Types and casting in Python

Polars types are explicit: cast deliberately, and strict by default.

import polars as pl

frame = pl.DataFrame({
    "n": ["1", "2", "oops"],
    "kind": ["snippet", "example", "snippet"],
})

cleaned = frame.with_columns(
    pl.col("n").cast(pl.Int64, strict=False),
    pl.col("kind").cast(pl.Categorical),
)
print(cleaned.schema)
print(cleaned)
print(cleaned["n"].null_count(), cleaned.estimated_size("b") > 0)

How it works

cast raises on overflow unless strict=False.
schema reports every column's type at once.
Categorical stores repeated strings once.

Keywords and builtins used here

as
print

The run, in numbers

Lines: 14
Characters to type: 329
Tokens: 126
Three-star pace: 100 tpm

At the three-star pace of 100 tokens a minute, this run takes about 76 seconds.

Type this snippet

Step 4 of 4 in Series & frames, step 4 of 32 in Polars.

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