Sep 232015
 

Overview

I recently wrote about emotional vs. accurate comparisons and several people questioned whether the word “emotional” was appropriate.  (Several people questioned my assertions, too.  You can read their comments here.)

For this discussion I’ll use the term “engagement” in place of “emotion” and we’ll look into the challenges of creating public-facing visualizations that attract and engage, are clear and accurate, and do these things without “dumbing down” the subject matter.

Time Magazine and a cumbersome infographic

Stephen Few recently wrote a great post about the following infographic that appeared in Time Magazine in August, 2015.

Figure 1 -- Time Magazine's "Why we still need women's equality day" infographic. See http://time.com/4010645/womens-equality-day/.

Figure 1 — Time Magazine’s “Why we still need women’s equality day” infographic. See http://time.com/4010645/womens-equality-day/.

I have three major problems with this treatment.

  1. This is an important subject but the cutesy approach trivializes it.
  2. With so many chart types I have to work very hard to make comparisons among the different areas (Federal, Congressional, etc.). In addition, the chart is very long and requires a lot of scrolling.
  3. I strongly suspect that most people thought this was a dashboard having to do with Republicans and Democrats. I know that for me, whenever I see red and blue in a political context I think Republicans and Democrats and I had to fight this expectation to see that this was about men and women.

Stephen Few’s redesign

Here is Few’s redesign.

Figure 2 – Stephen Few’s clear and compact redesign.

Figure 2 – Stephen Few’s clear and compact redesign.

The collection of stacked bars makes it very simple to compare across the various categories and treats an important subject with the seriousness that is warranted.

But…

Few’s treatment is rather clinical and may be a little too dry for Time Magazine.

So, is there a way to fashion a graphic that is clear and accurate, like Few’s, but does more to draw the reader in?

Alberto Cairo’s redesign

Stephen Few asked Alberto Cairo to have a look at the source graphic and Cairo was able to turn out the following in a matter of minutes.

Figure 3 -- Cairo's redesign of Few's redesign.

Figure 3 — Cairo’s redesign of Few’s redesign.

Here are Stephen Few’s comments upon seeing the redesign:

“Alberto,

You’re the man! I love your improvements to the graphic.

You described your version as middle ground between my position and that of the embellishers, but I don’t see it that way. I’m an advocate of the kinds of embellishments that you added to the graphic for journalistic purposes, for they don’t detract from the information in any way. I’ve always said that journalistic infographics can be both informative and beautiful without compromising either. Doing this takes skill, however, that relatively few of the folks producing infographics possess. It also takes graphic design skill that I don’t possess, which is why I don’t design journalistic infographics. You’ve illustrated what it takes to do this well. As I said, you’re the man.”

I think Cairo would be the first to agree that there are many shortcomings to his rendering (e.g., colors, the guy on right looks like he’s holding a boomerang and not reading a book, etc.) but remember, Cairo put this together in a few minutes simply to show that it is in fact possible to create something that is beautiful and emotionally engaging without sacrificing one pixel of analytic integrity.

 

Sep 212015
 

Overview

I’ve conducted a lot of Tableau training classes and have found three things that confuse students simply because of the nomenclature Tableau uses for these things.  These three terms are

  • Headers
  • Table Calculations
  • Quick Filters

Headers

Consider the chart below that has both mark labels and an axis along the bottom.

Figure 1 -- Bar chart with visible axis.

Figure 1 — Bar chart with visible axis.

Because each bar has a label we don’t need to see the axis.  We can hide the axis by right-clicking it and selecting…

Figure 2 -- Turning off the header turns off the... footer.

Figure 2 — Turning off the header turns off the… footer.

… Show Header.

Yes, indicating that we don’t want to display a header will make Tableau hide…

the footer!

As I explain to students, in Tableau anything that surrounds a chart is called a Header.  If it’s along the top of a chart, it’s a Header.  Left side of the chart?  Header?  Bottom?  Header.  Right side?

Header.

Table Calculations

I know the first time I saw this I thought “Table Calculations” pertained to a visualization that used text tables. As I explain to students, I think of table calculations as Tableau having the ability to do math in its head.

Consider the example below where we show the raw vote count for each candidate from the 2012 US presidential election.

Bar chart based on query to the back-end database

Figure 3 — Bar chart based on query to the source database

Here, Tableau has queried the underlying database and is displaying the results based on that query.

