polars.min#

polars.min(exprs: Series) → PythonLiteral | None[source]#

polars.min(exprs: IntoExpr | Iterable[IntoExpr], *more_exprs: IntoExpr) → Expr

Get the minimum value.

If a single string is passed, this is an alias for pl.col(name).min().

If a single Series is passed, this is an alias for Series.min(). This functionality is deprecated.

Otherwise, this function computes the minimum value horizontally across multiple columns. This functionality is deprecated, use pl.min_horizontal instead.

Parameters:

exprs: Column(s) to use in the aggregation. Accepts expression input. Strings are parsed as column names, other non-expression inputs are parsed as literals.
*more_exprs: Additional columns to use in the aggregation, specified as positional arguments.

See also

min_horizontal

Examples

Get the minimum value of a column by passing a single column name.

>>> df = pl.DataFrame(
...     {
...         "a": [1, 8, 3],
...         "b": [4, 5, 2],
...         "c": ["foo", "bar", "foo"],
...     }
... )
>>> df.select(pl.min("a"))
shape: (1, 1)
┌─────┐
│ a   │
│ --- │
│ i64 │
╞═════╡
│ 1   │
└─────┘

Get column-wise minimums for multiple columns by passing a regular expression, or call .min() on a multi-column expression instead.

>>> df.select(pl.min("^a|b$"))
shape: (1, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 2   │
└─────┴─────┘
>>> df.select(pl.col("a", "b").min())
shape: (1, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 2   │
└─────┴─────┘