Emphasize The Shape of Your Data

“There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.” – Henry D. Hubbard in the preface to William C. Brinton’s Graphic Presentation, 1939.

Data visualization translates words and numbers into visual cues such as color, size, position, and shape. Humans can process such visual cues much more easily and quickly than words and numbers. Today, I’m here to talk about shape because I don’t think we turn to shape often enough to engage and educate with data. The three area charts below provide a great example of the power of shape. The charts show estimates of the distribution of annual income among all world citizens over the last two centuries. By considering the change in the shape of the data across the three time periods and in relation to the poverty line, we learn a lot. Most significantly, we learn that, over the 215 year time period, the majority of people went from living below the poverty line to living above it. We learn even more by considering the shape of the distribution for each color-coded region.

So consider taking a page from this playbook. Rather than showing change over time in one chart. Consider using shape to tell the story by showing the distribution of something (e.g. income, course grades, number of clients) at different time periods in adjacent area charts.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

10 Essential Data Facts For Non-Data People: The Cheat Sheet

Reposted from January 2022

Here are ten data facts for non-data people who, nevertheless, have to deal with data sometimes (i.e. most of us). This is the cheat sheet. Click on the “Learn More” buttons for additional information served up in comic strip format!

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Check Your Data Blind Spots

You’ve heard it before. We see what we want to see. It’s called confirmation bias, and we are all susceptible. Confirmation bias is a big problem to those presenting or consuming data (i.e. all of us.) How can we draw our own and others’ attention to the data that does NOT fit our existing beliefs? How, in other words, can we check our blind spots?

The great thing about your blind spot when it comes to driving is that you know it exists. Your rearview mirrors do not show you an area next to and behind your car. So you learn to check that area in a different way. Experienced drivers do it by rote. Wouldn’t it be great if we also could remember that we have data blind spots and learn to check them automatically?

Here are some ideas for making your blind spots visible. All of them involve doing something before you look at data (in the form of a spreadsheet, table, chart, map, or graph) to help you look at the data with fresh eyes.

  1. Make predictions before looking at data. To prevent seeing only the data that confirm our beliefs, we can make predictions before looking at the data. In Staff Making Meaning from Evaluation Data, Lenka Berkowitz and Elena “Noon” Kuo suggest that, before sharing data with program staff, “have them spend 10 minutes writing down predictions about what the data will say. This exercise helps surface beliefs, assumptions, and biases that may otherwise remain unconscious.” This can involve drawing a predicted trend in the data or jotting down guesstimates of key data points. Then look for differences between your predictions and the actual data and consider:

    • What may have contributed to the differences,

    • What more do you need to know to take action, and 

    • What actions might you consider immediately?

  2. Consider your “null hypothesis” before looking at data. This approach is a variation on strategy number one.  Rather than making a prediction, you pose this question to yourself: If what I expect is NOT true, what might I see? This is analogous to how researchers conduct experiments.  Rather than trying to prove that a hypothesis (e.g. A is affecting B) is correct, researchers aim to collect sufficient evidence to overturn the presumption of no effect, otherwise known as the null hypothesis. It’s sort of like innocent until proven guilty. The idea is to take the opposite view to the one that you hold and then look for evidence to support it. If you can’t find that evidence, then your assumption might be correct. This approach makes you think more critically and perhaps more dispassionately when encountering data.

  3. Set decision criteria before looking at data. “Many people only use data to feel better about decisions they’ve already made,” notes Cassie Kozyrkov in Data-Driven? Think again. To avoid this, you can frame your decision-making in a way that prevents you from moving the goalposts after you’ve seen where the ball landed. Before considering the data, determine your cutoffs for action. For example, you and your colleagues might decide that program participation below 150 in any given month requires investigation and possible action. Let’s say that twelve-month data show participation below 150 in six months. The pre-established cutoff can prevent you from only focusing on the worst months when participation was below 75.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How and Why to Visualize Variability

