Lately I have finally got around to start implementing an old project to simplify data visualizations in Julia. The idea is to combine what is generally called "Grammar of Graphics", that is to say the ability to cleanly express in a plot how to translate variables from a dataset into graphical attributes, with the new interactive plotting package Makie. This effort led to the package StatsMakie and this blog post gives a general overview on how to use it.

This post is a summary of my Google Summer of Code work on project Sputnik: a GUI toolkit based on web technology to analyze data in Julia. The project had several distinct parts: Building tools creating UI widgets in Julia Pre-GSoC state of the art While several packages existed already (namely Interact and InteractNext) to create web based widgets in Julia, they both had serious limitations. Interact could only be run in a Jupyter Notebook and was therefore not suitable to create local electron apps or to serve apps remotely.

The new Interact framework allows packages to define "interactivity recipes" taking only a small dependency on the Widgets.jl package. As an example, let's see how to add a simle recipe for interactive partition Plots in JuliaDB. JuliaDB already offers static partition plots: the user specifies the x axis, potentially the y axis, the statistics (Mean(), Extrema(), Hist(25), etc...) and the number of partition and gets the plot as output. This is very user friendly but still require a bit of typing and could be annoying for datasets with many columns, and we'd like to create a GUI for it.

Create nestable custom widgets in Julia Since the last update I have mainly been working on tools for web app creation in Julia. The work has been on two fronts: on the techical side, I transitioned from using Vue.js to using Knockout.js to sync Julia values to Javascript values on the user facing side, I've been working on a framework for custom widgets creation, so that using a @widget macro users can define their own custom widgets / recipes to visualize their custom types with simple code