Let’s Make a Bubble Map
bost.ocks.org
bost.ocks.org
In the talk, he emphasized the importance of incorporating Makefiles into the workflow more than the text of this tutorial does. It basically documents exactly where you got the data from and what basic transformations you applied to it. The NYT uses this to streamline their process of developing graphics--so if, say, a graphic from six months ago needs to be revisited again for a new story on the same topic, nobody has to fumble around trying to remember where the data came from, etc. I got the impression that this was the advice of someone who had been burned by not following it in the past.
Super cool visualization, and great that you put the code on GitHub for everybody to see.
For anybody interested in the code behind:
[1] https://shan.io/bower/ [2] http://bl.ocks.org/mbostock/4060606 [3] http://www.dannydorling.org/wp-content/files/dannydorling_pu... [4] http://www.jasondavies.com/maps/dorling-world/
I'd say the choice between choropleth and dorling maps depends on what sort of data you want to present, or am I missing something?
What I mean is, if the bubble size represents a different information from the color depth (i.e. figure 10, page 12 f the dorling paper shows population as a bubble, AFAICT) than it makes sense, but if it's just another encoding of already represented information it seems weird.
I.e. in the "dorling world" map I have lost plenty of informations (I have no idea what northern and eastern europe countries are what anymore, while I can tell them at a glance on a normal map) but I have not gained anything.
The east coast has a much higher density of small counties, giving the NY area a look very different from that around LA.
Compare the Houston and Dallas metro areas - Houston has a very distinct large bubble, while Dallas has more overlapping smaller bubbles which make it look smaller, even though it contains more people.