Thursday, May 22, 2014

the story you want to tell...and the one your data shows

I was working on a makeover for a recent workshop when it became apparent that the story being told wasn't quite right, or at least wasn't exactly the story I would tell after looking at the data in a couple of different ways. In the following post, I'll walk you through an anonymized version of the makeovers and my corresponding thought process.

The original visual looked something like the following. It was accompanied by the headline, "Price has declined for all products on the market since the launch of Product C in 2010."


Based on the headline, what we're most interested in looking at here is the trend of cost over time for each product. The variance in colors across the bars distract from this and make the exercise more difficult than need be. Bear with me here, as we're going to go through probably more iterations of looking at this data than you might typically, but I think the progression is interesting.

For a first look, let's remove the visual obstacle of the variance in color and see what the resulting graph looks like (at the same time taking other steps to make sure things are appropriately labeled and de-clutter by removing unnecessary gridlines, tick marks, etc.):


Going back to the original headline, we're primarily interested in what has happened since Product C was launched in 2010, so let's emphasize the relevant pieces, forcing our attention there, and see what that reveals:


Upon studying this for a moment, we see clear declines in the average retail price for Product A and Product B in the time period of interest, but this doesn't appear to hold true for the products that were launched later. Plus, you've probably been thinking as you've scrolled through these bar chart iterations that we are looking at time, so perhaps a line graph would make more sense. Let's see what that looks like in the same layout as above:


If it wasn't already apparent, it probably now is with the above that it likely makes sense to graph all of the lines against the same x-axis so that we can more easily compare them to each other. This also reduces the clutter and redundancy of all of those year labels. The resulting graph might look like this:


With this view, we can much more easily see and comment on what's happening over time. Again, going back to that initial headline, I might modify it to say something like, "After the launch of Product C in 2010, the average retail price of existing products declined."


But this view also allows us to see something perhaps more interesting and noteworthy: "With the launch of a new product in this space, it is typical to see an initial average retail price increase, followed by a decline."


And perhaps we'd also want to note, "As of 2014, retail prices have converged across products, with an average retail price of $223, ranging from a low of $180 (Product C) to a high of $260 (Product A)."


Note how, with each different view of the data, you were able to more or less clearly see certain things. You can use the strategy above to highlight and tell different pieces of a nuanced story. Just make sure that the story you are telling is the same one that your data shows!

If you're interested, you can download the Excel file with the above visuals here.

Thursday, May 15, 2014

the visual displays I use most

As part of a project I'm currently working on, I recently went through all the visuals I've created in the past year - for workshops, this blog, and consulting work - and categorized them. Out of the 200+ visuals that I created, there were only a dozen different types of visuals that I used (and just 7 that, together, account for more than 90% of the total visuals I created).

I thought it might be useful to share the stats with you, along with some related blog posts (some of the posts linked below focus directly on the given type of visual display, while others simply show an example of their use).

the visual displays I use most
with % of total displays created in the past year
  1. Horizontal bar graph - 27%
  2. Line graph - 16%
  3. Horizontal stacked bar graph - 14%
  4. Vertical bar graph - 10%
  5. Simple text - 8%
  6. Vertical stacked bar graph* - 8%
  7. Slopegraph - 8%
  8. Heatmap* - 3%
  9. Area graph - 2%
  10. Waterfall chart - 2%
  11. Scatterplot* - 1%
  12. Table - 1%
*I seem to be lacking posts with examples of these types of visuals: 
I'll add over time and link here once the posts are live.

This is certainly not an exhaustive list of types of visual displays of information. But in my experience, just a handful of different types of visuals will meet the majority of your everyday storytelling with data needs.

Wednesday, May 14, 2014

500,351

That's the number that just caught my eye when I was looking up a past post on my blog a moment ago. If you look over to the left, you'll see it, too. Well, not exactly, as it's likely continued to tick up a little since I began writing this post. It reflects the number of views this blog has had since I launched it in December 2010. Just two words come to mind when I see it: thank you.

Thank you for reading, for your comments and your general interest in storytelling with data.

This seems like a good (albeit random) point to pause for a moment, to link back to some popular posts you may have missed and ask you to weigh in on what you'd like to see here in the future.

popular posts in case you missed them
The 10 most popular posts (based on number of page views) are listed below (plus a bonus 11th that has 10 tips and links to related posts).
  1. no more excuses for bad simple charts: here's a template
  2. how to do it in Excel
  3. the waterfall chart
  4. strategies for avoiding the spaghetti graph
  5. a Google example: preattentive attributes
  6. my penchant for horizontal bar graphs
  7. chart chooser
  8. the power of simple text
  9. logic in order
  10. slopegraph template
  11. celebrating (almost) 100 posts with 10 tips
what would you like to see covered here in the future?
Suggestions on future topics, questions you'd like me to opine on, or data visualization challenges you're facing are welcome. Leave a comment with your thoughts or email me directly at cole.nussbaumer@gmail.com.

where should I go in 2015?
I'm also looking ahead to my 2015 public workshop schedule. If you'd like to recommend a city or location, you can do so here.

Thank you very much for reading!

Thursday, May 8, 2014

calling all Bay Area data viz gurus

Facebook recently announced their 2nd bi-annual Viz Cup, bringing together the finest Bay Area vizzers for a night of competition and fun! I'm excited and honored to be one of the judges at the event, which will take place the evening of May 20th at Facebook headquarters in Palo Alto, CA.

Click here for additional info and to RSVP.

If you're interested in what I'll be looking for when it comes to effective data viz, check out this post, recapping the last event. I hope to see you there!