[SPARK-49553][PYTHON][DOCS] Remove the experimental API notes for pan…

…das related functions

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This PR removes the experimental API notes for applyInPandas/applyInArrow/mapInPandas/mapInArrow.

### Why are the changes needed?
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These functions are no longer experimental.

### Does this PR introduce _any_ user-facing change?
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No

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Existing tests

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No

Closes #48042 from allisonwang-db/SPARK-49553-remove-experimental.

Authored-by: allisonwang-db <allison.wang@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

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

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