With a table calculation, Tableau looks at the results that are already on display, as it were, and then does some additional internal calculations.  In the case of asking Tableau to show the percent of total, Tableau adds up the total for all three candidates and then divides the tally for each candidate by that total.

As I said, I find it helpful to think of Tableau Calculations as Tableau doing math in its head.

Quick Filters

To filter results in Tableau, you drag dimensions and measures from the Data window to the Filters card and then apply the settings you want for the various filters.

If you want easier access to the filter settings you can right-click a filter and select Show Quick Filter.

The problem with this term is that people new to Tableau think this pertains to speeding up the filter when it in fact means that you just want the filter control to be visible on a worksheet or a dashboard.  It has nothing to do with making filters quick.  In fact, having lots of quick filters on a worksheet can slow Tableau down because Tableau has to calculate what selections should appear in each of the quick filters.

The only rationale I can see for the name is that it allows you to access the settings quickly rather than having to go through the Filters dialog box.  Still, it’s quite confusing for those first learning Tableau.

Summary of confusing terms

Here’s a summary of the terms that often confuse people new to Tableau.

Term What students think it means What it actually means
Header Something at the top of a chart Anything that surrounds a chart
Table Calculation Something having to do with text tables / cross tabs The ability for Tableau to do math “in its head”
Quick Filters Some setting that makes filters work faster Make the filter control visible

What should we call these things and should Tableau rename them?

Given just how entrenched Tableau is it may be too late to change these terms, but if it’s not too late…

In the case of Show Quick Filters I would change it to Show Filter Control.

What about Table Calculations and Headers?  Got any ideas?

 

Sep 152015
 

Overview

Figure 1 – Bar charts are better than pie charts are better than donut charts.  Most of the time.

Figure 1 – Bar charts are better than pie charts are better than donut charts.  Most of the time.

As anyone who has read this blog knows I’m definitely a “bar charts are better than pie charts are better than donut charts” kind of guy, at least when you need to make an accurate comparison.

But in my classes, as I rearticulate the case against pies and donuts, I find myself wondering if there are in fact times when a pie chart might be a better choice.

Most of my data visualization work is for internal purposes so I focus on making it easy for people to make an accurate comparison.

But as my clients and I make occasional forays into public-facing visualizations I think about how to make it easy for people to make an emotional comparison.  By this I mean that I want people viewing the visualization to just “get it”.

Better yet, I want people to get it, be engaged by it, and in some cases, “feel” it.

With this in mind, in this post we’ll explore cases where

  • a pie chart is in fact as good, if not better, than a bar chart.
  • circles and spheres do a better job conveying magnitude than do bars.
  • a waffle chart produces an emotional wallop without compromising analytic integrity.

Where a pie chart trumps a bar chart

So, it’s the year 2034 and in this somewhat dystopian future there’s a movement afoot to add an amendment to the US constitution banning the use of pie charts.

Those of you familiar with the United States Constitution know that three-quarters of the states need to approve an amendment for said amendment to become law.  In 2034 it turns out the 39 of 50 states will in fact ratify the amendment.

Does that get us the needed 75%?  Here’s a simple, compact chart that lets us know immediately.

Figure 2 -- The amendment banning pie charts passes as I can see that the "Yes" votes fill more than three quarters of the circle.

Figure 2 — The amendment banning pie charts passes as I can see that the “Yes” votes fill more than three quarters of the circle.

It’s so easy to see that the “Yes” votes fill more than three-quarters of the pie that I don’t need labels indicating the large slice is 78% and small slice is 22%.

Compare this with a bar chart.

Figure 3 -- Did the "Yes" exceed 75%?  Without labels it's very hard to tell.

Figure 3 — Did the “Yes” exceed 75%?  Without labels it’s very hard to tell.

Without labels showing the percentages I cannot tell for sure if the “Yes” bar is more than three times larger than the “No” bar.

Okay, Okay, Okay!  I know that a simplified bullet chart would work, too.

Figure 4 -- A bullet chart shows that we've exceeded the goal.

Figure 4 — A bullet chart shows that we’ve exceeded the goal.

Yes, the bullet chart makes it clear that I’ve exceeded my goal but I need to know that the goal was 75%.  I don’t need the goal line with the pie chart.

So, does this mean that it’s okay to use pie charts instead of bar charts?

No.  Based on this example it’s only okay to use a pie chart (singular).  In addition, your pie chart (singular) needs to meet the following conditions:

  • One of the slices has to make up at least 50% of the pie.
  • If you’re pie has more than two slices you don’t ask people to compare the smaller slices.

