polars.Expr.struct.with_fields#

Expr.struct.with_fields(

*exprs: IntoExpr | Iterable[IntoExpr],

**named_exprs: IntoExpr,

) → Expr[source]#

Add or overwrite fields of this struct.

This is similar to with_columns on DataFrame.

New in version 0.20.27.

Parameters:

*exprs: Field(s) to add, specified as positional arguments. Accepts expression input. Strings are parsed as column names, other non-expression inputs are parsed as literals.
**named_exprs: Additional fields to add, specified as keyword arguments. The columns will be renamed to the keyword used.

See also

field

Examples

>>> df = pl.DataFrame(
...     {
...         "coords": [{"x": 1, "y": 4}, {"x": 4, "y": 9}, {"x": 9, "y": 16}],
...         "multiply": [10, 2, 3],
...     }
... )
>>> df
shape: (3, 2)
┌───────────┬──────────┐
│ coords    ┆ multiply │
│ ---       ┆ ---      │
│ struct[2] ┆ i64      │
╞═══════════╪══════════╡
│ {1,4}     ┆ 10       │
│ {4,9}     ┆ 2        │
│ {9,16}    ┆ 3        │
└───────────┴──────────┘
>>> df = df.with_columns(
...     pl.col("coords").struct.with_fields(
...         pl.field("x").sqrt(),
...         y_mul=pl.field("y") * pl.col("multiply"),
...     )
... )
>>> df
shape: (3, 2)
┌─────────────┬──────────┐
│ coords      ┆ multiply │
│ ---         ┆ ---      │
│ struct[3]   ┆ i64      │
╞═════════════╪══════════╡
│ {1.0,4,40}  ┆ 10       │
│ {2.0,9,18}  ┆ 2        │
│ {3.0,16,48} ┆ 3        │
└─────────────┴──────────┘
>>> df.unnest("coords")
shape: (3, 4)
┌─────┬─────┬───────┬──────────┐
│ x   ┆ y   ┆ y_mul ┆ multiply │
│ --- ┆ --- ┆ ---   ┆ ---      │
│ f64 ┆ i64 ┆ i64   ┆ i64      │
╞═════╪═════╪═══════╪══════════╡
│ 1.0 ┆ 4   ┆ 40    ┆ 10       │
│ 2.0 ┆ 9   ┆ 18    ┆ 2        │
│ 3.0 ┆ 16  ┆ 48    ┆ 3        │
└─────┴─────┴───────┴──────────┘