has_mandatory_values

has_mandatory_values(data, items, group_by=None)

Ensure that all specified values are present in their respective column.

Parameters

data: PolarsLazyOrDataFrame

Polars DataFrame or LazyFrame containing data to check.

items: Dict[str, list]

A dictionnary where the keys are the columns names and the values are lists that contains all the required values for a given column.

group_by: Optional[PolarsOverClauseInput] = None

When specified perform the check per group instead of the whole column, 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({"a": [1, 2]})
>>> df.pipe(plg.has_mandatory_values, {"a": [1, 2]})
shape: (2, 1)
┌─────┐
│ a   │
│ --- │
│ i64 │
╞═════╡
│ 1   │
│ 2   │
└─────┘
>>> df.pipe(plg.has_mandatory_values, {"a": [3, 4]})
Traceback (most recent call last):
...
pelage.types.PolarsAssertError: Details
Error with the DataFrame passed to the check function:
--> Missing mandatory values in the following columns: {'a': [3, 4]}

The folloing example details how to perform this checks for groups:

>>> group_df_example = pl.DataFrame(
...     {
...         "a": [1, 1, 1, 2],
...         "group": ["G1", "G1", "G2", "G2"],
...     }
... )
>>> group_df_example.pipe(plg.has_mandatory_values, {"a": [1, 2]})
shape: (4, 2)
┌─────┬───────┐
│ a   ┆ group │
│ --- ┆ ---   │
│ i64 ┆ str   │
╞═════╪═══════╡
│ 1   ┆ G1    │
│ 1   ┆ G1    │
│ 1   ┆ G2    │
│ 2   ┆ G2    │
└─────┴───────┘

>>> group_df_example.pipe(plg.has_mandatory_values, {"a": [1, 2]}, group_by="group")
Traceback (most recent call last):
...
pelage.types.PolarsAssertError: Details
shape: (1, 3)
┌───────┬───────────┬────────────────┐
│ group ┆ a         ┆ a_expected_set │
│ ---   ┆ ---       ┆ ---            │
│ str   ┆ list[i64] ┆ list[i64]      │
╞═══════╪═══════════╪════════════════╡
│ G1    ┆ [1]       ┆ [1, 2]         │
└───────┴───────────┴────────────────┘
Error with the DataFrame passed to the check function:
--> Some groups are missing mandatory values