polars.datatypes.List

class polars.datatypes.List(
    inner: PolarsDataType | PythonDataType,
)

Variable length list type.

Parameters:

inner

The DataType of the values within each list.

Examples

>>> df = pl.DataFrame(
...     {
...         "integer_lists": [[1, 2], [3, 4]],
...         "float_lists": [[1.0, 2.0], [3.0, 4.0]],
...     }
... )
>>> df
shape: (2, 2)
┌───────────────┬─────────────┐
│ integer_lists ┆ float_lists │
│ ---           ┆ ---         │
│ list[i64]     ┆ list[f64]   │
╞═══════════════╪═════════════╡
│ [1, 2]        ┆ [1.0, 2.0]  │
│ [3, 4]        ┆ [3.0, 4.0]  │
└───────────────┴─────────────┘

__init__(
    inner: PolarsDataType | PythonDataType,
) → None

Methods

__init__(inner)
base_type()	Return this DataType's fundamental/root type class.
from_python(py_type)	Return the Polars data type corresponding to a given Python type.
is_(other)	Check if this DataType is the same as another DataType.
is_decimal()	Check whether the data type is a decimal type.
is_extension()	Check whether the data type is an extension type.
is_float()	Check whether the data type is a floating point type.
is_integer()	Check whether the data type is an integer type.
is_nested()	Check whether the data type is a nested type.
is_numeric()	Check whether the data type is a numeric type.
is_object()	Check whether the data type is an object type.
is_signed_integer()	Check whether the data type is a signed integer type.
is_temporal()	Check whether the data type is a temporal type.
is_unsigned_integer()	Check whether the data type is an unsigned integer type.
to_dtype_expr()	Return a DataTypeExpr with a static DataType.
to_python()	Return the Python type corresponding to this Polars data type.

Attributes

inner