Every dataset includes variability. The people and things we measure differ from one another in many ways. And visualizing data always involves some decisions about how much of that variability to show. There are tradeoffs:

  1. If you show too much variability, you obscure patterns and trends. To understand anything with data, we usually need to reduce its complexity. We can’t extract meaning from a table full of numbers and letters. So we summarize the data through such activities as grouping people, concepts, and time periods; calculating averages; or organizing individuals or groups in a rank order. This process allows us to detect patterns and trends within the data. Patterns and trends become even more apparent when we visualize the data in the form charts, maps, and graphs by assigning visual cues such as color, size, and shape to groups and values. However, too many colors, sizes, and shapes make discerning the patterns and trends more difficult.

  2. If you show too little variability, you obscure reality*. Overly simplified visualizations do not show just how complex and messy the data actually is. And the viewer may mistake the simplified, summarized version of the data as reality.

You can find a great example of problem #2 in Eli Holder’s article Divisive Dataviz: How Political Data Journalism Divides Our Democracy. He describes the danger of red and blue political maps in the U.S. in this way: “there’s no such thing as a “red state” or a “blue state.” Consider Texas, which is often called a “red” state. In the 2020 presidential election, more Texans voted for Joe Biden (5.26 million) than every other “blue” state, except for California. Even New York, a Democratic stronghold, had roughly 20,000 fewer Biden voters than Texas. . . . While popular election maps accurately reflect the ‘winner-take-all’ dynamic of the electoral college, they create the misimpression that state electorates are monolithic blocks of only-Republicans or only-Democrats.”

And the misimpressions such maps engender have real-world consequences. Holder describes an experiment in which people were shown either dichotomous maps or continuous maps (see examples below). Those shown dichotomous maps were more likely than those shown continuous maps to feel that their state was dominated by one party and thus that their votes mattered less because the election outcome was a foregone conclusion.

So when deciding how many shades of gray or circle sizes to show, consider how much summarization is needed to make patterns and trends perceptible without misleading the viewer with an oversimplified view of the data. Take, for example, these three versions of a map. They each show the same CDC chronic illness survey data with a “diverging color palette” in which blue states ranked high on health indexes; orange states ranked low; and gray states were in the middle. The maps differ in the degree of variability shown. Which map allows you to see corridors of good and bad health without oversimplifying the matter?

*More specifically, the full reality of the data. This 60-second data tip doesn’t get into the nature of reality in general!

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

One Dataset, 100 visualizations

Today’s tip is to check out the 1 dataset, 100 visualizations project. It shows 100 different ways to visualize this simple dataset:

 

It’s fun to compare the different charts and see how they provide different perspectives on the data. For example, to visualize this data, many of us would create a stacked bar chart like this one and call it a day.

 

But look at how this chart allows you to better understand each country’s relative position in relation to number of world heritage sites between 2004 and 2022. We can more easily see, for example, that Denmark leapfrogged Norway.

 

These 100 charts make a strong case for visualizing your data in a number of different ways before selecting one which provides the perspective needed.


To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Not Your Grandmother's Icons

We have all seen icon charts that look like this (even if our grandmother didn’t create them):

Want to make an icon chart that actually looks like real people as in the example below? Well, of course, you can just find some cool silhouette icons and use any graphic design program — such as Canva or Adobe Illustrator —  to layout and color icons as you wish. However, if you want the chart to be interactive, you will need to use a program like Tableau or Power BI. I created the chart below in Tableau. It provides more information when you scroll over the icons. Scroll down for Tableau instructions.

Here’s how I did it:

(Note: These directions assume basic knowledge of Tableau. If you don’t have that knowledge, here’s a good video on Tableau basics.)

  1. I selected 10 head silhouettes to use as icons. You can find great (free) icons on sites like flaticon , The Noun Project, or Canva. Be sure to save each icon as a separate PNG file with a transparent background.

