It’s all about the bike: First Tableau #IronQuest submission

COVID-19 induced isolation has been good to me in terms of getting time to do some Tableau work. I had my heart set on completing my first ever Iron Quest submission. This months theme was the “Quantified Self”. As soon as I read about the theme, I immediately knew what I wanted to visualise: the cycling history.

What’s Iron Quest?

For those not in the know Iron Quest is an initiative begun by Sarah Bartlett. Sarah describes it on her website as:

Iron Quest is a monthly community-led data visualization project which follows a similar format to

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#MakeoverMonday 2020 Week 21: Revenues by music format over time

I’m back in the #MakeoverMonday fold after a break for a number of months. Being a former music journalist I felt obligated to participate in this week’s challenge which involved 40 years of data on US music sales by format. Here’s the original visualisation from an article by Nick Routley.

While the original visualisation was actually quite good and informative, I did give myself an hour or two to have a play in Tableau Public as well as the open-source GNU Image Manipulation Program (with the problematic acronym) where I had a go at designing a custom logo based … Read the rest

COVID19 and International Students: ABS Overseas Travel Statistics: Total Movement by Visa Group

Randomly, I was looking for some arrival and departure data for international students in Australia, seeking to test the theory that there had not been any mass scale departures of overseas students since Australia declared a COVID19 a pandemic.

Somewhat conincidentally, Professor Andrew Norton tweeted this chart literally hours earlier.

I was immediately alerted to the existence of a brand new ABS dataset. I quickly did a bit of data wrangling/shaping and uploaded … Read the rest

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