Maybe I was afraid he’d grill me–he did.

Maybe I was afraid he’d ask something to get me in trouble–he did!

Maybe I was just too busy–I was.

I’m so glad I finally sat down to talk with Jon for a proper podcast!

We thought it’d be fun to video-record our convo, too. You can listen to the podcast through Jon’s site or watch the video below.

About Jon

Don’t know Jon yet?

Jon is an economist, writer, teacher, and creator of policy-relevant data visualizations. He is considered a leading voice for clarity and accessibility in how researchers communicate their findings.

We’ve known each for nearly a decade already, and even tell the funny story of how we met in the podcast.

10+ Tips from an International Dataviz Speaker

After traveling all over the world to provide data visualization training for the past six+ years, I’ve made list of tips from the point of view as an international dataviz speaker.

(We recorded this podcast in January 2020 and you’ll hear me say that I was about to travel to China. That trip is postponed indefinitely for obvious reasons.)

These are the things I wish I knew sooner about adapting my U.S.-centric trainings so that they’re not so U.S.-centric; working with foreign language interpreters; and even translating from Fahrenheit to Celsius.

Tip #1: Talk to the Person, not to the Interpreter

I’ve worked with sign language interpreters at universities and government agencies. More recently, I worked with foreign language interpreters in Hanoi (in which the attendees were wearing headsets so they can hear the interpreters translating my words).

The best practice is to look at the attendees, not at the interpreters. For example, if someone in the audience asks a question, the speaker should look at the audience member the entire time–not at the interpreter.

Making eye contact with the attendees is not only respectful, but helpful to both of you. Communication involves words, but communication also involves eye contact, body language, and the speed and tone of your speech. By looking at the attendee, you can pick up on all the nuances of his or her facial expressions and body language, which you would miss if you solely looked at the interpreter.

Tip #2: Share the Training Material with Interpreters in Advance

Sharing materials in advance is so helpful for the interpreter and the person needing the interpretation. It allows them the time to review the materials, become familiar with the topic, and also to know your key words and new vocabulary. For example, a sign language interpreter or foreign language interpreter may not have heard the terms “data visualization” or “dataviz” before your talk.

Sharing materials in advance also helps the interpreters to see how you’re planning to structure and organize your talk.

I don’t follow scripts, so I don’t have a script or speaking notes written out for the interpreters to read ahead of time. They’ve told me they simply like having a “head’s up” about the topics and vocabulary.

I usually share handouts during the presentation and then share a PDF’d copy of my slides after the presentation. Sharing materials in advance was new for me. It involves a little more prep time for the speaker, and forces you to finish your prep work much earlier than you normally would’ve, but the payoff for the attendees needing the interpreters makes it worth it.

Tip #3: Talk with the Interpreters Ahead of Time

I always try to talk to the interpreter ahead of time–and not just at 8:59 am for a 9:00 am presentation.

The first time I worked with sign language interpreters was at a university in a big hall. Knowing they would be there ahead of time was so helpful to me. I met with them about an hour before and went over my slides with them, gave them the overall format of my talk. That way, they know when I’ll break for an activity, etc. They also know when they’ll need to spell out terms like d-a-t-a-v-i-s-u-a-l-i-z-a-t-i-o-n or find a synonymous sign.

Hiccups happen though, and sometimes the interpreter shows up at 8:59 am for a 9:00 am presentation. In those cases, I give a quick rundown and start a few minutes late. The time spent with the interpreters is worth it, even if it means starting a few minutes late, because it means the day will go so much better for the attendees needing the interpreters.

Tip #4: Try to Avoid Slang and Idioms

This is hard one: Try to avoid slang or idioms. They’re everywhere, so this is tough!

