Ignoring parse errors

A bad value, the literal text "unknown", has slipped into the checkouts column of the vendor export. Polars normally fails when it can't parse a value into the inferred dtype. Tell Polars to skip these errors so the team can still load the rest of the data.

A normal row and the row with the bad value are printed for you so you can see what's going on.

Deze oefening maakt deel uit van de cursus

Scaling and Optimizing Data Pipelines with Polars

Bekijk cursus

Oefeninstructies

Add the argument that tells Polars to set bad values to null and continue scanning.

Interactieve oefening met praktijkervaring

Probeer deze oefening door deze voorbeeldcode aan te vullen.

result = pl.scan_csv(
    MESSY_CSV_PATH,
    separator=";",
    skip_rows=2,
    schema_overrides={
        "checkouts": pl.Int64,
        "branch_code": pl.String,
    },
    # Tolerate values that don't fit the schema
    ____=____,
).collect()
print(result)

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