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 exercicio faz parte do curso
Data Transformation with Polars
Instruções do exercicio
- Add a column
diff_from_avgshowingrentalsminus the hourly mean ofrentals.
exercicio interativo prático
Tente este exercicio completando este código de exemplo.
# Calculate how each rental differs from its hourly average
bikes.with_columns(
(pl.col("rentals") - pl.col("rentals").____().over("____")).alias("____")
)