Python : easy way to do geometric mean in python?

Question

I wonder is there any easy way to do geometric mean using python but without using python package. If there is not, is there any simple package to do geometric mean?

Asked By: user6922072

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Source

Answer 1

just do this:

numbers = [1, 3, 5, 7, 10]


print reduce(lambda x, y: x*y, numbers)**(1.0/len(numbers))

Answered By: Liam

Answer 2

The formula of the gemetric mean is:

$geometrical mean$

So you can easily write an algorithm like:

import numpy as np

def geo_mean(iterable):
    a = np.array(iterable)
    return a.prod()**(1.0/len(a))

You do not have to use numpy for that, but it tends to perform operations on arrays faster than Python. See this answer for why.

In case the chances of overflow are high, you can map the numbers to a log domain first, calculate the sum of these logs, then multiply by 1/n and finally calculate the exponent, like:

import numpy as np

def geo_mean_overflow(iterable):
    return np.exp(np.log(iterable).mean())

Answered By: Willem Van Onsem

Answer 3

In case someone is looking here for a library implementation, there is gmean() in scipy, possibly faster and numerically more stable than a custom implementation:

>>> from scipy.stats import gmean
>>> gmean([1.0, 0.00001, 10000000000.])
46.415888336127786

Compatible with both Python 2 and 3.*

Answered By: Marcin Wojnarski

Answer 4

Starting Python 3.8, the standard library comes with the geometric_mean function as part of the statistics module:

from statistics import geometric_mean

geometric_mean([1.0, 0.00001, 10000000000.]) # 46.415888336127786

Answered By: Xavier Guihot

Answer 5

Here’s an overflow-resistant version in pure Python, basically the same as the accepted answer.

import math

def geomean(xs):
    return math.exp(math.fsum(math.log(x) for x in xs) / len(xs))

Answered By: rmmh

Answer 6

Geometric mean

import pandas as pd
geomean=Variable.product()**(1/len(Variable))
print(geomean)

Geometric mean with Scipy

from scipy import stats
print(stats.gmean(Variable))

Answered By: user12295593

Answer 7

You can also calculate the geometrical mean with numpy:

import numpy as np
np.exp(np.mean(np.log([1, 2, 3])))

result:

1.8171205928321397

Answered By: gil.fernandes

Answer 8

you can use pow function, as follows :

def p(*args):
    k=1
    for i in args:
        k*=i
    return pow(k, 1/len(args))]

>>> p(2,3)
2.449489742783178

Answered By: Bairam Komaki

Python : easy way to do geometric mean in python?

Question:

Answers:

Geometric mean

Geometric mean with Scipy