from pyspark.sql.types import StructType,StructField, StringType, IntegerType
#Create User defined Custom Schema using StructType
mySchema = StructType([ StructField("First Name", StringType(), True)\
,StructField("Age", IntegerType(), True)])
#Create DataFrame by changing schema
sparkDF2 = spark.createDataFrame(pandasDF,schema=mySchema)
sparkDF2.printSchema()
sparkDF2.show()
#Outputs below schema & DataFrame
root
|-- First Name: string (nullable = true)
|-- Age: integer (nullable = true)
+----------+---+
|First Name|Age|
+----------+---+
| Scott| 50|
| Jeff| 45|
| Thomas| 54|
| Ann| 34|
+----------+---+