4 Learn about tile charts and create your own in Python
In data visualization, the size and shape of the available canvas are always important factors. This is a topic I covered in another recent article with a chart he calls the Crystal Bar Chart, which uses a two-axis approach as a means to save space.
In this article, we consider an axis-free approach that we developed to visualize sets of values as squares and save space by packing containers in the form of convex polygons or simple concave polygons. I’ve also done my best to fill this survey with code, so I hope it serves as a fun tutorial for other kinds of techniques and visualizations that may be useful.
The goal you should achieve by the end of this article is to explore standard and unconventional container shapes (shown below) in a way that optimizes available space and provides intuitive size comparisons. The idea is to present a set of values as similar shapes within their containers. Square your data!
Before diving into a new axis-less approach, consider some existing axis-based and axis-less methods to see if you can find a better competitor for measuring results. Let’s. For example, we’ll use Wikipedia’s information on the top 20 fastest animals as an example of data.¹
Axis-based data series visualization
It’s hard to compete with a sorted bar chart given the Y axis represents the values of the items. Let’s plot that first and then plot some more axis-based graphs using the vizmath package.
bar graph
# https://en.wikipedia.org/wiki/Fastest_animals (as of 1/26/2024)
# 20 fastest animals (top speed, mph)data = {…
