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.

Maybe you’re already using them…

Maybe you can make ’em in your sleep…

Or maybe you have no idea what I’m even talking about! (If that’s the case, stick around! This video is for you.)

You’ll learn about the differences between clustered bar charts and dot plots. Then, you’ll see a real-life example so you can start thinking about how you’d apply these in your own workplace.

What’s Inside

• 0:00 Intro
• 0:27 Dataviz On The Go
• 0:39 Obvious Differences (Bars vs Dots)
• 0:55 Subtle Differences (Length vs Endpoints & Distance Between Dots)
• 1:35 Dot Plots Avoid the “Diagonally-Down” Comparisons
• 1:57 Real-Life Example: School Climate Survey
• 2:59 Big A Accessibility (508/ADA compliance)
• 3:22 little a accessibility (intuitive)
• 4:22 Alternative Design: Dumbbell Dot Plots
• 4:48 Portrait vs Landscape Considerations
• 5:29 Your Turn

Download the Spreadsheet

It’s here: https://depictdatastudio.ck.page/clusteredbarsvsdumbbelldots

Transcript

Ann K. Emery: [00:00:00] Maybe you’re already familiar with dot plots. Maybe you’re already using them. Maybe you can make them in your sleep.

Or maybe you have no idea what I’m even talking about! If that’s the case, stick around. This video is for you.

You’re going to learn about the differences between clustered bar charts and dot plots.

And then I’ll show you a real life example. So you can start thinking about how you might apply this chart type to your own workplace.

I’m Ann Emery. You’re watching Dataviz on the Go, the series where I make quick tutorials as I’m racing around between workshops and webinars and conferences and consulting projects.

And speaking of consulting projects, I was recently in a meeting with a client and they were asking about these chart types, clustered bar charts and dumbbell dot plots.

And right away when you look at them, they’re obviously different! One’s got bars, one’s got dots, but there is a slight, smaller nuance that I want to draw your attention to here. [00:01:00] And that’s related to attention!

It’s related to where our eyes and brains, and therefore where our precious attention, goes when we look at each of these graphs.

So when you look at a bar chart, your eyes are going to look at obviously the end point, right? That’s the really juicy part of the bar chart.

With dot plots, they don’t waste any time. They cut right to the chase. I love them for their brevity and they just plot the end point. Okay, they don’t waste our ink and waste our time with all this, all this unnecessary ink.

Another slight difference is when you want to compare the end points, you have to do a little bit of a diagonally down movement to compare them, where dot plots plot everything on the same plane, so that it’s just a little bit faster, right?

Instead of stacked endpoints, it’s side by side: same line, same plane.

Alright, let’s look at a real life example because [00:02:00] this one with A, B, C, D and group one and group two is obviously super made up!

Let’s go back into the vault in my memory, where about 15 years ago, which is a million years ago, I was working on a lot of school climate surveys.

I did a lot of consulting for the U S Department of Education. I looked at test scores, all sorts of academic performance and school climate surveys, and I don’t remember the exact details of how this was measured, but I do know that we surveyed parents. And school staff, like the teachers and the principals and all the administrative staff. And then we compared how they responded on different measures.

This is the default graph that Excel is going to give you, which of course, if you’ve watched any of my other YouTube tutorials or read any of my blog posts over the years, you know, we can’t keep that. Okay. Let me just let, you know, just make it super duper clear what we’re not doing.

We’re not keeping these default, inaccessible settings. At a bare minimum, we’re going [00:03:00] to add Big A Accessibility –508 compliance and ADA compliance. That’s the usual stuff. That’s like making sure the font is big enough and dark enough, removing the legend and adding the direct labels right here, which is a win for grayscale printing and for custom words. Colorblindness.

And then we might even, I hope, I hope you do this. I hope you keep going with “little a accessibility” edits to make sure that your graph is really intuitive.

That’s going to be things like grouping, right? Finding groups of elements where parents scored the school higher, versus staff.

That’s going to be things like adding annotations, which, guess what? That’s just a good old text box. It’s a call- out box to help people figure out what the patterns are so that they’re not just guessing and searching and hunting for any type of insight.

This one, honestly, when it’s Big A and little a accessible, I’d say [00:04:00] it’s not that bad!

I wouldn’t lose sleep over this.

If you go this far with editing with your clustered bar charts, I’m going to say: virtual high five, leave it alone. You’ve graduated. No need to keep on going with editing unless you want to, unless you’re ready to really keep boosting your skills and try out something that’s a little bit more advanced.

And that advanced, uh, approach would be the dumbbell dot plot. Which as you know, only puts the emphasis on the end point, the juicy important part. And it helps draw your attention with this connecting line, the, the dumbbell part of it to the difference between the staff and the parents- or whatever groups you’re comparing in your project.

Now, you’re going to have to put the annotations on these finished charts in a little bit different spot, depending on whether you’re doing a landscape final project or a portrait final project.

So if this was going to be landscape, you’re going to have [00:05:00] space for the annotations off to the side. If it’s portrait, It’s going to be a lot narrower.

You’re just not going to have the space. So you’re probably going to have to put the call out boxes above each chart, something like this.

Here’s what I mean: landscape versus portrait. You’re just going to have to think very carefully about where everything fits. So it’s not so condensed that people can’t actually notice those important differences between your groups.

It’s your turn. Comment below this video. Let me know, are you using dot plots? For what? You probably aren’t doing school climate surveys. You’re probably using them for something completely different from this. And also let me know what types of how to questions you have. These are possible in good old Excel and PowerPoint and Word, but they require some advanced behind the scenes magic tricks to make them happen, which I am happy to share with you in future [00:06:00] videos.

The post What’s the Difference between Clustered Bars and Dumbbell Dots?? appeared first on Depict Data Studio.

Here’s a step-by-step guide to making your very first Tableau dashboard.

In less than an hour, you’ll be able to install the free version of Tableau, add your dataset, create a few charts, and then combine then into a dashboard. You’ll still have time left for formatting, too.

Step 1: Figure Out Which Version of Tableau You Need

There are a few options:

• Public: Free BUT your datasets and graphs will be publicly available.
• Desktop: Paid; about USD $1,000/year per user.
• Server: Paid.

This article compares the versions in more detail.

Step 2: Download Tableau Public

If this is your very first dashboard, I’d recommend starting with the free version, Tableau Public.

Here’s how you’ll install it:

• Visit https://public.tableau.com/en-us/s/download
• Enter your email address and click Download the App.
• The download begins automatically.
• It takes about 5 minutes.

Step 3: Import or Connect Your Dataset

Now, you’ll need to connect your dataset to Tableau.

You can add datasets from Excel, Sheets, QuickBooks, etc.

In this example, let’s pretend we’re visualizing demographic data from an Excel spreadsheet, like this:

Here’s how you’ll add your dataset to Tableau:

• Open Tableau Public.
• Connect to a File: Microsoft Excel. Open your file.
• You’ll see the names of the Excel Sheets on the left.
• Drag in the sheet(s) you want to use for your Tableau dashboard.
• Pre-filter if needed.
• Connect multiple tables if needed. Joins combine the columns of two datasets, and unions combine the rows of two datasets. Joins are most similar to lookup functions in Excel. Unions are most often used when more data is coming in, and you need to add more rows to the bottom of the dataset.

The preview of your spreadsheet will look like this inside Tableau:

Step 4: Drag and Drop Variables to Create One Visual at a Time

We’ll build one chart at a time. Then, in a moment, we’ll combine them into a dashboard.

First, let’s visualize the Work Setting data in Sheet 1. We would drag Work Setting into Rows and Demographics (Count) into Columns. Congrats! You’ve got your first bar chart.

Next, we’ll drag and drop variables to create a Years of Experience histogram.

Finally, we’ll create a color-coded (“choropleth”) map by State.

We’ll create a bar or column chart first, and then simply change it into a map with the Show Me menu.

