Parsing a messy CSV

A third-party ebook vendor exports Seattle digital checkouts as a semicolon-separated CSV with two metadata rows above the real header. Configure your scan to handle the layout so the team can preview a clean table.

polars is loaded as pl. The path to the vendor file is in MESSY_CSV_PATH.

This exercise is part of the course

Scaling and Optimizing Data Pipelines with Polars

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Exercise instructions

Skip the 2 metadata rows above the header.
Tell Polars that the columns are separated by semicolons.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

result = pl.scan_csv(
    MESSY_CSV_PATH,
    # Skip the 2 metadata rows above the header
    skip_rows=____,
    # Columns are separated by semicolons
    separator="____",
).head(5).collect()
print(result)

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