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
Oefeninstructies
- Set up the 3-hour rolling window on the
timecolumn. - Calculate the sum of
rentalsand the mean oftempin the aggregation.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in 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")
)