In this video, you’ll see more than a dozen different charts that are possible inside Microsoft Excel.

What’s Inside

• 0:00 Intro
• 0:17 Dataviz On The Go
• 0:36 3 Levels of Excel Skills
• 1:05 Level 1: Overused Native Charts (Bars, Lines, Pies, etc.)
• 2:35 Level 2: Underused Native Charts (Combo, Tree, Sunburst, Maps, etc.)
• 4:01 Level 3: Non-Native Charts (Population Pyramids, Dumbbell Dots, Lollipops, etc.)
• 5:02 Disguises Needed for Non-Native Charts
• 5:54 Interactive Dashboards in Excel (Excel Tables, Pivot Tables, Pivot Charts, and Slicers)
• 6:16 Static Dashboards in Excel (Made in Excel, but Saved/Shared as PDFs)
• 6:41 Your Turn
• 6:55 A Personal Note

3 Levels of Excel Vizardry

I’ve taught data visualization in Excel a dozen different ways over the years.

Nowadays, I teach Excel dataviz based on the degree of behind-the-scenes hacking needed to produce that chart.

We start easy. Then, we work up to harder battles.

Here are the three Levels of Excel Vizardry:

• Level 1: Overused Native Charts
• Level 2: Underused Native Charts
• Level 3: Non-Native

Let’s go through some of the Excel secrets in more detail.

Level 1: Overused Native Charts

These are the familiar faces:

• Pies
• Donuts
• Bars and columns
• Clustered bars and clustered columns
• Stacked bars and stacked columns
• Line graphs

What are Native Charts?

“Native” charts mean they’re available from our menu with just a few clicks:

What’s Wrong with Overused Charts?

There’s nothing wrong with a bar chart here or there… but any chart gets boring when we show it over and over and over and over and over and over.

There’s also the issue of analytical depth — or lack of depth.. If we’re only using bar charts… then we’re only showing totals and averages. There are dozens more statistical approaches!

Beware! Formatting Needed

Stacked bar charts, for example.

They’re easy to make.

But we still have to:

• enlarge the font;
• darken the font (to pass official Accessibility rules for color contrast);
• directly label the data (so viewers aren’t relying on the colored legend alone — another Accessibility rule);
• outline the touching shapes in white (which helps with colorblindness and grayscale printing);
• show fewer increments in the scale (so it’s not so busy);
• decide whether to apply a dark-light contrast — or not (learn about data storytelling here); and
• adjust the gap width (if you want) to nudge the bars closer together.

Level 2: Underused Native Charts

This is where it starts getting fun!!

Excel can make:

• Combo charts (e.g., a column chart with a target line, as shown below)
• Overlapping Bars
• Area charts (where you shade the area underneath the line for better oomph and high color contrast)
• Slopes (a line chart with exactly 2 points in time, like pre and post)
• Small Multiples Lines (to combat the spaghetti line graph)
• Bumps (for rankings)
• Scatter plots (x and y)
• Bubble charts (x, y, and z)
• Tree maps (for nested categories)
• Heat Maps
• Sunbursts (nesting)
• Box and Whisker (to go beyond averages and show the min, quartile 1, median, quartile 3, and max)
• Waterfall (how pieces add to a net number)
• Radar (to compare several ordinal categories at once)
• Icons & Symbols (to make our graphs easier to navigate — and more memorable!)

Yes, These are Native Charts

Well… if you’re using the latest version of Excel.

If you’re on outdated software, (most of) these charts are still possible. They just get harder to make, i.e., they’re in Level 4 territory.

Yes, Underused Native Charts Add Variety (and Analytical Depth)

We’re not just adding variety for variety’s sake.

(Although common sense — and hundreds of consulting projects — has shown me that dataviz novelty is one of the best ways to increase engagement.)

Most importantly, we’re adding analytical depth. For example, a regular ol’ bar chart just compares the average or total of several categories. What if we compare them by location, too? Now we’ve got a heat map! We can spot geographical patterns, which would’ve been impossible in a bar chart.

Beware! Formatting Needed

Scatter plots are easy to make.

But we still have to:

• enlarge the font;
• darken the font (to pass official Accessibility rules for color contrast);
• add a key (that each dot represents one student);
• label the scales (with everyday language, like More skills gains, because scatter plots are notoriously difficult to read for people who don’t stare at graphs all the time); and
• decide whether to add a dark-light contrast.

Level 3: Non-Native Charts

Are you already using a variety of charts? Have you actually analyzed your data (beyond averages, and beyond totals)? Can you adjust the gap width, annotate the data, and apply colors strategically in your sleep?

Then you’re ready for Level 3!

With behind-the-scenes elbow grease, you can make:

• Stream Graphs
• Waffles
• B’Arcs
• Small Multiples Bars
• Population Pyramids
• Diverging Stacked Bars
• Lollipops
• Dots
• Swarm Plots
• Tile Grid Maps
• Sankey Diagrams

What are Non-Native Charts?

You won’t find any buttons that automatically make these charts.

Instead, we have to insert one chart type… and disguise it as something else.

For example, we have to insert a stacked bar chart… and disguise it as a waffle chart. You’ll need a Magic Table behind the scenes, too.

A stacked bar chart gets disguised as a population pyramid. Yes, you’ll need a Magic Table with placeholder values.

A scatter plot gets disguised as a dot plot, and so on. Each value gets assigned a x-y placeholder location inside the Magic Table.

Do these maneuvers turn your brain inside out and upside down? You’re not alone.

Learn More

If you’re consistently making, editing, and applying graphs from Level 3, you’re already a vizard. Get in touch so I can send work your way!

If you’re in Level 1 or 2, you’ll love Data Storytelling in Excel. You’ll go slow and steady so you don’t feel overwhelmed. You’ll dip your toe in… and then you’ll be swimming in the deep end in no time.

The post Which Graphs Can I Make in Excel? appeared first on Depict Data Studio.

Researchers, evaluators, and scientists complete my online courses. Or they bring me in for private workshops.

And they start applying what they learned. GREAT!!!

But it’s a little off. OOPS.

This is entirely my fault. I’ve been recommending that we use icons for years now — but I haven’t been clear enough about how to use them, and how not to use them.

In this blog post, you’ll see 8 different types of icon use. The good, bad, and ugly.

(1) Multi-Color 1990s-Era Clip-Art: NOOOOOOOO

Let’s start with what not to do: clip-art.

Icons and clip-art are similar, but not identical.

Icons use one color, so they hold up well in grayscale printing, or when very small.

Clip-art uses several colors, so it doesn’t hold up well in grayscale printing, and it’s hard to see when it’s small.

For these obvious reasons — clip-art is outdated and hard to see — clip-art gets The Big Red X.

(2) Cheesy, Posed Stock Photography: NOOOOOOOO

Gosh, I hope this one’s obvious.

I love adding photographs to reports, slideshows, and infographics.

But not the cheesy, posed type, like this.

Another Big Red X.

(3) One-Color Icons to Replace Words: NOOOOOOOO

One-color icons are okay.

But icons can only accompany words, not replace words.

(4) Icons to Accompany Words: Yes!

Let’s start by adding words: males and females.

Then, we’ll turn those choppy phrases into full sentences to remove guesswork.

We’ll bold a few key words to make it more skimmable.

We’ll color-code the keywords to match the icons (blue keywords for blue icons).

Finally, we’ll color-code by category: blue for one group, and green for another. You’d obviously use your brand colors, not mine, but the technique is the same: one hue per category.

Even if you’re the slowest typer in the world, these bare-minimum edits should only take a minute.

(5) Icons to Categorize: Yes!

Next, let’s add some actual, ya know, graphs.

Bar charts are fine, but they’re super boring if that’s all we have.

These are binary variables — a.k.a. yes/no variables — so two-slice pies are perfectly fine.

(Here’s my list of pie chart guidelines if you’re not familiar with my stance on pies.)

This is where we can add icons to categorize.

You see the difference, right?

I’m not a fan of using icons on their own, like the previous examples. They feel overly-simplistic and dumbed-down. But I am a fan of using icons to accompany other graphs, and to aid with categorization, like this:

We’re not limited to pies for binary variables.

