On this week’s episode of the podcast, I speak to author and teacher Nick Desbarats about his new book, Practical Charts: The Essential Guide to Creating Clear, Compelling Charts for Reports and Presentations.  Our conversation covers choosing appropriate chart types, emphasizing simplicity and clarity, and understanding when to use different formats. Nick aims to challenge dogmatic views on charts, such as the use of pie charts, and stresses the importance of catering to the audience’s familiarity with graph types. Our chat also includes insights on transitioning to online teaching during the pandemic, the distinction between clear graphs and dashboards, and the significance of mastering fundamentals in data visualization for beginners and intermediates. If you’re familiar with Stephen Few’s work, you’re also bound to find some behind-the-scenes gems in this week’s episode.

Topics Discussed

  • Choosing the Right Chart. Nick kicks off our conversation with an essential primer on selecting the appropriate chart types for different datasets. His focus is on simplicity and clarity, ensuring that the chosen chart communicates the intended message as effectively as possible.
  • Challenging Chart Dogmas. Prepare to have your preconceptions challenged as Nick takes on the controversial stance on pie charts and other commonly debated graph types. It’s all about breaking the mold and understanding why certain charts work better for specific audiences.
  • Catering to Audience Familiarity. A significant portion of our chat is dedicated to the importance of tailoring chart choices to the audience’s level of comfort and familiarity with different types of graphs. This segment is crucial for anyone looking to maximize the impact of their data presentations.
  • Clear Graphs vs. Dashboards. Nick and I talk about the distinction between creating individual clear graphs and designing comprehensive dashboards. Nick sheds light on how these two formats serve different purposes and require distinct approaches.
  • Fundamentals for Beginners and Intermediates. Whether you’re just starting out or looking to refine your skills, Nick emphasizes the importance of mastering the fundamentals of data visualization. This advice is gold for anyone aiming to elevate their chart-creating capabilities.


Guest Bio

As an independent educator and best-selling author, Nick Desbarats has taught data visualization and information dashboard design to thousands of professionals in over a dozen countries at organizations such as NASA, Bloomberg, Visa, The United Nations, Shopify, The Internal Revenue Service, and The Central Bank of Tanzania.

Nick is the author of the Amazon #1 New Release “Practical Charts” (2023) and the upcoming “Practical Dashboards” (2024) books, and he regularly contributes articles to The Journal of the Data Visualization Society (Nightingale) that are among that publication’s most widely read and shared. He also regularly delivers main-stage talks at conferences such as Tableau Conference, TDWI World Conference, SAS Explorers, Data Innovation Summit, and others, and has lectured at Yale University, The University of Toronto, and The Victoria University of Wellington (New Zealand).

Nick was the first and only educator to be authorized by Stephen Few to deliver his foundational data visualization and dashboard design workshops, which he taught from 2014 until launching his own workshops in 2019. Prior to that, he held senior executive positions at several software companies and was a cofounder of BitFlash Inc., which raised over $20M in venture financing and was sold to OpenText Corporation. In 2012, Nick was granted a United States patent in the decision-support field.

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00:12 – 00:14

Welcome back to the PolicyViz Podcast.

00:14 – 00:17

I’m your host, Jon Schwabish. Happy spring, everybody!

00:17 – 00:19

I hope you are well.

00:19 – 00:21

I hope your allergies aren’t too bad.

00:21 – 00:24

Here in Northern Virginia, we’ve got what we call the great pollinating.

00:25 – 00:31

It’s this green sort of dusty pollen over everything, which is, making our eyes water and our noses itch.

00:31 – 00:35

But we power on making our way towards summer.

00:35 – 00:41

On this week’s episode of the show, I welcome Nick Desbarats, author of the new book Practical Charts,

00:41 – 00:45

the essential guide to creating clear compelling charts for reports and presentations.

00:46 – 00:50

Now if you are new to the field of data visualization, this is gonna be a great episode for

00:50 – 00:56

you because you’re gonna learn some of the key features of creating better charts and graphs

00:56 – 00:59

from Nick’s work and from his book, Practical Charts.

00:59 – 01:05

He’s gonna talk about ways in which to choose your different chart types and how there is or

01:05 – 01:10

may not be rules, guidelines, strategies for creating better charts in your work.

01:11 – 01:15

If you are a more experienced data visualization creator or have been in the field for a while,

01:15 – 01:20

you’re gonna like this episode because Nick used to work with Steven Few.

01:20 – 01:26

Now if you don’t know that name Steven Few, Steven was one of what we might consider sort of

01:26 – 01:31

the one of the modern big people in the field of data visualization.

01:31 – 01:36

Wrote a great book, show me the numbers, and, had a blog and and some other great work. He has since retired.

01:37 – 01:42

But he worked with Nick on Nick’s teaching and instruction.

01:42 – 01:47

So you’re gonna get a little bit of behind the scenes action on how Nick worked with Steve and

01:47 – 01:52

developed his course, developed his instruction, and ultimately wrote this book to go along with that.

01:53 – 01:58

So in this episode, you’re gonna hear about how Nick approaches data visualization, the thinking

01:58 – 02:03

behind choosing different chart types when some are more or less appropriate.

02:03 – 02:08

We’re also gonna talk about the distinction between making graphs simple versus making graphs clear.

02:08 – 02:14

And we also finish up the episode talking a little bit about the distinctions between dashboards and more static graphs.

02:15 – 02:21

Now before I put you off onto this episode of the show and the interview, just a quick request.

02:21 – 02:26

If you could take a moment out of your day to rate or review this podcast on your favorite podcast

02:26 – 02:28

provider, I’d really appreciate it.

02:29 – 02:35

Those ratings, those reviews go a long way towards attracting more guests to join me on the

02:35 – 02:40

show so that we can help more people be better and more effective data communicators.

02:40 – 02:46

So just click on over to Itunes, Spotify, wherever you get your podcasts. Click those 5 stars.

