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".
本练习是课程的一部分
Data Transformation with Polars
练习说明
- Replace
"N/A"values in the"price"column with"10,99".
交互式实操练习
通过完成这段示例代码来试试这个练习。
# Replace missing prices with the estimated value
reviews.with_columns(
pl.col("____").____("____","10,99")
)