We could use pies, donuts, or square pies.

No matter the graph type, the icon usage is the same: They’re accompanying the graphs, and aid with categorization.

(6) Icons to Show Proportions: Yes!

We can also use icons as the visualization itself.

Collages of icons are called icon arrays. The square version is also known as a waffle chart.

For bonus points, we could add the male/female icons to aid with categorization, too.

You see the distinction, right? The primary icons (the collages of squares or circles) are used to visualize the data, not just decorate it.

(7) Overly-Simplistic Icons to Humanize: NOOOOOOOO

The only thing worse than one dumbed-down Gingerbread Person is a hundred of them.

NO MORE GINGERBREAD PEOPLE!!!

(8) Realistic Icons to Humanize: Yes!

I am a fan of using realistic icons to humanize the data.

You see the differences, right? We’re not using single icons just to decorate, like the first couple examples. We’re using icons to categorize and/or to show proportions.

And we’re not using dumbed-down Gingerbread People. We’re using realistic human silhouettes.

More Examples of Realistic Icons to Humanize

I want to normalize these realistic icons for you. Here are a couple examples from the wild:

• The proportion of female chairs in board or CEO positions in German companies
• COVID-19 won’t spread as easily when Oregon reaches herd immunity

Using Smaller Denominators

All icons — squares, circles, Gingerbread People, and realistic human icons — get tricky to read when they’re tiny.

In some projects, we can simplify our fractions.

I tried changing 42% of men to 42 of 100 men, and then to 21 of 50 men. That worked fine!

But when I tried changing 37% of women to 37 of 100 women, and then to 18.5 of 50 women… yuck. If our unit of analysis is people, we can’t talk about or visualize half a person. That’s confusing to our audiences.

So while I’d prefer to simplify the fraction, I can’t in this specific example.

Traditional and Storytelling Versions

Hopefully you’ve heard me talk about traditional vs. storytelling graphs before. If not, you can watch this video for a quick overview. Both versions are correct, but they’re correct for different types of audiences.

The Bottom Line

There are several different ways to use icons in data visualization, and some are better than others.

I don’t recommend clip-art (version 1) or cheesy stock photos (version 2).

I don’t recommend icons to replace words (version 3).

I don’t even recommend icons on their own (version 4).

Instead, at a bare minimum, we should be using icons to accompany other graphs and to categorize (version 5).

Better yet, I’d prefer that we use icons (like little squares or circles) to show proportions (version 6).

And when our unit of analysis is humans, I’d prefer that we use realistic human icons (version 8) and never the dumbed-down Gingerbread People (version 7).

Your Turn

Which version of icons are you currently using? Which one might you try in the future? Comment below with all your ideas! Bonus points for sharing links to your public-facing projects so we can learn from each other.

The post Use Icons to Visualize Data, Not Just Decorate appeared first on Depict Data Studio.

Benefits of Monthly Reports in Large Organisations

Why not just stick with annual reports? Or quarterly reports?

Monthly reports have at least eight advantages over quarterly and annual reports that outweigh the initial costs of automating them.

Data Literacy

Regular, consistently presented monthly reports enable people to become familiar with the terms and parameters used to produce metrics, thereby enhancing their understanding of where an organisation is heading in relation to its targets.

Everyone is on the Same Page

When the same parameters are used for each report the metrics are directly comparable, and everyone is on the same page.

Advanced Warning of Issues that Require Attention

Monthly reports enable potential problems to be detected and addressed early. 

Progress Towards Targets

Monthly reports show readers progress towards targets throughout the year. If metrics are falling behind targets, action can be taken to address the issue. Moreover, if a particular metric is meeting targets, resources can be diverted to prioritising areas that need attention.

Familiarity with Ebbs and Flows of the Year

Monthly reports can inform general patterns throughout the year.

In the example below, the organisation makes most of its sales in the month of July (around 25%) and in December (around 20%).

Generating reports on a monthly basis enables this organisation to estimate that if they haven’t made 50% of their sales by June (i.e. half way through the year) then there is no need to panic until they see the July report when a large peak in sales is expected based on prior years’ data.

