verticapy.vDataFrame.any¶

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

Uses the BOOL_OR aggregation method in the vDataFrame. This method checks if at least one true condition exists within a set of Boolean values. It’s particularly handy for situations involving binary data or when you need to determine if any of the conditions are met.

Parameters¶

columns: SQLColumns, optional: List of the vDataColumns names. If empty, all vDataColumns are used.
**agg_kwargs: Any optional parameter to pass to the Aggregate function.

Returns¶

TableSample: result.

Examples¶

For this example, we will use the following dataset:

import verticapy as vp

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

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

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

	bool_or
"x"	1.0
"y"	0.0
"z"	1.0

Note

All the calculations are pushed to the database.

Hint

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