02:47 – 02:48

Write a quick little review.

02:48 – 02:51

Won’t take you very long. I’d really appreciate it.

02:51 – 02:55

It helps the show be that much better and reach that many more people.

02:55 – 03:07

So Jon my discussion of practical charts with author and instructor and teacher, Nick Desbarats. Hey, Nick. Great to meet you. Very excited.

03:07 – 03:07


03:08 – 03:14

Welcome to the show. It I feel like we’ve been running like parallel circles for, like, a decade, maybe.

03:14 – 03:17

Probably. Probably something like that. Yeah. Yeah.

03:17 – 03:21

Long, long overdue, introduction Jon conversation. Looking forward to that. Maybe we

03:21 – 03:26

just maybe I just aged the both of us a little a little too much too early. Yeah. It’s

03:26 – 03:28

true. I’ve only been on the Internet for a year.

03:28 – 03:29

Right. Yeah. You’re right. Right.

03:29 – 03:32

I just found out about this old data thing. Yeah. Right.

03:33 – 03:37

So you have, you have this new book out, Practical Charts. Got it right here.

03:37 – 03:42

Oh, you’ve got it behind you too, which is a good CNN CNN, MSNBC move. Yeah.

03:42 – 03:44

So practical charts and then more practical charts.

03:45 – 03:50

Excited to chat with you about the book and your work, but maybe we start with a little bit

03:50 – 03:56

of background, how you got into Data and then and then how you got into deciding, like, needed

03:56 – 03:58

to write a book about the work that you do.

03:59 – 04:06

Sure. Yeah. So, way back, 50000 years ago, I was a software developer and, got, you know, a

04:06 – 04:10

little bored of that after a few years, moved around different areas of software organizations,

04:10 – 04:16

doing some product management, and then they end up doing a bit of marketing, bit of business development, bit of sales.

04:17 – 04:25

And then, probably maybe, I guess, about 15 years ago, I, just kinda stumbled on the field of

04:25 – 04:27

cognitive psychology, which I just found absolutely fascinating.

04:27 – 04:32

You know, cognitive biases, judgment, decision making, psychology of perception.

04:32 – 04:37

And I just started really inhaling, a lot of books, in that field, which I consider to be just

04:37 – 04:39

kind of a sideline interest.

04:39 – 04:40

It wasn’t kind of my day Jon. Right?

04:40 – 04:44

I was still basically doing software, during the day.

04:45 – 04:49

And then, I was working on a product that had a lot of data visualizations in it.

04:49 – 04:54

And like a lot of people, just kinda muddling my way through and, you know, doing what I thought

04:54 – 04:57

kind of looked good or or was probably the right thing to do.

04:57 – 05:01

But then I figured I should probably get a bit of formal training here.

05:01 – 05:08

And so I attended a workshop, by Stephen Few, who, you know, probably a number of your your listeners are gonna know.

05:08 – 05:13

But, Stephen is a, you know, very well known, person in the field.

05:13 – 05:15

You know, did a lot of groundbreaking work.

05:15 – 05:19

And that workshop, just like, you know, just blew my mind, really.

05:19 – 05:25

Yeah, it was kind of the intersection of my day job and my sideline interest in psychology. Right.

05:25 – 05:28

It was a mix of data and technology and psychology.

05:29 – 05:33

And so I was yeah, I was absolutely fascinated.

05:34 – 05:38

Ended up kind of staying in touch with Steve after the workshop.

05:39 – 05:42

And then a few months later, the conversation kind of evolved.

05:42 – 05:46

I pitched him on, maybe teaching his workshops. Mhmm.

05:46 – 05:52

And and he had had people who had kind of approached him before, about, teaching his workshops.

05:52 – 05:58

But, really, you know, if you’ve ever read any of his books or or or been to any of his workshops,

05:58 – 06:01

you know that it is actually more like 80% psychology.

06:01 – 06:06

And so most of the people who had approached him really only had technical backgrounds.

06:06 – 06:08

They didn’t really have a psychology background.

06:08 – 06:13

But because of my sideline interest that I’d had for a number of years by that point, you know,

06:14 – 06:22

he agreed and then trained me to teach his workshops, gave me a big sack of books to read. And yeah.

06:22 – 06:24

And then the very first workshop that I taught was at NASA.

06:25 – 06:26

Oh, wow.

06:26 – 06:29

Yeah. So I was really kind of jumped jumped into the deep end.

06:29 – 06:29


06:30 – 06:33

That was in, I guess, about 2014. Okay.

06:33 – 06:39

And then so, so I taught these workshops for, all of the world for, you know, over over a dozen

06:39 – 06:42

a dozen countries, until, 2019 Mhmm.

06:43 – 06:46

When, much to my surprise, Steve announced that he he was gonna retire. Right.

06:46 – 06:48

I didn’t didn’t know it was in his plans.

06:48 – 06:53

And so, he actually encouraged me at that point and said, oh, you know, you can still continue

06:53 – 06:58

teaching my courses, but if you wanted to develop your own, you know, maybe eventually write

06:58 – 07:01

some books, then, you know, encourage me to do that.

07:01 – 07:02


07:02 – 07:09

And so I started working Jon, dashboard course first called practical dashboards, and then,

07:09 – 07:15

database fundamentals course, which was the practical charts course, launched them straight into the pandemic.

07:16 – 07:17

Like everybody had to pivot.

07:17 – 07:23

I’d I’d been asked to teach online before, but I I’d always refused because I was like, Oh,

07:23 – 07:25

it’s going to be such a terrible user experience.

07:25 – 07:31

You know, nobody wants to watch a talking head on a screen for hours on end, but we all had to adapt

07:31 – 07:32

the world. Yeah.

07:32 – 07:38

Yeah. And so, so, yeah, I did a bunch of research in terms of how to teach online effectively,

07:38 – 07:43

rejigged the courses because you can’t just, as you’re probably aware, you can’t just transport

07:43 – 07:48

something that was designed for in person and and use it as is, online.