Efficiency

In large organisations there are often multiple committees and multiple analysts talking about the same data.

In some cases, producing a report for one department or area of an organisation can require a similar workload to producing the same report across the organisation.

Monthly reports produced for the organisation results in fewer requests for standard metrics from multiple departments. I’ve also received fewer urgent requests as people often refer to the last month’s report if they are in a pinch for data.  

Data Integrity

With many eyes looking at the data on a regular basis, data integrity issues can be picked up early.

It’s a Way To Celebrate Successes

If an area of an organisation has done particularly well during a month it will show up in the visualisations and be a cause for immediate celebration (rather than waiting a whole year).

Similarly, monthly reports provide a timely way to determine if a strategic initiative, such as a new marketing campaign, is working.

How to Choose the Right Metrics for Monthly Reports

You’re ready to make a monthly report! Now what?

It’s important to select metrics that are relevant over monthly time scales when producing monthly reports.

Using student numbers at a fictional educational institution as an example, the student headcount may not change monthly, but the number of student commencements and student completions likely fluctuate as the year progresses.

In this instance, it would be more informative to present information on the number of student commencements and completions in the monthly reports, and then in the annual report present the headcount of the student population. 

An organisation’s annual report should include the metrics that are important but don’t fluctuate throughout the year.

Good Metrics for Monthly Reports: Metrics that Fluctuate Throughout the Year

Not Good for Monthly Reports: Metrics that Don’t Fluctuate Throughout the Year

Good for Annual Reports: Metrics that are Important But Don’t Fluctuate Throughout the Year

Reducing Your Own Workload through Automation

One of the purposes of monthly reports is to reduce your workload.

You don’t want the monthly reports to take days to produce every month, so I recommend choosing metrics that you can automate and have easy access to that do not require a lot of manual processing to produce results, but are still informative.

How to Choose the Right Visualisations for Monthly Reports

Combining data from multiple areas within organisations can produce complex and highly dynamic data sets.

Provide Enough Context: Compare to a Target and/or Compare to the Same Time in Previous Years

It is therefore important to choose types of data visualisation that give readers enough information and context.

This will enable readers to determine whether the organisation or a department is performing better or worse in relation to a target compared to the same time in previous years.

Cumulative Line Charts: My Preferred Method

Cumulative line charts are my preferred method of data visualisation.

These charts enable readers to easily relate previous years data without having to compare among bar charts.

Cumulative line charts also allow readers to easily see troughs and peaks in previous years and how these influence the results.

Visualising Progress Towards Targets

It is useful to include organisational targets to enable readers to easily compare them to the data.

Progress towards targets can be visualised in several ways.

Pie and donut charts are probably familiar to most readers or reports and can be used in certain circumstances.

See Ann’s post on the seven guidelines for using pie and donut charts and for alternatives to pie charts.

Below is a waffle chart as an example of an alternative to a pie chart.

Ask for Feedback from Your End-Users

I’ve received great feedback, tips and ideas from the end-users of the data. End-users are coming at your report with fresh eyes and they are the ones that have to use the information at the end of the day, so it’s worth incorporating their feedback if you can.

Better yet, take the Great Graphs online course and find out more. I did, and I haven’t looked back.

Share Your Tips for Monthly Reports

Have you got any tips for monthly reports? Does your organisation use them? Share your thoughts below!

The post Why Your Organization Needs Monthly Reports appeared first on Depict Data Studio.

I recently partnered with a school system to visualize data about the percentage of their students who quality for free or reduced-price meals. In the United States, Free and Reduced Meals (a.k.a. FARMs) is basically how we measure poverty in schools. The more students who are eligible for free lunch (based on their family’s income), the more students who are low-income.

Before

Here’s the before version.

They wanted to compare one of the schools to the district as a whole.

The nested design almost made sense because it almost easily allows us to compare the school and district.

But the concentric circles throw off the proportions. Do you see the magenta segments? The outer ring is larger than the inner ring, so the outer five percent is incorrectly larger than the inner five percent. Oops!

After

Let’s look at three possible ways to better tell our story.

