I Used Free ChatGPT To Analyze Survey Data. Here's What I Learned.

1. You collect this type of survey data.

Here’s a familiar scenario. You survey your clients, participants, donors, volunteers, etc. and you include some “Other, please specify” options or other “open-ended” questions to better understand respondents’ opinions, experiences, etc.

2. But you don’t know what to do with it.

You collect your survey data but don’t have the time and/or analytical skills to deal with this qualitative data.* Maybe you create one of those horrible word clouds or, even more likely, you just analyze the quantitative data and ignore the qualitative data.

If you had the time and know-how, you might have “coded” the data in order to analyze it. This involves assigning themes to each open-ended survey response in Excel (or the like) or perhaps using one of these free tools.

*Quantitative data is numerical, countable, or measurable. Qualitative data is interpretation-based, descriptive, and relating to language.

3. But what about AI?

You’ve heard that it’s supposed to make tedious, repetitive tasks much easier, and coding survey responses certainly qualifies as both. Could you use the free version of ChatGPT to get this job done? I shared your curiosity and gave it a try. Bottom line: It helped to identify themes to use as codes but it didn’t do all the work for me. For a little longer description of my experience, keep reading.

4. Prepare for AI.

I watched this YouTube Video based on this article to learn how to craft a prompt that would likely get me what I wanted. I also found free survey data on the City of Chicago Data Portal to use for my experiment. The survey asked 43rd Ward residents about “other priorities” for their ward. I thought I could just upload the CSV data file to Chat, but it turns out you need the paid version for that. So I ended up pasting in the survey answers after entering the prompt. Also note that I used publicly available data. You should think twice about entering any type of sensitive data into Chat.

5. Craft the prompt.

Here it is. Yes, it’s long and yes, I say “please,” although I’m not sure if that affected the results!

6. Here’s what happened.

I first tried pasting in the prompt plus the data but that was too long for Chat. So I had to feed the data (all 23 pages) in batches of about 3 pages at a time and despite entreaties to Chat to update the charts based on ALL of the data I shared so far, it only gave me charts for the last batch I had entered, and I had to combine them in Excel. At first I was impressed with the almost instant tables, but I felt my AI assistant wasn’t quite listening to my instructions or just not understanding them. Still, I did develop this list of themes and Chat did code each survey response according to these themes, but I would not feel comfortable relying on these results and would want to possibly combine some of these themes and read through all the responses to see if I agree with the coding.

To see past data tips, including those about other chart types, scroll down or 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 Viz Inspo

Looking for ways to make your data more engaging? Take inspiration from these data tips on steal-worthy visualizations. Click on the images below to see the whole visualization and get suggestions on what to steal from it.

To see past data tips, including those about other chart types, scroll down or 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.

Pop Quiz: Guess What This Chart Shows

Reposted from September 2022

Go ahead and make a guess from the options below. Then scroll down to see how your response compares with others’ and what the answer is!

Keep scrolling!

The answer: The decline in child poverty in the U.S.


As reported in The New York Times, “the sharp retreat of child poverty represents major progress and has drawn surprisingly little notice, even among policy experts.” Read the article (and view the detailed line chart) to learn more about the role of government aid in lifting children and families out of poverty.

I share this chart with you—in this way—for a couple of reasons:

1) It’s an engagement strategy you can use. Rather than present a list of stats to your audience, you can engage them in your data by first quizzing them on an interesting, fun, or counterintuitive finding from your data.

2) Bad new bias. Bad news is more likely to be reported than good news, possibly because bad news sells, according to this article citing various research. Perhaps because of that bias, we may be more likely to assume a chart is telling a negative story. This chart is a reminder of the importance of taking a broader view to gain a more balanced understanding of an issue.

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.

Why You Should Know About Calendar Heat Maps

Want to see patterns in participation, fundraising, volunteering, or social media measures across an entire year? A calendar heat map might do the trick.

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. And the calendar heat map is a simple tool you can put to good use!

Active Ingredients (What is a calendar heat map?)

As in the example above, a calendar heat map shows a measure across days on a calendar. The measure might be the number of participants, dollars raised, volunteers recruited, social media engagement, etc.

Uses

Calendar heat maps provide a great way to see patterns in a measure over time, particularly if month and day of the week are important factors. For example, such a chart can help you detect whether participation is lagging on Mondays during summer months. In the example above, you can scroll over dates for more information and use the program filter to see participation for the selected program. Here are instructions for creating an interactive calendar heat map with Tableau and in Excel.