07:49 – 07:52

And, thankfully, it went, went really well.

07:52 – 07:57

It was, the courses are are and were, quite popular, you know, online.

07:57 – 08:03

And now I’ve started to do a bit, in person, but a lot of organizations still Jon the line. Right?

08:03 – 08:08

Because they hired so many remote workers and, you know, just to get everybody in the same room

08:08 – 08:09

would be a big deal.

08:09 – 08:10

Right. So

08:10 – 08:15

I’m hoping to do more in person, but it’s still mostly kind of Yeah. Mostly. At this point.

08:15 – 08:23

What is the biggest difference between Steve’s course, kind of the original Steve’s course versus what you teach now?

08:25 – 08:31

Well, I mean, you know, I should qualify anything I say that, you know, everything I do would not be possible.

08:32 – 08:35

Without the enormous number of things that I learned from Steve.

08:35 – 08:40

You know, not just about data visualization, but about teaching and pedagogy and retention and comprehension.

08:43 – 08:49

But I guess, you know, after teaching these courses many times, you know, I started to see maybe

08:49 – 08:55

some opportunities to provide more specific guidance than what I saw, not just in these courses,

08:55 – 09:00

but in fact, in other books and courses that I was aware of.

09:00 – 09:06

You know, I I I felt that, you know, the the the advice, especially around chart type selection,

09:06 – 09:13

tended to boil down in a lot of cases to, you know, use your judgment or, you know, do what looks right.

09:13 – 09:20

But I knew in teaching people who often had actually very little background in data visualization that that wasn’t helpful. Right?

09:20 – 09:23

They’re like, I just don’t have that experience.

09:23 – 09:26

I don’t I haven’t developed those intuitions yet. Right? Right.

09:26 – 09:34

And so, you know, just through kind of a lot of iteration, I started to develop guidelines around,

09:35 – 09:40

you know, mostly chart type selection, but also kind of other, you know, design choices as well

09:40 – 09:45

that ended up being what I felt were kind of more sort of usefully specific.

09:46 – 09:50

You know, instead of like things that were more kind of vague in terms of like, oh, you know,

09:50 – 09:52

you got to break down the total.

09:52 – 09:57

Well, you could use a bar chart or pie chart or a stock bar chart or, you know, a regular bar

09:57 – 10:00

chart or a Pareto chart or a waterfall chart.

10:00 – 10:02

You know, use your judgment.

10:02 – 10:05

Do you know, use use the one that you think kind of works best?

10:05 – 10:12

It’s like, actually, no, there are specific circumstances and conditions under which it does

10:12 – 10:16

and doesn’t make sense to use each of those chart types, and they’re not interchangeable. Right.

10:16 – 10:17

As you’re well aware, right?

10:18 – 10:23

There’s there’s a difference if you’re showing the same data as a regular bar chart or a stock

10:23 – 10:29

bar chart, for example, Different kinds of insights are Jon to be more or less visible.

10:29 – 10:36

And I just felt that it was possible to sort of, get more formal about that, you know, codified

10:36 – 10:38

a bit without being dogmatic. Right.

10:38 – 10:41

You know, I’m always I don’t use the term rules.

10:41 – 10:46

I call them guidelines because, you know, this is the way I do it.

10:46 – 10:49

And if you want to do it another way, that’s that’s fine.

10:49 – 10:52

You know, I’m definitely sort of okay with that.

10:52 – 10:58

And in fact, if, you know, like somebody like yourself who has a lot of experience is going

10:58 – 11:03

to probably deviate from those guidelines every so often. And that’s fine, really.

11:03 – 11:08

I consider them to be more like almost like training wheels, you know, like, especially for

11:08 – 11:12

people who are starting out, although even, you know, people who have quite a bit of experience

11:12 – 11:14

have said that they’re, you know, they also find that to be useful. Right.

11:14 – 11:14

But it basically kind of, you know, it starts you out with a good base, right?

11:14 – 11:15

Like if you if you

11:22 – 11:26

if you want to know kind of when to break the rules, the first step is kind of to know what

11:26 – 11:28

the rules are in the first place, except I hate that term.

11:28 – 11:31

I call them, you know, guidelines. Right.

11:31 – 11:37

And people have really responded to that as something to kind of latch onto Jon in a field where

11:37 – 11:43

there tends to be a lot of that tends to be quite vague around a lot of the Yeah. Decisions.

11:44 – 11:48

Yeah. It’s interesting I wanted to ask you because you because the book, the way you write it,

11:48 – 11:57

it kinda dances around this rules, guidelines, strategies, preferences, I don’t know, web of

11:57 – 11:59

trouble when it comes to those words.

11:59 – 12:03

But it but it’s also interesting, and I don’t wanna belabor talking about Steve too much.

12:03 – 12:09

But I think a lot of people, I think, felt that Steve’s writing, particularly on his blog, was

12:09 – 12:13

pretty dogmatic about do this, don’t do this.

12:13 – 12:17

But what I’m hearing you say is it’s kinda like the old matrix.

12:17 – 12:21

Like, you can kinda bend some of the rules, and then you can start to break the rules.

12:21 – 12:25

So, like, how do you, like, kinda help people see

12:26 – 12:26


12:26 – 12:32

Rule guideline and then just ignore all of it and, you know, go forward?

12:35 – 12:41

Like I said, I don’t consider that anything in my, books are, you know, kind of unbreakable.

12:42 – 12:43

Actually, it’s not entirely true.

12:43 – 12:47

There are there are a few points in the book where I say this is a mistake.

12:47 – 12:53

Like, if you show the data in this way, the risk that people are going to misinterpret the underlying

12:53 – 12:56

data is so high that you should just never do this.

12:57 – 12:59

But that is relatively rare. Right? Yeah.

