vastorbit.VastFrame.all¶

VastFrame.all(columns: Annotated[str | list[str], 'STRING representing one column or a list of columns'], **agg_kwargs) → TableSample¶

Applies the BOOL_AND aggregation method to the VastFrame. BOOL_AND, or Boolean AND, evaluates whether all the conditions within a set of Boolean values are true. This is useful when you need to ascertain if every condition holds. It is particularly handy when working with binary data or to ensure that all specified conditions are met within the dataset.

Parameters:

columns (SQLColumns, optional) – List of the VastColumns names. If empty, all VastColumns are used.
**agg_kwargs – Any optional parameter to pass to the Aggregate function.

Returns:

result.

Return type:

TableSample

Examples

For this example, we will use the following dataset:

import vastorbit as vo

data = vo.VastFrame(
    {
        "x": [True, False, False],
        "y": [False, False, False],
        "z": [True, True, True],
    }
)

Now, let’s use the all aggregator for specific columns.

data.all(
    columns = ["x", "y", "z"],
)

	bool_and
"x"	✗
"y"	✗
"z"	✓

Rows: 1-3 | Columns: 2

Note

All the calculations are pushed to the database.

Hint

For more precise control, please refer to the aggregate method.