Calculating the hourly total with window functions
Continuing with the London bike-sharing data, you want to spot unusual demand patterns like events or disruptions. To do this, compare each hour's rentals to its typical total across all days. Window functions let you add group statistics while keeping every row intact.
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
- Calculate the sum of
rentalsgrouped byhourand name the columnhourly_total.
exercicio interativo prático
Tente este exercicio completando este código de exemplo.
# Add the hourly total using a window function
bikes.with_columns(
pl.col("rentals").____().over("____").alias("____")
)