Categorical columns

In the flights data there are two columns, carrier and org, which hold categorical data. You need to transform those columns into indexed numerical values.

This exercise is part of the course

Machine Learning with PySpark

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Exercise instructions

Import the appropriate class and create an indexer object to transform the carrier column from a string to an numeric index.
Prepare the indexer object on the flight data.
Use the prepared indexer to create the numeric index column.
Repeat the process for the org column.

Hands-on interactive exercise

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

from pyspark.ml.feature import ____

# Create an indexer
indexer = ____(inputCol=____, outputCol='carrier_idx')

# Indexer identifies categories in the data
indexer_model = indexer.____(flights)

# Indexer creates a new column with numeric index values
flights_indexed = ____.____(____)

# Repeat the process for the other categorical feature
flights_indexed = ____(inputCol=____, outputCol='org_idx').____(____).____(____)
flights_indexed.show(5)

Edit and Run Code