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  3. Scaling and Optimizing Data Pipelines with Polars
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연습 문제

Previewing the data lazily

You've joined the Seattle city data analysis team. They track every Seattle Public Library checkout in a multi-million-row CSV, and the reporting team wants a quick peek at the data. Keep the query lazy until after head(5) so Polars only reads the rows you need.

polars is loaded as pl, and the LazyFrame library was built from the CSV file.

지침

100 XP
  • Take only the first 5 rows of the library LazyFrame.
  • Trigger execution and assign the resulting DataFrame to result.