  2. I added the icons to the shapes folder in my Tableau Repository. Here’s a short video on how to do that.

  3. I connected a data file (such as an Excel or CSV file) to Tableau Public (the free version of Tableau). The file included 40 rows, one for each applicant, and columns for:  a unique identifier for applicants (such as an ID number), selection status (whether applicants was or wasn’t selected to be a participant, and 3) the silhouette image assigned to the applicant.

  4. In Tableau, I started a new worksheet, changed the marks type to shape, and dragged:

    1. The ID number to the columns shelf (note that ID number should be a dimension not a measure);

    2. The selection status dimension to color on the marks card; and

    3. The silhouette dimension to shape on the marks card.

  5. I clicked on shape on the marks card, clicked on “Reload Shapes,” selected the shape palette that I added to my Tableau Repository in Step 2,  assigned head shapes to the various values for the silhouette dimension., and then clicked “OK.”

  6. I clicked on color on the marks card and adjusted the colors for the “selected” and “not selected” values.

  7. I dragged ID number to the filters shelf and selected ten ID numbers to show.

  8. I changed the view from standard to entire view and clicked on size on the marks card and adjusted the size of the heads as I preferred.

  9. I hid the header and title, duplicated the worksheet, and selected different IDs using the filter. I then repeated this step to create two more worksheets.

  10. I created a dashboard, added a vertical container, dragged the four worksheets into the container, clicked on the drop down menu for the container (in the upper right corner of the container) and selected to distribute contents evenly. I then adjusted the layout by adding outer padding and added in a text box.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Data Dashboard Treasure Hunt

Looking for a way to engage your staff, board members, and others in your data dashboard? Want them to understand how to use it and how it can inform their work? Here’s a great idea from MiraCosta College: a dashboard treasure hunt! Each page features one page of the dashboard along with questions that require the user to interact with the dashboard. Correct answers lead the user toward a hidden treasure. Try it for yourself:










Source: Treasure Hunt by MiraCosta College on Tableau Public

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How to Extract Meaning from Survey Data

You just conducted a survey of your clients. participants, board members, visitors, or community members, and chances are you used some Likert Scales in that survey. In other words, you asked respondents to state their level of agreement or disagreement on a symmetric agree-disagree scale. A typical 5-level Likert scale is:

Strongly Disagree - Disagree - Neither Agree nor Disagree - Agree - Strongly Agree

Here’s a FAQ (which is more like a QYSA: Questions You Should Ask) on visualizing Likert Scale data to extract useful information.

Have you collected data just once or multiple times with this survey?

If this is a one-time deal, then I would suggest that you visualize the data using a stacked bar chart. Exactly which type of stacked bar chart depends on what you are trying to understand and show. Check out this Daydreamming With Numbers blog post: 4 ways to visualize Likert Scales. It walks you through various options. If you have collected the data two or more times, read on.

Should I calculate average scores and compare them?

A common way to look at change over time with Likert Scale data is to assign numerical values to each response (e.g. Strongly Disagree: 1, Disagree: 2, Neither Agree nor Disagree: 3, Agree: 4, Strongly Agree: 5) then calculate the average across respondents at two or more points in time and compare them. Some may even use a statistical test (such as a paired sample t-test) to assess whether the averages are “significantly” different. This may seem like an obvious way to deal with the data, but there are problems with it:

  • The distance between 4 and 5 is always the same as the distance between 2 and 3. However, the distance between Agree and Strongly Agree is not necessarily the same as the distance between Disagree and Neither Agree nor Disagree. So we may be distorting respondents’ opinions and emotions by assigning numbers to these response options.

  • Respondents are often reluctant to express strong opinions and thus gravitate to the middle options. Averaging a bunch of middle options (2, 3, and 4) only amplifies the impression that respondents are on the fence.

  • Averages do not give us a sense of the range of responses. The average of these 4 responses (5,1,1,1) is the same as the average of these 4 responses (2,3,2,1). Also averages result in fractional results which can be hard to interpret. Does an increase from 4.32 to 4.71, even if it’s statistically significant, really mean anything in the real world? At best, we can say that the aggregated results changed from somewhere between Agree and Strongly Agree to another place that is a little closer to Strongly Agree.

