Calculate mean, median and mode using Python

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Mean, median and mode are three statistics that measure the central tendency of numerical data. Mean is the average of sample, and median the mid point of the sample with value sorting from the lowest to the highest, and mode is the value that occur most frequently in the sample. In Python there are various data objects, they can be list, or Numpy ndarray. Here we will show how to calculate mean, median and mode for various data objects in Python.

1. Calculating mean, median and mode for list in Python

#mean
testlist = [5,8,22,4,5,13,7,266,1,8,23,14,32,4,7,8,6,9,23,7,8]
def Average(lst):
    return sum(lst) / len(lst)

ave = Average(testlist)      #mean
ave
Out[2]: 22.857142857142858

#median

testlist.sort()
mid = len(testlist) // 2
midn = (testlist[mid] + testlist[-mid-1]) / 2
midn

Out[3]: 8.0

#mode

from statistics import mode
mode(testlist)

Out[4]: 8

2. Calculation of Mean, median and mode for Numpy array

import numpy as np

#mean
salary = np.random.randint(38, high=60, size=1500)
np.mean(salary) 
Out[5]: 48.415333333333336

#median
np.median(salary) 
Out[6]: 48.0

#mode
from scipy import stats
stats.mode(salary)
Out[9]: ModeResult(mode=array([58]), count=array([85]))

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