How to create dataframe from list in Spark SQL?

here is how -

from pyspark.sql.types import *

cSchema = StructType([StructField("WordList", ArrayType(StringType()))])

# notice extra square brackets around each element of list 
test_list = [['Hello', 'world']], [['I', 'am', 'fine']]

df = spark.createDataFrame(test_list,schema=cSchema) 

You should use list of Row objects([Row]) to create data frame.

from pyspark.sql import Row

spark.createDataFrame(list(map(lambda x: Row(words=x), test_list)))

i had to work with multiple columns and types - the example below has one string column and one integer column. A slight adjustment to Pushkr's code (above) gives:

from pyspark.sql.types import *

cSchema = StructType([StructField("Words", StringType())\
                      ,StructField("total", IntegerType())])

test_list = [['Hello', 1], ['I am fine', 3]]

df = spark.createDataFrame(test_list,schema=cSchema) 

output:

 df.show()
 +---------+-----+
|    Words|total|
+---------+-----+
|    Hello|    1|
|I am fine|    3|
+---------+-----+