Stacked Columns

Here’s my first attempt. At the very least, we need to transform our circles into rectangles.

For all of these makeovers, I selected two colors: one color for the district and another color for the school. I also made the District and School text stand out in a large font size. You would use your own branded colors and fonts, not mine.

My Former Researcher Brain loves stacked charts. Researchy types like me tend to default to this layout. I’m not sure why… just because we’re used to stacked charts?

There’s nothing inherently wrong with stacked charts. They just tend to be overused. Even though I design data visualizations for a living, I still can’t shake my Former Researcher tendencies, and I tend to draft reports with way too many bar charts. As I’m editing my own work, I look for places where I can swap out my overused bar chart for another chart type. I don’t include variety just for variety’s sake. I look for places where the chart’s messaging might be clearer through another chart type.

Waffle Charts

Another option is a waffle chart, like these two waffles. Waffles contain 100 little squares. They’re like square pie charts.

This approach almost works. I like it, but I don’t love it. I’m not in love with the labels. I tried creating text boxes for each of the segments—e.g., 27% free meals or 5% reduced meals—but it was impossible to arrange the text boxes on top of the waffle without looking cluttered or busy. Then, I moved the text boxes to the top of the graph, where they are now… but the viewers have to zig-zag their eyes back and forth between the words and the squares. Good. But not great.

Icon Arrays

Or, go big-picture with icon arrays. I love this approach, and the school district did, too.

In this icon array, we intentionally collapsed the categories—we combined free and reduced into a single category—to focus on big patterns so that our audience wouldn’t get lost in the weeds.

We also intentionally transformed the percentages into whole numbers, which is a better approach for non-data people (i.e., regular people who don’t stare at spreadsheets all day). Whole numbers are a lower numeracy level than percentages, so more people will understand the information.

And we intentionally focused on small numbers—3 in 10 students instead of 30 in 100 students—so that the numbers feel more tangible.

Want to try icon arrays yourself? A heads up: You must be comfortable with rounding. Thirty-two percent of students in the district qualified for free or reduced meals, but I rounded that 32 down to 30. I don’t suggest coloring-in part of an icon. Partially-colored icons can get confusing, especially if you’re using those little people icons.

Icon arrays shine when you need an at-a-glance overview. For example, you might use icon arrays for slideshows or executive summaries. You can save the nuanced stacked columns or waffles for the body of the report.

Your Turn

This isn’t an exhaustive list of options.

What additional designs can you come up with?

Bonus: Download the Materials

Want to explore how I made these visuals? Download the slides and use them however you’d like.

Download the Slides

The post Students Receiving Free and Reduced Meals: From Nested Donuts to an Icon Array appeared first on Depict Data Studio.

What makes a good graph great? Let’s answer that question by taking a walk down memory lane.

Earlier in my career, I was a researcher for a large nonprofit in Washington, DC. We gathered for all-staff meetings every few months, all 100 of us standing like sardines inside our largest conference room. In those meetings, we needed to know more about the teenagers and families we were working with in the community and whether our afterschool programs were effective.

When it was my turn to report on the data, I would stand in front of my fellow sardines and show a slide like this on our tiny, grainy projector screen.

Staff squinted, straining their eyes to read small, diagonal text. I mumbled through a few talking points, like how we worked with a lot of Latino teenagers. They clapped, sort of, when I was finished, and the next person on the agenda began her presentation.

Nowadays, I know better. Here’s how I would revamp that slide if I were to design it today.

• First, I would remove a lot of unnecessary ink. I would delete the logo and the redundant sentences and remove the gray background shading. I would also remove the 3D effect, which was distorting the data—making the columns look taller or smaller than they really were.
• Next, I would more intentionally use text to help tell a story. As an organization, we spent a lot of time serving Latino and African American youth in the surrounding neighborhoods. In the original column chart, the names of the ethnicities were too close together to be legible to staff in the back of the room. I would rotate the vertical column chart into a horizontal bar chart, then reorder the categories so that the Latino and African American youth would be listed first.
• Finally, I would apply strategic branding and design choices. This includes incorporating the organization’s fonts and color palette and using dark colors and an annotation to help key numbers pop.

