[MINOR][PYTHON][DOCS] Remove duplicated versionchanged per versionadded

### What changes were proposed in this pull request?

This PR addresses all the cases of duplicated `versionchanged` directives with `versionadded` directives, see also apache#42597.

Also, this PR mentions that all functions support Spark Connect from Apache Spark 3.5.0.

### Why are the changes needed?

To remove duplicated information in docstring.

### Does this PR introduce _any_ user-facing change?

Yes, it removes duplicated information in PySpark API Reference page.

### How was this patch tested?

CI in this PR should validate them.

### Was this patch authored or co-authored using generative AI tooling?
No.

Closes apache#42602 from HyukjinKwon/minor-versionchanges.

Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

python/docs/source/reference/pyspark.sql/functions.rst

@@ -21,6 +21,9 @@ Functions
 =========
 .. currentmodule:: pyspark.sql.functions
 
+A collections of builtin functions available for DataFrame operations.
+From Apache Spark 3.5.0, all functions support Spark Connect.
+
 Normal Functions
 ----------------
 .. autosummary::

python/pyspark/sql/conf.py

@@ -39,11 +39,7 @@ def __init__(self, jconf: JavaObject) -> None:
 
     @since(2.0)
     def set(self, key: str, value: Union[str, int, bool]) -> None:
-        """Sets the given Spark runtime configuration property.
-
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-        """
+        """Sets the given Spark runtime configuration property."""
         self._jconf.set(key, value)
 
     @since(2.0)
@@ -52,9 +48,6 @@ def get(
     ) -> Optional[str]:
         """Returns the value of Spark runtime configuration property for the given key,
         assuming it is set.
-
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
         """
         self._checkType(key, "key")
         if default is _NoValue:
@@ -66,11 +59,7 @@ def get(
 
     @since(2.0)
     def unset(self, key: str) -> None:
-        """Resets the configuration property for the given key.
-
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-        """
+        """Resets the configuration property for the given key."""
         self._jconf.unset(key)
 
     def _checkType(self, obj: Any, identifier: str) -> None:
@@ -84,9 +73,6 @@ def _checkType(self, obj: Any, identifier: str) -> None:
     def isModifiable(self, key: str) -> bool:
         """Indicates whether the configuration property with the given key
         is modifiable in the current session.
-
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
         """
         return self._jconf.isModifiable(key)
 

python/pyspark/sql/dataframe.py

@@ -2268,9 +2268,6 @@ def to(self, schema: StructType) -> "DataFrame":
 
         .. versionadded:: 3.4.0
 
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-
         Parameters
         ----------
         schema : :class:`StructType`
@@ -2299,6 +2296,8 @@ def to(self, schema: StructType) -> "DataFrame":
         * Fail if the nullability is not compatible. For example, the column and/or inner field
             is nullable but the specified schema requires them to be not nullable.
 
+        Supports Spark Connect.
+
         Examples
         --------
         >>> from pyspark.sql.types import StructField, StringType
@@ -3577,9 +3576,6 @@ def unpivot(
 
         .. versionadded:: 3.4.0
 
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-
         Parameters
         ----------
         ids : str, Column, tuple, list
@@ -3599,6 +3595,10 @@ def unpivot(
         :class:`DataFrame`
             Unpivoted DataFrame.
 
+        Notes
+        -----
+        Supports Spark Connect.
+
         Examples
         --------
         >>> df = spark.createDataFrame(
@@ -3663,9 +3663,6 @@ def melt(
 
         .. versionadded:: 3.4.0
 
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-
         Parameters
         ----------
         ids : str, Column, tuple, list, optional
@@ -3688,6 +3685,10 @@ def melt(
         See Also
         --------
         DataFrame.unpivot
+
+        Notes
+        -----
+        Supports Spark Connect.
         """
         return self.unpivot(ids, values, variableColumnName, valueColumnName)
 
@@ -4265,9 +4266,6 @@ def dropDuplicatesWithinWatermark(self, subset: Optional[List[str]] = None) -> "
 
          .. versionadded:: 3.5.0
 
-        .. versionchanged:: 3.5.0
-            Supports Spark Connect.
-
          Parameters
          ----------
          subset : List of column names, optional
@@ -4278,6 +4276,10 @@ def dropDuplicatesWithinWatermark(self, subset: Optional[List[str]] = None) -> "
          :class:`DataFrame`
              DataFrame without duplicates.
 
+         Notes
+         -----
+         Supports Spark Connect.
+
          Examples
          --------
          >>> from pyspark.sql import Row
@@ -5243,9 +5245,6 @@ def withColumnsRenamed(self, colsMap: Dict[str, str]) -> "DataFrame":
         .. versionadded:: 3.4.0
            Added support for multiple columns renaming
 
-        .. versionchanged:: 3.4.0
-            Supports Spark Connect.
-
         Parameters
         ----------
         colsMap : dict
@@ -5261,6 +5260,10 @@ def withColumnsRenamed(self, colsMap: Dict[str, str]) -> "DataFrame":
         --------
         :meth:`withColumnRenamed`
 
+        Notes
+        -----
+        Support Spark Connect
+
         Examples
         --------
         >>> df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])