Downcasting numeric columns

Now that the ranges look safe, cast the numeric columns to smaller dtypes. Use Int32 for the integer columns and Float32 for the floats where lower precision is still good enough for summary stats.

The movies DataFrame is preloaded for you.

Latihan ini merupakan bagian dari kursus

Scaling and Optimizing Data Pipelines with Polars

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Instruksi latihan

Cast vote_count and budget to pl.Int32.
Cast runtime and vote_average to pl.Float32.

Latihan interaktif langsung praktik

Cobalah latihan ini dengan melengkapi kode contoh ini.

movies_optimized = movies.with_columns(
    # Integer columns to Int32
    pl.col("vote_count").cast(pl.____),
    pl.col("budget").cast(pl.____),
    # Float columns to Float32
    pl.col("runtime").cast(pl.____),
    pl.col("vote_average").cast(pl.____),
)

result = movies_optimized.select(
    "movie_title", "budget", "runtime", "vote_average", "vote_count"
).head(8)
print(result)

Edit dan Jalankan Kode