vastorbit.VastFrame.min¶

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

Aggregates the VastFrame by applying the MIN aggregation, which calculates the minimum value, for the specified columns. This aggregation provides insights into the lowest values within the dataset, aiding in understanding the data distribution.

Parameters:

columns (SQLColumns, optional) – List of the VastColumns names. If empty, all numerical 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": [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 minimum for specific columns.

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

	min
"x"	1.0
"y"	1.0
"z"	1.0

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.