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Adding a custom expression

Your team frequently calculates per-listener metrics across different reports. To make this pattern even more reusable, create a custom expression that can be chained like any built-in Polars method.

polars is loaded as pl. The DataFrame spotify is available with album streaming data.

Diese Übung ist Teil des Kurses

Data Transformation with Polars

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Anleitung zur Übung

  • Define per_listener() to divide its input by the monthly_listeners column.
  • Attach the function to pl.Expr to make it chainable.
  • Apply the custom method on the streams column.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

# Define the per_listener function
def per_listener(input):
    return ____ / pl.col("____")


# Attach the function to pl.Expr
pl.Expr.____ = ____

# Use the custom method on the streams column
result = spotify.with_columns(
    pl.col("____").____().alias("streams_per_listener")
)

print(result.head())
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