Calculating the difference from hourly mean

Totals are useful, but deviations tell a richer story. Calculate how much each hour's rentals differ from the average for that hour across all days to quickly flag above-normal or below-normal demand.

polars is loaded as pl. The DataFrame bikes is available with columns time, rentals, temp, and hour.

Deze oefening maakt deel uit van de cursus

Data Transformation with Polars

Bekijk cursus

Oefeninstructies

Add a column diff_from_avg showing rentals minus the hourly mean of rentals.

Interactieve oefening met praktijkervaring

Probeer deze oefening door deze voorbeeldcode aan te vullen.

# Calculate how each rental differs from its hourly average
bikes.with_columns(
    (pl.col("rentals") - pl.col("rentals").____().over("____")).alias("____")
)

Code bewerken en uitvoeren