12:59 – 13:06

Like, most of what I I kind of advocate, I I would definitely put in the, you know, the category of guidelines. Mhmm.

13:07 – 13:09

It’s just that I think, yeah.

13:09 – 13:15

And I do have sort of an aversion to not just Steve, but anybody who is very kind of dogmatic

13:15 – 13:18

about like, this is this is correct. This is incorrect.

13:19 – 13:27

You know, it’s like, well, you know, a yeah, it’s rarely that simple. Right? Right. There are often exceptions.

13:27 – 13:30

And in fact, that’s one of the reasons why I wrote the book is to kind of dove into that and

13:30 – 13:39

say, okay, let’s talk about those exceptions and those cases where, you know, a general principle

13:39 – 13:41

maybe kind of doesn’t apply.

13:42 – 13:48

And so, you know and this is one of the kind of things things that I struggle a little bit little bit with, Tufti’s books.

13:48 – 13:53

Edward Tufti is another person that, you know, your readers may or may not be familiar with,

13:53 – 13:59

but he’s one of the godfathers of, visualization that when I read his books, I I’m often thinking,

13:59 – 14:04

you know, yes, this is usually a good idea, but not always.

14:04 – 14:13

And those exceptions are, in fact, very important because those exceptions in certain cases can occur quite frequently.

14:13 – 14:19

And so, you know, one of my goals is to really, like I said, to to go beyond that in terms of,

14:19 – 14:23

like, let’s actually flesh it out in terms of, like, well, what are the exceptions?

14:23 – 14:27

What are the specific circumstances under which, for example, it might actually make sense to

14:27 – 14:33

use a pie chart and, you know, where, you know, both Steve and Data would say, like, never use pie charts. Right.

14:33 – 14:36

Well, you know, pie charts are often misused.

14:37 – 14:41

There may be a bit overused, but does that mean that you should never use them?

14:41 – 14:47

Well, no, it’s just that figuring out when to use a pie chart is actually surprisingly tricky.

14:47 – 14:49

You know, like I have, you know, you’ve probably seen that in the book, I have these decision

14:49 – 14:53

trees about which chart types to use and, you know, to show the breakdown of a total, for example.

14:56 – 15:01

And, you know, there are like at least 6 major chart types for doing that, you know, stack bar,

15:01 – 15:06

regular bar, Pareto chart, waterfall chart, and, you know, and pie chart. Mhmm.

15:06 – 15:11

And there are about 8 considerations that you need to take into account when you’re trying to

15:11 – 15:15

figure out which is the best one for the situation at hand.

15:15 – 15:18

And so there is a path that leads to pie charts.

15:18 – 15:24

It’s just that knowing what that path is is not as straightforward as something that’s as simple

15:24 – 15:30

as like never use pie charts or always use pie charts to show the breakdown of a total. Right. Right. Right.

15:30 – 15:32

Like not neither of those are good advice.

15:33 – 15:35

It’s unfortunately, it’s just a little more complicated than that.

15:36 – 15:41

But it is possible, I think, to codify it because, you know, a lot of, you know, another sort

15:41 – 15:47

of common thing that I that I hear, especially among even more experienced chart creators is,

15:47 – 15:52

you know, say, well, this kind of thing is just really, you know, impossible to codify.

15:53 – 15:57

It’s just it’s too complex. It’s too nuanced. There’s too many exceptions.

15:58 – 16:03

You know, it’s just something you you kind of develop with experience and judgment over time.

16:03 – 16:09

And so there I kind of pull back and go, well, you know, yes, it is complex, but it’s not that complex.

16:10 – 16:16

I think it is possible to actually codify it in a way which is, you know, relatively simple,

16:16 – 16:23

but it’s not as simple as like always use pie charts for the breakdown of a total or never use pie charts. That’s too simple.

16:23 – 16:30

And so so I kind of, I think, hopefully found a good kind of middle ground in terms of something

16:30 – 16:36

that is not so simple that it’s not going to be useful or it’s going to give you bad design decisions really often.

16:36 – 16:43

But it’s also not this kind of nebulous cloud of experience and judgment and intuition either,

16:44 – 16:47

because that’s not helpful for especially for beginners. Right?

16:47 – 16:53

Yeah. It’s interesting because it seems to me when as I read through the book that the target

16:53 – 17:01

reader, as you’ve mentioned, is kind of that somewhat beginner, maybe intermediate, person creating data visualizations.

17:01 – 17:08

But you also do have a chapter on motion and a chapter on interactivity, a chapter on on animation.

17:08 – 17:09

They’re kind of they’re shorter chapters.

17:09 – 17:17

And so is your avatar of the target reader that sort of beginner intermediate person creating

17:18 – 17:26

static graphs and reports or on social media and not so much worried about that interactive

17:26 – 17:29

dashboards or what things look like on mobile phones?

17:29 – 17:32

Is that sort of like the core person you’re you’re thinking about?

17:32 – 17:38

Yeah. I mean, in terms of, if you think about it more kinda from a use case perspective, if

17:38 – 17:41

people are creating, you know, what I call everyday charts, right?

17:41 – 17:46

These are charts for reports and presentations. It’s not data art.

17:46 – 17:53

They’re not highly technical scientific, graphics, not, like, really, you know, customized interactives

17:53 – 17:56

like you’d find in The Washington Post or The New York Times.

17:56 – 17:58

Not really my my target reader.

17:58 – 18:02

I think that people who are, you know, creating those types of charts would probably benefit

18:02 – 18:08

from reading the book to maybe kind of get a little bit more solid on some of the fundamentals.

18:08 – 18:15

But, you know, really, I only bring people as far as those kind of everyday charts.

18:15 – 18:19

And a lot of people tend to think, Oh, well, but you know, do you really even need to read a

18:19 – 18:26

book to create these kind of simple everyday charts for some presentations. And yeah, you do.

