10 Rules To Elevate Your Data Viz (Rule #9)

“Good design is like a refrigerator—when it works, no one notices, but when it doesn’t, it sure stinks.”

–Irene Au

A jumble of elements in any design, including data visualization design, stinks. That’s why alignment is one of 10 composition rules for good design. Here’s the 60-second version of this rule.

Composition Rules (#9) by Amelia Kohm

What Does “Align Elements” Mean?

Alignment is placing text and other design elements so they line up. It orders and organizes your elements. It also creates visual connections and improves the overall readability of a design. You can align elements to a margin or to other elements in a design. Elements can also be aligned along a central axis.

How Can I Apply This Rule to Data Viz?

Aligning charts, maps, graphs, titles, subtitles, and other elements of a data viz design is a simple way to bring order to your composition. Like straightening up a messy room, aligning elements makes it easier for the viewer to navigate the design and find information. Also, a clean design, like a clean room, is more inviting.

To improve alignment, consider:

• Using left alignment with text in most cases. It’s how we read and usually works best. Only use right or center alignment with a small amount of text (like a title or subtitle).

• Using a grid. Many design and data viz tools have grid overlays. Some can snap your elements onto your grid.

Now let’s consider some examples.

In this dashboard, the charts, maps, titles, and text boxes are aligned both vertically and horizontally along a 4 x 3 grid. The result is a balanced and approachable look despite the multitude of charts and text elements.

Source: Dzifa Amexo on Tableau Public

This composition uses both left and right alignment to create a serene, symmetrical design. The designer emphasizes alignment by adding actual lines along some of the text elements.

Source: Dhruv Popat on Tableau Public

This diverging bar chart makes good use of center alignment, but the numbers at the top are not aligned with the text and chart below, giving it an off-kilter feel.

Source: Sanaz Jamloo on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules To Elevate Your Data Viz (Rule #8)

Design — including data viz design — is about both the elements that you include (text, images, charts, etc.) and about the space between them. Using this “white space” strategically is one of ten composition rules discussed in greater detail in this article from Canva. Read on for the 60-second version of this rule.

Composition Rules (#8) by Amelia Kohm

What Does “White Space” Mean?

“White space” is the space between and around elements in a design. Think of a single tree in an empty field versus a tree surrounded by other trees in a forest. If you want the viewer to focus on a particular tree (or chart, chart element, or title) clear the area around it.

How Can I Apply This Rule to Data Viz?

Too often we look for ways to pack more information into a dashboard or other type of data viz design. But when we do this, we lose the power of white space.

Use white space to draw attention to your focal points. Use white space to give the eye some breathing room. And, as long as I’m mixing metaphors, consider this: a busy, crowded design is a cacophony in which none of the individual components can be fully appreciated. So delete unnecessary elements or, if the viz is interactive, make additional information available on demand by scrolling or clicking a button.

Here’s an example of a dashboard that crowds information into one view, leaving little white space. As a result, it’s difficult to determine the focal points and, unless you are familiar with the data or highly motivated to extract meaning, you may give up on it quickly.

Source: Peter James Walker on Tableau Public

This dashboard, by contrast, uses plenty of white space to highlight focal points and not overwhelm the viewer.

Source: Sarah Burnett on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules To Elevate Your Data Viz (Rule #7)

“Rhythm is music’s pattern in time. Whatever other elements a given piece of music may have (e.g., patterns in pitch or timbre), rhythm is the one indispensable element of all music.” (Britannica.com). Repetition serves the same role in visual composition as rhythm does in music. And it’s one of ten composition rules discussed in greater detail in this article from Canva. Read on for the 60-second version of this rule.

Composition Rules (#7) by Amelia Kohm

What Does “Repeat Elements of Your Design” Mean?

Like rhythm in music, repetition brings unity to any design. It marries disparate elements. In a single composition, repeating typeface, color, shapes, or images can result in a balanced, coordinated look. In a series of compositions, repeating visual elements helps to tie them together, communicating that each is part of a larger whole.

How Can I Apply This Rule to Data Viz?

It’s a good idea to keep a record of the typefaces, type sizes, line weights, colors, etc. that you use in any data viz project ( (aka a “style guide”), and look for opportunities to repeat them. When designing a multi-page dashboard, using similar styes and layouts for each will help the user to find information quickly.

