Regional population structures at a glance

[This article was first published on Ilya Kashnitsky, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

fig0

I am happy to announce that our paper is published today in The Lancet.

Kashnitsky, I., & Schöley, J. (2018). Regional population structures at a glance. The Lancet, 392(10143), 209–210. https://doi.org/10.1016/S0140-6736(18)31194-2

At a glance

Demographic history of a population is imprinted in its age structure. A meaningful representation of regional population age structures can tell numerous demographic stories – at a glance. To produce such a snapshot of regional populations, we use an innovative approach of ternary colour coding.

Here is the map:

fig1

We let the data speak colours

With ternary colour coding, each element of a three-dimensional array of compositional data is represented with a unique colour. The resulting colours show direction and magnitude of deviations from the centrepoint, which represents the average age of the European population, and is dark grey. The hue component of a colour encodes the direction of deviation: yellow indicates an elderly population (>65 years), cyan indicates people of working age (15–64 years), and magenta indicates children (0–14 years).

The method is very flexible, and one can easily produce these meaningful colours using our R package tricolore. Just explore the capabilities of the package in a built-in shiny app using the following lines of code:

install.packages("ticolore")
library(tricolore)
DemoTricolore()

Replication materials at github

Folow us on Twitter: @ikahhnitsky, @jschoeley.

SEE ALSO

To leave a comment for the author, please follow the link and comment on their blog: Ilya Kashnitsky.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)