Data Viz Done Right

June 12, 2017

Makeover Monday: How old was artwork when it was purchased by Tate?

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I'm not gonna pretend...this was a tough data set. I'd have much preferred it if Eva provided only the two numbers of the pie chart, yet I'm always up for a challenge. Let's start by looking at the original chart:

What works well?

  • A pie chart with two slices is really easy to understand.
  • The slices are labeled so I don't have to guess at their values.
  • The colors are easy to distinguish.
  • The largest slice starts at 12 o'clock.

What could be improved?

  • There's no title.
  • Who is Turner? Why does he have such a large proportion?
  • Is the data accurate? HINT: No, it doesn't match with the data on GitHub.
  • There's no reference to the source.
  • There's no really story to it. When I ask "so what?", I can't answer the question.
  • It's boring.

What were my goals?

  • Since Turner makes up 95% of the artwork, I'm more interested in everyone else. I've filtered out Turner.
  • The Tate seemed to make purchased in bunches. Instead, how about looking at how old pieces are when they are purchased?
  • What is the distribution of the age of the pieces purchased?
  • Provide an option to find an artist.
  • Include a way to view the piece of art as a thumbnail.
  • Display every individual piece of art (inspired by Pooja Gandhi).
  • Provide details in the tooltip.
  • Make it look a bit more "artsy" by going with a monochrome theme.

Overall, this data set proved pretty challenging to find any insights. Turner was such a large proportion that I couldn't see anything in the data until I got rid of him. It also helped to hide all of the fields I didn't want to use. Two simple, yet effective ways to make the data more understandable.

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