For example, I might say, “At the end of the day…”

But what does that mean to a Vietnamese speaker for whom English is their third or fourth language? What this phrase really means is, “The most important thing I want you to remember is…”

Or, a “low-hanging fruit edit” would instead be “the easiest edit to make to your graph is…”

It was hilarious–and humbling–to listen to this podcast recording! I heard a dozen more idioms and slang terms throughout my conversation with Jon.

Over the years I’ve had to unlearn my bad academic habits of speaking way too formally. I actually used to try to sound like a textbook with perfect speech and sentence structure. Argh, how boring and awkward!! Now, my speech is intentionally imperfect and conversational in workshops. That style is perfect for English speakers, but it’s a huge challenge for everyone else. I’ve given hundreds of talks to English-speaking audiences, but only a dozen talks to non-native English speakers, so this is something I’m still working on. Sigh. I’ll get there!

Tip #5: Try to Avoid Contractions

Try not to speak in contractions.

Instead of saying “don’t do this thing,” say “do not.”

For a lot of us, the “t” in “don’t” is nearly silent… or there’s a noise in the room… and our attendees will only hear the “do.”

I’ve learned to instead say “do not” and make sure to put an emphasis on the “not” with both my voice and my hands to ensure that the meaning is clear.

I even do this in the U.S. because most training settings have poor audio quality. There’s construction noise outside… someone’s phone rings… the door slams shut… there are conversations outside in the hallway… coughs… sneezes… shuffles of papers… the list goes on.

Saying “do not” instead of “don’t” is more than just a speech pattern; it’s forced me to become more clear on my dataviz recommendations. 

Tip #6: Try to Avoid Religious Phrases

Since speaking in Southeast Asia, I have actively tried to avoid using religious phrases.

For example if I’m holding my laser pointer, and it flies out of my hand (which happens more than you think!), my instinct would be to say “oh my goodness!” or “oh my gosh!”  

That phrase has zero translation to someone who’s not in a Judeo-Christian culture.

Interpreters will translate everything in an effort to make it feel more real and natural. What do interpreters make of the phrase “oh my goodness?” Does that mean it’s literally good that I dropped my laser pointer? What a confusing phrase.

Tip #7: Try to Use Your Clearest, Accent-Free Voice

This may be a little controversial… but try to avoid speaking with an accent.

I’m from Virginia and don’t have a southern accent, in my opinion… except when I’m around people from the south. Then, I can get a little southern-sounding.

When I’m around fellow millennials, I can get a little millennial-sounding.

You have to turn all that off. You have to speak in the purest, accent-free version of yourself.

Tip #8: Use Body language

As I said earlier, communication is not just words. Body language is also another way we communicate with each other and it can be so helpful (or harmful) in a presentation.

Body language and cues matter because if an attendee is listening to an interpreter there’s often a delay in what I say and then what they hear. During that time though they’re looking at me and can see from my body language if what I’m saying is positive or negative.

If you’re asking them to start using a new dataviz practice…

• nod your head
• smile with your mouth and with your eyes
• give a thumbs up
• give an “okay” sign

If you’re asking them to avoid using a dataviz practice…

• Shake your head “no” from side to side
• Use your facial expressions to indicate “no”
• Give a thumbs down
• Make an “x” motion with your arms

Talking with your hands isn’t just for decoration. And it doesn’t have to be distracting. You can use your hands productively to reinforce what you’re saying with your voice.

Tip #9: Find Non-U.S. Graphs and Maps

When you’re speaking in another country, make sure you’ve got examples from that country.

For example, if you’re showing currency, use the currency symbol for the country you’re speaking in.

When showing how to color code maps, I use a U.S. map in the U.S. but a South American map if speaking in South America.

Tip #10: Adjust the Agenda to the Culture You’re In

You have to adjust the agenda to the culture you’re in. In the podcast, Jon shared an example where one of our speaker friends was giving a training in the United Arab Emirates. That speaker needed to account for planned prayer time during his training agenda. There are cultural differences that you need to build in to your agenda and be considerate of.

