vastorbit.VastFrame.count_percent¶

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

Performs aggregation on the VastFrame using a list of aggregate functions, including count and percent. The count function computes the number of non-missing (non-null) values within the dataset, providing us with an understanding of the data’s completeness.

On the other hand, the percent function calculates the percentage of non-missing values in relation to the total dataset size, offering insights into data integrity and completeness as a proportion.

Parameters:

columns (SQLColumns, optional) – List of VastColumn names. If empty, all VastColumns are used.
sort_result (bool, optional) – If set to True, the result is sorted.
desc (bool, optional) – If set to True and sort_result is set to True, the result is sorted in descending order.
**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 count percentage for specific columns.

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

	count	percent
"y"	7.0	87.5
"z"	6.0	75.0
"x"	4.0	50.0

Rows: 1-3 | Columns: 3

Note

All the calculations are pushed to the database.

Hint

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