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".
This exercise is part of the course
Data Transformation with Polars
Exercise instructions
- Replace
"N/A"values in the"price"column with"10,99".
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Replace missing prices with the estimated value
reviews.with_columns(
pl.col("____").____("____","10,99")
)