Step 5: Combine the Sheets into a Dashboard

Now, let’s combine our three individual graphs into a single dashboard.

Here’s how:

• Along the bottom, click on the icon to create a New Dashboard.
• Then, in the Dashboard tab on the left:
  • Choose the device (Desktop, Tablet, phone, etc.).
  • Adjust the size as needed.
  • Drag the Sheets into the main dashboard area.
  • Add Objects as needed (e.g., Blank to add some white space between visuals).
  • The individual graphs can be tiled or floating. I prefer tiled.
  • Check the box to Show dashboard title.

Step 6: Format, Format, Format!

It’s easy to create graphs in Tableau.

Like many software programs, it’s not so easy to format them to be Accessible (508/ADA compliant) and accessible (intuitive).

Here are some bare-minimum edits to get you started.

Apply brand fonts. Go to Format –> Workbook to change all the fonts in your file at the same time (rather than changing one visual at a time). Here’s an article with more info.

Apply brand colors. I personally just go to Marks –> Colors –> More Colors and enter the RGB or HEX codes. Or, here’s an article with a coding option.

I love color-coding by category (i.e., one brand color per graph). This is an easy way to make a dense dashboard feel not-so-dense.

Apply a text hierarchy. Make sure the dashboard title is largest, boldest, and darkest. You’ll also need Heading 1s, and you might need Heading 2s.

As usual, left-aligned text is faster to read then centered or justified text.

As usual, horizontal text is faster to read than diagonal or vertical text.

Don’t forget to turn bulleted tooltips into complete sentences for an extra boost of accessibility.

Your formatted dashboard might look something like this:

Step 7: Share the Dashboard

That’s it! Let’s share it with colleagues.

In the upper left corner, click on File. Choose Save to Tableau Public. Log in. Or, create a username.

Once the dashboard is saved to Tableau Public, you can save the dashboard as an image file, a PDF, a PowerPoint slide, etc.

Learn More

If you’d like to learn more about getting started with Tableau, check out Dashboard Design. This 4-course bundle includes a half-day course on Tableau.

The post How to Make Your First Tableau Dashboard appeared first on Depict Data Studio.

Accessibility means different things to different people.

I see two main types: Big A and little a.

1. Big A Accessibility means that our graphs meet official accessibility guidelines so that they’re understandable for people with disabilities. In the United States, that means 508 Compliance.
2. Little a accessibility means that our graphs are understandable for non-technical audiences; skimmable; and generally not a garbage heap of jargon.

Both Big A and little a are central in my work.

Here’s where you can learn more.

Big A Accessibility

Here’s a (partial) list of everything you’d need to do to pass 508 compliance guidelines.

Directly Label

Remove legends and directly label the data.

Add White Outlines

Outline the touching, filled shapes with white borders (i.e., cells in a heat map, slices in a pie chart, locations in maps, rectangles in stacked bar charts).

Make Sure Graphs are Legible for People with Color Vision Deficiencies

Red-green colorblindness isn’t the only type, but it’s most common.

And, it’s the most problematic for data visualization. We love to use “stoplight coding,” especially in dashboards. We’ve all seen dashboards where green means “we met the target” and red means “we didn’t.”

For people with color vision deficiencies, those reds and greens just look like yellows all blended together.

Tips:

• Avoid red-green color combos (try red-blue, orange-green, or orange-blue for stoplight coding instead).
• Use direct labels.
• Test your drafts.

Make Sure Graphs are Grayscale-Friendly

Printing is less common nowadays, especially with so many people working from home indefinitely. Who wants to pay for their own color ink?!

Your infographics, reports, slideshows, and reports might still be printed.

And they might be printed in grayscale.

Let’s plan for grayscale printing ahead of time to make sure the visuals will still be legible, just in case they’re printed.

Tips:

• Use direct labels.
• Add white outlines.
• Test your draft.