Let’s consider some examples of data viz that effectively use repetition.

Small multiples charts show the power of repetition. Zach Gemignani describes this approach well. “Small multiples use the same basic graphic or chart to display difference slices of a data set. Small multiples can show rich, multi-dimensional data without trying to cram all that information into a single, overly-complex chart.” Once you know how to read one of the side-by-side charts, you can quickly extract meaning from the whole array. The small multiples chart below allows us to rapidly discern that women directors have directed a small percentage of the most popular movies regardless of genre, with no clear improvement over time.

Source Max Tham on Tableau Public

This dashboard repeats the same charts and KPIs for each unit in a hospital. It allows administrators to rapidly assess the current need and distribution of resources, compare units, and adjust resources accordingly. Repetition of color, fonts, and header styles also helps to unify information about different units.

Source: Slalom NYC on Tableau Public

In this series of dashboards on crises in various African nations, Alexander Varlamo uses a strict style guide to unify them.

Source: Alexander Varlamov on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules To Elevate Your Data Viz (Rule #6)

Today I give you a composition rule which is often ignored in data viz — but at its peril. The rule is deploy contrast. It’s one of ten composition rules discussed in greater detail in this article from Canva. Read on for the 60-second version of this rule.

Composition Rules (#6) by Amelia Kohm

What Does “Boosting or Reducing Contrast” Mean?

Our brains are wired to perceive objects that differ significantly from their background. The objects that really pop out are those that contrast due to their color, size, orientation, or motion. So when designing charts, maps, and graphs, we should give some thought to contrast.

How Can I Apply This Rule to Data Viz?

Not only do we want our focal points to pop out, we also want some aspects of the composition, those lower in the hierarchy, to fade a bit by NOT contrasting as strongly with the background. By doing this, we not only help our main titles, captions, and data points to shine, we also provide more information for the interested viewer.

Let’s consider some examples of data viz that effectively use contrast.

Below is a series of visualizations related to the 2020 explosion in Beirut. It uses contrasting size and color to make some elements pop (the title, the KPIs, and the location of destruction and damage on the map) and other elements fade backward (the explanatory text and location of other ammonium nitrate disasters.)

Source: Soha Elghany on Tableau Public

Similarly these vizes, showing rat sightings in New York, effectively use shades of gray so that the viewer can easily pick out the locations where — and the years and months when — rats are most visible.

Source: Claire Kim on Tableau Public

In these vizes, red and white contrast with the black background. Red is used for key information about poverty. White is used for important contextual information. And gray is used for everything else.

Source: Ash Shih on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules To Elevate Your Data Viz (Rule #5)

Using complementing elements is one of ten composition rules discussed in greater detail in this article from Canva. And it applies as much to data viz as to any other type of composition. Read on for the 60-second version of this rule.

Composition Rules (#5) by Amelia Kohm

What Does “Use Complementing Elements” Mean?

Graphic design artists choose images that look good together. Data visualizers should do the same by making sure that charts, maps, and graphs which are presented together complement each other visually,

How Can I Apply This Rule to Data Viz?

• Use the same color palette in each chart. And remember that the meaning of a color should be the same in side-by-side charts. You should not use a dark blue to signify participants aged 20-40 in one chart and to signify those living in a particular zip code area in an adjacent chart.

• Use the same chart type for each chart. Part of the beauty of the small multiple chart is that the elements of the composition complement each other due to their similarity. Please see example below.

• Use consistent type in each chart. You wouldn’t use different fonts or font sizes in side-by-side charts, would you? Yes? Well, then this tip is for you.

• Use similar marks and channels in each chart. Data visualizations represent data using “marks” such as bars, lines, and circles. A mark represents data through “channels” which include its position, shape, size, or color. A larger circle, for example, can mean a greater number of something than a smaller circle. Charts that use similar marks and channels have similar looks and thus tend to complement each other visually.

Let’s look at some examples.

This dashboard repeats colors, charts, and marks and so, although a lot of different data is presented, the overall look is unified because the elements complement each other.

Source: Alex Dixon and Tarannum Ansari on Tableau Public

The repetition of chart types in small multiples charts, like this one, makes for a cohesive overall design.

Source: Christian Felix on Tableau Public

And here again, the designer repeats visual elements such as text boxes and chart types to bring the different aspects of the composition together.

Source: Chantilly Jaggernauth on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules To Elevate Your Data Viz (Rule #4)

Balancing out your elements is one of ten composition rules discussed in greater detail in this article from Canva. And it applies as much to data viz as to other types of composition. Read on for the 60-second version of this rule.

Composition Rules (#4) by Amelia Kohm

What Does “Balancing Elements” Mean?

Think of how you balance things on an old fashioned balance scale (pictured above). You can achieve balance by:

1) Placing the same elements on each side. This is called symmetrical balance.

2) Placing an assortment of elements which total to the same weight on each side. This is called asymmetrical balance.

What do we mean by weight when it comes to design? Well, more prominent (larger, darker, brighter) objects have more weight than less prominent ones.

How Can I Apply This Rule to Data Viz?

When designing a dashboard or any other type of composition that involves data viz, give some thought to where you place elements to balance them out.

The top part of this dashboard shows asymmetrical balance. The title and text on the left are balanced by the mini charts and KPI* on the right. The small multiples chart that comprises the rest of the dashboard is an example of symmetrical balance.

Source: Ivett Kovacs on Tableau Public.

This dashboard achieves asymmetrical balance by placing the title and text in the upper left corner and information about the City of Toronto in the lower right corner. The map, which crosses from the lower left to the upper right, is placed for symmetry as well. Each quadrant of the composition has similar weight.

Source: JR Copreros on Tableau Public

To see past data tips, including those about other composition rules, click HERE.

*KPI: Key Performance Indicator

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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.

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10 Rules To Elevate Your Data Viz (Rule #3)

Graphic artists think about hierarchy whenever they design anything. Analysts making charts and graphs often ignore hierarchy, but at their peril. This is one of ten composition rules discussed in greater detail in this article from Canva. Read on for the 60-second data viz version of this rule.

Composition Rules (#3) by Amelia Kohm

What Does “Hierarchy” Mean?

You create a hierarchy when you design elements (like text, images, and charts) according to their significance. Generally, the most significant elements are bigger and bolder, and the less significant ones are smaller and fainter. We’ve already talked about making your focal point big, bold, and centrally located. We’ve also talked about using leading lines to direct attention from the focal point to other elements in the composition. The visual hierarchy provides additional cues to help the viewer discern: 1) what are the key takeaways, and 2) what are the more minor details.

How Can I Apply This Rule to Data Viz?

Consider the most important elements of your data viz including titles, subtitles, labels, charts, and chart elements (such as particular lines on a line chart or particular dots on a scatterplot.) Then make your most important elements bigger or bolder. You might also add more white space around them or give them a contrasting color to the rest of the viz. Then make the less important elements smaller and/or fainter.

Below are two versions of a data dashboard by Swati Dave. The first image shows the dashboard with many of the hierarchy cues removed. The second image show’s Dave’s original dashboard which applies a visual hierarchy to help guide you through the viz. Which do you find easier to digest?

Dashboard With Few Hierarchy Cues

Dashboard With More Hierarchy Cues

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules to Elevate Your Data Viz (Rule #2)

Here’s another composition rule that artists know and that analysts can apply when presenting data: direct the eye with leading lines. This is one of ten rules discussed in greater detail in this article from Canva.

Embed 10 rules of composition by Amelia Kohm

What Does “Direct The Eye With Leading Lines” Mean?

The first thing you want your audience to see is the focal point. Leading lines are like signposts which tell the viewer where to go after the focal point. They can be lines, arrows, or other shapes which guide viewers’ eyes in a certain direction.

How Can I Apply This Rule to Data Viz?

Source: Data Viz for Nonprofits

Flowcharts, as I’ve written before, are engaging, easy to digest, and charmingly analog. And what makes them so user-friendly are the leading lines directing our attention from the focal point (in this case: “Do you plan to vote?”) to other elements of the chart.

Source: Christian Felix on Tableau Public

This chart on air quality uses leading lines to relate the bar chart at the top to locations on the world map below.

Source: Pradeep Kumar G on Tableau Public

Leading lines can be used to draw attention to particular data points. In this chart, leading lines are used to direct your focus to foods that have a particularly high and low carbon footprint.

To see past data tips, including those about other composition rules, click HERE.