I’ve worked with several religious groups in the U.S. who incorporate prayer time and religious services into the workday. They’ve always told me about prayer time in advance, which is helpful. Then I can plan the rest of the content around those scheduled blocks.

Tip #11: Translate Between the 12-Hour or 24-Hour Clock

Speaking of agendas… Remember that many countries follow the 24-hour clock, which Americans sometimes refer to as military time.

If I have a slide showing the day’s agenda, or a printed agenda, I’ll quickly translate the times between 12-hour and 24-hour time before the session.

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Tip #12: Learn to Translate Fahrenheit to Celsius

Here’s another tip that I remembered at the very end of the podcast–Fellow Americans, we have to learn to translate Fahrenheit to Celsius!

I’ve needed this translation in the most practical ways. For example, I remember sitting in a way-too-cold training room in Guatemala, and I was having trouble adjusting the wall thermostat by myself. I needed to call the hotel staff and request a new temperature–in Spanish, and in Celsius. Room temperature in the U.S. is around 70 degrees Fahrenheit, which is around 21 degrees Celsius. This 70-to-21 temperature translation is honestly the only one I can remember, but it’s the most practical and important for my work.

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Formatting Reports

In the podcast, Jon surprised me when he asked about formatting reports. I always thought everyone was concerned with formatting reports, and I never really realized how many blog posts I’ve devoted to this topic before.

I work with a lot of different types of groups: for-profits, non-profits, big, small, etc. In a perfect world, they would all have very short, succinct reports in addition to many other formats (slideshow, handouts, info graphic, social media, press release, etc). And while that’s the case in some groups, for most it’s not in process and not happening yet. But they all do have a report of some kind, so my plan is always to take that and make it a great report.

Color-Coding Reports by Chapter

Jon and I talked about one of my favorite dataviz techniques, which is color-coding reports by chapter.

The idea behind this is you might have a long report but we still need to make it easy for people to find what they’re looking for.

I recommend people use their branding colors rather than picking at random.

So Chapter 1 is brand color 1, Chapter 2 is brand color 2 and so on.

And everything in that chapter is the same color: the headings, the graphs, the call-out boxes, and even the bullet points.

When the reader sees a new color, they know that a color change = a content change.

You can view more examples of color-coding by category here.

If you only have a few hours to edit your report, color-coding by chapter is, by far, the best use of your editing time.

Using Everyday Software in Reports + Dataviz

I’m not a huge fan of specialized software, I use everyday products to make great reports. Word, Excel and PowerPoint are the common denominators when you’ve got many people working on the same report. Creating reports in a software everyone is familiar ensures that they will continue to use the report even when I’m gone.

Controversial Dataviz Advice

Jon loves to get me in trouble, so he asked me whether I have any controversial dataviz advice!

There are definitely some topics that are debated in the data viz world. Here’s my stance on just a couple of controversial topics.

Pie Charts Are Okay

I teach that pie charts are okay–in certain situations. I have a whole blog post with a list of seven rules for using pie charts.

A million people in the dataviz community disagree and say that we should never use pie charts. But, they never follow up with advice on what to do instead. It’s SO unhelpful to bash pie charts without offering better alternatives, which is where all my pie chart makeover blog posts come in.

Whether Bar Charts Should Start at Zero

There’s differing opinions on whether bar charts should start at zero (also known as a zero axis or zero baselines). I would suggest you listen to Jon’s PolicyViz podcast episode #66 with Jessica Witt. She’s an expert on this and I think her recommendation is a good guideline to follow.

In my workshops, I am very clear that you must label your minimum and maximum. I wasn’t always to clear on this but I changed my tune after the last election cycle because I felt like graph-makers were purposely being misleading by not starting charts at zero–and also not labeling their scales.

Your Turn

I brainstormed a dozen ways that we need to adapt our training styles when speaking in our home country vs. when visiting another country… but there are probably a dozen more. Someday, in all my “spare” time, I’ll write a follow-up blog post with additional tips. In the meantime, what am I missing?

