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.
Este ejercicio forma parte del curso
Data Transformation with Polars
Instrucciones del ejercicio
- Create an expression that divides
streamsbymonthly_listeners. - Apply the expression variable and sort by
streams_per_listenerin descending order.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# 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())