Makeover Monday 2019 Week 3: Minimum Wage Earners in America

This week, we tackle both Makeover Monday Week 3 and the January Storytelling with Data Challenge. For Makeover Monday, we visualize the percentage of U.S. workers earning minimum wage. For the SWDChallenge, we try using new data viz tools (Google Data Studio for Ryan, Microsoft Power BI for Marc).

The original chart for Makeover Monday shows the percentage of hourly paid workers in each state that earn minimum wage or less for 2017.

What works well?

  • The monochromatic, 4-colour scale is aesthetically-pleasing and easy to interpret.
  • Showing the data on a map makes geographic patterns stand out, in particular the belt of darker blue stretching from Louisiana to Virginia.

What could be improved?

  • Smaller states in the northeast are imperceptible on the map. Using a tile map would give all states equal prominence.
  • Data is shown for only the most recent year. It would be interesting to see how the percentage has changed over time.

What Marc did:

  • Created a tile map. Each chart shows the trend in the percentage of workers earning minimum wage or less for the respective state.
View in Power BI

In the spirit of trying something new for the #SWDChallenge, I decided to use Microsoft Power BI. It was easy to get started with Power BI Desktop, which has a built-in connector to data.world. After getting the data imported, it took only a few clicks to create my first chart.

The Power BI interface is intuitive, adopting the same ribbon menu as Microsoft Office products. The “visualizations” and “fields” configuration panes are also similar to the data and style panels in Google Data Studio.

I found the chart formatting options sufficiently flexible. It was easy to set the axis ranges and hide the axes. I appreciated the built-in title field for every chart. Arranging charts on the canvas was a bit frustrating; although there is a snap to grid feature, it doesn’t apply when multiple objects are selected.

Overall, I succeeded in created the viz that I envisioned, without any significant hurdles. However, I have only scratched the surface of what Power BI can do. Perhaps I will return to Power BI for some future vizzes.

What Ryan did:

  • Charted the overall percentage of workers earning above min. wage, below min. wage, and the total. I avoided doing state comparisons as there are different state level minimum wages.
  • I liked how easy it was to create smooth lines in Data Studio, but I could see that the trends were being misrepresented so I went with the regular lines.
View in Data Studio

I used Google Data Studio for this month’s #SWDChallenge. I’ve pretty much only used Tableau for data visualization thus far, so it was great to learn another tool.

Data Studio is easy to navigate and I liked how the interface looked. In particular, I liked the grid layout which helped with formatting and how easy it was to create smooth lines. I also enjoyed the ability to copy and paste text boxes which isn’t possible in Tableau. Some formatting that is easy in Tableau, such as labeling start/end of lines or hiding one axis, I wasn’t able to figure out in Data Studio.

Although this is a simple chart, I like the interactivity with the highlighted marks and tooltips. I look forward to seeing how Data Studio improves in the future!

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