wilcoxon_test_fl()

The function wilcoxon_test_fl() performs the Wilcoxon Test.

Note

• wilcoxon_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 wilcoxon_test_fl()(data, test_statistic,p_value)

Arguments

• data: The name of the column containing the 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

wilcoxon_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 wilcoxon_test_fl = (tbl:(*), data:string, test_statistic:string, p_value:string)
{
    let kwargs = pack('data', data, 'test_statistic', test_statistic, 'p_value', p_value);
    let code = ```if 1:
        from scipy import stats
        data = kargs["data"]
        test_statistic = kargs["test_statistic"]
        p_value = kargs["p_value"]
        def func(row):
            statistics = stats.wilcoxon(row[data])
            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) [
'Test #1', dynamic([23.64, 20.57, 20.42]),
'Test #2', dynamic([20.85, 21.89, 23.41]),
'Test #3', dynamic([20.13, 20.5, 21.7, 22.02])
]
| extend test_stat= 0.0, p_val = 0.0
| invoke wilcoxon_test_fl('sample1', '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 = "Wilcoxon Test")
wilcoxon_test_fl(tbl:(*), data:string, test_statistic:string, p_value:string)
{
    let kwargs = pack('data', data, 'test_statistic', test_statistic, 'p_value', p_value);
    let code = ```if 1:
        from scipy import stats
        data = kargs["data"]
        test_statistic = kargs["test_statistic"]
        p_value = kargs["p_value"]
        def func(row):
            statistics = stats.wilcoxon(row[data])
            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) [
'Test #1', dynamic([23.64, 20.57, 20.42]),
'Test #2', dynamic([20.85, 21.89, 23.41]),
'Test #3', dynamic([20.13, 20.5, 21.7, 22.02])
]
| extend test_stat= 0.0, p_val = 0.0
| invoke wilcoxon_test_fl('sample1', 'test_stat', 'p_val')

id             sample1        test_stat        p_val
Test #1, [23.64, 20.57, 20.42], 0, 0.10880943004054568
Test #2, [20.85, 21.89, 23.41], 0, 0.10880943004054568
Test #3, [20.13, 20.5, 21.7, 22.02], 0, 0.06788915486182899