Import necessary libraries

  Initialize the Spark session

  Create the required data frame

from pyspark.sql import SparkSession
#Set up SparkContext and SparkSession
spark=SparkSession \
.builder \
.appName(“Python spark example”)\
.config(“spark.some.config.option”,”some-value”)\
.getOrCreate()
#Creating RDD using parallelize function
df = spark.sparkContext.parallelize([(2, 4, 6, ‘Row1’),(3, 6, 9, ‘Row2’),
(4, 8, 12, ‘Row3’)]).toDF([‘col1’, ‘col2’, ‘col3′,’col4′])
df.show()
#Creating RDD uding createDataFrame function
Emp_det = spark.createDataFrame([
(1,’J.Priyanka’,18000,700,28,1,’HR’),
(2,’Bhavani’,20000,700,28,0,’ACC’),
(3,’S.Priyanka’,16000,700,28,0,’DATA ENTRY’)],
[“ID”,”NAME”,”SALARY”,”TA”,”Working_days”,”Leaves”,”DEPT”])
Emp_det.show()
#Using read and load function
df1=spark.read.format(‘com.databricks.spark.csv’).options(header=’True’,inferschema=’True’).load(“/home/…../weight-height.csv”)
df1.show(5)