18:26 – 18:30

I mean, as you well know, like, it’s really easy to screw up a bar chart, you know, or maybe

18:30 – 18:36

to use a bar chart when in fact you should have been using a line chart or a pie chart or something else. Right.

18:36 – 18:42

Like these these decisions actually require a surprising degree of skill even if you’re talking

18:42 – 18:45

about these, quote, unquote, you know, simple charts. Yeah.

18:45 – 18:48

Yeah. Back to the rules part real quickly.

18:48 – 18:53

Are there any I’ll use the word rules, although I you know, there there’s definitely quotes around that.

18:53 – 18:56

But do you have any rules that you view as ironclad?

18:57 – 19:02

Like, for me, I think I can only think of 1, but I’m curious if there are any that you have

19:02 – 19:08

that are, like, all, like, all or, you know, never ever do this or, you know, always do it this way.

19:08 – 19:10

Well, I have to know what your one rule is there.

19:10 – 19:12

Well, I wanna see yours. Oh, okay. I’ll give you mine.

19:12 – 19:19

So I think I think mine is the bar chart where people sort of break the bar.

19:19 – 19:23

You know, they have, like, the outlier bar, and they’re like, well, I’m just gonna, like, put

19:23 – 19:25

that little jagged line and just gonna shorten it.

19:25 – 19:34

Because I think that, I can’t think of any exceptions where that just distorts our perception of the data. Right? Yeah.

19:34 – 19:34

And it’s

19:34 – 19:39

just it’s just arbitrary where you’re gonna cut it and how you’re just gonna adjust your your axis.

19:39 – 19:45

And I and like, you know, I think a lot of people would say, you know, bar charts start at 0,

19:45 – 19:48

But I think there are probably exceptions to that.

19:48 – 19:54

Like, you know, if you’re gonna start if if you’re gonna normalize your data at, say, 1, well,

19:54 – 19:59

so, you know, in that case, 1 is kind of equal to 0. Right? But, like okay.

19:59 – 20:01

So so is 1 the right point?

20:01 – 20:06

So but I think that broken bar chart, which you talk about in the book, I I think that might

20:06 – 20:11

be for me like the ironclad rule, which I rarely talk about in classes because which I guess

20:11 – 20:12

I should, but it seems so obvious to me.

20:12 – 20:18

Like, those those arbitrary things to me are the ones that I get I get nervous about. But yeah.

20:19 – 20:27

Yeah. I mean, I think if if I do have any, quote unquote rules, where I just and I and I like

20:27 – 20:28

the way you described it.

20:28 – 20:34

It’s like it’s just it’s something where I just cannot think of a scenario where that’s a good idea. Right?

20:34 – 20:40

So it doesn’t mean that they don’t exist, but it means that, like, I have not come across a

20:40 – 20:41

good use case for it yet. Yeah.

20:42 – 20:45

And so if you wanna call that a rule, you know, sure. Sure. Yeah.

20:46 – 20:52

But and and and so any of the kind of rules that I would have would be of the negative type. Right?

20:52 – 20:55

There’s never an always do this. Right.

20:55 – 20:58

It’s it’s always, you know, never, never do this.

20:58 – 20:59


20:59 – 21:00

And that would I would agree. Yeah.

21:00 – 21:03

Like, never break the scale, quantity scale. Yeah.

21:03 – 21:08

I cannot think of a situation where that’s going to be, you know, a good idea.

21:10 – 21:12

What would be some other nevers?

21:12 – 21:16

Well, a controversial one that I have is, never use box plots.

21:17 – 21:19

Oh, never. Okay. So I’m curious about that one.

21:20 – 21:25

Yeah. So, I I wrote an article about this on, Nightingale, the journal of of the Data Visualization

21:25 – 21:28

Society a year or 2 ago, and it just blew up.

21:29 – 21:32

It was, you know, got hundreds of of reactions and interactions.

21:33 – 21:36

But I, you know, I used to teach bar charts.

21:36 – 21:41

Like, you know, bar charts were in Steve’s courses, or not bar charts, box plots. Yeah.

21:43 – 21:49

But I just, you know, after seeing the thousandth person kind of be like, you know. Yeah.

21:50 – 21:55

And then eventually kind of like, oh, right. Okay, I get it.

21:55 – 22:00

It really sort of started to make me rethink, like, k, like, there’s just a huge cognitive hurdle

22:00 – 22:01

associated with this chart type.

22:02 – 22:06

You know, when is it really doing something that alternative chart types can’t do?

22:06 – 22:10

When is it showing some kind of insight or answering some kind of question that you couldn’t

22:10 – 22:15

answer with a simpler chart type, like a strip plot, for example, which is much easier to understand,

22:16 – 22:21

you know, or even a histogram, which is, you know, a little more more complicated, but still

22:21 – 22:22

a lot easier to understand.

22:22 – 22:27

People don’t understand, have to understand quartiles or mediums or anything like that.

22:27 – 22:34

And I couldn’t come up with any scenarios in which, you know, the the insight that I was trying

22:34 – 22:40

to communicate, could be communicated in box plots, but could not be communicated in simpler chart types.

22:41 – 22:47

I looked and I and when that article came out and went viral, I asked people, I was like, Look,

22:47 – 22:48

you know, prove me wrong.

22:48 – 22:55

Like, show me examples of data where you’re showing the same data as a box plot, but then also

22:55 – 23:00

the strip plot and a histogram or stacked histograms in that case because you need several histograms.

23:00 – 23:06

And then tell me what you’re seeing in the Bosch plot that you’re not seeing in the simpler chart types.

23:07 – 23:08

I just didn’t get any.

23:09 – 23:15

So I vaguely remember that article, but let me ask, and then and then maybe I’ll I’ll give you

23:15 – 23:17

an example, but where I think it could work.

23:17 – 23:23

But when you say, no box plots, are you again thinking about those the way you you you said

23:23 – 23:25

mentioned earlier, like the everyday chart?