Warnings

Depending on your needs, other charts that show change over time may be more useful to you. For example, if you need to more clearly see the amount of change over time, a line graph might serve you better. For other chart types that show change over time, see below.

Fun Fact

Here’s a fun calendar heat map showing more/less common birth dates.

Source: Amitabh Chandra on Tableau Public

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

Source: Visual Vocabulary by Andy Kriebel on Tableau Public

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 Activate Board Member Fundraising With Visuals

Reposted from January 2023

I recently came across this excellent article by The Fundraising Authority. As promised in the title, it provides a “Simple, Step-by-Step Process for Getting Your Board to Refer New Prospects to Your Non-Profit.” In a nutshell, here are the four steps:

  1. Explain how referrals work and assure your board members that no one they refer will be asked for money until they indicate a desire to get involved.

  2. Show board members how many people they actually know through a mind mapping exercise.

  3. Ask board members for referrals usually in person.

  4. Bring referral success stories back to board meetings on a regular basis.

My tip is to enhance steps 2 and 4 with visuals.

Visuals for Step 2: For the mind map, the point is for board members to brainstorm all the people they know by considering people in different categories of their lives. You can use Canva whiteboards (or a similar tool) to create a mind map that the board member (pictured in the middle) can use to add the names of people in each category on virtual post-it notes.

Visuals for Step 4: The article claims that “this is a key step. Nothing will convince your board members to bring you more referrals than hearing from other board members that have done it successfully.” You can visualize the donors whom various board members brought in using tools like Flourish to show their networks, as in this example. Scroll over the circles to interact with it and learn more. Some board members brought in donors who, in turn, brought in other donors. To make something similar, select one of the network graph templates on Flourish and fill in the data needed. (See snapshots of the data I added for the visual below.)

Links data

(used to show who is connected to whom)

Points data

(used to show groups by color, size points according to amount of donations, and add images for board members)

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.

Sure Data Confuses You. You Are An Early Human.

Reposted from August 2022

I recently read this article which suggests that, if we avoid a large catastrophe, we may be living at the early beginnings of human history. That is sort of mind-boggling. But even if we are not early humans, we are certainly at the beginning of our journey with data.

We aren’t so good at processing words and numbers and making sense of them. Think about the last time you looked at a spreadsheet and got the gist of it in a few seconds. By contrast, we can get the gist of a photo in less than a few seconds. That’s because our brains have evolved over millions of years to process visual information — color, shape, size, placement — at lightening speed. Indeed, our survival depended on it. Think about detecting predators in the tall grass at a distance.

Processing words and numbers is a quite recent activity for humans, as the timeline below shows. Perhaps, as our brains evolve, we will be able to discern a spreadsheet at a glance. But, until then, we should consider visualizing our data by translating words and numbers into color, shape, size, and placement in the form of charts, maps, and graphs.

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.

Another Data Viz Resource You Should Know: USAFacts

Here’s a new addition to my highly-curated resources list: USAFacts. I occasionally write a 60-second data tip describing a particular resource, including why I think it’s cool. And I link each of these tips to a resources list on my website.

What is it?

USAFacts is dedicated to making government data more accessible. The idea is to help people understand where their tax dollars are going and to help those working on issues of concern in the philanthropic, nonprofit, and public sectors to easily access information to inform their decisions.

Who’s it for?

The general public, policymakers, philanthropists, nonprofit managers, and researchers, among others.

Who’s behind it?

After he retired from tech and began to focus on philanthropy, former Microsoft CEO Steve Ballmer wanted to understand what the government spends on programs to help people and the outcomes of those programs. However, unlike businesses, US governments are not mandated to compile reports on their expenditures. He then hired data analysts to compile this data, and this was the origin of USAFacts, a not-for-profit, nonpartisan civic initiative which is solely funded by Ballmer.

Why I think it’s cool

It’s free and the data is shared under a Creative Commons license. They only ask that you credit USAFacts when using their curated material. Most of their data is visualized and all of it is well-documented. Charts can be easily downloaded in an image format or embedded into your website using an embed code like the chart below.

