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.

Deze oefening maakt deel uit van de cursus

Data Transformation with Polars

Bekijk cursus

Oefeninstructies

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

Interactieve oefening met praktijkervaring

Probeer deze oefening door deze voorbeeldcode aan te vullen.

# 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")
)

Code bewerken en uitvoeren