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.
Cet exercice fait partie du cours
Data Transformation with Polars
Instructions
- Add a column
diff_from_avgshowingrentalsminus the hourly mean ofrentals.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Calculate how each rental differs from its hourly average
bikes.with_columns(
(pl.col("rentals") - pl.col("rentals").____().over("____")).alias("____")
)