cast() method in PySpark
The cast() is used to change the data type of a column.
Syntax pyspark.sql.Column.cast(‘datatype’)
In this exercise, we are using the datasource data.csv. You can download the datasource and use for the transformation.
Example: First create the SparkSession and read the data from the CSV file.
Python
# Import the SparkSession module from pyspark.sql import SparkSession # Initialize a Spark session spark = SparkSession.builder.appName("App Name").getOrCreate() # Import the Data df = spark.read.csv("data.csv", header=True, inferSchema=True) # Show the data in the DataFrame df.show()
The output of the above code is shown below:

Converts the 'Salary' column to double data type.
Python
df = df.withColumn('New Salary', df['Salary'].cast('double')) df.show()
The output of the above code is shown below:

Converts the Height column to int data type.
Python
df = df.withColumn('New Height', df['Height'].cast('int')) df.show()
The output of the above code is shown below:
