Transcript
Speaker: This episode of the PolicyViz podcast is brought to you by JUMP's Statistical Discovery Software from SAS. JUMP's powerful, easy -to -use visualization capabilities allow you to both explore your data for hidden insights and create interactive graphics that tell a compelling story. Enhance your presentations with dynamic graphics powered by world -class analytics in JUMP.
Speaker: Visit www .jmp .com to download a 30 -day free trial to see for yourself how with JUMP, data visualization and exploratory analysis go hand in hand.
Speaker: Welcome back to the Policy This Podcast. I'm your host, John Schwabish. On this week's episode of the show, I'm super excited to have special guest, good friend, former co -podcast host, Stephanie Evergreen on the show. Stephanie, welcome to the show. Hey, John. How are you? Thank you. I'm so glad to be back here with you. It's been a long time, friend. I miss you. It's like old times now, right?
Speaker: That's right. Back together. Back together. Getting the band back together.
Speaker: Now, of course, some folks may not know that Stephanie and I hosted a podcast on presentations called the Rad Presenters Podcast, which we then stopped doing because we both got too busy and tired. And summertime was looming, so that sounded like more fun to be on the beach. How was your summer? It's good. I mean, I feel like that makes us sound like we're old. That's true. Like we got too tired. But really, it's just because we were both doing such awesome stuff. That's right. That's right. That's a better way to put it. It wasn't tired. It was just being too awesome is really.
Speaker: It was too much awesome. Summer was great, very busy, very, very busy. My book came out in, I think it was May, and so there's just always a lot of work to do around that.
Speaker: expectations to me and and things like that. Right. And this is our second book, right? Yes, on data visualization. This one. Well, so for those who don't know, effective data visualization, the right chart for the right data. You want to talk about a little bit, you know, who was for and what you're thinking as you're going into doing another a second book on data? Yeah, well, the motivation for the book really came from the workshops that I do, because
Speaker: You know, many of us, lots of us out there in the world give very general workshops on data visualization theory, overview, best practices kind of stuff. But then people always want to know, well, how do I actually do it? Like, tell me what buttons to push. And so I've had those kinds of workshops for a long time too, where we'll have
Speaker: anywhere from a half a day to two days in a computer lab together or we've all got our laptops out and we're working with data and we're actually creating dot plots or diverging stacked bars or something like that. But there's only so many people I can fit into those, you know, like you can only if you if you've ever tried to run a workshop with people actually like doing things on their laptop, you kind of go around looking over their shoulder and helping them out and stuff. So
Speaker: I've always had limited seating in there, and so I've only been able to reach a smaller number than I've hoped. So the book is a companion, because it tells you the step -by -step with the screenshots and everything on how to make all these awesome impactful charts on your own. So you get your reference guide right there. Right. So you have the first one, which is more of theory, background, best practices. And then this book is a companion that actually puts that in practice.
Speaker: Yes, it exactly shows you exactly how to do it. What buttons to push inside Excel. So it is Excel based Excel and PowerPoint. So it's not going to be for the people who are already like cooking up some magic in JavaScript or something like that. They're going to be pretty disappointed. So what was the process like of moving from a book where, you know, a little bit more like a research book, like your dissertation, you know, on best practices and theory and the research to moving to a book with that's a little more hands on a little more step by step.
Speaker: You know, it wasn't too difficult because I've already been blogging about these things for a long time. I think one of the things that's made my blog so popular is that I tell people exactly how to do it there. So this is wrapping it up into a tidier package and including a little bit more of the theory about when you would choose what chart type, under what circumstances you'd want to use it, what data set it's going to be best for. So the inside cover of the book is the chart chooser.
Speaker: that I give out in my workshops that tells people basically like how to pick the best church type for you. And then we make graphs for every single one of those church choices in the church user throughout the book and explain why. So I think it's super helpful in that way. And it's, it is far more applicable, like a practical and then the first book, even though that one was pretty practical too, but this one's like super nitty gritty. Right.
Speaker: So how do you approach the chart chooser part of the workshops? I mean, I think this is a question we hear all the time, right? And it's like, I have these data, what's the chart I should use, right? And of course there is no, usually there's no like, right chart. So how do you, how do you approach that when you're, when you're working with clients? Well, usually I start up by asking them, what's the point they're trying to make? Because it's not so much the data set. It's the point that you need to be making from that data set that really helps you figure out what chart type you need. And then it's going to point you to a couple of different options.
Speaker: Um, but once we know like what the point is we're trying to make and the audience we're trying to talk to, we can get, we can hone in on at least a smaller set of chart choices. And then I tell people to try, try each one and see how it looks, see if it's really telling what you want it to say.
Speaker: and they can pick from there. Right. It's also interesting that your book, as opposed to probably many of the other dataviz books, has a lot more of references to the research, be it true dataviz, not true, but pure dataviz research or cognitive science or neuroscience research. So when you are, is that just like your PhD background instincts just kicking in that everything has to be backed up with some actual research?
Speaker: Yeah, I mean, some ways, once you've come up through that sort of upbringing, it's hard to let it go. But I also think it helps because the people I know out there who are trying to push for better data is inside their organizations. It's usually what did somebody in my workshop call it? They called it like educating up. They got to convince their bosses and the senior VPs that this is actually a good idea. And one of the best ways to do that is to come armed with some research that says this isn't just me or this isn't just some blog posts I read.
Speaker: This is legit. Yeah. Um, and I think the same thing holds true for some groups in general who are hard to convince like, um, academics. Whenever I go to like a higher education or sometimes I'll go to a, um, organization that's filled with PhDs and they just don't buy it, you know, they've kind of been cultivated in the old way of doing data. Isn't the way you convince them is really through that research. Right.
Speaker: So are there core things, are there like one or two like core things that you tell people when they're working in Excel? What is the one thing that people or one or two things that people should know when they're creating data visualizations in Excel? Well, so it's a little hard to answer, only because I think that these two things you need to know are platform agnostic, no matter what software you're working in. Never use the default colors, because it just looks like you don't you didn't try hard.
Speaker: And I can spot the tableau default colors from a mile away now too. I'm sure a lot of people can. And always give your title the so what, make your title a declarative sentence that tells you something about the data that you're trying to show. I mean, I think titles are one of the most important ways we have to frame the story in our data sets. And we just don't use them very much. We have these generic titles like
Speaker: sales rates and everybody is like, so what about the sales rates? So if we just use the opportunity to say something important that we want people to know about the data set, I think we're in a better place. So good titles and anything but the default color schemes. And again, like I said, you can do that in any software. Yeah. No, I agree with you on the titles. Here's my hypothesis that people think
Speaker: that if they say something about the chart, that they are somehow imparting some bias, you know, their own bias for the reader. Sales over time, instead of saying sales have grown over time, which they've said in the text, but for some reason they're, people are sort of, they don't want to say it in the chart. I don't quite understand why. Yeah. Yeah. It's so true. Well, and I think it comes back again to that academic upbringing.
Speaker: Um, where you're taught to just be so neutral and objective and let the reader come to some conclusions and things like that. And I tell people that that might be appropriate for like a journal article where your audience is that peers, other nerds who do want to dig through that and look at it on their own. But for the rest of us on the whole, when we get into like, when we get out of academia and into jobs.
Speaker: people are actually paying us to tell them the answer. Like that's what we got hired for was to find out the results and tell them, and they don't want to have to spend half their day digging through to find out what that is. So better to just tell them up. And then of course, you know, if they people want to explore the data and look for other stories, it's right there inside the graph. Yeah, right.
Speaker: So changing the default colors, awesome. More active titles that have an impact have a message or story. What about the actual nitty gritty of making a chart in Excel? What do you find that people just seem to miss or can improve upon generally? Are there things that you've seen when you're teaching people that you're like, oh yeah, this is the same thing I've seen 100 times before that people don't recognize or realize that they can do?
Speaker: Yeah, it's one of the things that I think has been so consistent lately is the need to get rid of the lines. And I wish there was a more elegant way to say it. Maybe Tufti would call it the clutter or the noise. And I see people because it's such anything they miss who are so focused on the graph type itself or the colors that are in it or the title that we miss.
Speaker: All the little tick marks and the dark grid lines and the chart borders and the axes lines and all those things are really most of the time unnecessary. But we forget about them. It's one of those things that you don't even notice.
Speaker: that it's there until you see a graph without it and you're like, wow, that's so clean. And it's like, yeah, I just took out all the, all the lines. Um, and I see it happening in, um, tables too. I mean, I know that we're never going to completely get rid of tables. They've got to roll out there in the world, but people put tables in these like dark black boxes. Every single one is in this like black box, these
Speaker: thick borders and it's so it feels so intense and so overwhelming and people are just like I don't understand why it feels overwhelming because it's a table but the answer is it's all the lines. So I think it's something that's easy to overlook but it goes a really long way in taking care of a graph and making it look cleaner regardless of the graph type that you're choosing.
Speaker: Let's take a detour for a moment and talk about all the other stuff that you're doing because I'm sure you have a lot going on. You've had a nice vacation, had a nice summer, but now it's back to it, right? So what do you have? Let's talk about travel and presentations for a little bit since that's where you and I got our start in the podcasting world. So what are you looking forward to in terms of presenting this year or at least let's say in the next few months?
Speaker: Yeah, well, I'm leaving on Tuesday for Hawaii. Okay, so that's pretty good right there. That's pretty good. I'm going to Indiana in a few weeks. Yes, John. All right, you're going to Hawaii. That sounds pretty good.
Speaker: Yeah, that'll be great. It is. It's gonna be a really nice year. I'm working with AOL this year and Goodwill Industries. So I'll be in New York and I'll be in DC and I'll be in Atlanta and I'm working with the Kauffman Foundation. So I get to go to I think that's Kansas City, which I'm sure is really awesome. Yeah.
Speaker: So yeah, it's going to be a really great travel schedule through the end of this year, and it is like completely already booked through the end of 2016. And in the process, on those plane rides, I'm going to be working on the second edition of my first book. Oh, there you go. That's like the only time I ever find to write, yes. Because why not? Just add it on top. It's a challenge. So I was just going to say, the second edition of the first book, we're doing the first book now in full color. So it's not just even a simple update.
Speaker: Like a complete radio of every single visual every figure that's in the whole thing there you go I'm not just fixing the typos, but actually reworking a lot of it. Yeah, it's a substantial difference for sure now review are you prepping any Substantially new talks for the next few months are these a lot of your bread -and -butter talks where maybe some tweaks here and there was anything you're sort of starting from scratch and
Speaker: That's a good question. The answer is yes. At the American Evaluation Association, that's my home team, we've got a conference in Atlanta in October.
Speaker: presents some research that we are wrapping up right now that looks at actual use of research reports from people like you guys, policy places, think tanks, and that sort of thing, and connecting it to their graphic design and data visualization.
Speaker: We're actually checking on whether those kinds of graphic enhancements have any kind of impact on subsequent use in real life by actual policymakers. Actual people. So the result of that are, yeah, like real use, not just use by dudes on canonical Turk, or theoretical use, or what I prefer, but no actual real use in real life. Right. Which I think we really need some data around that. Interesting. That sounds interesting.
Speaker: Yeah. You also just launched your new online video data vis lessons that you're calling right evergreen data visualization academy. You want to talk about that a little bit? That's right.
Speaker: Yeah, so this is another way to put my workshop content into the hands and brains on the hearts of more people because I'm basically taking the workshop we do that's hands -on and putting it all online. So we've got videos in there, video tutorials on the step -by -step instructions on how to make the things like .plus.
Speaker: And we've also got the tutorials in R. So if you are a person who's like really geeked out about R, you can go there and get the code and see the screenshots on what it should look like at each stage of the way.
Speaker: We've got templates for people who are short on time and just need to pop something in there. The forum is also great. People have been making great use of that so far. So they're putting in their own dot plots to get feedback. And so it's like some real -time coaching from peers and from me, which is hard to get. So that's super fun. Plus, we've got fun stuff in there, here and there. So how is moving to R? From primarily using Excel to doing coding in R, how is that working for you?
Speaker: Yeah, no, I'm not doing it. I got a guy. You got a guy. I got a guy to do that for. Yeah. I got a guy. I got a guy over here. He's great. I've been working with him for a long time. He did some art tutorials for my book, too, that are on the student companion site for the book. But he's done many, many more that are all part of the academy.
Speaker: I don't have to mess with any of it. He's great and he's getting certified in Tableau too. So I think we might see some of that coming out as well. That's great. That's great. Yeah. Have the whole suite of tools and you just have to start. Then you got to get a guy to do D3 for you and you'd have the whole suite. Yeah, right.
Speaker: I don't know if I can go that far. Yeah. That's like a whole other level. Cool. What else have we missed? We have lots of talks. You're getting to Hawaii and Kansas City and DC, of course, and New York. Lots of travel. You've got your academies. I'm sure you have other fun projects in the works. Anything else you want to talk about?
Speaker: Yes, one of the other small projects that's super fun right now, we've got a Kickstarter campaign going with my friends over at Fast Forward Consulting, where we made playing cards that are chart -choosers. So it's a slight modification on the chart -chooser that's on the inside of my book, but a significant amount of overlap. And we've got them in a deck of cards that you can get on Kickstarter. And I'm sure you know how Kickstarter works. There's different levels of purchase.
Speaker: One of them is you get all the Excel templates and you get all the Tableau templates to make all these cool graphs, yeah. And you can get the infographic that we have of our chart chooser and then the biggest level you can pick is access to the Academy along with a deck of playing cards. So that's super fun.
Speaker: Yeah, so there's still room for the Kickstarter, and we have a couple of seats left in the Academy. But everything is selling like hotcakes. That's great. So this is good. That's great. Well, good luck with all of the activities you have going on, and of course with the edits to the next edition of your first book. Thank you. And thanks for coming on the show. It's been fun doing another podcast with you. It's like old times. I know, John. I super love it. Thanks for having me on.
Speaker: All right, thanks for coming. And everyone, thanks for tuning in to this week's episode. If you have comments or suggestions, please let me know and please do rate the show on iTunes or Stitcher or your favorite podcast provider to let other folks know about the show. So until next time, this has been the Policy Vis Podcast. Thanks so much for listening.
Speaker: This episode of the PolicyViz podcast is brought to you by JUMP's Statistical Discovery Software from SAS. JUMP's powerful, easy -to -use visualization capabilities allow you to both explore your data for hidden insights and create interactive graphics that tell a compelling story. Enhance your presentations with dynamic graphics powered by world -class analytics in JUMP.
Speaker: Visit www .jmp .com to download a 30 -day free trial to see for yourself how with JUMP, data visualization and exploratory analysis go hand in hand.
