Cassidoo IQofW 2020-03-09

mean_median_mode.py

# This week's question:
# Given an array of unsorted integers, return the mean, median, and mode.

import math
from functools import reduce

def mean_median_mode(N):
    print('given', N)
    SN = sorted(N)
    mean = 0
    median = 0
    mode = []
    l = len(N)
    if l == 2:
        mean = (N[0] + N[1]) / 2
        median = mean
        mode.append(N[0])
        mode.append(N[1])
    else:
        mean = reduce((lambda x, y: x + y), SN) / l
        mid = math.floor(l/2)
        if (l % 2) == 1:
            median = SN[mid]
        else:
            median = (SN[mid] + SN[mid - 1]) / 2
            if int(median) == math.floor(median):
                median = int(median)
        mode_count = [0] * (1 + SN[-1])
        # accumulate counts of each member of the set
        for i in range(l):
            mode_count[SN[i]] += 1
        # determine value of greatest occurance
        max = 0
        lSN = len(SN) - 1
        for i in range(lSN):
            if mode_count[i] > max:
                max = i
        # determine which set values have highest occurance
        for i in range(len(mode_count)):
            if mode_count[i] == mode_count[max]:
                mode.append(i)
    return { 'mean': mean, 'median': median, 'mode': mode }

N = [ 1, 2 ]
print(mean_median_mode(N))
N = [ 5, 2, 1, 4, 3 ]
print(mean_median_mode(N))
N = [ 5, 2, 1, 4, 4, 3 ]
print(mean_median_mode(N))
N = [ 5, 2, 1, 4, 4, 3, 6, 6 ]
print(mean_median_mode(N))