Thread by @jburnmurdoch

New project:

A “Bar Chart Race” animation showing the changing ranks of the 10 biggest cities in the world since 1500.

Fascinating to watch giant cities vanish after falling in conquests, and amazing that three UK cities were in the top 8 in the late 1800s.

Notes:
• Full code for the animation here on @observablehq observablehq.com/@johnburnmurdo…
• I’ve tried to build this in a fairly reproducible way, such that you give it a dataset containing entity, year, value, and it does the rest
• Feedback welcome!
#dataviz

Data:
• Pre-1900 I’m using @nasaearthdata’s “Historical Urban Population, 3700 BC  to  2000” sedac.ciesin.columbia.edu/data/set/urban…
• Post-1900 it’s that merged with data from the UN and Demographia on urban agglomerations data.london.gov.uk/dataset/global…

For anyone wondering what happened to Vijayanagara (fell from 3rd to nowhere in 1565):

‘The Sultanate army reached Vijayanagara, looted, destroyed and burnt it to ruins over several months. Urban Vijayanagara was abandoned and remained in ruins ever since. It never recovered.’

For those wanting to make their own Bar Chart Race™, this simple one that I made earlier is a good place to start observablehq.com/@johnburnmurdo…

Swap out my dataset for anything with columns for `year` and `value`, write a title, and the rest will pretty much take care of itself.

For optimal performance, I recommend calculating another field — `lastValue` — which is just a one-year lagged version of the `value` column, as this makes the intra-year animations much slicker, but it’ll work well enough without.

Courtesy of my wonderful colleague @tomhannen, we now have a new version of the cities animation up on the @FinancialTimes, including a voiceover from yours truly, suitably exciting music and a pointer to how to make your own animations using @observablehq ft.com/video/83703ffe…