23:26 – 23:31

Or because because I can imagine for the everyday chart reader, you know, reading the Washington

23:31 – 23:35

Post or, you know, Twitter or something like that. I I totally agree.

23:35 – 23:40

Like, people you know, most people just don’t understand or or, you know, don’t have experience

23:40 – 23:43

reading what a percentile is or a quartile is and totally get that.

23:43 – 23:49

But, like, in a scientific journal or an academic peer reviewed journal, you know, that cognitive

23:49 – 23:55

hurdle is probably not as high because those readers are probably familiar with those graph types.

23:55 – 23:59

I’m always fascinated, for example, when I, like, dive into the biology literature, which is

23:59 – 24:01

very rare and very brief.

24:01 – 24:06

But, like, I see these chart types, and I’m like, I have no idea what you guys are showing.

24:06 – 24:11

But, like, I’m not a p I don’t have a PhD in biology and have no idea what to talk about.

24:11 – 24:14

But I’m sure, you know, the editors and peer reviewers are like, oh, yeah.

24:14 – 24:16

This is a blah blah blah chart. Right? So Yeah.

24:18 – 24:21

Yeah. I, even in those cases. Right?

24:21 – 24:24

Like, towards the end of the article, I kind of addressed that.

24:24 – 24:30

And because even if you have, like, expert statisticians who have been looking at box plots

24:30 – 24:35

for years years, like, there’s still which which I, you know, I fell into that category, by the way.

24:35 – 24:39

I’m I’m a not expert statistician, but, like, I had been looking at box plots for a long time.

24:39 – 24:40

I knew exactly how to read them.

24:40 – 24:42

I was very familiar with them.

24:42 – 24:47

But then even with with me, when I would take the same data and show it as a strip plot or,

24:47 – 24:52

you know, stacked histograms, I was still able to read them much more quickly and easily.

24:53 – 25:00

I often spotted trends, anomalies, patterns, gaps, clusters that just weren’t visible at all. Right. And in the box,

25:00 – 25:02

you’re just picking up the

25:02 – 25:04

or even with like expert audiences.

25:04 – 25:11

I still made the argument that, no, I think even they are better off with, you know, these kind

25:11 – 25:14

of I mean, I was gonna say simpler chart types, but they’re not just simpler.

25:14 – 25:21

They’re also more informative and less cognitively demanding regardless of what your level of expertize actually is.

25:21 – 25:25

You know, and I made the same argument with, connected scatter plots as well.

25:25 – 25:29

And another article last last year about that that got a lot of attention.

25:30 – 25:34

But I I basically, you know, I subjected it to the same test.

25:34 – 25:40

Like, can you take the same data and show it in this kind of very cognitively demanding chart

25:40 – 25:42

type, but show it in simpler chart types?

25:42 – 25:47

Like, in that case, you know, the alternatives were just, like, 2 line charts that were stacked

25:47 – 25:50

on top of one another or an indexed, line chart.

25:50 – 25:56

And then tell me what you can see in the connective scatterplot that you can’t see in these simpler chart types.

25:56 – 25:59

And nobody could come up with anything.

26:00 – 26:01

No, no, no use cases.

26:01 – 26:06

And so so I was like, okay, this isn’t that it’s not that connected scatterplots or box plots

26:06 – 26:07

are are bad chart types.

26:07 – 26:14

It’s just that there are simpler alternatives which are always able to say the same thing and in often cases more.

26:14 – 26:17

And so why would you use those Right. Arc types?

26:17 – 26:20

Right? Well, I I think and and this was this was something I Jon.

26:20 – 26:25

This is this is a good segue to what I wanted to talk about because you you start the book right

26:25 – 26:28

at the beginning saying, you know, you’ve heard people say things.

26:28 – 26:33

He’s like, keep it simple and know your audience and tell a story, and then you sort of go into

26:33 – 26:34

there’s there’s more to it than that.

26:34 – 26:40

But this this concept of simplicity, I hear people say that all the time, and I don’t I don’t

26:40 – 26:45

love that word because I think what we’re trying to do is is clarify, not necessarily keep it simple.

26:45 – 26:51

But to the connected scatterplot, I again think there’s differences in your goal.

26:51 – 26:55

I think back to, like, Hannah Fairfield’s kind of, like, not original scatterplot, but the kinda

26:55 – 27:01

ones that that made the connected scatterplot, you know, kinda famous is she definitely could

27:01 – 27:03

have created that as 2 line charts or an index chart.

27:03 – 27:11

But, again, if you are, you know, you’re a Sunday afternoon New York Times reader, Like like,

27:11 – 27:16

I I think in that case, at least, that was more about the experience, right, of reading this

27:16 – 27:21

chart with the annotation to sort of bring you through this journey. Yeah.

27:21 – 27:28

Maybe 2 line charts or an annex chart would have made that simpler in in the sort of sense that it’s 2 line charts.

27:28 – 27:34

We don’t know how to read line charts, move Jon, but to engage in New York times audience on

27:34 – 27:39

a Sunday afternoon and bring them through that, that what I would call more of a story than

27:39 – 27:42

what most people think of the store than stories.

27:42 – 27:46

You know, in that case, I think it achieves a goal. Right?

27:46 – 27:51

As opposed to if you’re writing an academic peer review article or you’re writing a report where

27:51 – 27:56

you’re like, here’s this hypothesis and here’s the evidence to support it. Yeah.

27:56 – 28:00

The connect and scatterplot, I think, more times than not, doesn’t really do that job.

28:00 – 28:07

Yeah. I mean, yeah, that that is definitely a very valid point. Right?

28:07 – 28:11

Like and in the beginning of the book, really, the main kind of message of of the introduction

28:12 – 28:15

is I consider charts to be graphics for doing a Jon.

28:15 – 28:18

And this is quite different than how most people think of that. Right?

