mutually_exclusive_ranges

mutually_exclusive_ranges(data, low_bound, high_bound, group_by=None)

Ensure that the specified columns contains no overlapping intervals.

Parameters

data: PolarsLazyOrDataFrame

Data to check

low_bound: str

Name of column containing the lower bound of the interval

high_bound: str

Name of column containing the higher bound of the interval

group_by: IntoExpr | Iterable[IntoExpr] = None

Parameter compatible with .over() function to split the check by groups, by default None

Returns

Name	Type	Description
	PolarsLazyOrDataFrame	The original polars DataFrame or LazyFrame when the check passes

Examples

>>> import polars as pl
>>> import pelage as plg
>>> df = pl.DataFrame(
...     [
...         [1, 2],
...         [3, 4],
...     ],
...     schema=["a", "b"], orient="row"
... )
>>> df.pipe(plg.mutually_exclusive_ranges, low_bound="a", high_bound="b")
shape: (2, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 2   │
│ 3   ┆ 4   │
└─────┴─────┘

>>> df = pl.DataFrame(
...     [
...         [1, 3],
...         [2, 4],
...         [5, 7],
...         [6, 8],
...         [9, 9],
...     ],
...     schema=["a", "b"],
...     orient="row",
... )
>>> df.pipe(plg.mutually_exclusive_ranges, low_bound="a", high_bound="b")
Traceback (most recent call last):
...
pelage.types.PolarsAssertError: Details
shape: (4, 3)
┌───────┬─────┬─────┐
│ index ┆ a   ┆ b   │
│ ---   ┆ --- ┆ --- │
│ u32   ┆ i64 ┆ i64 │
╞═══════╪═════╪═════╡
│ 0     ┆ 1   ┆ 3   │
│ 1     ┆ 2   ┆ 4   │
│ 2     ┆ 5   ┆ 7   │
│ 3     ┆ 6   ┆ 8   │
└───────┴─────┴─────┘
Error with the DataFrame passed to the check function:
--> There were overlapping intervals:
DataFrame was sorted by: ['a', 'b'],
Interval columns: low_bound='a', high_bound='b'