# \[ANN\] BayesHistogram.jl - for optimal histogramming

**URL:** <https://discourse.julialang.org/t/ann-bayeshistogram-jl-for-optimal-histogramming/89454>\
**Category:** Package Announcements\
**Created:** [October 28, 2022, 4:39pm UTC](https://discourse.julialang.org/t/ann-bayeshistogram-jl-for-optimal-histogramming/89454 "2022-10-28T16:39:37Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![francesco.alemanno](https://avatars.discourse-cdn.com/v4/letter/f/e8c25b/32.png) [@francesco.alemanno](https://discourse.julialang.org/u/francesco.alemanno)\
**Post date:** [October 28, 2022, 4:39pm UTC](https://discourse.julialang.org/t/ann-bayeshistogram-jl-for-optimal-histogramming/89454/1 "2022-10-28T16:39:37Z")

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Hello everyone!  
@jling and I have developed this package in order to satisfy those who hate the binning rules found in most analysis/plotting libraries.

If you’ve ever found yourself writing `bins=:fd`, `:sturges`, `:scott`, and so on, without ever finding a rule that gives you the right compromise between resolution and noise, then you’ve landed in the right thread.

Come take a look at BayesHistogram:

> **[GitHub - francescoalemanno/BayesHistogram.jl: pure Julia package for optimal...](https://github.com/francescoalemanno/BayesHistogram.jl)**
>
> pure Julia package for optimal histogram binning, based on piecewise constant model. - GitHub - francescoalemanno/BayesHistogram.jl: pure Julia package for optimal histogram binning, based on piece...

Thank you!