What are alternatives to calculating averages?

Visualize the spread of responses. If you don’t have too many questions (or can group questions together) some simple side-by-side stacked bar charts might do the trick. See sketch 1 below.

Use the mode or median rather than average.The mode is the number that occurs most often in a data set and may be a good way to describe the data if one response dominated. The median is the middle value when a data set is ordered from least to greatest. If responses tend toward one end of the scale (i.e. are skewed), it may be more reasonable to use the median rather than the average. If you feel that the assumption of equal spacing between response options is legit, then you might stick with the average.

Visualize average, mode, or median using one of the following chart types (see sketches 2-4) to understand and show change over time.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

New and Improved Stacked Bar Chart

Here’s a simple solution to a problem with stacked bar charts. Yes, they allow you to compare the size of different groups as well as the subgroups within each group. But comparing the subgroups is tough because — for all but one of the subgroups — you have to compare the length of the bar segments without a common baseline.

The bar chart below, created with Tableau, solves that problem by adding a filter so that you can see the whole bars by selecting “All” but also see only one or more subgroups so you can easily make comparisons across just those subgroups. In this chart, I’ve also set the sort order so that it’s always in descending order regardless of the filter selections. See info below on how I set the sort order in Tableau.

See how this chart works by interacting with it yourself! Change the selections on the checkboxes.

To sort questions in descending order regardless of the response option chosen, click the dropdown arrow on Question in the rows shelf and select Sort . . .

. . . .Then choose to sort by Field in descending sort order and choose the name of the field that indicates number of respondents.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Jitter Your Charts

A jittered bar chart shows the individuals that make up the bar. In this example, each circle represents an employee within a given city department. Larger circles represent higher salaries and smaller circles lower salaries. You can scroll over each circle to learn more. It’s another great way to show the individuals within an aggregate. And it’s easy to create in Tableau (just watch this four-minute video) or in Excel (here are instructions).

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Is The Chihuahua Syndrome Infecting Your Data?

This “sketchplanation” gives a name to a familiar problem.* Chihuahua is challenging to spell. If humans are entering dog breeds into a database or spreadsheet, chances are there are going to be spelling errors unless they can select from a list of breeds or there is another sort of data validation. It’s hard to extract meaning from data that is inaccurate. “Capitals, spaces, misspellings, hyphens, numbers stored as text, numbers entered as letters (I, O), accents, straight/curly apostrophes, dates out of order, languages, dialects, abbreviations, and more are all routes for misleading your analysis.” So make a plan to clean your dirty data and to keep it clean over time. Also, when visualizing data in programs like Tableau, you can group common misspellings into one new field. In this way, the misspelled entry will be automatically corrected in visualizations that use the new field. Also, Tableau Prep Builder comes with most subscriptions to Tableau and allows for easier data preparation including combining, shaping, and cleaning data for analysis within Tableau.

To see past data tips, click HERE.

*Chihuahua Syndrome” was coined by Edward Tufte.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

10 Tips for Presenting Data Like An Artist

Resposted from March 2021

To make great charts, maps, and graphs, you need to channel both your inner analyst and your inner artist. Here are 10 rules about composition that artists know and that analysts (and the rest of us) can apply when presenting data. Bookmark it! Print it out and pin it to your bulletin board!

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Before Showing A Percentage, Read This

Reposted from October 2021 (And yes, I know that the percentages > 100%, that’s the joke. . . .)

Here’s what I’m going to do in 60 seconds today:

  • Give you three percentages. They might be the type of percentages that you share in proposals, reports, your website, or in social media posts.

  • Give you the backstory on these percentages.

  • Convince you to think carefully next time you want to present a percentage.

Here goes.

#1: Two percent of clients in Program A dropped out in the first three days of the program.

#2: 60% of first time donors in March made a second gift.