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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.

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10 Rules to Elevate Your Data Viz (Rule #1)

Data visualization is like one of those unlikely couples. One partner is outgoing and a great storyteller. The other is introverted and sticks to the facts. To make great charts, maps, and graphs, you need to channel both partners in this odd couple: the artist and the analyst.

So over the next several weeks, I’m going to offer up key rules about composition that artists know and that analysts (and the rest of us) can apply when presenting data. I will focus on ten rules discussed in more detail in this article from Canva. This time it’s about finding your focus.

Composition Rules (#1) by Amelia Kohm

What Does “Find Your Focus” Mean?

Decide what you want your audience to focus on first. To choose a focal point, think about the main message you hope to communicate. You can direct attention to words or data points related to your focal point by placing them in the center of the composition, by coloring them so that they contrast with the background, or by using larger type than used elsewhere in the composition.

How Can I Apply This Rule to Data Viz?

Source: Richard Speigal on Tableau Public

This map uses contrasting color to direct your attention to the focal point: the location of lighthouses in England and Wales. The focal point is also the title, which is in much larger type than the rest of the text. Finally, the color chosen looks like radiating light, further emphasizing the focal point.

Source: Agata Ketterick on Tableau Public

This map also uses contrasting color to clarify the focal point: locations of extreme snowfall. And it uses color strategically: white=snow. These locations are placed in the center of the image and further emphasized by the bar chart.

Source: Zainab Ayodimeji on Tableau Public

This simple bar chart uses the title and contrasting colors to ensure that you don’t miss the focal point.

Stay tuned for more composition rules in coming weeks!

To see past data tips, click HERE.

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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.

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Data source: Pew Research Center, 2020

The data shown here are from the American Trends Panel Wave 59 survey conducted by Pew Research Center. The American Trends Panel is a nationally representative panel of randomly selected U.S. adults recruited from landline and cellphone random-digit-dial surveys. The survey dates are January 6-January 20, 2020. The chart includes data on respondents who identified themselves, in response to a survey question regarding ideology, as "Very Liberal," "Liberal," "Very Conservative," or "Conservative." Respondents who identified as "Moderate" or did not respond to the ideology question are not included in the data shown on the charts. For more information on the survey, click here..

Why You Should Know About Box Plots

Here’s yet another in a series of tips on different chart types. The idea is to fill up your toolbox for making sense of data. This week, I give you the box plot.

Active Ingredients (What is a box plot?)

Like a histogram, a box plot shows how spread out your data points are. The box plot below shows the affordability of housing in neighborhoods in ten cities. Each red circle represents a zip code area. The gray boxes show where 50 percent of the zip code areas fall on the affordability scale (larger numbers mean more affordable, smaller ones mean less affordable). And the median (or middle number) is where the dark gray meets the light gray.

Box plots also show a lot of other information (see image below). Some call this type of chart “a box and whisker plot” because the lines extending from the boxes are known as the “whiskers.”

Source: Flowing Data

Uses

A box plot provides a detailed snapshot of your data. No data points are hidden or obscured by summarizing numbers such as averaging them. For example, Houston and Chicago have the same average affordability score (.13) but we can see at a glance that although they are similarly affordable cities, Houston has a wider range of affordability. And, we can see that although New York is, in general, more affordable than Los Angeles, New York has some zip code areas that are much less affordable than the median seems to suggest. There are also some extreme outliers including the circle at -1.0 affordability which is New York City's 10013 zip code area (Soho and Tribeca).

Warnings

Not everyone (or every application) draws a box plot the same. For example, sometimes the whiskers extend to the minimum and maximum values and others place outliers beyond the lines. However most box plots include the median, upper quartile and lower quartile.

Fun Fact

Mary Eleanor Spear invented what she called a “range bar” in the 1950s. It would later be known as the box plot.

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

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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.

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Create A Map Dashboard To Show Your Organization's Reach

An interactive map is a great way to show donors, board members, prospective funders and other stakeholders whom you serve, including their age, location, income, and other characteristics. I’m doing a webinar on December 10, 2020 where I will teach you how to create an interactive map dashboard, like the one below, in less than an hour using Tableau Public, the free version of Tableau, a powerful data visualization tool. You can create a map dashboard with a simple Excel file, as long as it includes geographic data, such as zip codes. And you can embed the dashboard on your website, as I’ve done here. Play around with the dashboard below to explore the possibilities. And click HERE to register for the webinar.

