has_columns

has_columns(data, names)

Check if a DataFrame has the specified

Parameters

data: PolarsLazyOrDataFrame

The DataFrame to check for column presence.

names: Union[str, List[str]]

The names of the columns to check.

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, 3], "b": ["a", "b", "c"]})
>>> df.pipe(plg.has_columns, "b")
shape: (3, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ str │
╞═════╪═════╡
│ 1   ┆ a   │
│ 2   ┆ b   │
│ 3   ┆ c   │
└─────┴─────┘

>>> df.pipe(plg.has_columns, "c")
Traceback (most recent call last):
    ...
pelage.types.PolarsAssertError: Details
Error with the DataFrame passed to the check function:
--> Missing columns if the dataframe: {'c'}

>>> df.pipe(plg.has_columns, ["a", "b"])
shape: (3, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ str │
╞═════╪═════╡
│ 1   ┆ a   │
│ 2   ┆ b   │
│ 3   ┆ c   │
└─────┴─────┘