Rolling aggregations on multiple columns

What if you need rolling statistics on multiple columns at once? The .rolling() method lets you compute aggregations over a time-based window for several columns simultaneously.

polars is loaded as pl. The DataFrame bikes is available with columns time, rentals, and temp.

Diese Übung ist Teil des Kurses

<Kurs>Data Transformation with Polars</Kurs>

Kurs ansehen

Übungsanweisungen

Set up the 3-hour rolling window on the time column.
Calculate the sum of rentals and the mean of temp in the aggregation.

Interaktive praktische Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Set up the 3-hour rolling window
bikes.rolling(index_column="____", period="____").agg(
  
    # Calculate sum of rentals and mean of temp
    pl.col("rentals").____().alias("rolling_total"),
    pl.col("temp").____().alias("rolling_mean_temp")
)

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