scipy stats.gamma() | Python

sciPy stats.hmean() | Python

Last Updated : 07 Feb, 2019

scipy.stats.hmean(array, axis=0, dtype=None) calculates the harmonic mean of the array elements along the specified axis of the array (list in python). It's formula -

Parameters : array: Input array or object having the elements to calculate the harmonic mean. axis: Axis along which the mean is to be computed. By default axis = 0 dtype: Optional. It sets the type of returned element. Returns : Harmonic mean of the array elements based on the set parameters.

Code #1:

Python3 1==

# Harmonic Mean 

from scipy.stats.mstats import hmean 
arr1 = hmean([1, 3, 27]) 
 
print("Harmonic Mean is :", arr1)

Output:

Harmonic Mean is : 2.18918918919

Code #2: With multi-dimensional data

Python3 1==

# Harmonic Mean 

from scipy.stats.mstats import hmean
arr1 = [[1, 3, 27], 
        [3, 4, 6], 
        [7, 6, 3], 
        [3, 6, 8]] 
 
print("\nHarmonic Mean is :", hmean(arr1)) 

# using axis = 0
print("\nHarmonic Mean is with default axis = 0 : \n", 
      hmean(arr1, axis = 0))

# using axis = 1
print("\nHarmonic Mean is with default axis = 1 : \n", 
      hmean(arr1, axis = 1))

Output:

Harmonic Mean is : [ 2.21052632  4.36363636  6.04195804]

Harmonic Mean is with default axis = 0 : 
 [ 2.21052632  4.36363636  6.04195804]

Harmonic Mean is with default axis = 1 : 
 [ 2.18918919  4.          4.66666667  4.8       ]

scipy stats.gamma() | Python

V

vishal3096

Improve

Article Tags :

Practice Tags :

python

Similar Reads

scipy stats.erlang() | Python

scipy.stats.erlang() : is an Erlang continuous random variable that is defined with a standard format and some shape parameters to complete its specification. it is a special case of the Gamma distribution. Parameters : q : lower and upper tail probability x : quantiles loc : [optional] location par

scipy stats.hypsecant() | Python

scipy.stats.hypsecant() is an hyperbolic secant continuous random variable. to complete its specificaitons it is defined with a standard format and some shape parameters. The probability density is defined in the â€œstandardizedâ€ form. Parameters : -> α : scale -> β : shape -> μ

sciPy stats.alpha() | Python

scipy.stats.alpha() is an alpha continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles a : shape parameter loc : [optional] location parameter. Default = 0 scale : [opt

scipy stats.gamma() | Python

scipy.stats.gamma() is an gamma continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : -> q : lower and upper tail probability -> x : quantiles -> loc : [optional]location parameter. Default = 0 -> scale : [

scipy.stats.expon() | Python

scipy.stats.expon() is an exponential continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles loc : [optional] location parameter. Default = 0 scale : [optional] scale p

scipy stats.chi() | Python

scipy.stats.chi() is an chi continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles loc : [optional] location parameter. Default = 0 scale : [optional] scale parameter.

scipy stats.f() | Python

scipy.stats.f() is an F continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability a, b : shape parameters x : quantiles loc : [optional] location parameter. Default = 0 scale : [optiona

scipy stats.halfnorm() | Python

scipy.stats.halfnorm() is an Half-normal continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : -> q : lower and upper tail probability -> x : quantiles -> loc : [optional]location parameter. Default = 0 ->

scipy stats.dgamma() | Python

scipy.stats.dgamma () is an double gamma continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles loc : [optional]location parameter. Default = 0 scale : [optional]scale

scipy.stats.chi2() | Python

scipy.stats.chi2() is an chi square continuous random variable that is defined with a standard format and some shape parameters to complete its specification. Parameters : q : lower and upper tail probability x : quantiles loc : [optional]location parameter. Default = 0 scale : [optional]scale param