#3: 25% of people who attended our XYZ event said that they were unlikely or very unlikely to recommend the event to others.

And here is the backstory on each of the percentages:

#1: Two percent of clients in Program A dropped out in the first three days of the program. Backstory: There were 50 participants in Program A. That means only one person dropped out.

#2: 60% of first time donors in March made a second gift. Backstory: There were 5 new donors in March. That means that 3 made second gifts.

#3: 25% of people who attended our XYZ event said that they were unlikely or very unlikely to recommend the event to others. Backstory: Eight people attended XYZ event. That means two people provided the low rating.

Did the backstories cast a different light on the percentages for you? Perhaps you were imagining more people were involved? When the numerator or the denominator is fairly small, it’s usually best to present both in raw numbers rather than give a percentage. The raw numbers present a clearer understanding of the situation that you’re trying to describe. In fact, when numbers are small, percentages can be downright misleading.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Why and How To Use Free Data

There’s a treasure trove of free data out there. And I know what you are thinking: “I can barely deal with my own data much less anyone else’s!” But think again. What if you could show the need for your services, your potential audiences, or other factors that affect your work without having to collect any data yourself?

Here’s an example of something you might do. I downloaded free data (in the form of an Excel spreadsheet) from the U.S. Department of Agriculture’s website on food access in 2019. I then combined this data with a list of counties that a (fictional) organization serves in Illinois to create the map below.

You can find any number of websites with lists of free data sources, such as this one. I found the USDA data by following the link from this page to Data.gov which is home to the US government’s open data.* I then clicked on “Data” on the navigation menu and searched for the topic of interest to me.

Fair warning, when searching for free data online, you are likely to find yourself in quite a few rabbit holes. So here are a few tips to make your search more fruitful:

  • Before you begin searching, know what you are looking for. Consider what geographies, time periods, or populations you need. Also, think about what data format you need. Perhaps you can only deal with Excel or CSV files. When visiting a free data site, determine if any of the data files available for download meet your needs asap. If it’s not clear, then give up and try another site.

  • If you need local data, check out your city government’s website. Many have open data available for download.*

  • Look for a data dictionary or some other type of documentation to understand what is included in the data, how the data was collected, and what each data field means. Sometimes this is included on a tab in the downloaded data file. Pay attention to what might be missing from the data and the biases that could be baked into it.

  • Link back to data sources (or attribute with text) when showing the data in charts, maps, and graphs.

  • Combine free data with your own data using zip codes, city names, census tracts or other data fields to link the two data sources.


    * Open data is data that can be freely used, re-used, and redistributed by anyone, subject only, at most, to the requirement to attribute and share-alike.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

More Fun Chart Hacks in Canva

I bring you more chart hacks in Canva!

Canva has a number of simple chart designs that you can adapt to your needs. After starting a design in Canva, click on “Elements” and then type in “chart” in the search window to see the chart options shown in the image to the right. Each allows you to customize the chart by entering in a few data points.

HERE are some ways that I have shared in the past to use other options in Canva to hack out some fun charts. And below, you’ll find a few more ideas.

Chart Hacks

Start a design in Canva by clicking on the “Create A Design” button (upper right corner of screen), selecting a size (such as presentation), and then try one of my hacks.

HACK 1: Place a chart in a landscape: For this bar chart hack, find a landscape by searching in “Elements” (on left side of screen). Landscapes with large, cloudless skies work best. Drag the image onto a page and size it as you like. With the image selected, click on “Edit Image” in the upper left corner of the design area and then use the Background Remover tool to remove the sky. Now create a chart using the chart tools (see above). With the chart selected, click on “Position” in the the upper right corner of the design area and select “Backward” to put the chart sligtly behind the landscape image. (See how the bottoms of the bars in the image below are behind the hills?) Finally, find a sky image by searching in “Background” (on left side of screen) and add it to the design.

