Compatible with Python 3.7, and 3.8, 3.9

The fitter package is a Python library for fitting probability distributions to data. It provides a simple and intuitive interface for estimating the parameters of different types of distributions, including continuous and discrete distributions. With fitter, you can easily fit a variety of distributions to your data and compare the fit of different distributions to choose the best-fitting one. The package is designed to be easy to use and requires minimal setup, making it a useful tool for data scientists and statisticians working with probability distributions.

pip install fitter

fitter is also available on conda (bioconda channel):

conda install fitter

A standalone application (very simple) is also provided and works with input CSV files:

fitter fitdist data.csv --column-number 1 --distributions gamma,normal

It creates a file called fitter.png and a log fitter.log

First, let us create a data samples with N = 10,000 points from a gamma distribution:

from scipy import stats
data = stats.gamma.rvs(2, loc=1.5, scale=2, size=10000)

Now, without any knowledge about the distribution or its parameter, what is the distribution that fits the data best ? Scipy has 80 distributions and the Fitter class will scan all of them, call the fit function for you, ignoring those that fail or run forever and finally give you a summary of the best distributions in the sense of sum of the square errors. The best is to give an example:

from fitter import Fitter
f = Fitter(data)
f.fit()
# may take some time since by default, all distributions are tried
# but you call manually provide a smaller set of distributions 
f.summary()

See the online documentation for details.

Setting up and maintaining Fitter has been possible thanks to users and contributors. Thanks to all: