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.

In this video, let’s make a starter dashboard in Microsoft Excel.

You’ll learn how to make four quick visuals:

1. Sparklines
2. Data bars
3. Symbol fonts
4. Color scales

I use these visuals over and over in my real-life consulting projects.

Watch the Tutorial

Sparklines

Sparklines are helpful for visualizing patterns over time, like daily, weekly, monthly, quarterly, or annual data.

To create sparklines:

1. Highlight the first row of your table.
2. Go to the Insert tab.
3. Go to the Sparklines section.
4. Click on the first one (a Line sparkline).
5. Choose where we want to put the sparklines (off to the right of the table).
6. Click insert and enjoy the sparklines!

We can also edit our sparklines!

We might adjust the data source, type (from line to column), or color. I typically gray everything out and highlight a high point or low point in a dark brand color.

We can also group and ungroup our sparklines (e.g., if we want each category in our dashboard to have its own color).

And if we change our mind, we can clear them out.

Data Bars

Data Bars give us horizontal bars (as opposed to sparklines’ vertical columns).

They’re helpful for visualizing summary statistics like totals or averages.

To create data bars:

1. Highlight the cells you want to visualize (e.g., the total column).
2. Go to the Home tab.
3. Click on the Conditional Formatting button.
4. Select solid-filled data bars.

Symbol Fonts

I use checkboxes to visualize whether I met a goal or target.

We can get quick checkboxes through symbol fonts!

In the video, you’ll see me write an =if() statement to transform g’s and c’s into Webdings checkboxes.

Audiences love the checkboxes. They’re intuitive, colorblind-friendly, and grayscale printing-friendly.

Color Scales

a.k.a. heat maps or heat tables.

I love color scales for visualizing the interior of my table—when I want to compare lots of rows and columns to each other.

To create color scales:

1. Highlight the cells you want to visualize (i.e., the interior of the table).
2. Go to the Home tab.
3. Click on the Conditional Formatting button.
4. Select Color Scales. Most of the time, we’ll use a Green-White Color Scale. That’ll make the big numbers dark (and the small numbers will be light).

Combos

In real life, we might combine several of these techniques.

We might add color scales to the interior of the table…

We might compare the totals with data bars…

We might add Webdings checkboxes to see whether we met a goal…

And we might add more data bars to see how far we were over or under our goal.

Formatting

In real life, we’d edit these quick visuals.

I suggest:

• Using brand colors and brand fonts.
• Outlining the color scales in white (so the cells can be differentiated against each other).
• Placing the data bars in a separate column than their numeric labels.
• Coloring the checkboxes (rather than boring black).
• Adjusting the colors in the over/under bars (to avoid scary red).
• Moving the labels to the over/under bars to their own column (via an =if() statement to save time).

Download this Spreadsheet

Try it yourself!

Download this spreadsheet.

Explore the completed version with the =if() statements.

Use the empty version to practice alongside me as you replay the video.

Get in Touch

If you get stuck, reach out o­n LinkedIn.

The post How to Make a Not-So-Scary Starter Dashboard in Excel appeared first on Depict Data Studio.

—

When COVID-19 pushed many events online, I decided to host a virtual Christmas trivia event for my family.

Participants answered questions over four different rounds in teams of three to six people. The rounds each had five questions and all questions were Christmas- or New Year-themed.

Before: Compiling the Data in a Spreadsheet

To support scorekeeping, teams had an individual score sheet where they wrote and marked their own answers.

I had a master score sheet that would automatically pull their scores together so all teams scores were combined into one page.

I’d then show this master score sheet via screen share at half-time and at the end of the event.

The master score sheet looked like this:

While it brought all the scores into one place, it wasn’t very easy for my participants to quickly pull out the key information (i.e., how well their team was doing).

I decided to apply some of the lessons I learned in the Dashboard Design course to make the sheet more accessible.

After: My Trivia Night Dashboard

First, I had to decide what type of dashboard I wanted to make.

In the course, Ann provided a handy Dashboard Cheat Sheet that helped me see different options.

I decided because I had one time point and wanted to compare categories (i.e., teams) that bars would likely be best.

I also decided to convert the numerical scores into percentages because not all rounds had the same number of possible points. Percentages would be a more consistent indicator.

Now it was time to make the dashboard.

It was easy to follow along step by step with Ann’s stacked bar dashboard video tutorial.

I made the following dashboard using the Data Bars feature in Microsoft Excel:

What I Learned about Dashboards and Excel

Not only were the steps easy to follow, but I also learned about better dashboard and Excel practices.

These tips help make your life easier and your dashboards more editable and readable.

Some of my lessons learned include:

• Always put a title, subtitle, and date on the dashboards.
• If your text is in a colour, make it bold so it is easier to read.
• Add a white border around cells to add white space.
• Use cell styles and Theme Colours to make formatting more consistent and easier to edit (I somehow did not know about this in Excel even though I use it regularly in Word).
• Give yourself a bit of time to do the final editing to make it sure fits on a page

With this dashboard, I found it much easier to see:

• How well teams did in each round (e.g., team 6 struggled with Round 4, but excelled in Round 3).
• How teams compared to each other.
• How hard each round was (e.g., Round 2 was on average harder than Round 3).

Designing a Second Dashboard

Encouraged by my dashboard attempts, I decided to try one more dashboard.

I wanted to know within each round, which questions did teams get right and wrong.

This would help me identify which questions were too easy and which were too hard. It’s a fine balance to get when hosting trivia!

I thought about including it in the same dashboard above, but I then I watched one of Ann’s videos about the four types of dashboards.

This reminded me that it’s okay (and even better) to make different dashboards for different audiences.

I had to do a bit of data cleaning first. I ended up with a table that showed for each question in each round the percent of teams that got that question fully correct:

While it had the information that I needed, I found it hard to identify any patterns or the take home message.

I remembered that in the Dashboard Design course Ann had a video on how to compare categories using heatmaps. (Here’s a blog post tutorial you can read.)

I used the steps to create this:

What I Learned from My Second Dashboard

As with the first dashboard, there were some great tricks.

Essentially, if you’re doing something manually (like changing the text colour to white on the darker cells or individually colouring cells) there is almost always a better way! You can use Excel’s conditional formatting to automatically color-code background fills and/or font colors.

I found it much easier to identify patterns both within round and across rounds.

For example, teams generally had a harder time with questions in Round 2 than they did with Round 3 (there are more lighter cells).

Using this dashboard, I could easily pick out questions which were too hard and too easy.

Questions That Were Too Hard

Round 1 – Question 4: What is the name of this dish and where is it eaten on January 6? (Answer: Rosca de Reyes; Mexico)

Round 2 – Question 2: What is the highest grossing Christmas movie (according to Wikipedia)?

Options: a. The Grinch b. Krampus c. The Polar Express d. Elf

(Answer: The Grinch)

Questions That Were Too Easy

Round 4 – Question 2: What fruit is a traditional stocking stuffer?

(Answer: Citrus fruit like an orange, mandarin, clementine)

Round 3 – Question 4: What performance is this song played in? (Bonus: Who is the composer?)

(Answer: The Nutcracker; Tchaikovsky)

(Sound clip source: Dance of the Sugar Plum Fairy Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 3.0 License, via Wikimedia Commons)

I really enjoyed how approachable and practical the videos in this course were.

I can’t wait to continue to apply the tips and techniques I learned both at work and for fun!

Maybe at next year’s trivia I’ll have to test some of the dashboard designs for comparing change over time.

Connect with Emily

LinkedIn: https://www.linkedin.com/in/emilysross/

The post Using Dashboards to Make a Family Trivia Event Even Better appeared first on Depict Data Studio.

Ready to escape the bar chart? I talked about Designs to Start Using Instead at the DataScienceGO conference in April 2021.

Watch the Conference Session

Choose Your Own Adventure

This was a Choose Your Own Adventure presentation, where I gave the conference attendees a chance to vote for the chart families they wanted to learn about.

These non-linear presentations aren’t for everyone. You need to be extremely comfortable with the topic area and with presenting. You can learn more about Choose Your Own Adventure presentations here.