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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.

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How Data Viz Can Save Your Thanksgiving

Well it looks like the gantt chart (tip #87) has become a Thanksgiving tradition here at Data Viz for Nonprofits. Thanksgiving involves many more dishes than you would normally serve in one meal. Even if you are cooking for just those in your household (and I hope you are), logistics are key. So I give you my color-coded gantt chart. I use it every year, and it works like a charm. I took all my recipe data and came up with this chart to make sure I had my timing right. Made it in good old Excel. Nothing fancy, but it did the trick. Feel free to adapt it to your recipes or perhaps your next fundraising event!

Happy Turkey/Tofurky Day.

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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.

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How To Show The Real People Behind The Data

Data visualizations can provide something that photos and case studies—for all of their visceral appeal—cannot. Context. Charts, maps, and graphs give us the critical context that we cannot see in a photo or in a story about one person, such as how prevalent a problem is, where it is occurring, or the impact of a program over time.

Data visualizations, of course, also have a downside. A chart, map, or graph is an abstraction that aggregates the stories of many individuals. And, as Joshua Smith points out: “It’s really hard to tell a powerful story in aggregate when all of the humans and all of their lives and moments and emotions are plotted under a single data point, often represented through a behavioral variable, e.g. “sales”, or “likes”. In aggregate, we lose all the parts and pieces that make characters relatable and memorable.”

So can we have the best of both worlds? Can we put photos and other information about real people into data visualizations? Yes! Consider one of these strategies.

Follow Individuals Through The Data

The idea is to explain an issue, a problem, or a situation through the stories of select individuals. Ludovic Tavernier explains the the situation of Somali refugees through the stories of two Somali women. Ayaan and Shamshi, in a series of visualizations entitled Two Years Late. Tavernier labels particular data points to show where Ayaan and Shamshi fit into the larger picture.

Source: Ludovic Tavernier (on Tablea Public)

Dot = Person

Another approach is to make each mark (e.g. dot, square, bar) represent an actual person and allow the viewer to scroll over marks to learn more about these individuals. This is Eve Thomas’ strategy in Stop and Search which shows the disproportionate rate at which Black people are stopped and searched in London.

Source: Eve Thomas (on Tableau Public)

Here’s another example from JR Copreros in which each dot represents a real person who was convicted of a crime and later exonerated.

Source: JR Copreros (on Tableau Public)

Show Both The Forest and The Trees

Perhaps the simplest strategy is to include both aggregated data (the forest) and disaggregated data (the trees) in the same visualization. The chart below shows the number of absences for both individual students and the average number of absences across all students.

Filter Charts By Individuals

Another way to zoom in on particular trees is to include a filter that allows you to show results for just one person. This visualization by David Borczuk allows you to choose just one woman in Madagascar who suffered from obstetric fistula, a medical condition in which a hole develops in the birth canal as a result of childbirth.

Source: David Borczuk (on Tableau Public)

On the lighter side, you can click on any character in Glee to learn more about that character in various charts in this data dashboard by Jennifer Dawes.

To see past data tips, click HERE.

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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.

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What You Should Know About Word Clouds

This tip is a warning. In other tips, I have encouraged you to use a particular type of chart for specific purposes. But in this tip, I’ll suggest that you NEVER use this chart under ANY circumstance. I’m not alone is my aversion to word clouds. Plenty of others, including Jacob Harris, a senior software architect at The New York Times, have articulated their distaste. This tip is basically the 60-second version of Harris’ 2011 article on the topic.

Active Ingredients (What is a word cloud?)

A word cloud shows how many times various words in a document are used. More common words are larger. Less common ones are smaller. The varying sized words are arranged “into some vaguely artistic arrangement,” as Harris puts it.

Uses

There are no good uses of the word cloud. As its name suggests, it clouds meaning rather than clarifies it. I created the word cloud above using one of the many online word cloud generators. It shows the frequency of various words in “Goldilocks and the Three Bears.” Does it provide any insight into the story for you?

Sometimes organizations create word clouds not to convey insight but because they want a graphic on a topic and can’t think of what else to use. But photos or illustrations of almost anything are almost always going to be more engaging than a bunch of words floating around in a cloud.