The post 10+ Tips from an International Dataviz Speaker appeared first on Depict Data Studio.

It’s intimidating to sit in front of a blank screen and try to start developing your report, infographic, or dashboard from scratch. What data sources will you include? How will you analyze the data? What type of graph will best present your results?

The NHVRC provides hundreds of pages of data about home visiting across the United States. Our team works together behind the scenes to create and finesse each visualization. We want to make sure the numbers are accurate, easy to understand, and visually appealing.

As we tweak the design elements of the 2018 Home Visiting Yearbook—the NHVRC’s third major publication since launching in 2017—we’ve revisited some of our earliest conversations around data visualization. This brief presents our process in five simple steps, along with images of our products at various phases. We hope this inside look can help guide readers looking to share their own home visiting data.

Step 1. Select Your Data Sources

Will you use publicly available datasets? Will you need to collect new data? Which specific variables are available? Sit down with your teammates and select data sources together, just like the NHVRC did during one of our earliest brainstorming sessions. Your process doesn’t have to be fancy. Handwritten notes and whiteboards work just fine.

Step 2. Choose Your Unit of Analysis

Next, think about how you’ll analyze your numbers. For the NHVRC, we decided to provide both national- and state-level analysis of the numbers. The 2017 Home Visiting Yearbook and follow-up Data Supplement) present a map of the United States, so that readers can see where home visiting programs operate across the country. Later, we provide individual state profiles, so that readers can learn about the children and families who benefit from home visiting in particular states and territories. We also decided to provide model-level details in a series of model profiles.

Step 3. Brainstorm Your Page Layout

It’s one thing to design a single graph. It’s another to design an entire page or an entire report! The graphs need a logical, intentional flow from one to the next. Start broad and then go deeper. For the NHVRC State Profiles, we started with the broadest details, like the name of each state and the number of children reached by home visiting programs. Then, we dove into demographic details about those children and their caregivers.

Step 4. Choose the Right Chart for Each Variable

Will you use a pie chart, a bar chart, or something else altogether? Here are a few familiar chart types and some that you may not have encountered before.

Pies and Donuts

Let’s start with the most familiar chart of all, the pie chart. Some data visualization trainers advise against using pie charts at all. That’s probably because so many of us accidentally include too many slices, like this impossible-to-read pie. Here’s what not to do.

Two-slice pies are fine. You can also try an alternative, like a two-slice donut, two-slice waffle, or two-slice icon array. Icon arrays contain miniature shapes, like the miniature coffee cups below.

Bar Charts

Bar charts are another familiar chart type. My advice—if you’re not sure which chart to use, start with a bar chart instead of a pie chart. Bars are often easier to read than pies, especially when you’ve got more than two categories.

The only problem with bar charts is that they tend to be overused. Try an alternative, like a lollipop chart, which places a dot at the end of the bar. Lollipops tend to look cleaner than bars, and they focus viewers’ attention where you want it—on the endpoints.

If you decide to continue using bar charts, consider adding valuable context. Does your organization track your progress toward meeting year-end goals or specific outcomes outlined in grants or contracts? If so, add a target line or use overlapping bars to showcase your achievements.

Line Charts

Need to show how something has unfolded over time? Try a line chart to let your viewers see all the peaks and valleys. Want to focus on the big picture? Try a slope chart, in which viewers focus on the steepness of the slope over time.

When you’re using line charts, beware of the spaghetti line! Spaghetti lines crisscross and intersect—just like a pile of tangled spaghetti—making them near-impossible to decipher. If you see a spaghetti line chart in your project, don’t worry. You can try making it easier to read by highlighting a single line of interest in a darker color or testing a small multiples layout in which you build multiple small charts, one per line.

