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.
Bu egzersiz, kursun bir parçasıdır
Data Transformation with Polars
Egzersiz talimatları
- Add a column
diff_from_avgshowingrentalsminus the hourly mean ofrentals.
Uygulamalı etkileşimli egzersiz
Bu egzersizi bu örnek kodu tamamlayarak deneyin.
# Calculate how each rental differs from its hourly average
bikes.with_columns(
(pl.col("rentals") - pl.col("rentals").____().over("____")).alias("____")
)