Exploratory Data Visualization

First, we talked about my three favorite techniques for exploratory data visualization:

1. Spark lines
2. Data Bars
3. Heat Tables

Spark Lines

Want to add miniature trend lines to your spreadsheet? Here’s how:

• Highlight the top row of your dataset (the numbers that you want to visualize).
• Go to the Insert tab.
• Click on the Sparklines button.
• Follow the instructions: Choose where you want the sparklines to be placed. I usually position them off to the right side of my dataset.

Data Bars

Want to explore your dataset with miniature horizontal bars? Here’s how:

• Highlight the data you want to visualize.
• Stay on the Home tab.
• Click on the Conditional Formatting button.
• Choose a solid-filled Data Bar.

Heat Tables

We can also explore our dataset with instant color-coding. Here’s how to add a heat map or heat table to your spreadsheet:

• Highlight the data you want to visualize.
• Stay on the Home tab.
• Click on the Conditional Formatting button.
• Choose a Color Scale.

PLEASE avoid the inaccessible options—anything with red and green. Most of the Conditional Formatting options are absolute garbage, to be honest. Here’s a blog post that lists which Conditional Formatting options to avoid altogether—and what to use instead.

Want more info? In the video, you’ll see me open Excel and provide how-to tutorials.

Maps

Next, we discussed a few options for maps.

Choropleth Maps

You’ve seen this one: The regular ol’ color-coded map, or choropleth. Big numbers are dark. These maps are familiar and intuitive.

But, there’s a problem with regular maps: The large places can dwarf the small places. No matter how dark we color-in tiny Delaware, for example, the larger places like Texas and Alaska will always steal the show.

Cartographers have a name for this misleading issue with regular maps. It’s called The Alaska Effect.

Tile Grid Maps

Don’t worry, we’re not doomed by The Alaska Effect! There are a couple alternatives worth mentioning.

Square tile grid maps can help us overcome The Alaska Effect. Every location is the same shape and size, so now our audience only has to look at color. In other words, since Delaware and Texas are the same shape and size, we’re free to focus entirely on color.

BUT.

There’s a learning curve with tile grid maps. They’re almost too novel. Sometimes we spend more time focusing on why our home state isn’t in the right spot than on actually finding patterns in the data.

Tile grid maps have become more and more common over the years. In the video, I show you some real-life examples from the Urban Institute, the Washington Post, Child Trends, CNN, and National Geographic.

Hex Maps

Rather than using squares…. What if we try hexagons?

With six edges, hex maps give us more flexibility in arranging the shapes. That way, the maps can look closer to real-life maps.

In the video, I discuss some additional advantage of hex maps:

• Hex maps combat the Alaska Effect.
• Hex maps include more of the correct neighboring states compared to square maps.
• Hex maps include the correct southern tips.
• Hex maps include more notches for the Great Lakes.
• Hex maps visualize the correct four corners of the U.S.

And of course, hex maps aren’t just for the United States. You can create maps for zip codes, Census tracts, states, provinces, countries, etc. In the video, I show you a waffle map of African countries.

The post Escaping the Bar Chart appeared first on Depict Data Studio.

I can’t tell you how many times I’ve heard this from workshop participants.

Bill Gates, are you reading this??

Microsoft Excel is lonnnnng overdue for some updates.

Don’t get me wrong—it’s still my favorite program. With 750 million users worldwide, I won’t be switching to anything else. It’s used by every business professional I know for at least part of their workflow.

Earlier this week, I was invited to guest lecture at Baruch College. Thanks to Professor Mahmoud Kamal Ahmadi for inviting me!

I’m normally very zen about data visualization. I expected to bring that peace of mind to Professor Ahmadi’s students.

Here’s my calm before the storm selfie:

“Sure, some of Excel’s default formatting is hard to decipher. And isn’t accessible for people with disabilities,” I’ve said a million times. “But with some behind-the-scenes editing, we can still make powerful visualizations inside Excel.”

I’m getting tired of making excuses for Microsoft.

Shouldn’t they know better by now??

I started to teach the Baruch College students about exploratory data visualization with conditional formatting. I couldn’t help but rant about the bad formatting as I went. It was 8pm at night. My filter had disappeared; I couldn’t help it. Sorry not sorry, Microsoft.

Wait, What’s Conditional Formatting??

Conditional Formatting is a fancy way of saying “if-then visuals.”

If the number is above 50, then fill the cell with red.

If the number is below average, make the font bold.

On and on.

Conditional Formatting is Ann K. Emery’s favorite button in Excel (along with the pivot tables button). It’s hiding in plain sight on our Home tab.

How to Use Conditional Formatting in Microsoft Excel

Conditional Formatting lets us create near-instant visuals.

These visuals are helpful for both exploratory and explanatory purposes. Exploratory data visualization is for us, the spreadsheet users and graph-makers. These near-instant visuals help us uncover patterns. Explanatory data visualization is typically for others, like our supervisor, Board of Directors, or other stakeholder groups. These near-instant visuals can be shared with others inside of dashboards, scorecards, and one-pagers to explain key findings to our audiences.

Here’s how to use Conditional Formatting in Microsoft Excel:

1. Highlight or select some of the values in your spreadsheet. You can use Conditional Formatting on numbers, percentages, currency, and even words.
2. Go to the Home tab.
3. Click on the Conditional Formatting button.
4. Choose one of the options, like Highlight Cells Rules, Top/Bottom Rules, or Data Bars.
5. Enjoy your near-instant visual!
6. Edit edit edit. With the cells still selected, go back to the Conditional Formatting button. On the very bottom of the list, you’ll see an option for Manage Rules. This is a fancy way of saying edit. You can adjust most aspects of your visual: the colors, the cutoff values, more.

Conditional Formatting in Microsoft Excel that Should Be Retired ASAP

Conditional Formatting is mostly excellent.

I love the speed. I love the instant understanding I get by seeing my numbers come to life.

But I hate hate hate the ableism.

Some of the Conditional Formatting options are terrible for people with color vision deficiencies.

Others are terrible for grayscale printing. (When was the last time you got excited about paying for colored ink cartridges?)

Others are just terribly busy-looking and could easily be improved with Graphic Design 101 skills.

Here are 24 of Excel’s conditional formatting techniques that should be retired ASAP.

These visuals are:

• too time-consuming to read,
• not accessible, or
• look like they’re from 1995.

3 Arrows (Colored)

Nice try, but so busy. I’ll show you something better in a moment.

3 Triangles

A bit easier to skim, but we can do better.

4 Arrows (Colored)

Why do the yellow arrows point in two different directions?

3 Arrows (Gray)

4 Arrows (Gray)

5 Arrows (Gray)

There’s nothing useful here. Don’t make me write three different sentences about why these three options are worthless.

3 Traffic Lights (Unrimmed)

I’m about to become really unpopular with 99% of people who make business dashboards, but….

We should really stop using traffic light color-coding altogether.

Green-red color combos aren’t accessible for people with color vision deficiencies (more on this later).

Sure, red-green combos are intuitive. For those of us who can see them. But they’re useless for everyone else.

3 Traffic Lights (Rimmed)

Let’s make the colors even smaller and harder to see.

Red to Black

These tones are confusing to me. Don’t we associate both red and black as “bad” colors? Why is red = high percentages? And black = low percentages? Sure, Excel lets us flip-flop these colors, but the question remains—aren’t red and black both “bad?”

4 Traffic Lights

Now, Excel is saying that black is even worse than red?? These inconsistencies kill me. And since when do traffic lights have 4 different colors? I’ve never seen a black lightbulb in a traffic light. So more for intuitive traffic light coding.

3 Signs

I want to love these. Although the 3 Signs design would technically pass 508 compliance accessibility guidelines (because our viewers aren’t relying on color alone—they can also see the different shapes) it’s still so busy.

There’s also the issue of combining both categorical coding (a diamond vs. triangle vs. circle) with diverging coding (red is worst, yellow is medium, green is best). Forgive the jargon, but as a research methods geek, this bothers me.

3 Symbols (Circled)

These tiny symbols would be impossible to skim at a glance in a tiny spreadsheet.

3 Flags

GAH. Probably the hardest to read from this bunch.

3 Symbols (Uncircled)

Maybe the easiest to skim from this bunch? But still a bit busy.

3 Stars

This design gets creativity points.

5 Quarters

These aren’t so bad to skim right now—because I’ve already organized the spreadsheet from lowest to highest. Imagine a mismatched list (e.g., 20%, then 80%, then 10%, then 50%….). It would get messy.

5 Boxes

There could be more contrast between the gray and blue, i.e., it would be easier to read if the gray was a bit lighter, or the blue a bit darker.

4 Ratings

I actually love bar and column charts for at-a-glance findings.

But, these would be easier to read if they were horizontal bar charts, not vertical column charts.

I’ll show you an example with horizontal bars in a moment.

5 Ratings

Same shortcomings here.

Data Bars (Gradient)

Speaking of bar and column charts… Do you see how much easier it is to compare bars than columns?

BUT, not these gradient bars. We need to retire these. The most important part of the bar chart is the right-most endpoint. So why does Microsoft fade these out to lighter colors… therefore making the most important thing harder to see???

Data Bars (Solid)

Winner winner chicken dinner! More of these, please.

Green-Yellow Red Color Scales

Yes, I know what you’re thinking. This stoplight coding is intuitive.

But only for those of us who can see red and green as distinct colors. For people with color vision deficiencies, this color scheme is worthless.

Let’s retire this ableist color scale from Excel.

Green-White-Red Color Scales

Not accessible. Ableist.

Blue-White-Red Color Scales

Better than the red-green color coding, since at least it’s legible for people with color vision deficiencies.

But, this wouldn’t print well in grayscale. More on this in a moment.

Green-Yellow Color Scale

Not horrible… but not as clear as it could be.

Green-White Color Scale

Winner winner chicken dinner! More of these, please.

Look at the green-yellow and green-white options next to each other.

Do you see how the green-white color scale is easier to read? The white is, well, whiter than the yellow. Therefore, there’s even more contrast when compared to the green.

This scale is colorblind-friendly and grayscale-friendly.

Red-White Color Scale

Winner winner chicken dinner! More of these, please.

This is the opposite tone of the green-white color scale.

In other words, use this color scale to emphasize that low = bad.

How about Grayscale Printing?

We should always assume that someone will print our visuals. That printing may happen in grayscale, not full color, to save money.

I did a quick grayscale test on these color scales to show you what they’d look like.

Do you see how the first three are worthless? The fourth one, green-yellow, is okay. The last two are the easiest to read.

(In Dataviz Jargon: Transform that diverging scale into a sequential scale. It’s harder to notice differences between two different hues, like red and blue, than to notice differences between gradations, like light green vs. dark green. And it’s impossible to read diverging scales in grayscale.)

How about Color Vision Deficiencies?

I also did a color-blindness check.

First, I uploaded a screenshot to the Color Vision Deficiency Simulator website.

Next, I investigated what the color scales would look like for someone with protanopia. Eek.

The first four are worthless.

Green-yellow is okay.

Green-white and red-white are best.

Well-Formatted Conditional Formatting in Microsoft Excel Worth Keeping

Keeping score? Here are the conditional formatting visuals we can keep using:

• Green-White Color Scale
• Red-White Color Scale
• Data Bars

I’ll add another keeper to the list: Squares and circles made with the Webdings symbol font.

For example, we can use Webdings g’s and the rept() function to create an icon array, as shown above.

Or, we can use Webdings g’s and c’s to create a series of filled-unfilled squares.

Or, we can use Webdings n’s to create a series of light-dark circles.

It’s faster to skim a list of filled-unfilled squares, or light-dark circles, than to skim the stars, flags, or mini column charts shown earlier.

