Tuesday, January 31, 2012

learning from good visuals

I find I spend a lot of time here discussing less than stellar information visualizations and how they can be improved. But there is also much to be learned about data viz best practices by examining good visuals and understanding why they are effective. I paused on one such graphic last week (see original article):

Here's a quick rundown of what I like about the above visual:
  • Everything is labeled (titles, axes, important values, data source), so there's no question about what you're looking at. The overall title explains what the visuals are intended to convince you of (so there's no guessing!). The points they want to highlight (2011) are shown clearly and draw attention through use of color-heavy call out boxes. 
  • The use of color is intentional (not what a graphing application randomly chose); note how red means the same thing in both graphs: total. This consistency is important for easy comprehension.
  • There isn't any extraneous stuff to dilute the audience's attention. Everything that's there is adding informative value.
  • The visual hierarchy of information is clear. The data draws your attention through color; titles are bold so you can't help but know what you're looking at. Axis labels are less emphasized (but still clearly legible) with non-bold font. Sources and gridlines are there to help interpret the data, but are pushed to the background through size and weight so they don't compete visually with the data.
  • Perhaps most importantly, the visual fits well with the article it accompanies. The graphs reinforce the main takeaways from the article and vice versa.
WSJ in general tends to have effective data representations, so if you're looking for more good examples, this is a great source. I still encourage you to maintain a critical eye when looking at any data visualization: observe what works well and what doesn't and try to emulate the effective parts in your own visuals.

Do you have any favorite sources for good data viz?


  1. good example. the big value markers on the right edges are helpful. reminds me a bit of the great NYTimes visual from a couple years back.


    Thanks for pointing out the good and the bad in the examples you present.

    I'm going to see Tufte next month. Can't wait. Saw him about 10 years ago.

    Al @imusicmash

  2. Also worth mentioning is how their decision to use a column chart facilitates comparisons across quarters. Trying to make that same comparison with a line chart is considerably more difficult.

    The grid lines are still a bit too salient IMHO.

  3. Great post! With regards to the visual hierarchy of information and clarity point -- how does font selection play into the design process? i.e., is that something that's determined by where the data is going to be published?

    Thanks Cole!

  4. I was reminded of another great source of excellent data viz today with the following post from David McCandless. I've yet to see a data viz from him that isn't beautiful and effective. In particular, I like how he often includes context (via text) within his charts.

    David McCandless: How Much does Hollywood Earn

  5. Al: the NYT graph you linked to is amazing. I don't think I've seen anything like that before. Thanks for sharing!

    Rob: great point on bar charts being effective for the quarterly comparison. It's good to note that line charts should ONLY be used when you have continuous data, but just because you have continuous data doesn't mean you have to use a line chart - bars can work, too.

    George: I haven't done any research here, but my personal preferences when it comes to font are as follows:
    - Keep it consistent: changing fonts provides visual complexity for no good reason
    - Keep it sans serif: those little squiggly lines make the text harder to read!
    - Keep it legible: in general, choose a font that's bigger than you think you need, particularly for the important stuff; for some reason (I've never figured out why), people tend to err on the side of too-small font

    Thanks all, for the comments. Keep them coming!

  6. Here are a couple more good examples that I came across today: