How I Made That: Searchable Time Series Chart
When there are too many options or categories, it can be helpful to make the data searchable.
This was the last chart in a series of charts about shifting proportions of the sexes. After focusing on specific aspects of the data, I wanted to provide a way for people to look up their own jobs or any other job they were interested in.
With over 450-ish occupations, listing all the jobs or putting them in a dropdown menu didn’t make sense. It would take up too much space. A search bar on the other hand, lets someone immediately zoom in, which brought me to this:
This is how I made that.
To access this full tutorial and download the source code you must be a member. (If you are already a member, log in here.)
Get instant access to this tutorial and over a hundred more, plus courses, guides, and additional resources.
You'll get unlimited access to hundreds of hours worth of step-by-step visualization courses and tutorials for insight and presentation — all while supporting an independent site. Source code and data is included so that you can more easily apply what you learn in your own work.
The tutorials are very helpful to move from "Oooo, cool!" to how to actually DO the cool.
Members also recieve a weekly newsletter, The Process. Keep up-to-date on visualization tools, the rules, and the guidelines and how they all work together in practice.
See samples of everything you gain access to:
More Tutorials See All →
How to Make Dot Density Maps in R
Choropleth maps are useful to show values for areas on a map, but they can be limited. In contrast, dot density maps are sometimes better for showing distributions within regions.
How to Hand Edit R Plots in Inkscape
You can control graph elements with code as you output things from R, but sometimes it is easier to do it manually. Inkscape, an Open Source alternative to Adobe Illustrator, might be what you are looking for.
How to Make Frequency Trails in R
Also known as ridgeline plots, the method overlaps time series for a 3-D-ish view of the data. While perhaps not the most visually efficient, the allure is undeniable.