Use Plenty of Color Contrast

The other night, as I was reading my 4-year-old a bedtime story, I was struggling to read the words on the page. The book used colored font against a colored background, and the words were kinda small. Those were all fixable problems!

Tips:

• Don’t use colored text against a colored background. Here’s how to place text on top of photos so that it’s legible.
• Make sure all your colored text (e.g., for headings) is bold.
• Make sure your grays are dark enough. Software defaults are terrible at this. Enlarge and darken those defaults!!

Use Larger Fonts

Increase the font size (I recommend 11+ for documents and 18+ for slideshows, not Excel and Tableau’s puny size 9 defaults).

Again, the software defaults don’t help us here. Their defaults are usually way too small.

Add Alt Text

Add alt text to all images for standalone documents (reports, dashboards, infographics, etc.), including graphs.

Molly Burke’s Instagram is my favorite alt text inspo.

little a accessibility

These are techniques that won’t necessarily help you pass official accessibility guidelines… but are still a good idea if you want to make charts that people actually understand and use.

Actually Use Graphs

Use less text and more graphs!!!

Add graphs alongside those boring bullet points.

Choose the Right Chart

Go beyond the bar chart.

Use Data Storytelling

Use data storytelling, which I define as:

• writing takeaway titles instead of topical titles and
• highlighting one key finding at a time in a darker color.

Color-Code by Category

One of my favorite techniques of all time.

Color-coding by category helps us chunks the information into manageable pieces.

We can color-code in presentations, reports, dashboards, and one-pagers.

Lower the Reading Level

I’ve written about reading levels several times:

• In this blog post, you’ll see a re-written chart title for a conference slide.
• Here are some common data phrases, re-written.
• Here are some common research methods phrases, re-written.

Lower the Numeracy Level

Here’s how.

Use a Consistency Text Hierarchy

Make sure all the Heading 1s match, all the Headings 2s match, and so on.

Use Horizontal Text

It’s faster to read than diagonal and vertical text.

Avoid Underlines

Only use underlines for hyperlinks (not for headings).

Avoid ALL CAPS

It feels like shouting and takes longer to read than mixed case letters.

Place Text Next to the Graph

Not on the next page so that it’s faster to read.

Add Symbols and Icons

They make graphs easier to navigate and they boost the memorability of our findings.

• Here’s an example with state icons.
• Here’s how to use the StateFace font.
• Here’s an example with realistic human icons (instead of gingerbread people).
• And the realistic human icons, in a GIF!

Presentation-Specific Techniques

Talk about one thing at a time so that what your audience is hearing and seeing match.

Use a microphone!!! In-person and online. I don’t care if you think your voice can fill the room. It can’t, especially for people who are hearing-impaired. For virtual presentations, purchase a microphone. Or, at the bare minimum, wear the earbuds that came with your phone (because they likely have a built-in microphone). Tinny, echo-y sounds are hard for all of us.

Report-Specific Techniques

Follow the 30-3-1 approach. Limit the body to 30 pages (or less!), and then create a separate 3-pager and 1-pager.

Use visual appendices instead of black and white appendices to make the patterns more obvious.

Dashboard-Specific Techniques

Don’t expect busy, non-technical audiences to interact with your dashboards.

Involve the End Users

Involve the end users in the sensemaking process, e.g., by using data placemats and by following the Choose Your Own Adventure method in presentations.

Listen to what users say they need… but give them what they actually need.

Remember the Humans Behind the Data

I love this example.

Your Turn

Which of these techniques are you already using?

Why techniques might you try in the future?

The post “Big A Accessibility” and “little a accessibility” Tips for Data Visualization appeared first on Depict Data Studio.

Dashboard is a tricky term; it means different things to different people.

In this article, you’ll learn how to:

• choose between various dashboard types (static or interactive, single or series); and
• deal with common dashboard challenges.

Lea Pica’s Present Beyond Measure Podcast

I recently had the chance to be on the Present Beyond Measure podcast, hosted by Lea Pica.

Lea is a seasoned digital analytics practitioner, social media marketer and blogger with over 11 years of experience building search marketing and digital analytics practices for companies.

