Python Polars Cheat Sheet: Fast DataFrames for Busy Engineers

Polars hits the sweet spot between Pandas’ ease and Spark’s scale. If you’ve ever waited on a groupby or cursed a memory error, this cheat sheet is for you. I’ve pulled the patterns that save time in real pipelines, not just toy examples. Bookmark this before your next ETL run. Setup and Basics First, get Polars and a dataset. The lazy API is the default now, so you’ll rarely need to call .lazy() explicitly. Start with a CSV or Parquet file, or create a DataFrame from scratch. pip install polars pyarrow import polars as pl df = pl.read_csv('data.csv') # or pl.read_parquet() df = pl.DataFrame({'a': [1, 2], 'b': ['x', 'y']}) Selecting and Filtering Polars uses expressions, not strings. This feels odd at first but pays off when you chain operations. The syntax is consistent: every column is an expression you can transform, filter, or aggregate. df.select(['a', 'b']) # columns by name df.select(pl.col('a').alias('renamed')) df.filter(pl.col('a') > 10) df.filter(pl.col('b').is_in(['x', 'z'])) df.filter(pl.col('a').is_null()) Transforming Data Polars expressions are composable. You can nest them, reuse them, and even store them in variables. This is where the library shines over Pandas. df.with_columns(pl.col('a').cast(pl.Float64)) df.with_columns(pl.col('a').fill_null(0)) df.with_columns((pl.col('a') * 2).alias('a_doubled')) df.with_columns(pl.col('b').str.to_uppercase()) df.with_columns(pl.col('a').is_between(10, 20)) Grouping and Aggregations Groupbys in Polars are lazy by default. This means you can stack multiple aggregations without materializing intermediate results. The syntax is clean, but watch out for the order of operations. df.group_by('b').agg(pl.col('a').sum()) df.group_by('b').agg([pl.col('a').mean(), pl.col('a').max()]) df.group_by('b').agg(pl.col('a').quantile(0.9)) df.group_by_dynamic('timestamp', every='1d').agg(pl.col('a').sum()) Joins and Concatenation Joins in Polars are explicit. You’ll specify the join type and the columns to join on. Concatenatio