[Python] Best way to get percentage counts in Polars

I frequently need to calculate the percentage counts of a variable. For example for the dataframe below

df = pl.DataFrame({"person": ["a", "a", "b"],
"value": [1, 2, 3]})


I want to return a dataframe like this:

shape: (2, 2)
┌────────┬──────────┐
│ person ┆ percent │
│ --- ┆ --- │
│ str ┆ f64 │
╞════════╪══════════╡
│ a ┆ 0.666667 │
│ b ┆ 0.333333 │
└────────┴──────────┘


What I have been doing is the following, but I can't help but think there must be a more efficient / polars way to do this

n_rows = len(df)

(
df
.with_columns(pl.lit(1)
.alias('percent'))
.group_by('person')
.agg(pl.sum('percent') / n_rows)
)

Continue reading...