storytelling with data: don't eat farmed fish

I spotted the following video at one of my favorite blogs, FlowingData. I consider it a great example of storytelling with data: straightforward, no extraneous information, attention-grabbing without being overly flashy, moderate use of stats to back up key points.


Eating Fish from Nigel Upchurch on Vimeo.

Personally, I avoid farmed fish on the basis of their health profile. The video calls out other fish, but farmed salmon are also often fed grains, rendering the fish fattier yet with a lower level of healthy omega-3 fats than their wild counterparts (farming also introduces things like antibiotics and pesticides that I'd rather not consume). As the video points out, there are sustainability concerns as well.

information discovery: education & income by religion

A couple of weeks ago, the New York Times ran an article, Is Your Religion Your Financial Destiny?, which included the following infographic.

As my friend, Dave, who shared the article with me, pointed out - the color isn't necessarily informative, but it is an interesting way of carrying the gridlines across the page and certainly makes the visual eye-catching. I find the data it shows so very interesting.

Across the y-axis on the left, we see the percent of population with household income above $75K. The x-axis across the top shows percent that graduate from college. The dots plotted on the graph denote the various religions. You can quickly see that in general the higher the percent graduating from college, the higher the percent of >$75K income, which makes sense - one would expect positive correlation between education and income.

As my eyes scroll over the graphic, taking in the information, a couple of things make an impression. First, the wide spread: less than 10% of Jehovah Witnesses graduate from college (many don't finish high school, according to my mother's empirical evidence from the small sample she knows from her neighborhood) and their incomes reflect this. On the other end of the spectrum, over 70% of Hindus have a college degree. Also interesting: the places where the dots across the page do not follow a monotonically increasing line. For example, a greater proportion of Buddhists graduate college than Presbyterians, however a smaller proportion of Buddhist households have income over $75K compared to Presbyterians. The same phenomenon exists between Reformed Jews and Hindus. The Times refers to these anomalies as "less affluent than they are educated" and points to cultural influences and possibly discrimination as the root cause.

This isn't a case where the infographic is meant to highlight a single takeaway or recommendation; rather, it invites the audience to explore and draw their own conclusions: a tool for information discovery. Happy exploring!

secondary y-axis

The question of the secondary y-axis comes up every time I teach a data visualization course. As you've probably deduced by now, my general bias is for ease of interpretation. The challenge with adding a second y-axis is that it's not always clear which data series belongs to which axis. That said, I think there are ways to do this that get over this hurdle.

Earlier today, I was reading an article from the latest McKinsey quarterly shared by a colleague (thanks Andrew, if you're reading this!). The topic: big data. Of particular interest to me, given that I work in an analytical field, was the forecast shortage of analytical talent to make use of the growing world of data, something McKinsey raised in the article as a competitive advantage. In addition to interesting content, there were a number of graphs included in the article - some good, some not so good. It was one of these less than stellar views that acted as the impetus to this post: the following.

I think this visual is mostly pretty good. The takeaway is described clearly and the graph reinforces it visually.

But it could be a little better.

My one gripe, as you can perhaps anticipate, is with the blue circles showing Persons Unemployed across the bottom. Because the blue of the circles is darker than the bars, your eyes are drawn there by a visual cue that says "pay attention to this, it's the most important", whereas I'm not sure that's the case. Based on the takeaway at the top, the decrease in spending and lack of increase in unemployment seem to be of roughly equal importance. So let's make them look that way in the visual. Also with the numbers embedded in the circles, you have to read them and think about what they mean more than you would need to if this were shown visually.

My thought when I looked at this was that both of these issues could be solved by use of a secondary y-axis. Here's my makeover:

As mentioned, the main challenge with a secondary y-axis is making it clear which series belongs to which axis. One way around this is to not show the second y-axis, but rather label the series directly. In this case, I actually didn't show either axis.

What's your view on the secondary y-axis? Should it be embraced? Verboten? Leave a comment with your thoughts.