Diagonal text takes longer to read than plain ol’ horizontal text, so we want to avoid it.

In this lesson, you’ll learn 5 ways to fix those lonnng chart labels:

What’s Inside

• 0:00 Intro
• 0:58 Fix 1: Slow-to-Read Diagonal Text
• 1:18 Fix 2: Unreadable Tiny Text
• 1:38 Fix 3: Cartoonishly-Big Chart
• 2:38 Fix 4: Column Chart into Bar Chart (with Change Chart Type)
• 3:27 Fix 5: Forced Line Breaks in Chart Labels
• 3:56 What NOT To Do: Clicking the Space Bar a Bajillion Times
• 4:10 What TO Do: Alt + Enter
• 4:38 Mixing and Maxing these 5 Fixes for Your Dataset
• 4:58 Your Turn

Resources Mentioned

• Download the Excel file shown in the lesson
• Related tutorial: Adjusting the Outside and Inside Chart Borders in Excel

Transcript

Ann K. Emery: [00:00:00] If your chart has really long labels, chances are, Excel did this.

It probably tilted the labels diagonally, which takes longer to read, obviously, or it might’ve done the thing where it gives you some of the words and then dot, dot, dot, and it cuts them off. And. We can’t keep that.

So in this video, I’m going to show you five fixes.

And your data set is going to be totally different from my super fake one that I have here.

So you’re going to have to try these different fixes and then please, please, please comment below the video and let me know which fix works for you. Um, I’m Ann Emery. You’re watching Dataviz on the Go, the series where you learn dataviz time savers inside everyday software like Excel and PowerPoint and Word. And speaking of dataviz being on the go, I am leading office hours for my online course students in three minutes.

So let’s go, let’s go through these fixes really quickly. All right.

Fix number one [00:01:00] is you could just leave it alone and say, I don’t care if diagonal text takes longer to read, screw the people looking at this graph. They’re just going to have to take longer to read it. I know you’re not thinking that. I just wanted to show you like what, what not to do.

Okay. So we’re not just going to leave it like that.

Fix number two, uh, you could just say. I don’t care if people wear contacts or glasses. I’m just going to shrink down the font size until everything is horizontal. But, uh, I know, I know you’re not that rude. Okay. You’re not doing unreadable font either.

So that brings us to fix three, which actually might work. Fix three is you take your chart and you make it bigger until the labels are horizontal and it might have to be really big. It might have to be like, how big does it like this big? And then you have to adjust the inside border so you don’t have this weird white space.

I’ve got [00:02:00] other videos about this that I’ll link to up above too. If you’re like inside border, outside border, what’s that? You can go watch that quick tutorial as well. Now, enlarging the chart to get horizontal, easy to read labels, it might just work. Like if, if this chart is going into a wide PowerPoint slide, you can have a wide chart.

But what if your chart has to fit in this little teeny tiny spot on your dashboard screen? Then, uh, Your chart can’t be this wide, right? So this one gets like a, what are we kind of scoring the solution? Like a, a maybe, like a meh kind of squiggle. All right, fix four. You could change your columns into bars.

People think, Oh, now I’m going to have to delete my chart and start over. False. You don’t have to do that. You’re just going to take your chart and click on it. You’re going to do a right click and you go to change chart type. Bars and columns are similar, but Excel does not [00:03:00] consider them to be identical charts.

So you go to change chart type, it opens up the menu and you’re going to pick the bar chart. Okay. And then you still, of course, have to resize it a little bit. You’re left with this weird white space, but then your labels have all the breathing room that they need on the side. I often pick this solution.

I often change columns into bars. I have to do this for many, many projects. So that one’s going to get like a hooray. Check that it works. And then fix number five, I had to do this recently on a chart that looked similar to this. These aren’t the real countries or the real like scores or whatever this pretend data set would be about.

But the chart did look more or less like this. And I had to do fix five, which is forced. I’m going to show you what not to do, and then what to do. A forced line break would be, you take something that has two words, like South Korea. Here’s what not to do. You do space, space, space. And if you do enough [00:04:00] spaces, it forces a line break.

And that works, but there’s a little bit of a fancier behind the scenes workaround. So a forced line break, I would suggest would be Alt Enter. You’re going to have to look at your keyboard to do this. You’re going to click in between the two words where you want the line break and you’re going to do Alt Enter.

Hold down alt and then do enter, and it makes a new line. You can see it in that cell. You can see it up here in the formula bar, and then you can see it in the chart. In real life, you might actually have to mix and match some of these fixes. You might have to do a forced line break. You might have to enlarge the font size or shrink it just ever so slightly.

You might have to make the chart wider. Or not. Okay. So hopefully these five fixes have given you like some ideas, right? For your own troubleshooting. Okay. It is time for office [00:05:00] hours. I’ve got to go. I am a little bit late. Unfortunately, it’s your turn. Give this a try and comment below the video and let me know, did this work?

Did this not, did you run into some other challenge that you need help with? Let me know. And I’ll probably make a video just for you. Thank you.

The post Lonnng Bar Chart Labels: 5 Fixes to Avoid Diagonal and Cut-Off Wording in Excel appeared first on Depict Data Studio.

Most of these charts from my prior work were ineffective. Of course they were. Data visualization is a new skill for most researchers and evaluators.

One of my old charts was so horrific that I just had to share it with you:

What’s so bad? you ask. I see these all the time, you say. Can’t they just tilt their head to read the words, you argue.

