# Dataviz Challenge #6: Unit Charts

Lately I’ve been feeling let down by summary statistics: the min and max, mean and median, quartiles and standard deviation… They do their job well enough. Summary statistics tell a summary. An aggregate story, bringing all the messy scores together into some sort of cohesion. We grab the averages and stick them in bar charts.

But sometimes we don’t want to summarize, we want to highlight the variety in scores and remind readers that the chart is actually made up of individual people, not just the mean or median. Long live the messy data, the dispersion, the distribution, the spread!

I could tell you a few descriptive statistics: min = 26%, max = 100%, Q1 = 64%, Q3 = 83%, median = 74%, mean = 73%, standard deviation = 15%. Or, I could show you the spread in this unit-chart-turned-histogram.

Unit charts are not your new go-to chart. They do not replace bar charts. They are not appropriate for all datasets. They’re best for those few moments when you choose to emphasize individual units of data. A unit could be 1 person, or 10 people, or 1 school, and so on. Units can be represented in circles or squares or triangles. Units can be stacked on top of each other to form a histogram, or they can be plotted along a line.

The dataviz challenge: Re-create the chart in in Excel, R, or some other free software program. Then, tweet a screenshot to @annkemeryBonus: Make a unit chart for your own data. Or, do you emphasize individual differences with other chart types? Share your ideas with the community!

The prize for playing: A professional development opportunity and bragging rights. I’ll post the how-to guide in a couple weeks.

Want to learn more? I’m presenting about charting techniques at the American Evaluation Association’s annual conference on Thursday, October 17, 2013 at 11am in Washington, DC. Hope to see you there!

# Dataviz Challenge #5: The Answers!

I’ve been in love with diverging stacked bar charts since I saw Joe Mako’s submission to Cole Nussbaumer’s dataviz challenge last December. Joe made this contest-winning chart. But in Tableau! The amazing but expensive software!

Could I ever create one in Excel?!

Yes! Luckily I’d learned about the Values in Reverse Order feature from Stephanie Evergreen. With Joe’s inspiration and Stephanie’s strategy, I started making these beauties for myself in Excel.

I wanted to share the chart secrets with all of you, so last month, I challenged readers to re-create a diverging stacked bar chart like this one:

It looks like I’m not the only one who loves diverging stacked bar charts. Congratulations to the 12 contestants! In order of submission, they are:

Most contestants seized the opportunity to use their own datasets and made adjustments as needed. For example, Sheila’s dataset fit a traditional stacked bar chart better than a diverging stacked bar chart, and Anjie needed to display cut-off scores.

So how do you make these diverging stacked bar charts, anyways?! There are at least two strategies: Either a) create two separate charts, a strategy demonstrated in previous posts like this one, or b) use floating bars, a strategy demonstrated in previous posts like this one. Stephanie Evergreen blogged about strategy B a few weeks ago and her explanation is pretty awesome, so I’m going to focus on strategy A today.

Here’s a slideshow about the two-charts-in-one strategy. Enjoy!

Want to learn more? I’ll be sharing my top 5 must-have chart strategies at the American Evaluation Association’s annual conference on Thursday, October 17.

For discussion: Nearly all of the contestants requested friendly feedback on their graphs. In most cases, contestants were trying these charts for the first time and thinking about whether or not these charts could be adapted for their datasets. What do you think?

# Dataviz Challenge #5: Diverging Stacked Bar Chart

Last week I shared strategies for improving any chart’s colors. One of the examples was a diverging stacked bar chart:

I love stacked bar charts because they’re pretty versatile, and because they’re a great chart for lots of evaluation and survey data. In my example, I looked at the percentage of survey respondents who selected strongly agree, agree, disagree, and strongly disagree on a satisfaction survey. But stacked bar charts can be used in dozens of different ways.

So when can you use a stacked bar chart?

• Stacked bar charts are for part-to-whole relationships. Use them when you want readers to see both a) one portion of the bar and b) compare that piece to the entire bar.
• Stacked bar charts can be used for tallies or percentages. A tally is the number of actual people, dollars, etc. For example, a nonprofit could display their funding sources in a stacked bar chart – \$100K from a foundation, \$200K from a government grant, and so on. The reader can see the size of each grant as well as how the grants stack up as a whole.
• Stacked bar charts can be used for nominal, ordinal, or diverging data. An example of nominal data is the racial/ethnic categories of your survey respondents. Ordinal data has a natural order – from best to worst, most to least, something to nothing – like my example. Diverging data is a subtype of ordinal data – when the categories are polar opposites and there’s a clear middle ground or neutral zone in between two ends.

And when can you use a diverging stacked bar chart? Diverging stacked bar charts are just for comparing several sets of ordinal data at once. They work best when you’ve got an even number of categories (like the 4 survey choices). Then, you can easily line up the midpoints along an invisible y-axis.

The dataviz challenge: Re-create the “after” version in Excel, R, or some other free software program. When you’re finished, email me or tweet a screenshot to @annkemery.

Bonus! 1) Adapt this chart for own data. Think outside the box! 2) There are at least two different ways to create diverging stacked bar charts in Excel. Can you find more than one solution? (And these charts are so awesome that you’ll even see one solution on Stephanie Evergreen’s blog next week!) 3) Don’t forget to use custom colors!

