Creating reusable expressions

Now that you can transform columns, you want to understand which artists have a dedicated fanbase by calculating streams per listener. Rather than rewriting this formula each time, store the calculation as a Polars expression variable that you can reuse across multiple DataFrames.

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

Cet exercice fait partie du cours

Data Transformation with Polars

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Instructions

Create an expression that divides streams by monthly_listeners.
Apply the expression variable and sort by streams_per_listener in descending order.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Create a reusable expression for streams per listener
streams_per_listener_expr = (
    (pl.col("____") / pl.col("____"))
    .alias("streams_per_listener")
)

# Apply the expression and sort by streams_per_listener
result = spotify.with_columns(____).sort(
    "streams_per_listener", descending=____
)

print(result.head())

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