polars.Expr.dt.second#

Expr.dt.second(*, fractional: bool = False) → Expr[source]#

Extract seconds from underlying DateTime representation.

Applies to Datetime columns.

Returns the integer second number from 0 to 59, or a floating point number from 0 < 60 if fractional=True that includes any milli/micro/nanosecond component.

Parameters:

fractional: Whether to include the fractional component of the second.

Returns:

Expr: Expression of data type UInt32 or Float64.

Examples

>>> from datetime import datetime
>>> df = pl.DataFrame(
...     {
...         "datetime": [
...             datetime(2000, 1, 1, 0, 0, 0, 456789),
...             datetime(2000, 1, 1, 0, 0, 3, 111110),
...             datetime(2000, 1, 1, 0, 0, 5, 765431),
...         ]
...     }
... )
>>> df.with_columns(pl.col("datetime").dt.second().alias("second"))
shape: (3, 2)
┌────────────────────────────┬────────┐
│ datetime                   ┆ second │
│ ---                        ┆ ---    │
│ datetime[μs]               ┆ u32    │
╞════════════════════════════╪════════╡
│ 2000-01-01 00:00:00.456789 ┆ 0      │
│ 2000-01-01 00:00:03.111110 ┆ 3      │
│ 2000-01-01 00:00:05.765431 ┆ 5      │
└────────────────────────────┴────────┘
>>> df.with_columns(
...     pl.col("datetime").dt.second(fractional=True).alias("second")
... )
shape: (3, 2)
┌────────────────────────────┬──────────┐
│ datetime                   ┆ second   │
│ ---                        ┆ ---      │
│ datetime[μs]               ┆ f64      │
╞════════════════════════════╪══════════╡
│ 2000-01-01 00:00:00.456789 ┆ 0.456789 │
│ 2000-01-01 00:00:03.111110 ┆ 3.11111  │
│ 2000-01-01 00:00:05.765431 ┆ 5.765431 │
└────────────────────────────┴──────────┘