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Scorched by the heat in Arizona

Finding meaning in Big Blue California

Via Twitter, Pat complained that this Bloomberg graphic is confusing:


The accompanying article is here. The gist of the report is that electric cars are much more popular on the West coast because the fuel efficiency of such cars goes down dramatically in colder climates. (Well, there are political reasons too, also discussed in the article.)

What makes this chart confusing?

Our eyes are drawn to big blue California, and the big number 25,295. The blue block raises three questions: first, how do we interpret that 25,295 number? How big is it? To what should we compare the number? Second, we notice a blending of labels--California is the only label of a state while all other labels are of regions. Third, the number under West is 31,783, even larger than 25,295 although it gets a smaller font size, a black-and-white treatment, and a seemingly small allocation of space.

It takes a little time to figure out the structure of the graphic. That the baseline is a treemap with the regions, and big blue California is a highlight that sits within the West region.

Tufte would not love the "moivremoire"  patterns, nor do I. I'd have left the background of the entire right side plain white.

I fail to see why this treemap form is preferred to a simple bar chart.


As I play around with the data, basically playing with stacking the data, I found a way to make a more engaging graphic. This new graphic builds off an insight from this data: that the number of electric cars sold in California is more than all other states combined. So here you go:


Since the article attributes the gap in sales to regional temperature, an even better illustration should bring in temperature data.



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Jean-Pierre Tanguay

I find the new version worse since I don't understand it. Anyone else? Looks like Tetris!


Plotting per head of population would also make more sense an increase the disparity, and just use a bar chart.


I have to disagree Jean-Pierre.
I didn't understand the old version, even after the guy explained it.
I only understood it when I saw the new version.

In the old version you can't easily tell that California is over 50% of sales. Even a rubbish pie chart would have done this!


It took me a long time to realize that the outline inside the blue bar was meant to represent the comparative measure.

I share Jean-Pierre's confusion over the tetris-style blocks used to build the comparative regions - can you explain the thought process behind using this approach instead of a simple stack?


I was picturing something more like this, for example:



jlbriggs & several others: Your version is also fine. The point of this post is getting out of the plot-raw-data setting; look at the data, figure out what is an interesting thing to say, and then design your graphic to highlight that point. Your bar chart brings out the message too. Recently, I have been experimenting with ways to achieve a better balance between precision and engagement. My chart wasn't trying to convey precision at the region by region level.
Thanks for bringing up this discussion.


Also, thanks to the reader who pointed out the "moire" typo, corrected. It's ironic that I had gone to Google to check the spelling while writing the post. Since enough people are misspelling it, Google's auto-complete suggests "moivre pattern" is correct. That is one of the downsides of count-based machine learning approaches; they assume common patterns to be true even when they may be inaccurate.


I truly don't see a problem with the original chart. While not the best form it's not really hard to decipher, moire' patterns aside. The numbers serve to eliminate area confusion for the upper two boxes, and the rest of the boxes are very distinct, size wise. California, shaded as a subset of "West", rather than confusing, is easy to see as a callout of a specific territory in the west (note that it has the same pattern in the background)... (Admittedly, I haven't read the article, but that's what I infer from the chart at first glance).


@kaiser - "look at the data, figure out what is an interesting thing to say, and then design your graphic to highlight that point"

This is a great point, and one that should be printed on the wall in any room where people do this work :)

I feel like this particular experiment was not entirely successful though. Visually, I found the remake more confusing than the original, with some of the same problems.

The lack of precision isn't the problem at all - the odd shapes of the regions were very distractingly confusing as I attempted to discern meaning from what apparently had none.

In addition, the transposing of a second, slightly different version of the overall shape on top of the California area could have used some explanation or a stronger visual connection.

I think engagement is a worthy goal, but I think if it means "try to figure this out" then it's going the wrong way.


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