polars.col

Create an expression representing column(s) in a dataframe.

col is technically not a function, but it can be used like one.

See the class documentation below for examples and further documentation.

---

class polars.functions.col.ColumnFactory(

name: str | PolarsDataType | Iterable[str] | Iterable[PolarsDataType],

*more_names: str | PolarsDataType,

)

Create Polars column expressions.

Notes

An instance of this class is exported under the name col. It can be used as though it were a function by calling, for example, pl.col("foo"). See the __call__() method for further documentation.

This helper class enables an alternative syntax for creating a column expression through attribute lookup. For example col.foo creates an expression equal to col("foo"). See the __getattr__() method for further documentation.

The function call syntax is considered the idiomatic way of constructing a column expression. The alternative attribute syntax can be useful for quick prototyping as it can save some keystrokes, but has drawbacks in both expressiveness and readability.

Examples

>>> from polars import col
>>> df = pl.DataFrame(
...     {
...         "foo": [1, 2],
...         "bar": [3, 4],
...     }
... )

Create a new column expression using the standard syntax:

>>> df.with_columns(baz=(col("foo") * col("bar")) / 2)
shape: (2, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ baz │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ f64 │
╞═════╪═════╪═════╡
│ 1   ┆ 3   ┆ 1.5 │
│ 2   ┆ 4   ┆ 4.0 │
└─────┴─────┴─────┘

Use attribute lookup to create a new column expression:

>>> df.with_columns(baz=(col.foo + col.bar))
shape: (2, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ baz │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ 1   ┆ 3   ┆ 4   │
│ 2   ┆ 4   ┆ 6   │
└─────┴─────┴─────┘

Methods:

__call__	Call self as a function.
__getattr__	Create a column expression using attribute syntax.

__call__(

name: str | PolarsDataType | Iterable[str] | Iterable[PolarsDataType],

*more_names: str | PolarsDataType,

) → Expr

Call self as a function.

__getattr__(name: str) → Expr

Create a column expression using attribute syntax.

Note that this syntax does not support passing data types or multiple column names.

Parameters:

name

The name of the column to represent.

Examples

>>> from polars import col as c
>>> df = pl.DataFrame(
...     {
...         "foo": [1, 2],
...         "bar": [3, 4],
...     }
... )
>>> df.select(c.foo + c.bar)
shape: (2, 1)
┌─────┐
│ foo │
│ --- │
│ i64 │
╞═════╡
│ 4   │
│ 6   │
└─────┘