polars.exclude#

polars.exclude( columns: str | PolarsDataType | Collection[str] | Collection[PolarsDataType], *more_columns: str | PolarsDataType, ) → Expr[source]#

Represent all columns except for the given columns.

Syntactic sugar for pl.all().exclude(columns).

Parameters:

columns: The name or datatype of the column(s) to exclude. Accepts regular expression input. Regular expressions should start with ^ and end with $.
*more_columns: Additional names or datatypes of columns to exclude, specified as positional arguments.

Examples

Exclude by column name(s):

>>> df = pl.DataFrame(
...     {
...         "aa": [1, 2, 3],
...         "ba": ["a", "b", None],
...         "cc": [None, 2.5, 1.5],
...     }
... )
>>> df.select(pl.exclude("ba"))
shape: (3, 2)
┌─────┬──────┐
│ aa  ┆ cc   │
│ --- ┆ ---  │
│ i64 ┆ f64  │
╞═════╪══════╡
│ 1   ┆ null │
│ 2   ┆ 2.5  │
│ 3   ┆ 1.5  │
└─────┴──────┘

Exclude by regex, e.g. removing all columns whose names end with the letter “a”:

>>> df.select(pl.exclude("^.*a$"))
shape: (3, 1)
┌──────┐
│ cc   │
│ ---  │
│ f64  │
╞══════╡
│ null │
│ 2.5  │
│ 1.5  │
└──────┘

Exclude by dtype(s), e.g. removing all columns of type Int64 or Float64:

>>> df.select(pl.exclude([pl.Int64, pl.Float64]))
shape: (3, 1)
┌──────┐
│ ba   │
│ ---  │
│ str  │
╞══════╡
│ a    │
│ b    │
│ null │
└──────┘