Where circles and sphere’s do better than bars

As we all know Jupiter is big, really big.

Just how much bigger is it than Earth?

Should I create a bar chart to show this? If I were to create one should I compare the radius or the surface area of each planet?

Or should I really go nuts and compare the volume of the planets?

I don’t think the dashboard shown above is nearly as effective as the visualization shown below.

Figure 5  -- "Size planets comparison" by Lsmpascal - Own work. Licensed under CC BY-SA 3.0 via Commons - https://commons.wikimedia.org/wiki/File:Size_planets_comparison.jpg#/media/File:Size_planets_comparison.jpg

Figure 5  — “Size planets comparison” by Lsmpascal – Own work. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:Size_planets_comparison.jpg#/media/File:Size_planets_comparison.jpg

Jupiter and Saturn – and even Neptune and Uranus – really dwarf earth and the other planets and with this visualization I feel it.

Even the simple chart comparing the area of the cross section of the planets gives me a better feel for the data than does the bar chart.

Figure 6 -- Circles comparing cross-section area of the planets.  Yup, I can tell that Jupiter is way bigger than Earth.

Figure 6 — Circles comparing cross-section area of the planets.  Yup, I can tell that Jupiter is way bigger than Earth.

Is it essential that I can tell exactly how much larger one planet is than another?  I don’t think it is and I much prefer the emotional pull of the circles and the spheres.

A Fun Tangent

One thing that’s very hard to express in a static chart is how much space there is between the sun and the planets.  To get a sense of just how incredibly vast the distances are check out this fascinating, albeit somewhat tedious, interactive visualization from Josh Worth.

Getting an emotional wallop with waffles

A few weeks ago Cole Nussbaumer posted a tweet asking people what they thought of this chart from The Economist:

Figure 7 – A waffle chart from the article "Teens in Syria".  See http://www.economist.com/blogs/graphicdetail/2015/08/daily-chart-6?fsrc=rss.

Figure 7 – A waffle chart from the article “Teens in Syria”.  See http://www.economist.com/blogs/graphicdetail/2015/08/daily-chart-6?fsrc=rss.

The first thing that surprises me about this is that The Economist went with a waffle chart and not a bar chart, like the one below.

Figure 8 -- The type of chart I would have expected to see in The Economist.

Figure 8 — The type of chart I would have expected to see in The Economist.

The second thing that surprised me was that I preferred the waffle chart.  Yes, as Jeffrey Shaffer correctly points out, the dots are so tightly packed that you literally see stars between the circles, but  this can easily be remedied.  The question on my mind is why do I prefer waffles?

My answer is that the having each dot represent one of the 120 people surveyed connected with me in a way that the bar chart did not. Combined with the percentage labels (which are critical to the success of the visualization) the waffle chart hit me hard and it did so without dumbing down the importance of the discussion one bit.

So, are bars charts always boring?

No!  In my next blog post I’ll show you an example of a bar chart embedded inside a “come hither” graphic that

  • attracts and engages
  • does not trivialize an important issue
  • represents the data clearly and accurately

Stay tuned.

Sep 012015
 

Overview

I’ll admit that I have a problem with treemaps in Tableau, but it’s not because the chart type is in some way inferior. My problem is with how people use – and misuse – treemaps.

Here’s a good example of misuse.  Instead of displaying something straightforward that looks like this…

Figure 1 -- The humble, but accurate bar chart

Figure 1 — The humble, but accurate bar chart

… some people feel compelled to add “visual variety” to their dashboards and instead create something that looks like this.

Figure 2 -- Look , Ma! I made a Mondrian!

Figure 2 — Look , Ma! I made a Mondrian!

Except for the “it looks cool” factor there’s no good reason to use a treemap in this situation.

So, when should you use a treemap?

What’s in a treemap and why it can be useful

With a treemap you have two attributes at your disposal:

  1. The size (area) of rectangles, and
  2. The color of the rectangles

A treemap consists of packed rectangles where the area of a rectangle corresponds to the size of a particular measure.  In the example above the size of the rectangle is based on the number of people that come from a particular region.  North America has the largest value so it’s represented with the largest rectangle. Europe has a smaller value to its rectangle is proportionally smaller.

Treemaps really come in handy is when you have A LOT of marks to plot and you need to show all of the marks in a compact area.

