Filling missing values
Finally, you can replace specific values directly. The finance team needs complete pricing data, but some products have missing prices marked as "N/A". Based on historical data, the average product costs around "10,99".
Cet exercice fait partie du cours
Data Transformation with Polars
Instructions
- Replace
"N/A"values in the"price"column with"10,99".
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Replace missing prices with the estimated value
reviews.with_columns(
pl.col("____").____("____","10,99")
)