Axes: Bold as Love

Looking at some charts feels like staring at a psychedelic album poster while on hallucinogens.

You might see dual axes, a bajillion tick marks and axis labels, too many data labels...it can be overwhelming. This is why my number one bit of advice for creating charts is to "do less". Simply start from a more minimalist position so your audience can actually concentrate on the important stuff in your chart, rather than being distracted by literally everything.

My second bit of advice? (Not that it's less important or impactful...)

Choose what's on your axes very carefully.

Every decision you make in data visualization should be driven by "intentionality". Make decisions for a reason. Don't just chart the data in your spreadsheet. Rather, figure out what your data actually means, then chart the important meaning, which may or may not be in the data itself, in its raw form.

"What on earth are you talking about", you ask? Let me illustrate with an example.

Recently I shared one of the most popular posts I've ever shared on LinkedIn.

People went bananas for this chart. And no wonder. It is a wonder. What makes it so good is that it is not a visualization of the raw data. When people visualize data like that, their visualizations usually end up looking like this:

That chart has no nuance to it. It's impossible to gain any understanding from that chart other than "as you get older, you get more money". That's all you can see here - more trillions for each generation as more time goes by. The different generations' share of trillions is different, but there's no indication of why or if it's expected/appropriate, etc. It's just "the data".

But the chart from my post, which is based on the EXACT SAME UNDERLYING DATA, is so incredibly insightful. It has sparked dozens of comments and makes people stop and literally say "wow", when they understand what it represents.

Why? Because of what they chose to put on the axes. What is actually being visualized? Is it the sum of wealth of each generation or the proportional share of each generation that's interesting? Is population worth factoring into the conversation or should we ignore it? And how about this next chart? How about instead of showing time, we show median age of cohort, so we can compare each generation too each other like apples to apples, since looking at the year 2000 makes it hard to compare Boomers (much older/richer) to Millennials (much younger/poorer) and understand what the numbers mean.

When you transform your data–instead of just showing the numbers you have, but instead converting them to per capita rates or median age or proportional share–you are often rewarded with the real insights available in your data, which would remain hidden if you simply visualize "the data" in its raw form.

Be intentional, even bold, when thinking about what goes on your axes in your visualizations. Do this during analysis and you'll discover truly interesting insights. Do this during communications and your audience will actually participate in those insights with you!

Note: there were some complaints about the original cover image for this article, which was the album cover from Jimi Hendrix' "Axis: Bold as Love", hence the title of this piece, but the album cover being somewhat tangential! (Thought it does align with the opening paragraph...)

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