Warnings

The number of times a word is used tells us nothing about the meaning of the text. Different words can have the same meaning and, conversely, the same word can have different meanings in different contexts. To get to meaning, you need to look at the frequency of concepts or themes, not words.

Word clouds aren’t the best tool even when the point is to analyze word usage. Check out the series of simple bar charts below. They provide more insight than any word cloud could because they allow us to easily discern the most/least popular words.

Source: NOW1051

(Sort of) Fun Fact

The word cloud technique originated online in the 1990s when they were called “tag clouds” and were use to show the popularity of keywords in bookmarks.

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

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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.

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Seeing Red, Blue, and Purple - What We Can Learn From Election Maps

A wide range of election maps are in your immediate future. What you learn from those maps depends, in part, on how they are designed. Indeed, election maps and other types of maps can change our attitudes toward issues. In this 15-second tip, I recommend that you invest an additional couple of minutes watching The New York Times’ excellent slide show on how election maps can fool you. It will help you to be both a better consumer and designer of maps.

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

Why You Should Know About Stacked Area Graphs

Another week, another useful chart to consider. This week, I give you the stacked area graph.

Active Ingredients (What is a stacked area graph?)

The stacked area graph is a variation of the area graph, which is simply a line graph with the area below the line filled in with color. In a stacked area chart, there’s more than one variable, so more than one line and shaded area. Additionally, these areas are stacked, one on top of the other.

Uses

Use this type of graph to compare the proportion of data units (people, groups, places, things, etc.) in different categories over time. This example from the Urban Institute does a great job of showing the relatively long sentences of those convicted of violent crime compared to the sentences of those convicted of other offenses. When this cohort of inmates entered prison in 2000, those convicted of violent crimes made up just 30 percent of the entire group. But 14 years later, they represented more than 80 percent of those still incarcerated.

2000 Entry Cohort by Offense Type

Source: The Urban Institute

Warnings

It can be difficult to discern exactly how many (or what percent of) data units each band of color represents. The lowest band is clear. But you have to do some math to determine the other bands. For example, in the chart above, I have to subtract 30 percent from about 58 percent to determine the percent of inmates in 2000 convicted of property crimes (the yellow band). The line graph below does a better job of showing what percent of the overall cohort each offense group represented over time. So only use a stacked area graph when you want viewers to focus mainly on the proportion of data units in each group over time.

Fun Fact

A cool variant of the stacked area graph is the streamgraph in which the bands are placed around a central axis rather than stacked on top of an axis. The New York Times’s streamgraph on movie box office revenues helped to make streamgraphs popular.

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

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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.

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Why You Should Know About Venn Diagrams

This week, I give you yet another useful-if-done-right chart, the Venn diagram.

Active Ingredients (What is a Venn Diagram?)

ICYMI, a Venn diagram shows overlapping categories or sets usually represented by circles.

Uses

These diagrams are great for showing the degree to which categories or sets overlap and what elements fall inside/outside of each set and each overlapping portion. The take home message is usually the shaded area where all of the circles intersect. So make that area easy to locate using color and labels. This example shows how an organization bridges the gap among three different types of organizations working on foreign policy.

Source: Network 20/20

Warnings

For me, Venn-diagram-fatigue sets in early. I get tired of discerning the meaning of each overlapping area pretty quickly. So I’d suggest limiting the number of circles. And, more importantly, clearly labeling the sets.

Here’s one that I gave up on after about 15 seconds:

Source: @DanNeidle

On the other hand, this Venn diagram works even with four sets because the sets (orphaned, wealthy, sidekick, and masked) are clearly marked and the intersection labels are simple.

Source: gliffy.com

Fun Fact

English mathematician John Venn is credited with inventing the Venn diagram in the 1860s, and, according to Phil Plait, there are two kinds of people in the world . . .

Source: DiscoverMagazine.com

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

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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.

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Why You Should Know About Parallel Coordinates Plots

Here is another tip in a series of tips on different chart types. The idea is to fill up your toolbox with an array of charts good for making sense of data. This week, I give you the parallel coordinates plot.

Active Ingredients (What is a parallel coordinates plot?)

