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# -*- coding: utf-8 -*-

import numpy as np

# additional packages

from scipy.stats.mstats import kruskalwallis

'''

 .. currentmodule:: scipy.stats.mstats

    This module contains a large number of statistical functions that can

    be used with masked arrays.

    Most of these functions are similar to those in scipy.stats but might

    have small differences in the API or in the algorithm used. Since this

    is a relatively new package, some API changes are still possible.

'''

# Get the data

'''

#These data could be a comparison of the smog levels in four different cities.

city1 = np.array([68, 93, 123, 83, 108, 122])

city2 = np.array([119, 116, 101, 103, 113, 84])

city3 = np.array([70, 68, 54, 73, 81, 68])

city4 = np.array([61, 54, 59, 67, 59, 70])

'''

group1=[27,2,4,18,7,9]

group2=[20,8,14,36,21,22]

group3=[34,31,3,23,30,6]

list_groups=[group1,group2,group3]

def Kruskawallis_test(list_groups):

    # Perform the Kruskal-Wallis test,返回True表示有显著差异，返回False表示无显著差异

    print"Use kruskawallis test:"

    h, p = kruskalwallis(list_groups)

    print"H value:",h

    print"p",p

    # Print the results

    if p<0.05:

        print('There is a significant difference between the cities.')

        return True

    else:

        print('No significant difference between the cities.')

        return False

Kruskawallis_test(list_groups)    

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