HACK 2: Show change over time in a chart “notebook.” For this chart, I created a series of donut charts using the chart tools (see above). Then I found a notebook graphic in “Elements.” I made several copies of the graphic and added the charts and labels to each page of the notebook.

HACK 3: Use number frames to label a key data point. For this chart, I created a line graph using the chart tools (see above). Then I searched for “number frames” in “Elements.” I added the relevant numbers to label the key data point on the graph and then dragged and dropped photos into the the number frames. Note that you can upload your own photos to Canva or use photos from their vast library of free photos in “Elements.”

HACK 4: Use videos to label a key data point. For something like the chart shown below, create a line graph using the chart tools (see above). Then type in “speech bubble” in the “Elements” search window. Limit the results to only photos by selecting the “Photos” option below the search window. Drag a speech bubble onto the design (and pointing to the key data point) and, with the speech bubble selected, click on “Edit Image” in the upper left corner of the design area and then use the “Shadows” tool to add a shadow to the speech bubble image. Now drag a video to the design and size it to fit inside the speech bubble. Note that you can upload your own videos to Canva or use videos from their vast library in “Elements.”

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Four Fun Chart Hacks

Have you played around with Canva? It’s a great, free online design tool. It includes lots of images and gifs and is easy to learn. Canva has a number of simple chart designs that you can adapt to your needs. After starting a design in Canva, click on “Elements” and then type in “chart” in the search window to see the chart options shown in the image below. Each allows you to customize the chart by entering in a few data points.

But I wondered how I could use other options in Canva to hack out some fun charts. Scroll down to see what I came up with.

 

Chart Hacks

Start a design in Canva by clicking on the “Create A Design” button (upper right corner of screen), selecting a size (such as presentation), and then try one of my hacks.

HACK 1: Use images to build bars: For this bar chart hack, I selected “Elements” and then searched for images of backpacks and then stacked them (by dragging and dropping) to create a bar chart about homework completion. You can use the “Show Rulers and Guides” option on the File menu to make the bars the right length.

HACK 2: Use icons to make a pictogram chart. Pictogram charts use icons to represent small sets of data. Each icon can represent one unit or any number of units (e.g. each icon represents 10). For this chart, I found a human graphic by selecting “Elements” and then searching for “human.” Then I colored the icons to show the number of students with failing grades and added labels using the text option on the left.

HACK 3: Use grids and photos to create a timeline of programs and events. Select “Elements” and type in “grid” in the search window. Canva will give you a bunch of frame options. Choose one and then select “uploads” to import photos of your organization’s events and programs. Then simply drag and drop photos into the grid and label bars using the text option on the left as in this example. Drag in a photo of something white for the empty cells.

HACK 4: Use frames and videos to create moving charts. For a bar chart like the one shown below, select “Elements” and type in “frame” in the search window. Canva will give you a bunch of frame options. Choose a rectangle shaped frame and place in the design, using the “Show Rulers and Guides” option on the File menu to make your bars the right length. Then select “Elements” and type in a key word for the type of image you want. I typed in “water.” Under the search window, click on “Videos” to show only video elements. Then drag and drop videos into the frames and label using the text option on the left.

For something like the line chart shown below, select “Elements” and type in “chart.” Select a line chart option and fill in data as needed. Then type in “frame” in the Elements search window. Choose a circle shaped frame and place in design over a data point, adjusting size as desired. Then select “Elements” and type in a key word for the type of image you want. I typed in “glow.” Under the search window, click on “Videos” to show only video elements. Then drag and drop a video into the frame. Use the “Position” button in the upper right corner to place the video “backward” (i.e. behind the chart). Label using the text option on the left.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

What We've Learned From All Those COVID Charts

COVID has taught us a lot about a lot of things, including data viz. Early in the pandemic, I asked: Which are worse: COVID haircuts or COVID charts? We all needed ways to understand what was happening, how bad it was, and what we should do. And many public and private entities turned to data viz to convey this information. But not all of them did a great job, particularly at the beginning. With time, those visualizing this data have learned a great deal, and we can apply this learning to charts showing all types of data.

