diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index f37777e13ee1..9d8e85cde914 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -588,6 +588,8 @@ def coalesce(self, numPartitions):
         """
         Returns a new :class:`DataFrame` that has exactly `numPartitions` partitions.
 
+        :param numPartitions: int, to specify the target number of partitions
+
         Similar to coalesce defined on an :class:`RDD`, this operation results in a
         narrow dependency, e.g. if you go from 1000 partitions to 100 partitions,
         there will not be a shuffle, instead each of the 100 new partitions will
@@ -612,9 +614,10 @@ def repartition(self, numPartitions, *cols):
         Returns a new :class:`DataFrame` partitioned by the given partitioning expressions. The
         resulting DataFrame is hash partitioned.
 
-        ``numPartitions`` can be an int to specify the target number of partitions or a Column.
-        If it is a Column, it will be used as the first partitioning column. If not specified,
-        the default number of partitions is used.
+        :param numPartitions:
+            can be an int to specify the target number of partitions or a Column.
+            If it is a Column, it will be used as the first partitioning column. If not specified,
+            the default number of partitions is used.
 
         .. versionchanged:: 1.6
            Added optional arguments to specify the partitioning columns. Also made numPartitions
@@ -673,9 +676,10 @@ def repartitionByRange(self, numPartitions, *cols):
         Returns a new :class:`DataFrame` partitioned by the given partitioning expressions. The
         resulting DataFrame is range partitioned.
 
-        ``numPartitions`` can be an int to specify the target number of partitions or a Column.
-        If it is a Column, it will be used as the first partitioning column. If not specified,
-        the default number of partitions is used.
+        :param numPartitions:
+            can be an int to specify the target number of partitions or a Column.
+            If it is a Column, it will be used as the first partitioning column. If not specified,
+            the default number of partitions is used.
 
         At least one partition-by expression must be specified.
         When no explicit sort order is specified, "ascending nulls first" is assumed.
@@ -892,6 +896,8 @@ def colRegex(self, colName):
     def alias(self, alias):
         """Returns a new :class:`DataFrame` with an alias set.
 
+        :param alias: string, an alias name to be set for the DataFrame.
+
         >>> from pyspark.sql.functions import *
         >>> df_as1 = df.alias("df_as1")
         >>> df_as2 = df.alias("df_as2")
@@ -1900,7 +1906,7 @@ def withColumnRenamed(self, existing, new):
         This is a no-op if schema doesn't contain the given column name.
 
         :param existing: string, name of the existing column to rename.
-        :param col: string, new name of the column.
+        :param new: string, new name of the column.
 
         >>> df.withColumnRenamed('age', 'age2').collect()
         [Row(age2=2, name=u'Alice'), Row(age2=5, name=u'Bob')]