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pythonintermediate

Polars DataFrame Operations

High-performance DataFrame operations using Polars: filtering, groupby, joins, and lazy evaluation.

python
import polars as pl

df = pl.read_csv('data.csv')

result = (
    df.lazy()
    .filter(pl.col('age') > 25)
    .group_by('department')
    .agg([
        pl.col('salary').mean().alias('avg_salary'),
        pl.col('id').count().alias('headcount'),
    ])
    .sort('avg_salary', descending=True)
    .collect()
)
print(result)

Use Cases

  • data transformation
  • analytics pipelines
  • large dataset processing

Tags

#polars#dataframe#etl#performance

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