What a difference!

I apply these techniques to all of my reports, slide decks, dashboards, and infographics—including a series of state profiles I recently partnered with the National Home Visiting Resource Center for the Data Supplement to the 2017 Home Visiting Yearbook. Here’s a behind-the-scenes peek at how an early draft received the same three-step treatment.

Remove a Lot of Unnecessary Ink

At a bare minimum, we needed to remove unnecessary design elements. In the example below, we removed the graph’s border, generic title, and vertical and horizontal lines. We also adjusted the wording and the colors.

Intentionally Use Text to Help Tell a Story

As data visualization becomes more popular, I often see people focus so much attention on creating good images that they forget about the text. Both can work together to tell your story. Here’s how we translated the bullet points from our spreadsheets into full sentences.

Apply Strategic Branding and Design Choices

We started with the NHVRC color palette. You might recognize these colors from the NHRVC web site. The “before” version of an NHVRC state profile is displayed below on the left. It’s colorful, sure, but the colors are primarily used to decorate the page. In the “after” version (displayed below on the right), we intentionally color-coded items by category. Information about children has turquoise text and graphs, while information about families uses purple text and graphs. We wanted readers to spot the two colors—and therefore distinguish between the two buckets of data—instantly.

We also used dark colors intentionally within sections. Do you see the turquoise bar chart depicting age ranges? Light turquoise corresponds to less age (i.e., younger children) while dark turquoise corresponds to more (i.e., older children). We applied darker colors intentionally in the waffle chart at the bottom of the page, too.

In the visual perception world, we call dark color a preattentive attribute. Our brains are wired to notice dark colors without any conscious thought. We can instantly see the difference between dark and light colors without even having to think about it!

These three steps can go a long way helping translate your data into compelling “data viz.” Visit the Data Supplement’s state profiles section to see these principles in action.

The post Home Visiting Dataviz: Three Steps to Making a Good Graph Great appeared first on Depict Data Studio.

Here’s how to make waffle charts within good ol’ Excel.

The first few steps are a little unexpected. We’ve got to fool Excel into making a 10×10 grid. You’ll have to trust me on this first step. It’ll look crazy at first, but it’ll make sense in a moment. Type a bunch of 1’s into your spreadsheet—10 across and 10 down.

Then, highlight your 1’s, go to the Insert tab, and select a 2D stacked bar chart. You can use a stacked bar chart (horizontal) or a stacked column chart (vertical). The end result will be the same either way.

The waffle chart is there! Well, kind of. It’s hiding behind a bunch of clutter. Let’s adjust the scale and then delete, delete, delete.

Adjust the vertical axis so that it stretches from 0 to 10 (rather than 0 to 12). To adjust the axis’ scale, first click on any of the numbers. For instance, you could hold your cursor directly over the 6, the 8, or the 10. You’ll see a rectangle appear around the outside of the numbers.

Then, right-click, and select the option at the very bottom of the pop-up window, which is called Format Axis.

Adjust the maximum bound from 12 to 10.

Now, the vertical axis only goes to 10—good. (Otherwise, our final product would’ve had some weird white space.)

Delete the title, legend, and scales. Remove the border and grid lines.

Reduce the gap width all the way down to 0%. This is your computer’s funny name for the space between the columns or bars. Follow my tutorial if this technique is new for you. The result is a big blob.

Modernize your visual with light gray fills and white outlines. Can you see the waffle?!

Fill in a few shapes with your darker action color. For example, you would fill in 57 of the 100 squares to represent 57 percent of people.

Finally, make sure your graph is a square (not a rectangle). No eyeballing. Activate your graph by clicking on the outside border. Then, go to the Format tab and look for the Size section. In this example, I set my chart to be 3 inches by 3 inches. This is a nice size for Word documents. You could place two 3-by-3 waffle charts beside each other on the paper. You’ll need larger waffles for your slide deck of course.

Bonus

Purchase the template ($5)

Have you used these stacked-bars-disguised-as-waffles in your own work? If so, please link to your document in the comments.

The post How to Make a Waffle Chart in Microsoft Excel appeared first on Depict Data Studio.