Rich Country, Rich Citizens? | #MakeOverMonday 2020 Week 7

A trifecta of MakeOverMondays complete! This time I went back to the bar for a visual essay examining country wealth. The dataset showed 2019 wealth values per country and was visualised by Credit Suisse like so:

Which is actually a pretty inviting visual just on its own, though proves to be difficult to interpret if you’re interested in small countries.

After some playing around, I mixed in some population data and began to look at it from the point of view of a citizen. Does living in a rich country mean you might be rich? I then brought in data … Read the rest

A new take on international education student enrolment data by region: Experimenting with Tableau mapping

The Department of Education, Skills and Employment provide the international education sector in Australia with a large amount of very useful data on international students studying within our borders. Much of it is provided in a number of formats – from pivot tables made available through Austrade’s Market Information Package to a range of data visualisations on the Department’s website itself.

Being a data visualisation aficionado and and analytics working in this field for nearly nine years now, I have used these resources heavily. However, one area that I had not particularly visited often was the Department’s international student Read the rest

Americans at Peace and War | #MakeOverMonday 2020 Week 6

Two weeks in a row now that I’ve managed to get something done for MakeOverMonday. This week’s challenge had us rearranging the visuals of this Washington Post article by Philip Bump titled “Nearly a quarter of Americans have never experienced the U.S. in peace time“.

I’d been procrastinating all week, checking out many great vizzes done by the Tableau community when all of a sudden an alternate design came to me like a bolt from the blue. How about doing something with the inverse of the provided data? 

The data provided simply a ‘birth year’ dimension and a … Read the rest

Leave our Bond alone? | #MakeOverMonday 2020 Week 5

So I finally managed to grab some free time to contribute something to the MakeOverMonday social data project. I’ve been a fan for many years and have often wanted to contribute – and finally I’ve done something that I’m relatively happy with. This is my data story analysing potential attitudes to changes in the James Bond character in terms of Brexit affiliations.

You can also … Read the rest

Tableau tricks: Adding colour to geomaps by continent or region

Tableau is a great tool for data visualisation. One major selling point of the product is its excellent mapping tools which make building visualisation fun and interpreting data a hell of a lot easier than in a flat table.

Recently, I was attempting to replicate a neat visualisation I saw on the Guardian’s data blog. Simply put, I wanted to measure some data by country but colour code the data by region as well. A trip through Tableau’s detailed online help and forums only turned up solutions that were either way too complicated or not quite suited to what … Read the rest