The prize for playing: Beer or coffee, my treat, the next time you’re in DC; a professional development opportunity; and bragging rights.

I’ll post the how-to guide in 3 weeks, on September 6. Happy charting!

# Dataviz Challenge #4: The Answers!

Two weeks ago, I challenged readers to re-create the “after” version of a small multiples bar chart. You can read the full post here.

Congratulations to the 6 contestants! Click on the contestant’s name to see their chart.

Most of them even applied this chart type to their own datasets. Sara, Elisa, and Angie ended up using different types of bar charts altogether. Check ’em out!

Now it’s time to post the how-to guide.

## Step 1: Study the chart that you’re trying to reproduce in Excel.

We’re trying to re-create a small multiples bar chart like the one shown below. We’re comparing how many small, medium, and large nonprofits reported using each evaluation technique.

Small multiples bar chart

## Step 2: And the secret to making a small multiples bar chart in Excel…

…is that we’re going to make six separate clustered bar charts. When we copy and paste the charts from Excel into PowerPoint or Word, they’ll look like a single cohesive chart.

Six small charts come together to look like one big chart.

## Step 3: Type the data into Excel.

Here’s one of several ways to align your data.

## Step 4: Create the first bar chart.

We’re going to create six bar charts. I started with Internal Tracking Forms.

A default bar chart showing the percentage of small, medium, and large nonprofits that use internal tracking forms.

You know the drill: Add data labels inside the end of your bars. Delete the legend, title, tick marks, grid lines, and horizontal axis label. (Later, we’ll insert new text boxes to label everything.) Adjust the axis so it goes from 0 to 100% (rather than 0 to 70%). Change the bar color. Use gray text to de-emphasize less important information like the axis labels. Reduce the gap width from 150% to something closer to 30% or 50%.

Hot tip: Keep the borders. We’ll delete the borders at the very end. The borders help us keep all the charts and text boxes aligned and even.

After a few clicks, we’ve improved the general look and feel of our bar chart.

Beginner Excel users: If you need extra instruction, check out how to make a basic bar chart and my Excel for Evaluation chart tutorials.

## Step 5: Copy the first chart.

Rather than re-create the wheel when making the second, third, fourth, fifth, and sixth bar charts, let’s save some time by simply copying the first chart.

Just use good ol’ fashioned copying and pasting to create a second bar chart.

## Step 6: Populate the second chart with the second chart’s data.

The first chart is for Internal Tracking Forms and the second chart can be for Interviews. Use the “select data” feature to put the Interview percentages into the chart.

To reduce cluttering, delete the second chart’s axis labels and use the business card trick to make sure each chart’s plot area is the same width and height.

## Step 7: Make the third, fourth, fifth, and six bar charts.

Do some more copying and pasting to create the third, fourth, fifth, and sixth bar charts.

## Step 8: Add text boxes to label everything and delete the borders.

Insert text boxes. Once everything is aligned, delete the borders.

Save time by copying and pasting text boxes, too. No need to create every single one from scratch!

## Step 10: Paste the charts into PowerPoint or Word.

Since we’ve got 6 charts and 14 text boxes, copying and pasting into PowerPoint or Word can be a pain.

Hot tip: Carefully select all 6 charts and 14 text boxes. Right-click and “group” all the items together. Then, you can copy and paste into PowerPoint or Word with a single click!

Grouping the items together makes inserting your small multiples bar chart into Word or PowerPoint a breeze.

# Dataviz Challenge #4: Small Multiples Bar Chart

In the third dataviz challenge, we started talking about making several comparisons at once. For example, when the Innovation Network team and I surveyed nonprofits in the State of Evaluation 2012 research, we found differences between small, medium, and large nonprofits’ evaluation practices and capacity.

The “before” chart: Let’s examine the percentage of small, medium, and large nonprofits that reported using various evaluation practices. When making comparisons between subgroups, we often create clustered bar charts. A default Excel chart might look something like this:

Before: A default clustered bar chart

Like I’ve mentioned before, there’s nothing technically wrong with this chart. But it’s too hard to find at-a-glance patterns.

The “after” chart: Here’s that same dataset as a small multiples bar chart:

After: Small multiples bar chart

I love small multiples bar charts because they allow us to see patterns instantly. Within a split second, you can see that the bars on the left side are a lot taller than the right side (quantitative vs. qualitative data collection practices). Within another second or two, you can also see a difference between the blue, green, and red bars –  small nonprofits were generally less likely to use these evaluation practices than medium or large nonprofits. What an improvement over the default chart!

The dataviz challenge: Re-create the “after” version in Excel, R, or some other free software program. When you’re finished, email me or tweet a screenshot to @annkemery.

Bonus: Instead of copying this dataset exactly, think about how you might use a small multiples bar chart in your own work. Can you re-create this chart using your own dataset?

The prize for playing: Beer or coffee, my treat, the next time you’re in DC; a professional development opportunity; and bragging rights.

I’ll post the how-to guide in two weeks. Happy charting!

P.S. Like what you see? Johanna Morariu and I would love to share dataviz principles with nonprofits at the upcoming #14NTC conference. Please vote for our session!