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 Create More Diverse, Equitable, and Inclusive Data Visualizations

Reposted from February 2022

When we visualize information, we make a series of decisions which affect the way that viewers process the information in our charts, maps, and graphs. Sometimes they don’t feel like decisions at all. We go with the default settings in the application we are using. Or we just do something the way it’s usually done. But a more diverse, equitable, and inclusive approach to presenting and visualizing data requires us to make those decisions more consciously and deliberately. Jonathan Schwabish and Alice Feng of the Urban Institute provide some helpful tips, based on the Urban Institute’s own style guide, which you can apply the next time you present data.

Here is a summarized version of Schwabish and Feng’s article.* And here is my 60-second version of their recommendations:

  • Use people-first language in titles, text, and labels associated with charts, maps, and graphs. For example, use “people with disabilities” rather than “disabled people.” Also the Urban Institute does not refer strictly to skin color. For example, they refer to “Black people” not “Blacks.”

  • Order and present groups purposefully. The first group shown in a table or the first bar in a chart can affect how readers perceive the relationship or hierarchy among groups. For example, if the first group is “Men,” then it may appear that men are the default group against which other groups should be compared. One way to prevent viewers from making certain comparisons is to display groups in side-by-side charts (aka “small multiples” charts) rather than on a single chart. In general, make ordering and grouping decisions to promote certain comparisons and prevent others.

  • Point to missing groups. If certain groups are missing from the data, explain why in text boxes or footnotes. Also add information on groups included in “Other” categories and consider providing a more specific label than “Other” which can have an exclusionary connotation.

  • Do not use color palettes that reinforce gender or racial stereotypes. This one may seem obvious, but it bears repeating. Also, the Urban Institute’s color palette is accessible to people with certain color vision deficiencies, and the contrast between those colors and white and black text meet basic accessibility guidelines.

  • Depict a variety of races and genders when using icons and avoid icons that make inappropriate depictions of people or communities or reinforce stereotypes such as showing traditionally feminine icons to depict nurses or traditionally masculine icons to depict bosses.

  • Find ways to show the people behind the data. Data visualizations are, by definition, abstractions of larger realities. But in the process of abstracting, we may obscure the lived experiences of the real people whom the data represent. Visualizations can remind viewers about the individuals behind the data by, for example, depicting them as individual circles rather than aggregating them in a single bar.

* The full paper has been published as an OSF Preprint and can be accessed 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.

Why You Should Know About Cycle Plots

If you are looking to explore patterns in participation or giving, a cycle plot can get you there.

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. To learn about other chart types, check out this index of data tips.

Active Ingredients (What is a cycle plot?)

A cycle plot shows how a trend or cycle changes over time. We can use them to see seasonal patterns. Typically, a cycle plot shows a measure on the Y-axis and then shows a time period (such as months or seasons) along the X-axis. For each time period, there is a trend line across a number of years. In the example below, we see that, on average (black lines show averages across years), there were the most travelers from Greece in August between 2001 and 2011, but we can also see that the number of travelers varied greatly from year to year. Use the filter to see trends for travelers from other countries.

Source: Travellers by Month Cycle Plot by Tai Shi Ling on Tableau Public

Uses

Cycle plots can help identify periods of time when the best or worst results are recorded. For example, you want to see trends in participation in your summer programs or patterns in year-end giving over the years. Cycle plots can be created in a number of data viz applications including Excel and Tableau.

Warnings

The range of years shown in each trendline can be shown on the X-axis or in the subtitle to the the chart, but the range should be clear and consistent across trendlines.

Fun Fact

William S. Cleveland and Irma J. Terpenning introduced the cycle plot in Graphical Methods for Seasonal Adjustment (1982) In their example below, we see that number of telephone installations are highest in late summer/early fall.

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

Title Image Source: Seasonality with Cycle Plots by Vladimir Trkulja on Tableau Public

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.

The Power of Substraction

“Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.”

―Antoine de Saint-Exupéry, Airman's Odyssey

If you have heard of any data viz guru, it’s probably Edward Tufte. And if you know one thing about Tufte, it’s probably the data-to-ink ratio. The data-to-ink ratio is the amount of ink (or pixels) that convey the data divided by the total ink (or pixels) used in the entire chart. The ratio, according to Tufte, should be as close to one as possible. In other words, most of the ink/pixels should be conveying data, and you should remove as much non-data ink/pixels as possible. Click through Joey Cherdarchuk’s slides below for a great example of what Tufte is talking about.

