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 exercício faz parte do curso
Data Transformation with Polars
Instruções do exercício
- Set up the 3-hour rolling window on the
timecolumn. - Calculate the sum of
rentalsand the mean oftempin the aggregation.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# 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")
)