levene_test_fl()

The function levene_test_fl() performs the Levene Test.

Note

• levene_test_fl() is a UDF (user-defined function). For more information, see usage.
• This function contains inline Python and requires enabling the python() plugin on the cluster.

Syntax

T | invoke levene_test_fl()(data1, data2, test_statistic,p_value)

Arguments

• data1: The name of the column containing the first set of data to be used for the test.
• data2: The name of the column containing the second set of data to be used for the test.
• test_statistic: The name of the column to store test statistic value for the results.
• p_value: The name of the column to store p-value for the results.

Usage

levene_test_fl() is a user-defined tabular function, to be applied using the invoke operator. You can either embed its code in your query, or install it in your database. There are two usage options: ad hoc and persistent usage. See the below tabs for examples.

Ad hoc

For ad hoc usage, embed its code using the let statement. No permission is required.

<!-- let levene_test_fl = (tbl:(*), data1:string, data2:string, test_statistic:string, p_value:string)
{
    let kwargs = pack('data1', data1, 'data2', data2, 'test_statistic', test_statistic, 'p_value', p_value);
    let code = ```if 1:
        from scipy import stats
        data1 = kargs["data1"]
        data2 = kargs["data2"]
        test_statistic = kargs["test_statistic"]
        p_value = kargs["p_value"]
        def func(row):
            statistics = stats.levene(row[data1], row[data2])
            return statistics[0], statistics[1]
        result = df
        result[[test_statistic, p_value]]  = df.apply(func, axis=1, result_type = "expand")
    ```;
    tbl
    | evaluate python(typeof(*), code, kwargs)
}
;
datatable(id:string, sample1:dynamic, sample2:dynamic) [
'Test #1', dynamic([23.64, 20.57, 20.42]), dynamic([27.1, 22.12, 33.56]),
'Test #2', dynamic([20.85, 21.89, 23.41]), dynamic([35.09, 30.02, 26.52]),
'Test #3', dynamic([20.13, 20.5, 21.7, 22.02]), dynamic([32.2, 32.79, 33.9, 34.22])
]
| extend test_stat= 0.0, p_val = 0.0
| invoke levene_test_fl('sample1', 'sample2', 'test_stat', 'p_val')

Persistent

For persistent usage, use .create function. Creating a function requires database user permission.

One-time installation

.create-or-alter function with (folder = "Packages\\Stats", docstring = "Levene Test")
levene_test_fl(tbl:(*), data1:string, data2:string, test_statistic:string, p_value:string)
{
    let kwargs = pack('data1', data1, 'data2', data2, 'test_statistic', test_statistic, 'p_value', p_value);
    let code = ```if 1:
        from scipy import stats
        data1 = kargs["data1"]
        data2 = kargs["data2"]
        test_statistic = kargs["test_statistic"]
        p_value = kargs["p_value"]
        def func(row):
            statistics = stats.levene(row[data1], row[data2])
            return statistics[0], statistics[1]
        result = df
        result[[test_statistic, p_value]]  = df.apply(func, axis=1, result_type = "expand")
    ```;
    tbl
    | evaluate python(typeof(*), code, kwargs)
}

Usage

datatable(id:string, sample1:dynamic, sample2:dynamic) [
'Test #1', dynamic([23.64, 20.57, 20.42]), dynamic([27.1, 22.12, 33.56]),
'Test #2', dynamic([20.85, 21.89, 23.41]), dynamic([35.09, 30.02, 26.52]),
'Test #3', dynamic([20.13, 20.5, 21.7, 22.02]), dynamic([32.2, 32.79, 33.9, 34.22])
]
| extend test_stat= 0.0, p_val = 0.0
| invoke levene_test_fl('sample1', 'sample2', 'test_stat', 'p_val')

id             sample1                    sample2                test_stat          p_val
Test #1, [23.64, 20.57, 20.42], [27.1, 22.12, 33.56], 1.5587395987367387, 0.27993504690044563
Test #2, [20.85, 21.89, 23.41], [35.09, 30.02, 26.52], 1.6402495788130482, 0.26950872948841353
Test #3, [20.13, 20.5, 21.7, 22.02], [32.2, 32.79, 33.9, 34.22], 0.0032989690721642395, 0.95606240301049072