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.
Este ejercicio forma parte del curso
Data Transformation with Polars
Instrucciones del ejercicio
- Set up the 3-hour rolling window on the
timecolumn. - Calculate the sum of
rentalsand the mean oftempin the aggregation.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# 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")
)