Finding the Best Distribution for Your Data with distfit

Knowing the distribution of your response variable can help modeling the data.

Introduction

Have you ever asked yourself what kind of distribution your data follows?

Knowing this is super important in data analysis and modeling. It helps with simulations, spotting unusual patterns, and figuring out risks.

Ergo, if you are not sure how to do that, there is a great tool for that: distfit. It is a Python library that helps you find the distribution that best fits your data.

What is the distribution of my data? | Image generated by AI. Meta, 2025. https://meta.ai

So, in this quick tutorial, I will show how you can figure out the best distribution for your data quickly and accurately using distfit.

Let's dive in!

What is distfit?

DistFit is a Python library that helps you figure out the probability distribution that best describes your dataset. It checks your data against 89 different theoretical distributions and tells you which one fits best.

Here’s what it can do:

• Fits lots of distributions: It can handle 89 different theoretical distributions.
• Scores the fit: It uses different methods, like RSS (Residual Sum of Squares), to see how well each distribution fits.