polars.Expr.is_first_distinct#

Expr.is_first_distinct() → Self[source]#

Return a boolean mask indicating the first occurrence of each distinct value.

Returns:

Expr: Expression of data type Boolean.

Examples

>>> df = pl.DataFrame({"a": [1, 1, 2, 3, 2]})
>>> df.with_columns(pl.col("a").is_first_distinct().alias("first"))
shape: (5, 2)
┌─────┬───────┐
│ a   ┆ first │
│ --- ┆ ---   │
│ i64 ┆ bool  │
╞═════╪═══════╡
│ 1   ┆ true  │
│ 1   ┆ false │
│ 2   ┆ true  │
│ 3   ┆ true  │
│ 2   ┆ false │
└─────┴───────┘