Step 5. Draft Your Visualizations with Sticky Notes

You may be tempted to sit down at your computer and begin creating charts right away. I’ve found it helpful to create drafts with good old paper and pencil before creating anything on the computer. I also like using sticky notes as I’m drafting because they allow me to move graphs around the page and get the placement just right. Your sticky notes might contain some of the pies charts, bar charts, or line charts shown previously.

While drafting the NHVRC State Profiles, we drew one graph covering one variable per sticky note. Then, we arranged and rearranged the sticky notes. As a team, we talked about which variables should come first, second, and third on each page. When we reached consensus, we started building the graphs on the computer. Drafting on paper saved us a lot of time and helped us develop a final product that reflected everyone’s input.

We hope this behind-the-scenes peek into our data visualization process and early images can help you during your own drafting process. Click through the NHVRC website to see our results so far and feel free to send us your data masterpieces!

The post Five Simple Steps to Creating Home Visiting DataViz appeared first on Depict Data Studio.

Before

Here’s a screenshot from one group’s (public-facing) research report. The authors of the report talked about wheelchairs that were given to people in other countries. This was the demographic section of the report so there were a few graphs showing who those wheelchairs went to — men, women, kids, adults, and so on. There are 3D pie charts but I don’t fault anyone for their before graphs. We’ve all been there.

After

The first pie chart was about gender–the proportion of wheelchairs distributed to men and women. According to my seven pie chart guidelines, gender can stay in a pie chart. Gender is a nominal/categorical variable and there are only a couple slices. We just need to reformat things a bit to make the graph easier to read. The before version is 3D, so the chart’s height makes the slices look larger or smaller than they really are. 3D distorts data.

There’s a legend below the chart so viewers would have to zig-zag their eyes back and forth to figure out which color corresponds to which slice. And the viewers would literally be zig-zagging because men are on the left side of the pie and on the right side of the legend, a software oddity. The after version is 2D; has labels directly on top of the slices to avoid wasting time hunting for information in the legend; and it uses colors from the organization’s logo rather than the software program’s default color palette.

The second pie chart was about age ranges–the proportion of wheelchairs given out to younger people and older people. According to my seven pie chart guidelines, age ranges can’t stay in a pie chart because age range is an ordinal variable. There’s a natural order or progression from younger people over to older people, so we need the chart to reflect that built-in characteristic. You could display these age ranges in a stacked bar chart or in a histogram. I went with a histogram because the 0-5 years segment was tiny and nearly invisible in a stacked bar chart. It’s faster to read left to right (the histogram) than to start at 12 o’clock and read clockwise (the pie).

I never cease to be amazed how small edits lead to a big impact. This page of the report looks completely different!

No, I didn’t keep the tables. When we see tables and graphs beside each other, our brains wonder whether the table matches the graph. Is this the same thing? Or different? Wait, it’s the same, right? So why did they include both? Oh, for the raw numbers? The graph has the percentages but not the numbers? That’s the only added value of the table? Redundant tables and graphs are unnecessarily burdensome for viewers. My rule of thumb is to display raw numbers for anything below 100 (3 of 7 people, not 43%) and percentages for anything above 100. We’re talking about well over 100 units here (either 886 or 866 wheelchairs, what an unfortunate typo) so we could’ve just displayed percentages in the pie chart and left off the raw numbers altogether.

However, this report was written for a technical audience, and technical audiences love extra details like numbers and percentages, so I simply included both within the after version.

Sometimes workshop attendees are afraid that including graphs will lengthen their reports. On the contrary, data visualization often decreases your report’s length. I freed up space by deleting the redundant tables. I decided to use that space for titles and subtitles to explain each graph. Before, the graphs were just slapped into the report without any explanatory text. I’m a visual person and prefer to read graphs over paragraphs. Other people prefer to read the paragraphs over graphs. Both viewers’ preferences are met when we add explanatory text alongside graphs.

The post Pie Chart Makeover: Transforming a Research Report appeared first on Depict Data Studio.

Does your organization need to track how much money you’re making and spending?