28:18 – 28:26

And so if the job is just to essentially kind of grab attention, that’s legitimate, you know? Yeah. Yeah. That is right.

28:26 – 28:28

Like, a lot of people say, oh, no, no, no.

28:28 – 28:31

That’s not like proper data visualization. Yeah. No. No. No.

28:31 – 28:34

Like, sometimes that is, that is the goal.

28:34 – 28:40

You just have to be aware that if you’re going to use some very unusual visualization or very

28:40 – 28:45

cognitively demanding visualization to get attention, that there are going to be costs associated with that. Right?

28:46 – 28:54

You know, like in my Connected Scatterplot article, I actually talked about that New York Times, you know, yeah, scatterplot.

28:55 – 29:04

And I was like, you know, I, I would bet good money that the vast majority of readers did not understand that chart.

29:04 – 29:09

They relied entirely on the annotations. Right. Right. Or they misinterpreted it.

29:09 – 29:10

They thought it was a standard line chart.

29:11 – 29:16

And then they’re coming out with a completely wrong understanding of the underlying data.

29:16 – 29:20

And so, yeah, it might have gotten a lot of attention, but at what cost?

29:20 – 29:30

Right. So Yeah. Yeah. I I just I I guess to your point, there’s there’s we have different purposes. Right? Like Very

29:30 – 29:31

much so. Yeah.

29:31 – 29:33

Yeah. You just wanna grab people’s attention.

29:33 – 29:36

Maybe use some sort of 3 d whatever. Right?

29:36 – 29:40

Like, ESPN, the magazine, I used to always kind of make fun of because they’re, like, every

29:40 – 29:43

graph in ESPN, the magazine was, like, a 3 d monstrosity.

29:43 – 29:48

But, like, their goal is just fundamentally different than what at least you and I are trying

29:48 – 29:53

to do 99% of the time, right, which is to make a point or to or or or Yeah. You know?

29:53 – 29:55

It’s not about getting clicks. Right?

29:55 – 29:57

It’s about informing and educating.

29:57 – 30:01

Yeah. Yeah. And and the the key, though, is really keep in mind that, you know, if you’re gonna

30:01 – 30:06

do something like that, you’re gonna go for kind of an attention grabby design. That’s fine.

30:06 – 30:09

Just be aware of the costs. Right?

30:09 – 30:13

Like, there are usually costs involved in doing that.

30:13 – 30:18

And if the cost is that, know, you’re gonna leave most readers with a just fundamentally incorrect

30:18 – 30:22

understanding of of the reality behind the chart, then maybe it’s not worth it.

30:25 – 30:27

What is your thought on this this distinction?

30:27 – 30:34

And so I’ve just been thinking about this, so I’m curious just to get your take on this distinction between simplicity and clarity.

30:34 – 30:38

Because I I feel people’s I hear people say, like, oh, you should be able to get it in a second.

30:38 – 30:50

Like, and that may or may not be true, but even very complex data can be represented so that it’s clear. Right?

30:50 – 30:52

The data itself is not simple.

30:52 – 30:55

If I think about, okay.

30:55 – 30:58

Try to come up with a good example off top of my head.

30:58 – 31:04

A line chart that has 50:50 states on it and maybe 2 of them are kinda highlighted. Right?

31:04 – 31:08

Like, I don’t know if I would call that a simple graph because it’s got 52 lines on it.

31:08 – 31:13

But if it’s, you know, colored correctly and, you know, we’ve got the highlighted lines versus

31:13 – 31:15

the gray lines, like, it’s clear. Mhmm.

31:15 – 31:23

It’s just not I I I think simple sort of undermines what’s going on in the data, right, that there’s complexity there.

31:23 – 31:27

And it’s our approach to clearly communicating it. That’s the goal.

31:28 – 31:35

Yeah. Yeah. I mean, yeah, I mean, that that’s a, you know, that’s a great point. Like,

31:38 – 31:39

I’m trying to remember this.

31:39 – 31:43

Like, I think it was an Einstein quote who basically said, you know, you said you Jon to simplify

31:43 – 31:47

but not oversimplify or something along those lines. Yeah. And probably butchering it.

31:47 – 31:54

But, but, yeah, like, you know, because the goal I think I think as a general principle, we

31:54 – 32:01

should try to simplify the charts, especially these everyday charts for reports and presentations, as much as possible.

32:01 – 32:07

But sometimes as much as possible is not very simple. Mhmm. You know? Yeah.

32:07 – 32:12

Like, if the the underlying message is just, you know, it’s more complex.

32:12 – 32:14

There’s, you know, several moving parts to it.

32:14 – 32:17

And if you take away some of those parts, it just doesn’t make sense anymore.

32:17 – 32:22

Or the audience just doesn’t, you know, they don’t get the the minimum necessary amount of information

32:23 – 32:25

to write between 2 together in their head.

32:27 – 32:33

You know, but I think the the the much, much more common problem is the opposite where people

32:33 – 32:36

make charts that are unnecessarily complex. Right.

32:36 – 32:39

Where they they’re you know, I’m looking at it.

32:39 – 32:44

I’m imagining a simpler version of that chart, which still accomplishes the same thing. Right?

32:44 – 32:49

Because kinda like what I was mentioning before, I consider that charts are graphics for doing a job. Right?

32:49 – 32:54

And so ultimately, what really matters at the end of the day is did the chart do the job that

32:54 – 33:00

you had in mind when you, you know, when you first decided to create a chart in the first place?

33:00 – 33:02

Because we don’t just create charts just to show the data. Right?

33:02 – 33:05

There’s always some ulterior reason. Right?

33:05 – 33:08

We’re trying to explain something to somebody.

33:08 – 33:10

We’re trying to answer a question that they’ve asked us.

33:10 – 33:14

We’re trying to maybe persuade them to take a course of action or adopt an opinion.

33:14 – 33:19

And ultimately, that’s what matters is how well does the chart do that?