How to Add Conditional Formatting to Your Microsoft Excel Spreadsheet

Want to create conditional formatting to explore initial patterns in your spreadsheet? Here are links to detailed tutorials:

• How to Create Data Bars in Microsoft Excel
• How to Make a Heat Table in Microsoft Excel
• More examples of easy-to-skim symbols and icons made with symbol fonts (Webdings and Wingdings)
• Webdings example: Re-envisioning a University’s Monthly Report: Two Reports with Two Different Purposes      
• Webdings example: Visualizing Your Annual Survey Results: Four Makeovers That Didn’t Work, and the Fifth That Did

Your Turn

What are some additional features of Excel that should be retired? Or added?

The post 24 Conditional Formatting Visuals in Microsoft Excel that Should Be Retired appeared first on Depict Data Studio.

This report summarized survey responses from both universities and their students. Even with hundreds of survey responses and dozens of survey questions, we kept the report’s body to just six pages!

How’d we choose which findings to include in the report’s main body?!

That can be a daunting task. But it doesn’t have to be.

It’s much easier to pare down our report’s content when we’ve got appendices to back us up.

We don’t have to worry about forgetting any important details, since readers can simply flip to the back to learn more.

We get to be transparent by showing all the data (in the appendices) without overwhelming our busy readers (by trying to shove everything into the body of the report).

This particular report was six pages long plus 33 pages of appendices!

What Can—and Should—Be Included in Appendices

Here’s everything that can be removed from the report’s main body and pushed to the appendix:

• Question-by-question survey responses (i.e., tables and tables of closed-ended and open-ended survey data)
• Data collection instruments (e.g., an empty copy of the questions from the survey)
• Transcripts from qualitative data collection (like focus groups or interviews)
• Meeting minutes or other official documents we might’ve referenced quickly within the body of the report
• Anything that would put our non-technical audiences to sleep
• Anything that’s not central to the key takeaway message from the report
• Anything we feel like we should include just in case
• Anything that one person who asks lots of questions might need to know about
• Patterns over time (e.g., our report’s main body could focus on this year’s data, but we might include tables that compare this year’s data to last year’s data in the appendix)

What Appendices Typically Look Like

Here’s what tables in the back of reports typically look like: Tiny font sizes, cluttered tables, and no visuals to help readers spot the key patterns.

But what if I told you our appendices could get even better than that—in under an hour??

Introducing… Visual Appendices!

Here’s my wish for your next report: Visual appendices!

5 Easy Edits to Appendices

Let’s start with those original appendices that I showed you a moment ago…

First, declutter the existing tables. Remove all the unnecessary borders and lines.

Oops! Too bare. Don’t worry, we’ll continue editing in the next step.

Second, I re-add the horizontal lines in gray rather than in black. Light gray horizontal lines ensure that our viewers can still read across the rows without distracting from the data by adding lots of dark ink.

Third, add visuals! This is the most fun part.

Fourth, apply a text hierarchy. A text hierarchy means our title is going to be the largest, boldest, darkest text on the page (followed by Heading 1s, 2s, and 3s).  

Fifth, add some plain-language text. In this fictional example, I’ve added a short introductory section. I’ve also changed the n=456 jargon into a friendly sentence: “We collected data from 456 respondents.”

3 Quick Visuals to Include in Appendices

There are plenty of quick visuals that we can include in our appendices. Here are a few of my favorite styles.

Bar Charts (or Stacked Bar Charts)

I showed you this approach already. We can build bar charts or stacked bars to visualize how many (“frequencies”).

Heat Tables (or Any Type of Color-Coded Cells)

I love creating heat tables to help readers spot the highs and lows in the dataset. Heat tables are more helpful than bar charts when our tables have several rows and columns (like these fictional tables below, which have seven columns each).

Trend Lines (or Vertical Columns)

Finally, I love creating trend lines (or, vertical columns) to show patterns over time. In this fictional example, we’re comparing how the patterns shifted between the 2012-13 academic year and the 2017-18 academic year.

The next time you’re adding appendices to your report, add visual appendices!

Bonus: Learn How to Make Visual Appendices

You’ll learn how to make these inside the Dashboard Design course.

The post Designing Visual Appendices for Your Next Report—In Under an Hour appeared first on Depict Data Studio.