I see way too many revenue and expenses numbers gathering dust in hard-to-read pie charts.

In this blog post, you’ll see how transforming your pie charts into a dashboard–built in good ol’ Microsoft Excel–can be more useful for your organization’s leaders.

Before: Comparing Across Pies

A couple weeks ago I was in Birmingham with the Alabama Power Company’s grantees. We spent two days learning data visualization principles and producing makeovers of their graphs.

One of the grantees was presenting their revenue and expenses data like this, in two pie charts.

I changed their numbers and categories in this anonymized version, but revenue included things like grants from foundations and expenses included things like payroll.

I’m not anti-pie but I do have a long list of pie chart guidelines.

These numbers can’t stay in a pie chart because:

• there are too many slices;
• we can only show one pie at a time—not two beside each other; and
• pie charts are only useful for showing a single snapshot in time (this group needed to compare quarterly spending, and pies can’t show trends over time).

After

Let’s look at three data visualization makeovers.

They get a little more helpful each time!

The Bare Minimum: Pies into Bars

At the very least, we need to convert the pies into bars. It’s easier for our brains to compare the lengths of bars than to compare the slices/angles/area of pies.

Yes, we could get fancy by making the expenses bars go towards the left since those are technically negative numbers.

Add Context to the Bars

I try to anticipate what types of mental math the viewers will be doing.

The organization’s leaders and Board members will probably need to know the total revenue and total expenses.

Rather than making those viewers do mental math or tally the numbers in the margins of their handout, I inserted text boxes with the totals.

What They Really Need: A One-Page Dashboard

The pie charts and bar charts above were only giving the viewers a single snapshot in time. To manage effectively, leaders need to monitor trends over time.

Imagine what this Board meeting would look like: the attendees have a handout about the fourth quarter’s revenue and expenses. Seeing the fourth quarter’s numbers is great, but what about the third quarter? Did we spend more, less, or about the same as the prior quarter?

The attendees would have to search through the stack of papers in their folders to find the prior quarter’s handout, place the two pages next to each other on the table, and then zig-zag their eyes back and forth across the table and try to make comparisons. Viewers should never have to lay two pages beside each other or scroll through documents to make comparisons. That’s your job as the designer: to anticipate what they need to compare — quarterly spending — and place those comparisons as close as physically possible.

I designed a one-page dashboard that did just that — placed the quarterly numbers directly beside each other to make comparisons natural and easy.

I visualized quarterly patterns with spark lines so that viewers could generally see whether numbers were going up, going down, or holding steady over the course of the year. Then, I anticipated that viewers would need to know the year-end totals for each of the categories. Viewers should never have to do mental math; you should do the math for them.

I visualized the year-end totals with data bars. Yes, we could’ve gotten fancy and made the expenses bars go towards the left to reflect that expenses are negative numbers.

And yes, we could’ve added a row at the bottom that calculated the difference between each quarter’s revenue and expenses to see whether we were cash-flow positive. This group’s priority was monitoring how things changed over time, so the design reflects that priority.

Quite an improvement over the pie charts, don’t you agree?

Bonus: Watch the Video Lesson

Want more behind-the-scenes details? Here’s a 13-min video for you.

Bonus: Download the Templates

Want to design your own revenue and expenses dashboard?

Purchase the templates, register for the Dashboard Design course, bring me in for a private workshop, or borrow my brain during a consulting session.

The post Monitor Your Organization’s Revenue and Expenses with a Dashboard in Microsoft Excel appeared first on Depict Data Studio.

Let’s walk through a real-life example!

A few weeks ago I was in Indianapolis with the juvenile detention alternatives initiative. This group wanted to graph:

• how many youth went to juvenile detention centers,
• by gender, and
• by quarter.

