Köppen Geiger Climate Classification: Shape files in Tableau

I day dream….a lot….

Often I think about moving somewhere else in the world, I guess many people do as well, but I can obsess with details such as cost of living, practicalities of moving there. That was how I came across numbeo and I ended up creating a visualisation on their indicies such as crime rates and house price to income ratio.

Climate is probably one of the biggest factors for me, that may have something to do with living in the UK for so long, and the British probably rubbed off on me their favourite past time – weather talk -. It’s not enough to know whether it’s hot or cold, I often look at other things, such as hours of sunshine. Did you know Calgary is the sunniest city in Canada, with over 330 days of sunshine per year? Or that Lisbon receives more rainfall than London per year, but London gets more rainy days, which makes for rather gloomy stats if you end up living/working there. 🙁

In my many internet voyages looking for information about climate variation I came across the Köppen Geiger Climate Classification

From Wikipedia:

“Köppen climate classification is one of the most widely used climate classification systems. It was first published by Russian Germanclimatologist Wladimir Köppen in 1884, with several later modifications by Köppen, notably in 1918 and 1936. Later, Germanclimatologist Rudolf Geiger (1954, 1961) collaborated with Köppen on changes to the classification system, which is thus sometimes called the Köppen–Geiger climate classification system.

The Köppen climate classification system has been further modified, within the Trewartha climate classification system in the middle 1960s (revised in 1980). The Trewartha system sought to create a more refined middle latitude climate zone, which was one of the criticisms of the Koppen system (the C climate group was too broad).”

Since I first came across it, I’ve been thinking of a way to better explore the maps, but I hadn’t found a good way until now.

Here’s their map for the observed climate between 1976-2000. I’ve wondered for sometime whether it would be possible to recreate this Tableau.


A few weeks ago I spoke to Allan Walker to ask him if he thought this was possible. Allan, came back with the map already done and told me I had to use shape files. Not wanting to use Allan’s finished work, I decided to look for a way to convert shape files into a Tableau friendly file and learn in the process.

Work has been manic so this has taken a back seat for a while, until now. This week I came across a pretty neat site, Safe-Software, the company seems to build software for data integration, but I didn’t spent much time looking into it as they had an ad on Twitter which said they converted shapefiles into .tde. BINGO!!!!

The way it works is very simple, you just have to drag the files, .shp, .dbf, .shx, .prj to the convert tool or all of them zipped up (careful, if you have other files mixed up in there it won’t work), and voilá a .tde comes up the other way.

Once I got the data in a tableau form, it was just a case of creating a map and adding a few groups and labels for better user interaction. Here’s the same picture as above but in Tableau, click to view interactive version.


You’ll have noticed how big Greenland looks in Tableau, that’s because of the Mercator effect where flat projections of the world map distort the dimensions of the continents.

From Wikipedia:

“The Mercator projection portrays Greenland as larger than Australia; in actuality, Australia is more than three and a half times larger than Greenland. As on all map projections, shapes or sizes are distortions of the true layout of the Earth’s surface. The Mercator projection exaggerates areas far from the equator.”

The other troublesome task was to colour the map. I could have used the same colours as the original, but I didn’t think they were very good. Only after I’d started I realised how difficult it would be define 30 different colours that made sense in relation to the various classifications.

To finish I created a comparison between the last observed 25 years (1976-2000) vs projected data for the same period 100 years later (2076-2100) and you can see how the world is warming up. Just have a look at how much the Polar Tundra of Greenland is going to shrink.

Now whenever I want look at a place to live, I just need to find out what it’s climate is and look on the map for similar regions across the globe. For instance the majority of Portugal is classified as Csb – warm temperature, summer dry with warm summers, and I can see that the the weather in the coastal region of California is quite similar. For something further afield, Adelaide in South Australia also share the same climate characteristics, now to decide where to move to :).


Thank you for reading