33:19 – 33:24

And so there’s a bunch of things that go into that, and one of them is simplicity. Right?

33:24 – 33:29

You you want to, you know, sort of make it as simple as possible for the audience to actually,

33:30 – 33:35

you know, understand what it is that you’re trying to explain to them or, you know, agree with

33:35 – 33:38

your opinion on on whatever it is. Right? And that’s hard.

33:39 – 33:41

Like, it’s hard to make simple charts.

33:41 – 33:46

Like I said, the most much more common problem is our charts are kind of needlessly complex.

33:47 – 33:51

And that’s kind of the underlying objection that I have with things like connected scatter plots

33:51 – 33:58

and box plots is that they in in every case that I’ve seen, they’re needlessly complex. Right?

33:58 – 34:02

They’re they’re forcing the audience to jump through cognitive hoops that they don’t have to

34:02 – 34:08

jump through in order to get the whatever the message of the chart actually, actually is.

34:08 – 34:10

Right. I wanna I wanna close-up with just one last thing.

34:10 – 34:18

You you mentioned at the beginning that you started your your data vis part of your career teaching dashboards.

34:18 – 34:23

And and this book isn’t really about dashboard design. And I’m curious.

34:25 – 34:27

I guess I’ll phrase the question this way.

34:27 – 34:30

I’ll make it sort of a debatable statement.

34:30 – 34:36

And so I’ll get your take on it that creating static graphs are harder than creating dashboards,

34:36 – 34:42

ignoring the tools and the technical challenges, that that creating an exploratory dashboard

34:42 – 34:47

is easier than creating the chart that you just described where you’re making a point, you’re making an argument.

34:49 – 34:56

I think that very much depends on what you mean by a dashboard. Right? Okay. Very good. Yeah. Yeah. Yeah.

34:56 – 34:58

You know, terms of a lot of baggage.

34:59 – 35:02

And, like, for example, in my dashboard course, I actually segment.

35:02 – 35:05

Like, the very first thing I do is say, we gotta segment this term.

35:05 – 35:10

We can’t talk about dashboard design best practices when dashboards like as far as most people

35:10 – 35:14

are concerned, a dashboard is any display with a bunch of charts on it. Right? Right.

35:14 – 35:17

And so that’s going to include all sorts of stuff.

35:17 – 35:21

It’s going to include basically like what you and I probably call infographics.

35:21 – 35:22

It’s going to

35:22 – 35:25

include interactives on, you know, news sites.

35:25 – 35:31

It’s going to include like real time status monitoring dashboards and manufacturing plants and

35:31 – 35:35

workout dashboards on your phone, like like all sorts of different things.

35:35 – 35:39

And so really, you know, I kick off the course by essentially segmenting dashboards

35:49 – 35:55

static chart? My, you know, my first sort of counter question would be, what kind of dashboard are we talking about?

35:55 – 35:55

Yeah. Yeah.

35:55 – 36:01

Because there are some kinds of dashboards that are very difficult, very challenging to nail. Right?

36:01 – 36:04

Much more so, I think, than than most static charts.

36:04 – 36:05

But there are other types of dashboards.

36:05 – 36:10

Like, if you’re basically creating kind of an infographic, like a collection of static charts

36:10 – 36:14

on a poster or something like that, that maybe that’s actually easier.

36:14 – 36:17

Right. Right. Well, that is a really good clarification.

36:18 – 36:23

And we won’t go into too much detail because I’ll just give you the the motivation maybe to

36:23 – 36:26

write your next book will be practical dashboards. Maybe will be the

36:27 – 36:28

Oh, it’s it’s in the pipe.

36:28 – 36:29

Okay. It’s in the pipe.

36:29 – 36:30

So we’ve got that to look forward to.

36:30 – 36:35

So we’ll get you back on the show when that book comes out. Perfect. Okay. So, Nick, last question.

36:35 – 36:39

And I’ll put the links to everything we’ve talked about with the 2 Nightingale articles.

36:39 – 36:43

And I’m of course, right after this, after this call, I gotta go back and read the box plot

36:43 – 36:46

one so I can I can think about that some more?

36:46 – 36:48

But where can folks find you?

36:48 – 36:49

How can they get in touch?

36:51 – 36:55

Best way is just through my website, which is practical, all one word.

36:56 – 37:02

I’m easy to find on LinkedIn because I am the only person with this name, unsurprisingly. And, yeah.

37:02 – 37:09

So, on on the, the website, you’ll find information about, about, my books and about upcoming workshops.

37:09 – 37:13

I do have one actually, coming up on, starting on May 6th.

37:14 – 37:16

About 3 times a year, I do public online workshops.

37:17 – 37:21

And so if people are interested in taking the practical charts course or the practical dashboards

37:21 – 37:26

course, which is also taught, during that workshop, then I would, welcome them to, register.

37:26 – 37:29

Terrific. Alright, Nick. Thanks so much for coming on the show.

37:29 – 37:31

The book is Practical Charts.

37:31 – 37:34

I hope folks will check it out, wherever you get books.

37:34 – 37:37

And, I’ll put links to all the, things we’ve talked about in the show notes.

37:37 – 37:39

So thanks again for coming on the show. It’s, this was great.

37:39 – 37:41

Yeah. Really great discussion. Lot of fun.

37:43 – 37:45

Thanks everyone for tuning into this week’s episode of the show.

37:45 – 37:48

I hope you enjoyed that conversation with Nick.

37:48 – 37:50

I hope you will check out his website.

37:50 – 37:51

I hope you’ll check out his book.

37:51 – 37:59

And from my perspective, I hope you will rate or review the show on iTunes, Spotify, or wherever you get your podcasts.

37:59 – 38:01

Really does help me out.

38:01 – 38:04

So until next time, this has been the PolicyViz Podcast.

38:04 – 38:06

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38:07 – 38:09

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