polars.date#

polars.date(year: Expr | str | int, month: Expr | str | int, day: Expr | str | int) → Expr[source]#

Create a Polars literal expression of type Date.

Parameters:

year: column or literal.
month: column or literal, ranging from 1-12.
day: column or literal, ranging from 1-31.

Returns:

Expr: Expression of data type Date.

Examples

>>> df = pl.DataFrame(
...     {
...         "month": [1, 2, 3],
...         "day": [4, 5, 6],
...     }
... )
>>> df.with_columns(pl.date(2024, pl.col("month"), pl.col("day")))
shape: (3, 3)
┌───────┬─────┬────────────┐
│ month ┆ day ┆ date       │
│ ---   ┆ --- ┆ ---        │
│ i64   ┆ i64 ┆ date       │
╞═══════╪═════╪════════════╡
│ 1     ┆ 4   ┆ 2024-01-04 │
│ 2     ┆ 5   ┆ 2024-02-05 │
│ 3     ┆ 6   ┆ 2024-03-06 │
└───────┴─────┴────────────┘

We can also use pl.date for filtering:

>>> from datetime import date
>>> df = pl.DataFrame(
...     {
...         "start": [date(2024, 1, 1), date(2024, 1, 1), date(2024, 1, 1)],
...         "end": [date(2024, 5, 1), date(2024, 7, 1), date(2024, 9, 1)],
...     }
... )
>>> df.filter(pl.col("end") > pl.date(2024, 6, 1))
shape: (2, 2)
┌────────────┬────────────┐
│ start      ┆ end        │
│ ---        ┆ ---        │
│ date       ┆ date       │
╞════════════╪════════════╡
│ 2024-01-01 ┆ 2024-07-01 │
│ 2024-01-01 ┆ 2024-09-01 │
└────────────┴────────────┘