Creating reusable expressions
Now that you can transform columns, you want to understand which artists have a dedicated fanbase by calculating streams per listener. Rather than rewriting this formula each time, store the calculation as a Polars expression variable that you can reuse across multiple DataFrames.
polars is loaded as pl. The DataFrame spotify is available with album streaming data.
Bu egzersiz, kursun bir parçasıdır
Data Transformation with Polars
Egzersiz talimatları
- Create an expression that divides
streamsbymonthly_listeners. - Apply the expression variable and sort by
streams_per_listenerin descending order.
Uygulamalı etkileşimli egzersiz
Bu egzersizi bu örnek kodu tamamlayarak deneyin.
# Create a reusable expression for streams per listener
streams_per_listener_expr = (
(pl.col("____") / pl.col("____"))
.alias("streams_per_listener")
)
# Apply the expression and sort by streams_per_listener
result = spotify.with_columns(____).sort(
"streams_per_listener", descending=____
)
print(result.head())