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A tool to fit data to many distributions and get the best one(s)

Project description Documentation Status

Compatible with Python 3.7, and 3.8, 3.9

What is it ?

The fitter package is a Python library used for fitting probability distributions to data. It provides a straightforward and and intuitive interface to estimate parameters for various types of distributions, both continuous and discrete. Using fitter, you can easily fit a range of distributions to your data and compare their fit, aiding in the selection of the most suitable distribution. The package is designed to be user-friendly 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

From Python shell

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)
# may take some time since by default, all distributions are tried
# but you call manually provide a smaller set of distributions

See the online documentation for details.


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





  • replace logging with loguru

  • main application update to add missing –output-image option and use rich_click

  • replace pkg_resources with importlib




  • fixed regression putting back joblib


  • removed easydev and replaced by tqdm for progress bar

  • progressbar from tqdm also allows replacement of joblib need





  • remove vervose arguments in Fitter class. Using the logging module instead

  • the has now a progress bar

  • add a standalone application called … fitter (see the doc)


was not released


adding new class called histfit (see documentation)



  • Fixed deprecated warning

  • fitter is now in readthedocs at



  • summary() now returns the dataframe (instead of printing it)



add manifest to fix missing source in the pypi repository.

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