This is the continuation of a blog post I published a few weeks ago on how to draw directed arrows in Tableau. The approach introduced there – I dubbed it the “linear” approach, as instead of drawing one line we created two additional lines for the arrowheads – works fine on scatterplots, but things turn out to be a bit more difficult when working with maps. This article shows how these difficulties can be overcome using some on-the-fly reprojection of our data. While I claim the arrows to be my original idea (at least I didn’t find anything similar on the web – please correct me if I’m wrong!), I can’t and won’t take credit for this one. All original work was done by Alan Eldridge and the @mapsOverlord herself, Tableau’s Sarah Battersby in an article on hexbinning on Alan’s blog back in 2015. Sarah is an absolute expert on all things map projection, as she has shown time and time again in articles on the topic on the official Tableau and Tableau Public blogs and elsewhere (as in: real scientific publications).
In a recent blog post I showed how easy it is to create maps in Tableau showing paths, basically lines connecting two points each: the start and end locations. Those can be departure and arrival airports of certain flight routes, origin and destination of refugee flows, source and sink of money transfers, … the possibilities are endless!
But now imagine a map with a line connecting two locations A and B. Or rather many such lines. What information does this hold for you? What insights can you get out of such a viz? There is one very important element still missing! That is: which direction is this connection? Sure, there are cases where direction doesn’t matter, but thinking of the three aforementioned example use cases, many times it does! So let’s give our connecting paths some directionality. Let’s take simple lines and make them arrows!
I had been planning to write this post for a long time. Not only have I been asked many times how to do this in my daily consulting work, but especially during and after my hands-on training “Stretching the Boundaries with Advanced Mapping” at our Tableau Conference On Tour 2017 in Berlin earlier this year. The question is pretty simple: How can I draw paths in Tableau? Oftentimes these are some kind of movement data, e.g. refugees or flight connections. The way to do this in Tableau is actually very easy – and some of the recently introduced features made it even easier – but it’s imperative to understand how Tableau draws lines and how the data therefore needs to be structured.
Have you ever received a spatial data set that you wanted to visualize in Tableau, only to find out the coordinates looked like this:
50°07'01.9"N 8°40'20.8"E If so, or if you’re just generally interested in geographic data and Tableau, this post is for you.
Tableau introduced the
R integration in version 8.1 back in 2013. That’s awesome because it opens up to Tableau the whole range of analytical functionality
R offers. Most of the time the R code being triggered from within Tableau is rather short, such as a regression, a call to a clustering algorithm or correlation measures. But what happens when the code you want to run out of Tableau is getting longer and more complicated? Are you still bound to the “Calculated Field” dialog window in Tableau? It’s nice but it’s tiny and has no syntax coloring or code completion for our precious