Looks vs Personality

Week 2 of Makeover Monday brings us survey data from YouGov.co.uk that looks at how men and women rank 6 different characteristics on importance when looking for a romantic partner.

Here is the original chart that inspired the makeover

What works well

  • I like the title, it’s very descriptive
  • The colors are nice and aren’t too similar
  • They separated men and women

What could be improved

  • There is a very low data:ink ratio with all the labels and axes
  • There are too many colors to remember what they represent. So I keep having to go back to the legend.
  • While stacked bars are good for showing part to whole relationships, it can be difficult to compare each part for each gender, which is what I’m most interested in.

When I first started to look at the data, I found it difficult. I don’t know why but I kept getting hung up on the fact that the data contained a value for each question AND rank. I had to scrap several ideas because of this issue. So the lesson here is:

  • Know the shape of your data
  • Then see how your idea fits that shape

So here is what I came up with. Click here for the interactive version

Looks vs Personality

Here’s what I did.

  • The title
    • On the visual, I switched the color dimension to gender and put the legend in the title. This is a nice way to clean things up
  • Color
    • As mentioned, I switched the color dimension to gender and separated each characteristic into its own column. This allows the users to quickly read down a column to see how each gender ranked any characteristic.
  • Comparison/Analysis
    • I mentioned above that I when I looked at the original, the thing I wanted to do most was to compare how each gender ranked a characteristic and what the percentage. To do this, I added a highlight action for each rank and question. This allows you to see how men and women both ranked a given question. Highlight actions

So there ya go, I wanted to stick as close to the original as possible and just improve it. And that’s the point of #MakeoverMonday!

Cheers!

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