polars_dataframe_filter_transform_aggregate_quickstart.py

1import polars as pl
2from datetime import datetime
3
4# Create a DataFrame
5df = pl.DataFrame(
6    {
7        "integer": [1, 2, 3, 4, 5],
8        "date": [
9            datetime(2025, 1, 1),
10            datetime(2025, 1, 2),
11            datetime(2025, 1, 3),
12            datetime(2025, 1, 4),
13            datetime(2025, 1, 5),
14        ],
15        "float": [4.0, 5.0, 6.0, 7.0, 8.0],
16        "string": ["a", "b", "c", "d", "e"],
17    }
18)
19
20# Filter, transform and aggregate
21out = df.filter(pl.col("integer") > 2).select(
22    pl.col("string"),
23    pl.col("float") * 10,
24    pl.col("date").dt.year().alias("year"),
25)
26
27print(out)