pep8 style changes

Author: Patrick Nicholson

python/pyspark/sql/context.py

@@ -245,7 +245,8 @@ def _inferSchema(self, rdd, samplingRatio=None):
 
     @since(1.3)
     @ignore_unicode_prefix
-    def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=True, numSlices=None):
+    def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=True,
+                        numSlices=None):
         """
         Creates a :class:`DataFrame` from an :class:`RDD`, a list or a :class:`pandas.DataFrame`.
 
@@ -276,7 +277,7 @@ def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=Tr
             We can also use ``int`` as a short name for :class:`pyspark.sql.types.IntegerType`.
         :param samplingRatio: the sample ratio of rows used for inferring
         :param verifySchema: verify data types of every row against schema.
-        :param numSlices: specify as :class:`int` the number of slices (partitions) to distribute 
+        :param numSlices: specify as :class:`int` the number of slices (partitions) to distribute
             ``data`` across. Applies to ``data`` of :class:`list` or :class:`pandas.DataFrame`.
             Defaults to `self.sparkContext.defaultParallelism`.
         :return: :class:`DataFrame`
@@ -337,7 +338,8 @@ def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=Tr
             ...
         Py4JJavaError: ...
         """
-        return self.sparkSession.createDataFrame(data, schema, samplingRatio, verifySchema, numSlices)
+        return self.sparkSession.createDataFrame(data, schema, samplingRatio, verifySchema, 
+                                                 numSlices)
 
     @since(1.3)
     def registerDataFrameAsTable(self, df, tableName):

python/pyspark/sql/session.py

@@ -416,7 +416,8 @@ def _createFromLocal(self, data, schema, numSlices=None):
 
     @since(2.0)
     @ignore_unicode_prefix
-    def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=True, numSlices=None):
+    def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=True,
+                        numSlices=None):
         """
         Creates a :class:`DataFrame` from an :class:`RDD`, a list or a :class:`pandas.DataFrame`.
 
@@ -446,7 +447,7 @@ def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=Tr
             ``int`` as a short name for ``IntegerType``.
         :param samplingRatio: the sample ratio of rows used for inferring
         :param verifySchema: verify data types of every row against schema.
-        :param numSlices: specify as :class:`int` the number of slices (partitions) to distribute 
+        :param numSlices: specify as :class:`int` the number of slices (partitions) to distribute
             ``data`` across. Applies to ``data`` of :class:`list` or :class:`pandas.DataFrame`.
             Defaults to `self.sparkContext.defaultParallelism`.
         :return: :class:`DataFrame`