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  3. Data Transformation with Polars
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अभ्यास

Finding gaps in both DataFrames

For data quality checks, you want to see all rows from both DataFrames - listings without benchmarks and benchmarks without listings. This helps identify gaps before analysis.

polars is loaded as pl, and the DataFrames hotels and type_benchmarks are available for you.

निर्देश

100 XP
  • Join hotels with type_benchmarks on type and beach, keeping all rows from both DataFrames.
  • Use coalesce=True to avoid duplicate join columns.