polars.Expr.search_sorted

Expr.search_sorted(
    element: IntoExpr | np.ndarray[Any,
    Any],
    side: SearchSortedSide = 'any',
    *,
    descending: bool = False,
) → Expr

Find indices where elements should be inserted to maintain order.

\[a[i-1] < v <= a[i]\]

engine:In Memory

Parameters:

element

Expression or scalar value.

side{‘any’, ‘left’, ‘right’}

If ‘any’, the index of the first suitable location found is given. If ‘left’, the index of the leftmost suitable location found is given. If ‘right’, return the rightmost suitable location found is given.

descending

Boolean indicating whether the values are descending or not (they are required to be sorted either way).

Examples

>>> df = pl.DataFrame(
...     {
...         "values": [1, 2, 3, 5],
...     }
... )
>>> df.select(
...     [
...         pl.col("values").search_sorted(0).alias("zero"),
...         pl.col("values").search_sorted(3).alias("three"),
...         pl.col("values").search_sorted(6).alias("six"),
...     ]
... )
shape: (1, 3)
┌──────┬───────┬─────┐
│ zero ┆ three ┆ six │
│ ---  ┆ ---   ┆ --- │
│ u32  ┆ u32   ┆ u32 │
╞══════╪═══════╪═════╡
│ 0    ┆ 2     ┆ 4   │
└──────┴───────┴─────┘