The digital magazine, Sapiens, recently reviewed the “emerging consensus” around how to display COVID data. In this tip, I give you the 60-second version of these rules and how they might apply to the work of any nonprofit organization.

1. Cases should be reported on a population-adjusted basis. Whether you are counting cases of COVID, school drop outs, or food insecurity, raw numbers don’t mean much. One hundred drop outs in a small school district should raise more alarms than the same number in a large district. Per-capita numbers are better. They allow us to compare populations of different sizes.

2. Cases should be reported on a rolling weekly basis. Numbers of cases can fluctuate on a daily basis for a variety of reasons. And these spikes and dips can make it difficult to discern overall trends. Regardless of the type of cases you are reporting, presenting rolling averages (aka moving averages) often works better than showing daily cases.

3. Certain thresholds are meaningful and remain so over time. Per capita numbers may give us a better sense of the magnitude of a problem, but they don’t tell us what to do. The color-coded COVID risks levels serve that purpose. We can show similar thresholds in charts showing other issues. For example, the dashboard below indicates when the number of people experiencing homelessness exceeds temporary beds available and thus when further action is needed.

Source: National Alliance to End Homelessness

4. Heat maps are useful. Heat maps use color to convey meaning. And among COVID maps, as noted in the Sapiens article, “colors and threshold values vary, but everyone is speaking the same general language. Green, blue, and white tend to mean things are under control while yellow, orange, and red suggest increasing danger.” Thus heat maps show us not only when action is needed but also where it’s needed. For example, in the maps below, states with high ranks and colored in blue shades are healthier, and states with low ranks and colored in orange shades are less healthy according to the Overall Health Index and the Chronic Illness Index. Gray states are in the middle of the range. This map helps us to discern corridors of good and poor health.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Why You Should Know About Connected Dot Plots

This week, I give you the connected dot plot. The name might not ring a bell, but I think you’ll recognize the face. It’s a pretty intuitive and useful chart for nonprofits. This is a continuation of a series of tips which introduce you to different chart types which are good for making sense of the type of data nonprofits collect.

Active Ingredients (What is a connected dot plot?)

A connected dot plot, aka “dumbbell plot,” shows the differences between two categories or two points in time. Usually circles indicate the values of each category or time period. For example, this segment of a larger chart from Pew Research Center gives us an intuitive way of comparing two age groups on their social media use. We can easily see where the gap is larger (Germany) and smaller (India). The stats to the right help to distinguish lines that are close in length such as the ones for Germany and France. Here are instructions for creating a connected dot plot with Tableau and Excel.

Uses

Connected dot plots can be much more effective in showing differences or changes over time than their more popular cousin: the grouped bar chart. Check out the two examples below which show the average score (on a five point scale) among respondents to a survey in 2018 and 2019. See which gives you a better sense of the change over time.

Grouped Bar Chart

Screen Shot 2021-08-16 at 11.35.55 AM.png

Connected Dot Plot

Warnings

In the examples above, the relative positions of the two categories or time points are the same in all cases: social media use was always greater in the younger group of users than in the older group, and the average score was always higher in 2019 than in 2018. What should you do when the positions flip flop? A good strategy is to call out these direction changes using arrows, colors, and/or legends as in this chart:


Fun Facts

Connected dot plots are sometimes called “Cleveland dot plots,” named for William Cleveland who, along with Robert McGill, studied different types of “encodings” in charts such as the length of a line, the area of a “slice” of a circle, and the position of a point along a common scale. They looked at what types of encodings humans decode most easily and, based on their findings, they designed a chart well-suited for human perception: the connected or “Cleveland” dot plot.

To see past data tips, including those about other chart types, click HERE.