Source: Darkhorse Analytics

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.

Presenting Data Fast and Slow

Reposted from May 2022

Sometimes we approach the challenge of sharing data with others as if we were trying to con a pet into taking a pill. We think that our audience is too busy, disinterested, or distracted to focus on the data. So we wrap it in something that attracts their attention and feed it to them as quickly as possible. The problem with this approach is that it may get the data into their brains—momentarily—but it won’t stay there long. See where the pill ends up in this video.

If we want others to LEARN from the data — which involves not only retaining it but also drawing knowledge from it and applying that knowledge in the future — then we need a different approach. Daniel Kahneman’s Thinking Fast and Slow can help us.

First a little background on how the brain works, according to the evidence Kahneman presents. For learning to happen, information first must get past System 1 of our brains. This is where fast thinking happens. System 1 is the harried gate keeper, madly processing all of the information that comes in through our senses, pitching most of it, keeping only what is deemed necessary. But making it through the gate is only half the battle. Once in, information confronts System 2. This is the part of the brain that allows for conscious thought or slow thinking. The problem is that System 2 is lazy. Conscious thought is hard, and System 2 is always looking for an excuse to avoid it. However, if System 2 engages with information, the resulting knowledge can find its way to long-term memory and learning happens.

So the challenge when presenting data is to make it past System 1 AND engage System 2. Let’s consider a series of vizes from Harvard Business Review (HBR) that I think meets both parts of this challenge. Yes, it’s an example from the for-profit world, but could easily work with nonprofit data. See snapshot of the first viz in the series below .

How to get data past System 1

Getting data past the System 1 fast-thinking gate keeper is all about grabbing attention. We process images much more quickly than words and numbers, so images are a great foot-in-the-door. The HBR viz does it with bright colors and a cool-looking, somewhat unusual chart. There’s plenty of information out there about how to attract attention, including the use of images with:

  • Stand out colors and textures

  • Human faces (we are wired to focus on them)

  • Novelty (images that are unusual in size, placement, etc.)

Data visualizations can use color as well as images to draw attention. But getting past System 1 is not nearly enough. For learning to happen, the viz also has to engage System 2.

How to engage System 2

System 2 is smart but lazy. So we need to pique its interest. The HBR viz starts with a title that poses a question. When confronted with an interesting question, we may be more likely to stick around for an answer. Then the viz leads you through the answer in a visually engaging way (see interactive version of the viz HERE). These are two great ways to slow down and engage the brain with data. Here’s a list of ways to engage System 2:

  • Ask a question in the title as the HBR viz does—questions beg answers.

  • Make it personal. We may be more likely to engage with data when we have a personal connection with it. This New York Times viz, for example, allows you to enter in your county to see what the barriers to COVID vaccination are in your area.

  • Highlight a surprising finding. Many of us love the counterintuitive and the creative. If you draw attention to something new that the data suggests, you may have a better chance at hooking System 2. For example, this viz from The Economist shows that China emits far less greenhouse gas per person than Western countries at the same stage of economic development. Or check out this viz by Dimiter Toshkov showing that small countries can be big players in development and good governance.

  • Hand draw it. There is some evidence that making information harder to consume, for example by presenting it with harder-to-read fonts, makes the brain slow down and engage in effortful and analytic processing. Although the jury is still out on this, I do find myself more likely to engage in hand-drawn vizes like two of the winners of the World Data Visualization Prize in 2019. Perhaps it’s simply the novelty of hand-drawn charts that engages me. Anyway, it’s something you might consider, and all you need is a pen and paper.

  • Walk them through it. A great way to slow down your viewers is to set the pace by walking them through the data as HBR does in the example. I love how HBR presents what the data might look like if our assumptions were confirmed followed by what it actually looks like.

Sources: Veritasium, Visual Content Space, MIT News, Springer Link,

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.

Don't Measure Impact . . . Wait, What?

