verticapy.vDataFrame.sum¶

vDataFrame.sum(columns: Annotated[str | list[str], 'STRING representing one column or a list of columns'] | None = None, **agg_kwargs) → TableSample¶

Aggregates the vDataFrame using SUM aggregation, which computes the total sum of values for the specified columns, providing a cumulative view of numerical data.

Parameters¶

columns: SQLColumns, optional: List of the vDataColumns names. If empty, all numerical 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": [1, 2, 4, 9, 10, 15, 20, 22],
        "y": [1, 2, 1, 2, 1, 1, 2, 1],
        "z": [10, 12, 2, 1, 9, 8, 1, 3],
    }
)

Now, let’s calculate the sum for specific columns.

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

	sum
"x"	83.0
"y"	11.0
"z"	46.0

Note

All the calculations are pushed to the database.

Hint

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