(These aren’t the exact numbers, age ranges, or years. But you get the idea.)

She already knew how to make population pyramids in Excel. Population pyramids require Level 4 vizardy skills. Woohoo!

But she wanted to take the population pyramid a step further, and she wanted to show how the population might change over time, especially for older adults.

So, she followed this online tutorial to add those curvy lines. (Yep, it’s made with a combo chart in Excel.)

Bare-Minimum Edits

As usual, we tackled the bare-minimum edits first:

• We removed the legend and directly labeled the data, which helps the graph pass “Big A Accessibility” rules (a.k.a. 508/ADA compliance).
• We nudged the bars closer together by reducing the gap width to make more of a smoothed-out histogram.
• We outlined the touching filled-in rectangles in white, a small detail that helps with grayscale printing.
• We used fewer colors. Before, there were 4 different hues: for 2020 males, 2030 males, 2020 females, and 2030 females. That’s a lot to keep track of! Instead, we color-coded by category (one hue for males, and another hue for females).

We also tried color-coding by year, instead of color-coding by sex, like this:

We were getting closer!

But we wanted to make sure that the forecasted numbers for 2030 were extremely obvious to viewers. For most of us, this isn’t a chart type that we see every day.

I was hesitant to keep the combo chart. This was an apples-to-apples comparison, so I wanted to use all bars.

(The bars/lines combo seemed more like an apples-to-oranges comparison, which this isn’t.)

Small Multiples Population Pyramids

Here’s a Dataviz Rule of Thumb:

Anytime your graph feels too dense… try creating more graphs.

Small multiples layouts can save the day!

The Traditional Version

We tried traditional and storytelling versions of a small multiples population pyramid.

Here’s what the traditional version would look like inside her report.

You’ll notice the topical titles, color-coding by category (one hue per year), and how the graphs are all one color.

The Storytelling Version

And here’s what the storytelling version would look like inside her report.

This version draws attention to the 65+ age group, which she wanted.

You’ll notice the takeaway title, the color-coding by category (one hue per year), the dark-light contrast (highlighting the residents who are ages 65+), and the annotations.

The Bottom Line

Even with the bare-minimum edits, I wasn’t a fan of the original combo chart. The bar-line combo was suggesting an apples-to-oranges comparison.

Instead, anytime your chart feels too dense (when there are literally lines and bars combined within one chart), try a small multiples layout instead!

We can format the chart as a traditional or storytelling version. In this case, storytelling was a perfect fit because we especially wanted to highlight the 65+ age group.

The post How to Visualize Population Projections with Small Multiples Population Pyramids appeared first on Depict Data Studio.

Are you lucky enough to have historical data at your fingertips?! Woohoo! What a treat.

Let’s weigh the pros and cons of a few different viz options.

The Table

Here’s what their tabulated data looked like, sort of.

Let’s pretend we’re looking at the number of doctor’s appointments that took place within their healthcare system.

That’s not the real variable, and these aren’t their real numbers, but you get the idea: They wanted to visualize patterns over the past four years.

Before: 1 Graph per Year

Here’s what their initial visualization looked like: a separate graph for each year.

Idea 1: Lonnng Column Chart with Bare-Minimum Edits

First, let’s tackle the Quick Wins, a.k.a. the Bare Minimum edits for branding and “Big A” Accessibility:

• Brand colors and fonts
• Darker font for better color contrast
• Sized for a slide (size 18-point font, 13 inches wide, 5 inches tall)
• Arranged left to right, rather than a grid
• “Grouped” all the graphs together for easier copying and pasting into a slide
• Horizontal text only
• Consistent scales to make comparisons across graphs easier
• Fewer demarcations on the y-axis (one label every 25,000 units)
• Changed the y-axis to a “number” format so that a zero appears at the bottom, not just a dash
• Then, only showing the left-most y-axis
• Wider columns, a.k.a. a smaller gap width

It felt inefficient to keep four separate graphs — too much extra work to align everything and then group everything — so I turned this into a single column chart.

Yep, I had to rearrange the four tables into one table in order to transform the four graphs into one graph. At the bottom of this blog post, you’ll see a link to download my Excel file so you can explore the behind-the-scenes tables and graphs for yourself.

Idea 2: Lonnng Column Chart with Data Storytelling

I’ve written about spoken about traditional vs. storytelling graphs a lot over the past decade. If these terms are new, then you can watch the most recent public-facing conference talk here.

In this version, I intentionally used data storytelling. This data was intended for a busy upper-management office, and leaders often prefer when we cut to the chase, instead of burying them in graphs that don’t say anything.

The presentation slide might look something like this:

• A takeaway slide title
• The topical graph title underneath
• Dark-light contrast
• Labels only on the columns of interest – for September and October

And no, I don’t love how the September labels are right-aligned while the October labels are centered, but this probably isn’t the winning approach, so who cares.

Idea 3: Lonnng Line Chart with Data Storytelling

Another option is a line chart with gray shading for the peaks.

Yes, this is a combo chart in Excel.

The presentation slide would look like this:

Idea 4: Single Line Chart with Data Storytelling

A final option is a single line chart that stretches from January to December, with each year’s data “stacked.”

Comparing All 4 Ideas

My favorite is Idea 4 because we can easily see the seasonal peaks.

Which one is your favorite, and why? Comment below.

This isn’t an exhaustive list.

Can you think of additional options? Comment below.

Giving a Powerful Presentation

Idea 4 is a sort-of dense graph — and it’s definitely a spaghetti line graph, so we’ve gotta continue adjusting it.

We’ll want to present it piecemeal to match our speaking points.

Otherwise, our audience will die of boredom.

Our bosses will wonder why they hired us.

And nobody will be able to make data-driven decisions based on the data… because while we’re explaining one piece, they’re looking at something else (the very definition of Death by PowerPoint).

The meeting might sound something like this:

I hope you enjoy my kindergarten photoshopping skills.

PowerPoint’s animation works fine for bullet points.

But, to “animate” graphs to match our voice, it’s usually easiest to create a bunch of different slides.

Download My Excel File

Want to explore how I made each graph?

You can download my spreadsheet here.

The post How to Visualize Multi-Year Patterns appeared first on Depict Data Studio.

We’ll call them the Statelandia Public Health Department.

Before

Here’s what their “before” version looked like.

The information on how many adults overall had been diagnosed with high blood pressure was tucked inside the title, while the graph focused on the breakdown by age group.

All the important details are there, hooray! But we all wanted more cohesion between the title and the graph.

Two Options for Visualizing “Overall” Data or Averages on Bar Charts

There are two primary ways to visualize our “overall” data or averages when we’re making bar or column charts.

The two options include:

1. Add a column. We can add intentional gaps between the “overall” data and the subgroups. In technical terms, the space is a preattentive attribute. Preattentive attributes help our audience recognize instantly that the overall vs. subgroups are a bit different.
2. Add a line. Another option is adding a line on top of the bars or columns. I’ve seen people add literal lines in Excel (Insert – Shape – Line). That works, but the fancier option is to use a Combo Chart in Excel. (If you’re not familiar with Combo Charts, you can download my template below.)

Let’s apply these two options to the blood pressure example.

Option 1: Visualize “Overall” Data by Adding a Column

I *think* this is my preferred approach. I’m still on the fence. Hmm…

A Few Quick Wins

I always start with Quick Wins. These edits can be tackled within minutes.

Quick Wins give us momentum so that we have mental energy to tackle the Not-So-Quick Wins.

Here’s what we edited:

• We changed the horizontal bar chart into a vertical column chart. Age groups are ordinal, and I generally try to arrange ordinal data from left to right. You can read more about my bar vs. column logic here, and you can learn how to make this quick rotation in Excel here.
• We rounded the decimal places to the nearest whole number. You can learn more about lowering the numeracy level of our graphs here.
• We moved the percentage labels inside the columns (so they don’t accidentally make the columns look taller than they really are).
• We decluttered the graph (removing gridlines, showing fewer increments on the y-axis, tucking the labels inside the columns, etc.).

Add an “Overall” Column with an Intentional Gap

Next, we added the “overall” data to the graph as its own column.

We also spaced the overall column apart from the others. These are separate types of data (an overall number is qualitatively different from a breakout by subgroups). They need to be arranged separately on the slide.

If you’re using Excel, simply add an empty row to the table that feeds into your graph.

You can learn more about adding intentional gaps in this blog post.

Adjust the Text Placement

Next, we moved around the text boxes.

All the important text was there — but in a single full-width text box.

We simply placed “like with like” — the overall text with the overall column, and the subgroup text with the subgroup columns.

We also moved the “year” data to the source at the bottom of the slide.

Bold the Key Words & Color-Code by Category

For extra skimmability, we bolded a few key words.

Then, we adjusted the colors. Separate colors for separate categories of information.

Color-coding by category is one of my all-time favorite dataviz techniques! You can see color-coding applied to one-pagers, recurring monthly reports, technical reports, and slideshows in these linked examples.

The final version would look like this:

Option 2: Visualizing “Overall” Data by Adding a Line

I love adding lines to visualize targets and goals.

We can add lines to visualize “overall” or “average” data, too.

BUT make sure to gray out something. Otherwise, the line chart gets messy.

You might gray out the columns, like this:

Or, you might gray out the line, like this:

Visualizing “Overall” Data on Line Charts

It’s easy to apply these techniques to line charts.

Just add another line!

Your Turn

Which approach is your favorite?

Adding a column?

Or adding a line?

And why?

For this case study, I prefer adding a column because it was easier to arrange the takeaway text in the right places (the takeaway text is simply above the columns). For the line charts, the takeaway text didn’t feel as seamless.

Comment below and share your own insights.

Bonus: Download My Spreadsheet

Not familiar with the intentional spacing in the bar chart?

Not familiar with the combo chart design in the line chart?

Download my spreadsheet here.

The post How to Visualize “Overall” Data or Averages in Bar Charts appeared first on Depict Data Studio.