Parallel coordinates plots look kind of like the electrical poles and wires along the highway. They are a series of axes (that’s the pole part) connected by various lines (that’s the wire part). Each axis represents a variable that you can measure numerically. Each line represents an individual unit, group, or category. For example, each line might be program that your organization offers. And one axis might be enrollment, another axis drop out rate, and another average rating on participant surveys. You can compare programs by seeing where each line hits each axis.

Uses

Parallel coordinate plots are great when you have a lot of measures and want to compare a bunch of individual units, groups, or categories on those measures. In the example below, each axis represents a different chronic illness and each line represents a state in the U.S. So we can see that the percent of adults with kidney disease is much lower than the percent of adults with arthritis across states. But we can also see where there is variation among states. For example, Oregon has a much larger percent of adults with depression than does Hawaii. The line for Hawaii is highlighted to allow the viewer to compare Hawaii to other states on various chronic illnesses. Note that in this example, each axis uses the same scale (percent of adults) but in some parallel coordinate plots, each axis has a different scale depending on the unit of measure appropriate for each variable.

Warnings

The order of the axes will affect how the data is perceived. In the example, I ordered the axes from diseases with relatively low prevalence to those with relatively high prevalence to allow the viewer to easily distinguish diseases in this way.

Parallel coordinate plots can get cluttered fast. You can avoid this by limiting the number of lines or axes or by greying out most of them and highlighting just one or two as in the example above.

Fun Fact

Parallel coordinates plots go way back, to at least the 1880s when Henry Gannett and Fletcher Hewes published one in the Statistical Atlas of the United States. Check out their parallel coordinates plot which shows the ranks of states on a wide range of issues in 1880 including populations density (DC ranked number 1), per capita wealth (California ranked number 1), and literacy rate (Wyoming ranked number 1).

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

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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.

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Why You Should Know About Dot Matrix Charts

I’d like to introduce you to yet another chart type. The idea is to fill up your toolbox for making sense of data. This week, I give you the dot matrix chart.

Active Ingredients (What is a dot matrix chart?)

Dot matrix charts show us data units as dots (or squares). A single data unit could be a person, a group of people, a building, a program, or any other thing that you are counting. Each dot is colored to show which category or group the data unit falls into.

Uses

Dot matrix charts are simple yet mighty. They give a quick overview of the relative size of different categories and how the parts relate to the whole. I was reminded of the power of dot matrices recently when reading about the COVID-19 School Response Dashboard in an article on the National Public Radio (NPR) website. The dashboard shows data drawn from reports from K-12 schools on their confirmed and suspected coronavirus cases, along with the safety strategies they're using.

If you check out the dashboard, you see these charts showing the percent of schools reporting cases among students and staff. Take a look at the Y-axis. It ranges from 0% to 1%. This allows you to see small differences between the charts on the left (confirmed and suspected cases) and the charts on the right (only confirmed cases). But it has a big disadvantage. It doesn’t give you a visual sense of just how few students and staff have, or may have, been infected based on data that schools have. (Note: A big unknown is the number of asymptomatic/untested students or staff. Rates might be higher if more students and staff were tested.)

Source: COVID-19 School Response Dashboard

NPR recast this same data in a dot matrix chart (below) with each square representing 50 people.* And the first thing you comprehend is that the vast majority of staff and students at the reporting schools have not been infected (again according to information that schools have). Without much more effort, you see that there are more suspected than confirmed cases. No need to inspect the Y-axis or subtract percent of confirmed cases from the percent of confirmed and suspected cases.

Source: National Public Radio

Warnings

All those dots or squares require a good bit of page or screen real estate. Sure, one circle or square can represent more than one person or other data unit. But at some point, a bar chart might make more sense. Dot matrix charts work best when there are just a few categories and the aim is to communicate one or two simple messages.

Fun Fact

Dots or squares need not be displayed in rectangular form. This Policy Viz chart arrays the dots in a semi-circle to show the distribution of U.S. House members in different political parties. Gray dots represent empty seats. You can learn how to create a chart like this one using Excel HERE.

Source: PolicyViz

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

*Note that the percentages displayed on the dashboard do not exactly match the numbers in the NPR dot matrix chart because the dashboard shows real-time data, and NPR used data from the dashboard on an earlier date than 9/24/20, the date when I took the image of the dashboard.

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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.

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