polars.approx_n_unique#
- polars.approx_n_unique(column: str | Expr) Expr [source]#
Approximate count of unique values.
This is done using the HyperLogLog++ algorithm for cardinality estimation.
- Parameters:
- column
Column name or Series.
Examples
>>> df = pl.DataFrame({"a": [1, 8, 1], "b": [4, 5, 2], "c": ["foo", "bar", "foo"]}) >>> df.select(pl.approx_n_unique("a")) shape: (1, 1) ┌─────┐ │ a │ │ --- │ │ u32 │ ╞═════╡ │ 2 │ └─────┘