What’s Wrong with my Previous Chart

Each of these mistakes–from the before I knew better period of my career, never to be revisited again–kept viewers from understanding the information:

• Generic and centered title (Should have a “so what?” and be left-justified.)
• No subtitle or annotations (So the viewer can’t skim the information.)
• Border (Should be removed.)
• Full grid lines (Should be lightened or removed altogether.)
• Legend (Should have direct labeling instead of the legend to avoid those back-and-forth eye movements.)
• Speaking of direct labeling… why did I label the axes and the bars? Overkill.
• Diagonal text (Should swap this vertical bar chart for a horizontal bar chart, leaving more room for the labels.)
• Default color scheme (Should use the client’s brand colors).
• An action color is there, kind of. Not really. It’s used incorrectly. Our brains are drawn to darker colors. Why was I drawing attention to the “possible items correct” section with the dark blue?
• Most importantly, why did I display the raw scores vs. the percentages? Can you imagine how much mental energy it must’ve taken my viewers to figure out what 2.9 vs. 2.6 vs. 6 means?

Before/After Makeovers

The first phase in learning about data visualization is usually critiquing charts. What, exactly, is wrong with your work or someone else’s? How can you learn from those mistakes?

The second phase is articulating specific ideas for how you’d make charts better.

The third phase is actually remaking your charts.

Some people stay in the first phase forever. My goal is to move more people into the third phase: actually improving your work.

So I’ll lead by example. Here’s how I’d re-do this chart today. I designed five different remakes.

Makeover #1: A Horizontal Clustered Bar Chart

First and foremost, I changed the chart type from a vertical column chart to a horizontal bar chart. Horizontal bar charts are great when the data labels are pretty long, like in this example. Your goal is to avoid diagonal text at all costs. It’s harder to read, so viewers get distracted, bored, or generally turned off and stop trying to decode your messy chart. I’m not a fan of vertical text either. (Not sure how to transform your vertical bar chart into a horizontal bar chart? I’ve got a tutorial.)

Next, I transformed the raw scores (“2.6”) into percentages (“43%”).

Finally, I addressed all the Low Hanging Fruit formatting issues. For example, I added a 10-word title and a 1-sentence caption; I deleted the border, grid lines, and tick marks; I placed the percentages on the bars so I could delete the axis; and I placed the years directly on the bars so I could delete the legend.

Why the black and white? Just for fun, I want to show you that you can still emphasize patterns without using bright, showy colors. In real life, would I match the action color to my client’s RGB codes? Absolutely.

What do you think of remake #1?

Makeover #2: A Clustered Stacked Bar Chart

I’ve experimented plenty with real-life clients to see whether they prefer regular bar charts or stacked bar charts. Here’s the typical response:

• Me: Here’s the first chart. [Regular bar chart.] What’s the message here?
• Client: Oh wow! Our participants are doing so well! 46%! That’s high! … Right? Or is that number low? Out of what? Out of 100%, right? Hmm…
• Me: You’re on the right track. Here’s the second chart. [Stacked bar chart.] What’s the message in this one?
• Client: Oh darn, we’ve got a long way to go. 46 out of 100%?! I need to speak with our program director about this. In fact, our whole team better see this. We need to figure out what we’re doing wrong before it’s too late!

A dozen conversations later, and the result is still the same: Nearly all my clients gain deeper insights about the findings through stacked bar charts instead of regular bar charts. What’s the response in your projects?

Makeover #3: A Small Multiples Bar Chart

The first two remakes are better than the original. That being said… clustered bar charts are my least favorite chart in the history of the world. They’re so cluttered. And worse, the comparisons are lost. With so many bars smushed together, it’s nearly impossible to see at-a-glance patterns between the two series of data.

In this example, I created a side-by-side bar chart so viewers could more easily see 1) the 2009 pattern on its own, 2) the 2010 pattern on its own, and 3) the difference between the two. Still in the bar chart family, but different patterns pop out, don’t you think?

I also used the action color (dark gray) to emphasize the Social and Ethical scores, and I added an annotation (the call-out box on the chart) to make my viewer’s comprehension even easier.

Want to make your own side-by-side bar chart? I’ve got a tutorial.

Makeover #4: A Dot Plot

Dot plots are often the superior chart. I use them to compare two points in time (like this example); two distinct groups (Program A and Program B); or, when I triangulate data, two distinct viewpoints (students’ perspectives vs. teachers’ perspectives).

But they’re not always superior. This dot plot doesn’t work. It’s too cluttered, isn’t it? Its more confusing than helpful. It’s because students improved on some areas, declined on other areas, and didn’t change at all on other areas.

The annotation isn’t helping, either; instead of adding clarity, it adds clutter.

For the rare viewer who’s willing to spend 60+ seconds interpreting the chart, it’s great because it shows more nuanced patterns than the other charts. But my guess is that the majority of viewers will lose interest after a few seconds because they can’t immediately grasp what it means.

Makeover #5: A Slope Graph

A slope chart is basically a line chart for two or three points in time.

This chart type is also effective at showing rankings (i.e., it’s easy to see how the skills are ordered on the left-hand side). 

For me, this chart is the winner. It’s easiest to understand at-a-glance. It ranks each of the skills areas. It shows differences over time. There’s a lot of cool stuff going on for the viewer to explore. It’s supplemented with a non-intimidating title, subtitle, and annotation. Yet, the information takes up very little ink and space.

Your Turn

Which remake would suit your audience best?

The post Avoiding Diagonal Text in Your Charts appeared first on Depict Data Studio.