Reposted from September 2022

Ghost of Christmas Yet To Come in The Chrismas Carol by Charles Dickens, Illustration by J. Leech, Source: Flickr

Most organizations should not waste time and money on impact evaluations. Measuring impact is difficult and expensive. It’s difficult because you need a good counterfactual. A counterfactual is what Dickens’s Ghost of Christmas Yet to Come shows Ebenezer Scrooge: what would happen if you did not change anything. The impact of an intervention or program is the difference between what happened and what would have happened without the intervention. Since, in the real world, you can’t observe the same group of beneficiaries with and without the intervention (as we do when we watch The Christmas Carol), you need a good proxy for the would-have-been condition. The best proxy is a group of potential beneficiaries that were randomly selected from a larger group of potential beneficiaries. These folks do not get the intervention. Then you can compare those who did and did not receive the intervention over time to estimate the impact of the intervention. This is called a randomized control trial or RCT.

Of course, withholding an intervention from potential beneficiaries can be a difficult and morally-questionable pursuit. And tracking a large group of beneficiaries and non-beneficiaries over time is expensive. This usually requires a team of skilled data collectors and analysts. Non-randomly-selected comparison groups are not nearly as good because they may differ from the intervention group in known or unknown ways. So it’s difficult to determine if the outcomes observed are due to the intervention itself or to pre-existing biases or characteristics. This costly and challenging process is further complicated by the need to start with a well-established intervention, one that has already worked out the kinks.

Due to the many challenges of measuring impact, most organizations should not waste time and money on impact evaluations. Instead, they should consider interventions that already have a strong research base, ideally because they have been rigorously tested with RCTs. (Check out: Where to Search for Evidence of Effective Programs.)

In a Stanford Social Innovation Review article, Mary Kay Gugerty and Dean Karlan suggest that, before beginning a new program, organizations ask: “What do other evaluations say about it? How applicable is the context under which those studies were done, and how similar is the intervention? Study the literature to see if there is anything that suggests your approach might be effective.”

Rather than assessing impact, your limited resources are better spent assessing implementation. You can do this by collecting data that shows whether what you planned is actually happening. If you can pinpoint where the problems are, you are in a better position to make fixes, alter plans, refine processes.  Many organizations make their plans using a logic model (aka theory of change). A logic model is a flow chart with inputs and outputs. The best logic models draw on past impact evaluations to determine what inputs are most likely to lead to what outputs. And organizations can easily assess progress to date by plugging their logic models into real time data. Interested? Read more about “living logic models” HERE.

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.

It's Love Data Week!

What’s that?

Love Data Week is an international celebration of data, taking place every year during the week of Valentine's Day. Nonprofit organizations, universities, government agencies, corporations and individuals are encouraged to host and participate in data-related events and activities.

What’s in it for me?

Lots of free online events, many of which are relevant to nonprofit work such as workshops on data visualization, infographics, data resources, data privacy, etc. See a full list of events HERE.

Where can I learn more?

HERE.

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 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.

How To Balance Your Information Diet

Here’s a question for you. And don’t go Googling. Just make your best guess.

Have the number of people experiencing homelessness in the U.S. increased or decreased since 2007?

Whatever your answer, you likely drew on your own personal experience as well as images and information from the media when guessing at the answer. Perhaps you drew on some statistics too. But, unless you have expertise in this area, probably not. Stick with me for a minute, and I’ll not only provide an answer to the question but also some insight into how we consume information.

Personal experience, media, and statistics affect how we understand any issue, and there are limits to each of these inputs. So we would do well to understand those limits before acting on our understanding by voting, donating, or making decisions about programs that our organizations operate. Max Roser’s article in Our World in Data (The limits of our personal experience and the value of statistics) walks us through some of those limitations:

Personal Experience

“The world is large, and we can experience only very little of it personally,” Roser notes. “For every person you know, there are ten million people you do not know.” Even the most social and well-traveled among us can have only a limited understanding of the world through personal experience. I, for example, do not know anyone personally who has been unhoused, and most of my interactions with people in this situation occur on the street when someone asks me for money. This experience provides no information about the breadth of the problem or the range of experiences with this issue over time.

Media

“This fact is so obvious that it is easy to miss how important it is: everything you hear about anyone who is more than a few dozen meters away, you know through some form of media,” Roser points out. “The news reports on the unusual things that happen on a particular day, but the things that happen every day never get mentioned. This gives us a biased and incomplete picture of the world; we are inundated with detailed news on terrorism but hardly ever hear of everyday tragedies like the fact that 16,000 children die every single day.” If I recently heard a story about a city clearing homeless encampments, I may assess the problem as larger, and if I haven’t heard about anything on the issue in awhile, I may assess it as smaller.