Sources: Storytelling With Data and UC Business Analytics R Programming Guide

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

What You Should Know About Sunburst Charts

This is a new addition to a series of tips on different chart types. In each tip, l give you need-to-know information in a format akin to the “Drug Facts” on the back of medication boxes: active ingredients (what the chart is), uses (when to use it), and warnings (what to look out for when creating the chart). The idea is to fill up your toolbox with a variety of tools for making sense of data. This time I give you the sunburst chart.

Active Ingredients (What is a sunburst chart?)

A sunburst chart is a multi-level pie chart. Each ring corresponds to a level in a hierarchy, with the highest level as the inner circle or ring. Each ring slice is either divided equally under its parent slice or is proportional to a value. Color is often used to highlight hierarchal categories. Check out the example below. The inner ring segments show the number of participants in three program areas of a community center. The outer ring segments shows the number of participants in specific programs within the three areas. Scroll over segments to learn more.

Uses

Although the pie chart gets a bad rap in the data viz world, this pie chart cousin shines in certain circumstances. It works best (in my opinion) when you want to show not only a hierarchy but also how each component of the hierarchy differs according to some measure. For example, you want to show which components have the most participants or funding, or the highest survey ratings.

Here are instructions for creating a sunburst chart with Tableau and Excel.

Warnings

Sunburst charts with a large number of ring slices are difficult to read. A good rule of thumb is to abandon your dreams of a sunburst chart if any of the segment slices are too small to label. Once you need a color legend, as in the example below, use another type of chart such as a tree diagram or treemap. Also, I think a tree diagram works better when you are just showing a hierarchy and not how the components differ according to a measure.

Source: Oracle

Fun Fact

Here’s an early example of a sunburst chart, published in Mechanical Engineering in 1921 according to Think Design. It shows the average annual net expenditure of the US federal government from 1910 to 1919.

Source: Think Design

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

A Better Alternative to Surveys?

When organizations want to understand the concerns, opinions, beliefs, or needs of their communities, clientele, or participants, they often turn to surveys. But I probably don’t have to tell you that surveys have many downsides. To name just a few:

  • The difficulty of asking the right questions in the right ways to really understand issues accurately and fully.

  • The difficulty of getting a decent response rate so that you can feel at least somewhat confident that responders’ viewpoints reflect those of the larger group.

  • The difficulty of extracting actionable knowledge from survey responses without a degree in data analysis.

I recently read about a tool that addresses some of the downsides of surveys. Polis is an open-source, real-time system for gathering, analyzing and understanding what large groups of people think in their own words.

Surveys present people with questions like this:

Source: https://www.examples.com/business/assessment/community-needs-assessment.html

By contrast, Polis allows participants to submit their own short comments on a topic specified by the “conversation” creator. Comments are then sent out semi-randomly to other participants to vote on by clicking agree, disagree or pass.

Most interesting to me are the visualizations that Polis generates in a report, which can be shared with all participants. The report includes, a viz like this:

Source: Polis

Each dot represents a comment or statement and is placed along a continuum to show the degree of agreement with the statement. In this conversation, you can see that there were many more consensus statements than divisive statements. And Polis says that’s usually the case. Polis can make consensus visible and thus may be a powerful tool when division so dominates our attention that we may be skeptical that any consensus among diverse groups exists.

When you scroll over a dot, the related statement appears below with stacked bar charts showing the amount of agreement (green), disagreement (red) and passes (gray) among participants overall and by opinion groups. An opinion group is made up of participants who tended to vote similarly on multiple statements and also have voted distinctly differently from other groups. Because the statement shown above (represented by the red dot in the chart) is toward the consensus end of the spectrum, the majority of participants in both opinion groups A and B agreed with the statement. That wasn’t the case for the statement shown below. Participants in opinion group A were much more likely to agree with this statement than those in opinion group B.

Source: Polis

The report also includes a summary of all of the consensus statements. (See example below.)

I can’t vouch for Polis — never used it myself — but I find its basic idea intriguing. If your organization is looking for a better way to understand a large group of people and is particularly interested in finding consensus hidden among all the noisy division, you may want to look into it.

Source: Polis

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.