Get startedGet started for free

Pandas UDFs

This exercise covers Pandas UDFs, so that you can practice their syntax! As you work through this exercise, notice the differences between the Pyspark UDF from the last exercise and this type of UDF.

Remember, there's already a SparkSession called spark in your workspace!

This exercise is part of the course

Introduction to PySpark

View Course

Exercise instructions

  • Define the add_ten_pandas() function as a pandas UDF.
  • Add a new column to the DataFrame called "10_plus" that applies the pandas UDF to the df column "value".
  • Show the resulting DataFrame.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Define a Pandas UDF that adds 10 to each element in a vectorized way
@____(DoubleType())
def add_ten_pandas(column):
    return column + 10

# Apply the UDF and show the result
df.withColumn("10_plus", ____)
df.____
Edit and Run Code