polars.Expr.approx_n_unique#
- Expr.approx_n_unique() Expr [source]#
Approximate count of unique values.
This is done using the HyperLogLog++ algorithm for cardinality estimation.
Examples
>>> df = pl.DataFrame({"n": [1, 1, 2]}) >>> df.select(pl.col("n").approx_n_unique()) shape: (1, 1) ┌─────┐ │ n │ │ --- │ │ u32 │ ╞═════╡ │ 2 │ └─────┘ >>> df = pl.DataFrame({"n": range(1000)}) >>> df.select( ... exact=pl.col("n").n_unique(), ... approx=pl.col("n").approx_n_unique(), ... ) shape: (1, 2) ┌───────┬────────┐ │ exact ┆ approx │ │ --- ┆ --- │ │ u32 ┆ u32 │ ╞═══════╪════════╡ │ 1000 ┆ 1005 │ └───────┴────────┘