Calculating a rolling sum
Continuing with the London bike-sharing data, hourly rental counts can jump dramatically from one hour to the next, making it hard to spot trends. Rolling statistics smooth out this noise by summing over a window of consecutive rows.
polars is loaded as pl. The DataFrame bikes is available with columns time, rentals, and temp.
Cet exercice fait partie du cours
Data Transformation with Polars
Instructions
- Add a column
rolling_totalwith the 3-hour rolling sum ofrentals.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Add a 3-hour rolling sum of rentals
bikes.with_columns(
pl.col("rentals").____(window_size=____).alias("____")
)