Brainstorming

There are a dozen ways to graph each dataset. For this data, we could utilize:

1. table
2. heat table
3. quarter-by-quarter pies (well, not the best choice)
4. one year-end pie
5. line graph with numbers
6. small multiples line graphs with numbers
7. clustered bar
8. small multiples bar
9. stacked bars with numbers
10. stacked bars with percentages
11. stacked area with numbers
12. stacked area with percents
13. and probably a few more that I haven’t thought of yet

Before: Quarter-by-Quarter Pies

Naturally, the quarter-by-quarter-no-way-these-don’t-work-pies were currently being used by a few people in the room. I adjusted the wording from youth going to detention centers to youth being served so that this example is relevant to even more of you.

The quarter-by-quarter pies are off the table. According to my pie chart guidelines, gender breakdowns are one of the only times it’s okay to use a pie chart (nominal variable, just a few slices, etc.).

But it’s really hard to make comparisons across multiple pies. Your eyes would have to jump from the 1st quarter pie to the 2nd quarter pie to the 3rd quarter pie to the 4th quarter pie and back again. I’m tired just thinking about it.

After

After we sketched ideas and discussed the pros and cons of each approach, we decided that stacked bars with numbers were the most promising. Stacked bars can display the number of males, females, and the totals. They’re also easy to label (compared to, say, a stacked area chart). We used vertical bars because time is ordinal.

My rule of thumb is to display numbers for anything less than 100 and percentages for anything over 100. Fewer than 100 youth went to these detention centers each quarter, so we displayed numbers.

For a Slideshow: Stacked Columns with a Short Title

Here’s the after version for a slideshow:

For a Report: Stacked Columns with a Subtitle

Here’s the after version for a handout or report, which intentionally contains a bit more explanatory text.

Bonus: Make This Yourself

No, I didn’t add the totals to each quarter’s bar chart with text boxes. Yes, that’s possible. It’s also a ton of work to crunch the numbers, create text boxes, and center them perfectly above each bar. This is a stacked bar chart with three segments: males, females, and totals. The total segment has a transparent fill so it looks invisible.

If you want to explore the strategy in more detail, watch the video or download the template.

Bonus: Download the Templates

Purchase the templates ($5)

The post Stop Putting Quarterly Trends in Pie Charts appeared first on Depict Data Studio.

Rules for Using Pie Charts and Donut Charts

Here are my guidelines for using pie and donut charts. Pie charts are okay when they:

1. are well-formatted. No 3D, exploding slices, leader lines, or legends.
2. display nominal variables. Ordinal variables don’t belong in a pie chart.
3. add to 100%. I’ve seen pies that only add to 90% because the designer deleted the “other” category and forgot to recalculate the new percentages.
4. contain positive numbers. I’ve seen designers place a mix of positive and negative numbers inside the same pie chart, which doesn’t make any sense.
5. display a single point in time. Patterns over time belong in a time series graph, like a slope chart, line chart, or dot plot.
6. only have two or three slices. Four slices is pushing it.
7. are displayed individually. Only show one pie chart at a time. No small multiples pies. Comparisons across multiple pies are time-consuming.

Finally, while I don’t consider this to be a strict guideline, pie charts tend to be easiest to read with common fractions, like a one-fourth vs. three-fourths pie or a one-third vs. two-thirds pie.

Circumstances When Pie Charts Are Okay

Given these guidelines, I use pie charts to show:

• male/female/etc. gender categories;
• yes/no survey responses;
• students who graduated high school on time vs. didn’t graduate high school on time;
• adults who live in single-family homes vs. adults who live in other housing types; and/or
• other binary data.

Alternatives to Pie Charts

Let’s tackle these pie charts! It’s not sufficient to tell you to avoid pie charts. You need to know what to do instead. Here are some pie chart makeovers that are inspired by my real projects.

If Your Pie Chart is Poorly Formatted… Then Format It!

