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Replacing missing values

You are preparing data for a machine learning model. In this case, you don't want to drop rows with missing values, instead you want to replace them with different approaches for different kinds of columns.

The spotify_df DataFrame is available for you.

This exercise is part of the course

Introduction to Polars

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Exercise instructions

  • Replace null values in the "streams" column with the .mean() of the "streams" column.
  • Replace null values in the "title" column with the string "Unknown".

Hands-on interactive exercise

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

filled_streams_df = spotify_df.with_columns(
    # Replace nulls in streams column
    ____,
    # Replace nulls in title column
    ____,
)

print(filled_streams_df)
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