You can listen to all of Lea’s podcast episodes here.

What’s Inside

Here are some of the topics we talked about:

• All about my journey into data viz and how I leveraged my skills.
• The poll that I use to start the conversation around data dashboards!
• Different perceptions of dashboards and the first steps for client conversations.
• The four types of dashboards and the steps in the planning process.
• The necessary software for dashboard creation and thoughts on the nuances between different programs.
• Tips and tricks for streamlining your data extraction process.
• Challenges that I have seen most often in the dashboard creation process.
• Unpacking the discussion around layout and chart types and my personal approach.
• My recommendation of an impactful book dealing with the power of text placement.
• Why I’m so excited about progress in the field of dashboard creation.

Defining the Term “Dashboard”

I asked Lea to give her definition of a dashboard (hint: there’s a million correct answers!).

Lea said,

“My definition of a dashboard is a single view suite of data chart modules, or data form modules, that are designed to alert a lay audience to the most critical business key performance indicators, business metrics, in a way that they can either make very basic decisions on their own or alert them to ask the proper teams to investigate those chains further.”

Whoa! That’s one of the most sophisticated answers I’ve ever heard.

Different Perceptions of Dashboards

Dashboard software programs are relatively new.

If you’ve entered the field recently, you might associate “dashboards” with specific software programs, like Tableau or PowerBI.

In the past, “dashboards” meant static one-pagers, like a printout or a PDF. For example, you might prepare a one-page handout of key metrics that would be printed and discussed at a board meeting.

How to Plan Your Next Dashboard Project

On the podcast, Lea and I talked about how to plan for your next dashboard project.

Step 1: Define the Term “Dashboard”

First, recognize that each team member has a different idea of the term “dashboard.”

Some people might want to dive in and build a dynamic dashboard.

Others might be envisioning a one-page PDF, or even some slides to discuss at a meeting.

Step 2: Static or Interactive?

Second, talk about whether you need a static or interactive dashboard.

Static means you need a meeting handout or a one-pager of key facts and figures. You could share the one-pager as an email attachment or post it on a website.

Busy leaders don’t have the privilege of time, so providing a one-pager is a gift. It’s like saying, “I’ve already dug through all the messy data, here’s what I think are the key findings for you in this neat, tiny, little package.”

Interactive dashboards (or dynamic dashboards) have drop-down menus, checkboxes, and buttons.  

We’ve all seen and used these dashboards, either on our computers or in our phone apps.

But, sometimes people don’t need or want that much information.

Technical audiences will probably appreciate an interactive dashboard, but non-technical audiences might appreciate a one-pager.

In the podcast, you’ll hear Lea and I discuss the mismatches we see.

Technical people like using interactive dashboards, so we make interactive dashboards. We have to pause and remember that our audiences might be non-technical, and they might prefer a static one-pager.

Step 3: Single or Series?

Third, figure out whether you a single dashboard or lots and lots of matching dashboards.

For example, leaders at a state education agency might need an overview of all the schools, aggregated together.

Principals would benefit from seeing their own school’s data.

Within a single project, you might need a single dashboard (the overview for the state education agency) and a series of matching dashboards (one per school for each of the principals).

Step 4: Choose Your Software Program

Finally, choose your software program.

Audience decisions should come before software decisions.

I’m a big fan of everyday software, so I tend to make most of my dashboards in Microsoft Excel.

Excel, PowerPoint, and Word are the common language among all the groups I work with, and I think people are pleasantly surprised to see how much Excel can do.

Common Dashboard Challenges

In the podcast, Lea and I discussed common dashboard challenges.

Designing Your First Dashboard

Getting your first dashboard set up is the hardest part.

If you’ve got a dashboard, I’d love to give you five gold stars, seriously.

You might have needed to hire new staff, attend training, or spend hours fiddling with that first dashboard. Celebrate your wins, vizard.

Making Sure Your Dashboard Isn’t Too Dense

Then, we talked about some specific design challenges.

