Connecting the Dots – Visualizing Paths in Tableau

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.

The OpenFlights.org route network visualized in Tableau

The OpenFlights.org route network visualized in Tableau

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Using Coordinate Data in Degrees (DMS) Format in Tableau

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.

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Population Lines - the Tableau Edition

Population Lines – the Tableau Edition

In 2013 Dr. James Cheshire from the Centre for Advanced Spatial Analysis at the University College London created a data visualization that was critically acclaimed back then and saw something of a renaissance a few weeks ago when a modified version by Henrik Lindberg made its way onto the Reddit front page. I had been mesmerized by the viz from the beginning, so when it reappeared in my blog reader I decided I had to try reproducing it in Tableau.

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The last available report per BookID is marked

Reporting Self-Updating Data Using Wildcard Union in Tableau

Imagine you have some kind of system that produces reports on your data – for this example I randomly decided to use bookings for events -, and these reports are published on a regular schedule. Now you want to see two things in your report:

  1. The current status of participants per event – both for past events (i.e. the actual number of participants) and for future events (i.e. the current number of people registered).
  2. An overview of how the number of people registered changed over time.

Also, your source system is publishing these data as .csv files. How can this be done?

Well, very easily using the new wildcard union feature introduced in Tableau Desktop 10.1! Read on to see how this can be done.

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Using Tokyo

In the introduction to the UN HABITAT report State of the World’s Cities 2012/2013: Prosperity of Cities it is written:

“As the world moves into the urban age, the dynamism and intense vitality of cities become even more prominent. A fresh future is taking shape, with urban areas around the world becoming not just the dominant form of habitat for humankind, but also the engine-rooms of human development as a whole. This ongoing evolution can be seen as yet another assertion, albeit on a larger scale, of the time-honoured role of cities as centres of prosperity. In the 21st as in much earlier centuries, people congregate in cities to realize aspirations and dreams, fulfil needs and turn ideas into realities.”
(United Nations 2012, v)

I could not agree more, and this is one of the reasons that I was captivated by cities from an early age, long before I started my academic career – or even had an idea of what an academic career is, for that matter. Cities interest me, cities fascinate me, and cities defined me. Having lived in Munich, Frankfurt, and Tokyo, and having visited many other amazing specimen worldwide has definitely had an impact on me and taught me many things. Studying cities is never boring and continues to surprise and astonish me on a regular basis.

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