So, this sounds like a great chart – we’ve got rectangles to show how big and small stuff is, color to group related rectangles intelligently, and we can fit a lot of stuff in small space.  Why not use this chart all the time?

The downside is that we are comparing the area of rectangles and with rectangles it is difficult to make an accurate comparison. People may be very good at comparing the length of bars but as a species we are not particularly good at comparing the area of rectangles (and we’re downright awful at comparing the area of circles.)

So, given the advantages and shortcomings, just when should you use it?  Let’s look at a particular scenario.

Showing Presidential Electoral Results

A Filled Map

Consider the electoral map below showing electoral votes by state for Barack Obama and Mitt Romney in 2012.

Electoral Map Filled

Figure 3 — Filled map showing electoral votes for the 2012 presidential election (displaying 48 out of 50 states)

Our Electoral College system is fairly confusing and I can only imagine how somebody from outside the US would look at this as there appears to be more red on the map than blue… but the blue guy won!

This discrepancy becomes even more pronounced when we include Alaska and Hawaii in the map.

Figure 4 -- Filled map showing electoral vote winners for the 2012 presidential election (displaying 50 states)

Figure 4 — Filled map showing electoral vote winners for the 2012 presidential election (displaying 50 states)

Clearly, a map designed to show how much area there is in a state fails with Electoral College results where the numbers are based on population not land mass.  In the example above there’s A LOT more red then blue, but again, the blue guy won the election.

Perhaps a different type of chart will do a better job?

Symbol Map

Here’s a symbol map of the same data.

Figure 5 -- Symbol map showing electoral vote winners for the 2012 presidential election (displaying 48 out of 50 states)

Figure 5 — Symbol map showing electoral vote winners for the 2012 presidential election (displaying 48 out of 50 states)

I think this is more accurate as there’s clearly more blue than red, but it’s still a tough read.  What else might work?

Cartogram

Here’s a cartogram from Professor Mark Newman of the University of Michigan showing the same data, except the polygons for each state has been adjusted to reflect the population of the state.

Figure 6 -- Cartogram showing election results where the shape of the state is based on its population and not land mass.

Figure 6 — Cartogram showing election results where the shape of the state is based on its population and not land mass.

While it’s very clear that there is more blue than red on this map there are two problems with this approach:

  1. There aren’t many tools that will support this type of distortion; and,
  2. This map will frighten small children.

Summary Bar Chart

Why not just display a simple bar chart showing the total number of electoral votes, like the one shown here?

Figure 7 -- Electoral vote count by candidate

Figure 7 — Electoral vote count by candidate

This is certainly very clear and we can see easily by how much Obama won, but we’re missing an important part of the story.

In US presidential elections a winner is chosen by tallying the electoral votes from each state and the summary bar chart doesn’t show us how each state contributes to the total for each candidate.

And the Winner is… ? The Treemap!

Here’s a treemap showing the exact same data.

Figure 8 -- Treemap showing 2012 electoral vote results

Figure 8 — Treemap showing 2012 electoral vote results

Of all the single visualizations I think this treemap tells the most complete story.  We can see just how much states like California, Texas, Florida, and New York contribute to the total as well as gauge —  to some degree  — just how many more electoral votes Obama received than did Romney.

One shortcoming, however, is that we can’t see the names of all the states as some of the rectangles are too small.

One way to address this is by adding a tool tip, as shown here.

Figure 9 -- Hovering over a mark allows me to see the name of the state and number of electoral votes.

Figure 9 — Hovering over a mark allows me to see the name of the state and number of electoral votes.

While this works, a problem we should address is that the small states are not easily searchable.  That is, if I want to know the results for Alaska, Hawaii, Delaware, etc., I have to go hunting for them.

At this point we’ve gotten about as far as we can get with a single chart.  To tell the complete story – and to make it easy for people to find results for a particular state – we should create a dashboard.

The Electoral Vote Dashboard

Here’s a dashboard that puts two of the views together and that allows the user to find a particular state’s rectangle by selecting the state from a list.

Figure 10 -- Electoral votes dashboard.  Selecting a state from the list will display that state’s rectangle in the treemap.

Figure 10 — Electoral votes dashboard.  Selecting a state from the list will display that state’s rectangle in the treemap.

While the “star” of the dashboard is the treemap, the summary bar chart and the selectable list make the story complete and we get a solid understanding of the 2012 Electoral College results.

And we achieved this without using an actual map.

Click here to interact with dashboard.