The biggest challenge I see is volume, or how much we try to include in a dashboard.

I see a lot of dashboards that look very full. They’ve got so many charts. They’re bursting at the seams.

If that happens in your project, take a time-out. Try to remember which one audience this dashboard is for.

It can’t be for your boss, board members, the public, fellow staff, and your peers.

Each of those groups is going to need different charts, so if you try to fit everyone’s information requests inside a single dashboard, it starts to overflow.

Pick your one audience, and then prioritize the data points that your one audience needs.

Use Familiar Bar Charts, or Variety?

Another common dashboard challenge is choosing the right chart type.

I come from a research background, so my go-to chart type is bar charts.

I have way too many bar charts. My drafts are bar, bar, bar, bar. As I edit, I add more variety.

There’s a delicate trade-off between adding variety and sticking with everyday charts, though.

In the podcast, you’ll hear Lea say that she sees a benefit in using everyday charts.

“People immediately understand what they’re supposed to understand from seeing those [familiar] charts. There’s no learning curve, there’s no training gap,” Lea explained.

In the podcast, you’ll also hear me talk about a recent client. Their dataset has three nested levels (i.e.., categories, subcategories, and sub-subcategories).

We brainstormed several options for their dashboard: a tree diagram, sunburst diagram, and Sankey diagram. Together, we weighed the pros and cons of each approach: What does it highlight? How easy is it for someone else to understand? Is this the pattern we really want to emphasize—or not?

But another consideration is time and software options. Is it worth the staff time to develop those charts for the dashboard? Or do we stick with the usual bar charts?

Book Recommendation: I Am a Book

In the podcast, you’ll hear Lea ask me whether I’ve read any good data or design books recently.

I mentioned I Am a Book. I Am a Portal to the Universe by Stefanie Posavec and Miriam Quick.

This book has my favorite text placement of all time. The Nobel Prize for text placement! It gave me permission to use huge fonts, diagonal fonts, and even circular fonts. What a masterpiece.

The Future of Data Storytelling

Finally, Lea and I talked about the future of data storytelling.

“I can’t wait until I can stop talking about some of the topics I’m talking about,” I said.

“Let’s re-record this in 10 years and our dashboard conversation, I cannot wait for that to be a different conversation.”

I can’t wait to stop saying that some interactive dashboards should actually be static.

I can’t wait to stop saying that non-technical and technical audiences have different dashboard preferences.

I can’t wait to stop saying that the leaders and the doers have different information needs.

Your Turn

What does the term “dashboard” mean to you? Every workplace has a slightly different definition.

What type of dashboard do you need for your project? Static or interactive? Single or series?

What are some of the most common dashboard challenges you’ve seen?

Connect with Lea Pica

Website: leapica.com

The Present Beyond Measure Podcast: leapica.com/podcast

LinkedIn: linkedin.com/in/leapica

The post How to Plan for Your Next Dashboard [Lea Pica’s Present Beyond Measure Podcast] appeared first on Depict Data Studio.

There’s a misconception that accessibility takes all day, that’s it’s costly, or that it’s complicated. Those are all false.

Accessibility is woven into all my trainings, but since this is a topic I get asked about a lot, I decided to make a new talk that’s focused just on accessibility for dataviz. 

In Spring 2021 I gave a talk at the Good Tech Fest conference about dataviz accessibility quick wins. 

The talk was a “Choose Your Own Adventure” style where the audience chose what we discussed from a list of options. They chose: 

• direct labels, 
• lower the reading level, and 
• lower the numeracy level. 

You can watch the recording or read the highlights. Enjoy! 

Watch the Conversation 

You’ll learn about lowering the numeracy level. Then, you’ll see a case study that combines several accessibility quick wins. 

How to Lower the Numeracy Level 

We’ve discussed how to lower the reading level, but how do we lower the numeracy level?  

Lowering the numeracy level just means making sure the numbers are easy to understand.  

There are a couple of stages to this, so even if you only move one step, that’s a win.  

