Makeover Monday, 2017 #36

The UN, #MakeoverMonday and #VizForSocialGood came together to challenge the data visualisation community to visualise results from the MYWorld survey on the UN Sustainable Development Goals. You can read more about the challenge on the Makeover Monday blog.

The design is geared towards a tablet as there were indications that the UN would like to use the finished viz on stands with tablets at various UN events like the forthcoming UN General Assembly in New York.

I’ve split the story into three pages to meet different aspects of the brief:

  1. The overall demographics of survey participants (I’ve also used this page as an opportunity to introduce the goals and the MYWorld survey questions);
  2. Responses across the 17 goals for question 2 and 3 of the survey (a sort order selector in the column headings allows the user to consider different rankings); and
  3. The ability for users to compare their country to another country (indications were that stakeholders were interested in, and motivated by, comparisons to their neighbours).

The proposed visualisation is available on Tableau Public with data extracted as at 23-Aug-2017 – screenshots below.

Page 1


It would be possible to include a country filter on this page (in the right hand column header) and to include a call to action prompting the user to consider what participation is like across various demographics within their country – and what they could do to increase or maintain participation.

The graph of participation over time is intended to show how participation is trending in terms of the goal of 1,000,000 respondents per year and a good place to show how many participants are aware of the goals over time.

Page 2


The continent and country filters at the bottom allow the user to focus in on their area of interest. They can move to page 3 for more detailed comparisons of specific goals. An improvement would be to allow the user to click a goal on page 2 to jump to page 3 with that goal selected.

Page 3


As well as the country comparisons this page also allows the user to compare responses by some of the other categories in the survey data – e.g. education level and HDI (human development index). Finally the page ends with a call to action to take the survey and a thank you for exploring the results. An alternative use of this space would be a call to action geared towards meeting the sustainable development goals.

Makeover Monday, 2017 #20

For week 20 Makeover Monday is collaborating with #VizForSocialGood and Inter-American Development Bank to look at youth employment trends in Latin America and the Caribbean. Great data set, great cause and a great opportunity for our data visualisations to make a difference. For some reason I also felt an increased sense of responsibility to understand and accurately represent the data!


Thoughts on the original charts

The original article walks  the reader through the overall headline figures, explaining the various categories and ending with a look at the sectors that young people are employed in. I spent a lot of time trying to understand how the various categories (Ninis, Nininis, unemployed but studying, informally employed, etc) added up to the total number of 15-24 year olds. So much so that in the end this seemed like a good angle to visualise. If I was struggling to make sense of the categories then there was a good chance others were too, and so explaining that graphically would be valuable.


The makeover

Design wise I wanted to bring in key numbers from the original article as headlines, but present and compare the proportions graphically. Pie charts were an option for the graphical component (given a limited number of parts to the whole), but waffle charts seemed to be a better fit for the flow of the visualisation:



The visualisation is also available on Tableau Public, where you can choose a country to drill into.



A quick nod to Andy Kriebel and his very helpful blog post and video on producing waffle charts in Tableau. This was my first attempt to create a waffle chart and Andy’s video was invaluable!



The first challenge was understanding the categories! You’ll note from the final waffle chart that I’m not quite there yet. If you hover over the grey section on the left (in the interactive version) you’ll see that I’ve labelled it “unknown”. I’m guessing that this category has to be those 15-24 year olds who are studying or training and are not seeking work. It’d be great to hear other people’s thoughts on whether this is correct, and whether I’ve accurately represented the categories.

Challenge two was a bit more prosaic. I built the headline components of the dashboard as worksheets in their own right. Each of these headline worksheets had a single text label incorporating the various numbers with text. What I hadn’t remembered until I finished was that I couldn’t apply a filter from one worksheet to another worksheet with a different primary data source. Rats! I had to go back and start these again, pulling in a dummy value from the waffle chart grid data source so that each worksheet had the same primary data source. Was there a better way to do this? If so I’d love to hear about it.

The final challenge was colouring the text in the headlines to avoid the need for a colour legend underneath each waffle charts. I could improve this aspect because the colours develop as the categories are expanded and consequently some colours are technically given two meanings.


Final thoughts

What else might I change? A waffle chart isn’t always as accurate as a pie chart (unless you can show enough squares!) so the eagle eyed will notice some rounding issues – e.g. two squares shaded for the 2.5 million unemployed who are studying out of 100 million young people . It would probably have been better to have more than 100 squares in each waffle to allow for more accuracy. Adding the percentage into the hover over would help here.

Part of me thinks that a concluding paragraph would be useful, but I wasn’t confident adding this with the unanswered question of the unknowns. Nevertheless I’ve learnt a lot about issues in employment for young people in Latin America, used a new chart type and hopefully contributed something valuable to the overall conversation and understanding.