Statistics

“The collection and production of good statistics is a major challenge,” writes Roser. “Data might be unrepresentative in some ways, it might be mismeasured, and some data might be missing entirely.” But, unlike personal experience and the media, it provides a way of assessing the full range of an issue. So it’s important to add statistics, along with personal experience and the media, to our information diet.

To add some statistics to your understanding of homelessness, the number of people experiencing homelessness in the U.S. decreased from about 650,000 in 2007 to about 580,000 (about 18 of every 10,000 people) in 2022 according to The 2022 Annual Homelessness Assessment Report to Congress.

We should not discount personal experience, the media, or statistics because of their limitations. But we should appreciate their limitations when forming opinions and taking actions based on them. As Roser notes: “Each way of learning about the world has its value. It’s about how we bring them together: the in-depth understanding that only personal interaction can give us, the focus on the powerful and unusual that the news offers, and the statistical view that gives us the opportunity to see everyone.” As described in many tips in this blog, well-designed charts make data/statistics more accessible to everyone and thus allow everyone to see everyone.

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 Beeswarm Charts

If you are looking to compare individuals, programs, locations, events, etc. on one or more measures, a beeswarm chart could be just the ticket.

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. To learn about other chart types, check out this index of data tips.

Active Ingredients (What is a beeswarm chart?)

A beeswarm chart (or swarmplot) is a type of data visualization that displays individual data points so that they don't completely overlap, resulting in a "swarming" effect. The beeswarm chart is related to strip plots and jittered strip plots, both of which are scatter plots with a measure on the vertical axis and a category on the horizontal axis. Strip plots become less useful when tightly packed data points start to overlap too much, obscuring patterns in the data. The jitter plot partly solves the problem but not as well as the beeswarm chart.

Uses

Beeswarm charts are useful to highlight individual categories or entities while still showing a distribution as a whole. In the example above, you can see that family events and smaller events were the most highly rated, while health events and larger events generally got lower ratings and that the distribution of average ratings was similar for introduction, beginner, intermediate, and advanced level events.

This type of chart is not native to most data viz applications but happily there is a free online tool called AdvViz that allows you to upload a CSV file to create a basic beeswarm chart and then download it as a Tableau file. From there, you can open it in Tableau Desktop and make adjustments to the formatting. That’s how I created the beeswarm chart above. You can also create this type of chart in Flourish and RAWGraphs.

Warnings

In the example above, I used color to distinguish different event types and circle size to show the number of participants in each event. When using color coding, make sure the colors contrast enough so that viewers can easily discern one category from another. Also, reducing the opacity of the color allows viewers to see overlapping circles. When using size to show a measure, make sure that the range of the measure is wide enough that the viewer can easily discern small from large. Small differences in size can be hard to detect.

Fun Fact

A beeswarm chart is a great way to show stressors on bee colonies! See chart below.

Source: Data Literacy


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

Sources: The Data Visualisation Catalogue

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.

Best Data Viz of 2023

Looking for a fun (if somewhat geeky) study/work break? Check out these best-of lists for 2023:

New York Times

Visual Capitalist

538/ABC News

FlowingData

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.

Do nonprofits have the necessary data to make good use of AI?

This is a question that I’ve been wondering about. Maybe you have too? So I used AI (artificial intelligence) to find an answer! Here is what ChatGPT spit out in a few seconds with my commentary on the side.

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.

Bar Chart Hack #5: A Little Fine-Tuning Can Transform A Chart

 
 

Welcome back to the 60-Second Data Tip series, “How to Hack a Bar Chart.” This week we look at some graphical fine-tuning that can transform a traditional bar chart into something that’s more engaging and more informative.

First I’ll show. Then I’ll tell.

Take a look at Chart A below. Then take a look at Chart B.

large_small_data (version 1).jpg

Chart A

voices.png

Chart B


Both are bar charts showing the same data. But B wins, hands down. Why?

Chart A truncates the Y-axis making the difference between large and small counties look bigger than it actually is. Chart B, by contrast, fills in the whole bar and darkens the portion not attending school or employed, thus giving us a sense of the size of both groups (those who are in and out of school and work) in large and small counties.

Chart B points us to the main takeaway with the title and annotations.

Chart B doesn’t have unnecessary and distracting visual elements such as gridlines and axes labels.

Chart B provides images to further emphasize the contrast between large and small counties.

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.