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.

Bu egzersiz, kursun bir parçasıdır

Data Transformation with Polars

Kursa Göz Atın

Egzersiz talimatları

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

Uygulamalı etkileşimli egzersiz

Bu egzersizi bu örnek kodu tamamlayarak deneyin.

# 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")
)

Kodu Düzenle ve Çalıştır