Matching on unique combinations
Joining on a single column like type can produce too many matches when that column isn't unique. A type_benchmarks DataFrame has target prices for specific type and beach combinations. To get one benchmark per listing, join on both columns so each combination uniquely identifies a row.
polars is loaded as pl, and the DataFrames hotels and type_benchmarks are available for you.
This exercise is part of the course
Data Transformation with Polars
Exercise instructions
- Join
hotelswithtype_benchmarksontypeandbeach, keeping only rows that match in both DataFrames. - Print a few rows to verify the result.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Join on type and beach for unique matches
with_targets = hotels.____(type_benchmarks, on=["____", "____"], how="____")
# Print a few rows
print(with_targets.____())