For example, let’s say you’re starting with 33.26%.

To lower the numeracy level, the first stage would be to round it to 33%. That’s a win!

The next stage would be to go from rounded percentages to fractions. So, we could turn that 33% into 1/3. Another win!

The final stage would be taking that 1/3 fraction and changing it to 1 in 3 in a sentence.

This is a general goal to aim for. It won’t work every single time for every single project. In other words, you can’t move from 33.26% to 1 in 3 for every project. Just try to move one step in every project.

Before: Percentages with Two Decimal Places

Let’s practice lowering the numeracy level.

Let’s talk about what’s already going well:

• It’s a donut chart with only two slices – check.
• It’s got dark-light contrast – check.
• And the sentence, “33.26% of participants agreed that the program was a good use of time” is readable. (It scored a 5.8 on the Flesch-Kincaid scale.)

After: Round to the Nearest Whole Number

Let’s make it even better!

I know you understand percentages. Of course you do. You’re reading a data blog.

But percentages are tricky for people who don’t work in data careers.

Percentages.

Percent changes.

Percentage point changes.

Percentiles.

Those are similar-sounding terms with completely different math and meanings.

No wonder others get confused by percentages.

Let’s be proactive and stop confusion at the source—by avoiding percentages whenever possible.

One improvement would be to round the decimal places to the nearest whole number.

After: Use Fractions Instead of Percentages

Another quick win would be to turn the 33% into a fraction (1/3).

After: Put the Fraction into a Sentence

And the best practice would be to turn the 1/3 into one in three.

You could also adjust the chart, transforming the donut chart into an icon array.

That way, there’s cohesion between the chart and the text (i.e., they both talk about one in three).

I don’t recommend using gingerbread people.

• Men don’t have to wear pants and women don’t have to wear dresses.
• Some people don’t identify as men or women.
• You may not know if the data collected represents men or women.

So, what to do instead?

Use icons of real people.

This example is about people, so let’s show the people.

This is symbol font called WeePeople. You can download this for free and use it to visualize people as the real human beings they are.

Accessibility Case Study

By now, you’ve learned about direct labeling, lowering the reading level, and lowering the numeracy level.

Let’s look at a case study and put it all together.

Here’s a before graph based on a real-life project. This organization was running a workforce development program.

In the Good Tech Fest session, I asked the audience to describe what they saw going wrong.

Here’s what they came up with:

• Diagonal text
• Decimals
• Change from a column chart into a bar chart
• Add a takeaway title
• Reverse the order
• Color coding

Within three minutes, we made quick edits that made a big difference.

Rotate the Chart

The first thing we did was rotate it from a column chart to a bar chart.

(We wanted all the text to be horizontal.)

Round Decimals to Whole Numbers

Our next edit was to round the decimals to the nearest whole numbers.

Add a Takeaway Title and Dark-Light Contrast

Next, we added a takeaway title.

Instead of “Participants Working in Each Industry,” we now have “20% of Participants Worked in Retail.”

Then, we highlighted the retail data. We changed that bar to a darker color and grayed out everything else. Dark-light contrast is an easy and effective data storytelling technique.

Add Fractions within a Sentence and Icons

We changed the percentage to a fraction in a sentence.

Then, we added icons, which makes our data more memorable.

Accessibility doesn’t have to take all day.

Accessibility doesn’t have to cost anything.

Accessibility doesn’t have to be complicated.

With a few quick edits, we’ve made this chart faster to read; we lowered the numeracy; we lowered the reading levels; and we made it more memorable.

Download the eBook

Want to learn more about accessible data visualization?

In this ebook, you’ll learn 10 quick wins for designing accessible data visualizations. These small edits can have a big impact for our coworkers, board members, and funders who have color vision deficiencies, hearing loss, or learning disabilities–and for all of us who are pressed for time.

For your complimentary copy, use code: goodtechfest

The post Accessibility Quick Wins: Lower the Numeracy Level appeared first on Depict Data Studio.