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Lazy train-test split

You have transformed the X variables. Now you need to finish your data prep by transforming the y variables and splitting your data into train and test sets.

The variables X and y, which you created in the last exercise, are available in your environment.

This exercise is part of the course

Parallel Programming with Dask in Python

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Exercise instructions

  • Import the train_test_split() function from dask_ml.model_selection.
  • The popularity scores in y are in the range 0-100, divide them by 100 so they are in the range 0-1.
  • Split the data into train and test sets using the train_test_split() function, make sure to shuffle the data, and set the test fraction to 20% of the data.

Hands-on interactive exercise

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

# Import the train_test_split function
from ____ import ____

# Rescale the target values
y = ____

# Split the data into train and test sets
X_train, X_test, y_train, y_test = ____

print(X_train)
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