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.
Questo esercizio fa parte del corso
Data Transformation with Polars
Istruzioni dell'esercizio
- Add a column
rolling_totalwith the 3-hour rolling sum ofrentals.
esercizio interattivo pratico
Prova questo esercizio completando questo codice di esempio.
# Add a 3-hour rolling sum of rentals
bikes.with_columns(
pl.col("rentals").____(window_size=____).alias("____")
)