspark/sql/pandas/group_ops.py
index 06834553ea96a..3173534c03c91 100644
--- a/python/pyspark/sql/pandas/group_ops.py
+++ b/python/pyspark/sql/pandas/group_ops.py
@@ -224,8 +224,6 @@ def applyInPandas(
         into memory, so the user should be aware of the potential OOM risk if data is skewed
         and certain groups are too large to fit in memory.
 
-        This API is experimental.
-
         See Also
         --------
         pyspark.sql.functions.pandas_udf
@@ -329,8 +327,6 @@ def applyInPandasWithState(
         Notes
         -----
         This function requires a full shuffle.
-
-        This API is experimental.
         """
 
         from pyspark.sql import GroupedData
@@ -484,8 +480,6 @@ def transformWithStateInPandas(
         Notes
         -----
         This function requires a full shuffle.
-
-        This API is experimental.
         """
 
         from pyspark.sql import GroupedData
@@ -683,10 +677,6 @@ class PandasCogroupedOps:
 
     .. versionchanged:: 3.4.0
         Support Spark Connect.
-
-    Notes
-    -----
-    This API is experimental.
     """
 
     def __init__(self, gd1: "GroupedData", gd2: "GroupedData"):
@@ -778,8 +768,6 @@ def applyInPandas(
         into memory, so the user should be aware of the potential OOM risk if data is skewed
         and certain groups are too large to fit in memory.
 
-        This API is experimental.
-
         See Also
         --------
         pyspark.sql.functions.pandas_udf