Statistics: Kurtosis & Describe

stats_01.py

from collections import namedtuple
import statistics as st
from collections import Counter

def kurtosis(a):
    N = len(a)
    mean = st.mean(a)
    sd = st.variance(a)**0.5
    kurt = sum([(i-mean)**4 for i in a])/N/sd**4
    return kurt

DescribeResults = namedtuple("DescribeResults", 
                            ("nobs", "minmax", "mean", "variance", 
                            "median", "skewness", "kurtosis"))
def describe(a):
    nobs = len(a)
    minmax = (min(a), max(a))
    mean = st.mean(a)
    var = st.variance(a)
    med = st.median(a)
    mo = Counter(a).most_common()[0][0]
    skewness = (mean-mo)/var**0.5
    kurt = kurtosis(a)
    return DescribeResults(nobs, minmax, mean, var, med, skewness, kurt)

if __name__ == "__main__":
    a = [1, 2, 10]
    print(describe(a))

stats_02.py

import statistics as st
from collections import Counter

def kurtosis(a):
    N = len(a)
    mean = st.mean(a)
    sd = st.variance(a)**0.5
    kurt = sum([(i-mean)**4/N for i in a])/sd**4
    return kurt

def describe(a):
    nobs = len(a)
    minmax = (min(a), max(a))
    mean = st.mean(a)
    var = st.variance(a)
    med = st.median(a)
    mo = Counter(a).most_common()[0][0]
    skewness = (mean-mo)/var**0.5
    kurt = kurtosis(a)
    return nobs, minmax, mean, var, med, skewness, kurt


if __name__ == "__main__":
    a = [1,2,3,4,5]
    print(describe(a))