Hands on GroupBy of Polars DataFrame in Python

import itertools as it
import polars as pl

df = pl.DataFrame(
    {
        "id": [0, 1, 2, 3, 4],
        "color": ["red", "green", "green", "red", "red"],
        "shape": ["square", "triangle", "square", "triangle", "square"],
    }
)
df

df.groupby("color", maintain_order=True).agg(pl.col("id"))

df.groupby("color", maintain_order=True).agg(pl.col("id").first())

def update_frame(frame):
    frame[0, "id"] = frame[0, "id"] * 1000
    return frame

df.groupby("color").apply(update_frame)

df.groupby("color").agg(pl.count().alias("n"))

pl.DataFrame(data=it.combinations(range(52), 4), orient="row").with_row_count().groupby(
    [
        "column_0",
        "column_1",
        "column_2",
    ]
).agg(pl.col("row_nr").min()).sort(
    [
        "column_0",
        "column_1",
        "column_2",
    ]
)

pl.Series((g, frame.shape[0]) for g, frame in df.groupby("color"))