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.
Este ejercicio forma parte del curso
Data Transformation with Polars
Instrucciones del ejercicio
- Add a column
diff_from_avgshowingrentalsminus the hourly mean ofrentals.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# Calculate how each rental differs from its hourly average
bikes.with_columns(
(pl.col("rentals") - pl.col("rentals").____().over("____")).alias("____")
)