The chart on the lower left is poorly formatted. This one is 3D, so the slices look larger or smaller than they really are… and, it’s exploding, which is distracting for viewers… and instead of the percentages being right on top of the pie slices, now there’s a tiny legend down below the pie, which means our viewers would have to zig-zag their eyes around the slide to tell which slice is which.

The final sin in this poorly-formatted pie chart is that there are leader lines, those gray lines connecting the 25% and 75% to their corresponding slices. Plus, So much ink is on the page, yet so little is actually focused on the data.

The well-formatted pie chart on the lower right is fair game. Gender is nominal or categorical, so that works. We’re only showing a single point in time, so that works too. And we’ve only got two different slices.

If You’ve Got Ordinal Data… Then Use a Stacked Bar Chart or a Column Chart

Ordinal or sequential variables have a natural order, like responses to a survey that go from strongly agree to agree to disagree to strongly disagree.

In this case, you’d swap out your pie chart and use a stacked bar chart instead, so that viewers can tell which category is at which end of the spectrum – the agrees on one side and the disagrees on the other side.

Another type of ordinal or sequential variable is age ranges. Histograms are a great alternative to pie charts when you’ve got ordinal or sequential groupings. Let your audience read across the screen from left to right (i.e., from lowest to highest).

If You’ve Got Negative Numbers…Then Use a Deviation Chart

I mentioned that pie charts are only for positive numbers, not negative numbers. Sometimes we have negative numbers when we’re dealing with changes over time.

In this example, we’re looking at four products and whether they increased or decreased in sales compared to the previous quarter. For example, Product A’s sales decreased 20% compared to the prior quarter while Product B’s sales improved 40% compared to the prior quarter.

Instead of a pie chart, we’d use a column chart or bar chart. In your software program, the negative numbers will automatically flip in the opposite direction of your positive numbers. The axis line runs across the middle at 0% and we can see which products went down (like Product A) and which products went up (like Products B, C, and D).

If You’ve Got Patterns Over Time… Then Use a Time Series Chart

What if you have time series data, that is, patterns over time? Maybe you’re trying to show data for each Quarter – Quarter 1, Quarter 2, Quarter 3, and Quarter 4 – or for each month, or for each year in the grant cycle.

Swap out your pie chart and use a line chart instead. You want viewers to see the beginning point – Quarter 1 – over to the end point – which is Quarter 4.

If You’ve Got More than Two or Three Categories… Then Use a Bar Chart

Pie charts are easiest to read with only two or three slices.

What if you have lots of different slices, like favorite ice cream flavors? This pie chart has too many slices – vanilla, chocolate, strawberry, mint, and cookie dough. It’s too hard for our brains to compare the slices to each other.

Swap out the pie chart for a bar chart and order the bars from greatest to least (or least to greatest). Chocolate would be listed first because it’s the most popular, and cookie dough would be listed last because it’s the least popular.

If You’re Tempted to Display More than One Pie at a Time… Then Use a Grouping of Stacked Bar Charts

What if you want to compare several companies, organizations, outcomes, etc. all at once? Pie charts are hard enough to read. Our brains don’t do well deciphering the angles, area, or circumference of circles. Two or three or four different pie charts can be understood, but with way too much mental energy.

In this example, we’re asking our viewers to look first at the 20% angle, and then at the 40% angle, and then their eyes have to zig-zag to the 60% angle, and then their eyes have to zig-zag over to the 80% angle. So. Much. Work.

In this case, you’d swap your small multiples pie chart for a small multiples stacked bar chart. The part-to-whole pattern is still there, but now our viewers’ eyes only have to make a single, diagonal swooping motion down the page to compare all four companies at once. Less energy required for reading, more energy reserved for making decisions based on that data.

Join the Conversation

Have you seen real-life pie charts or donut charts that are in desperate need of a makeover? Comment below and include a link to the example, and I may even include it in a future pie chart makeover blog post.

The post When Pie Charts Are Okay (Seriously): Guidelines for Using Pie and Donut Charts appeared first on Depict Data Studio.