Three weeks into 2018 and it’s Week 3 of Makeover Monday and I’m definitely keeping to my goal to complete all 52 weeks of this popular social data project. It really makes a huge difference making a commitment to improving my dataviz skills without going on and off every so often.
This week’s dataset for Week 3 looks at U.S. Household Income Distribution by State from 2009 to 2016 from the U.S. Census Bureau. The data looks at household incomes from $25,000 to more than $150,000.
The original viz is from Reddit and is featured on the Visual Capitalist website so here’s my thoughts on it.
What I like
- Legends are easily defined in the viz and you can find which bars represent the U.S. household incomes.
- The stacked bars are proportioned well and you can see that they add up to 100%.
- I really enjoy how the colours complement the bars which makes it easy to see the incomes within the viz.
What I don’t like
- It’s very unclear what years are represented in the viz (is it from 2009, 2010 or 2016?).
- Interactivity within the viz is very limited as it’s a static picture from first glance.
- In terms of the story aspect of the viz, I am struggling to find out what the angle is looking at the stacked bars for the States.
My goals for this week
- Be experimental with the choice of chart or map without resorting to bars or barbell charts.
- Identify an angle within the data and use that as the blueprint for building my viz.
- Don’t be afraid to not use all the data available within the data when creating my visualisation.
I have seen many hex maps over the past year and it just seemed fitting to produce my first-ever hex map in Tableau with this dataset. Whilst I found it difficult at first, I managed to learn how to put together the map very quickly, which is a big achievement for me because mapping is not one of my strong points in data visualisation.
With that said, here’s my Week 3 entry for Makeover Monday, looking at the comparison in household incomes over $200,000 in the District of Columbia State from 2009 to 2016.