vastorbit.VastColumn.std¶

VastColumn.std() → Annotated[bool | float | str | timedelta | datetime, 'Python Scalar']¶

Aggregates the VastFrame using STDDEV aggregation (Standard Deviation), providing insights into the spread or variability of data for the input column. The standard deviation is a measure of how much individual data points deviate from the mean, helping to assess data consistency and variation.

Returns:: std
Return type:: PythonScalar

Examples

For this example, let’s generate a dataset and calculate the standard deviation of a column:

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],
    }
)
data["x"].std()

Note

All the calculations are pushed to the database.

Hint

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