Scipy.stats.gumbel_l() | Python

Scipy is a Python library that is used for scientific computing and technical computing. It provides several statistical distributions functions along with a lot of other useful functions. One such function is stats.gumbel_l(). In this article, we will discuss the stats.gumbel_l() function and how to use it in Python.

What is Gumbel left-skewed distribution?

Gumbel left-skewed distribution also known as the Type-III Gumbel distribution is a probability distribution that is used to model the minimum value of a set of random variables. This distribution is similar to the Gumbel right-skewed distribution, except that it is left-skewed.

How to use stats.gumbel_l() in Python?

The stats.gumbel_l() function can be used to generate random numbers from the Gumbel left-skewed distribution. This function takes two arguments:

• loc: The mean of the distribution.
• scale: The standard deviation of the distribution.

Here is an example code snippet for generating random numbers using the stats.gumbel_l() function:

import numpy as np
from scipy.stats import gumbel_l

# Generate random numbers from Gumbel left-skewed distribution
loc = 0  # mean of the distribution
scale = 1  # standard deviation of the distribution
random_numbers = gumbel_l.rvs(loc=loc, scale=scale, size=10)

# Print the generated random numbers
print(random_numbers)

In the above code, we have imported the numpy and scipy.stats libraries. We have then specified the mean and standard deviation of the Gumbel left-skewed distribution using the loc and scale parameters. We have then generated 10 random numbers from this distribution using the gumbel_l.rvs() function and printed them.

Conclusion

In this article, we have discussed the Gumbel left-skewed distribution and how to use the stats.gumbel_l() function to generate random numbers from this distribution. We hope this article helps you in your future data analysis projects in Python.