Alright. So get this deep dive. It's gonna, like, totally change how you see book covers. You know? Yeah.

Like, forever. A bold statement. I like it. Right. Okay.

So you got this link right, a blog post by Eric Van Dornshund, all about designing a chemistry handbook cover. Okay. This is pretty standard so far. Yeah. Yeah.

But and here's the kicker. Get this. The cover itself, it is a data visualization. Oh, wow. Okay.

I'm intrigued. That's pretty cool. Right. Like, how cool is that? Yeah.

That's really cool. It's like, it's a really brilliant example of data storytelling, wouldn't you say? Oh, absolutely. It's like you see this, like, sleek design at first. Right?

Yeah. But then, wait a minute. It's showing you where people are engaging with this website, all mapped out across Mississippi. Yeah. And that's what makes us so clever.

He's taken something as simple as a book cover, right, and turned it into this, like, window into his audience. He can't help but be drawn in. You know? Like, what do those colors mean? What's going on?

Totally. It's like he's saying data can be, like, beautiful a and d informative. Exactly. Okay. So walk us through it.

Like, what are we actually seeing on this map? Okay. So the cover, it's showing us the counties in Mississippi. Okay. And each county, it's shaded based on website traffic.

So, like, how many people visited his website. And this is from 2020 to 2022. Okay. Got it. And he's used a color gradient from pink to blue.

Pink is high traffic, and blue means there were fewer visits. And I'm guessing that super pink county, that's gotta be where Mississippi State University is. You got it. Octaveah County, home to Mississippi State. It, like, really pops on the map.

Right? I did. Yeah. And here's a little detail I noticed. I don't know if you caught this.

He's marked the locations of Mississippi State and the University of Mississippi with these, like, subtle blue dots. Wait. Those dots aren't just for show. I thought those were just, like, part of the design. They are part of the design, but they're strategically placed.

It's like a little Easter egg, a nod to his background because he has connections to both those universities. Oh, that's awesome. I love that. Okay. But let's talk tech for a sec.

He mentions using rnggplot2 to create this. That's not, like, your average design software, is it? No. Not at all. And, you know, it really speaks to the fact that these powerful data visualization tools, they're becoming so much more accessible.

You don't need to be a coding whiz anymore to create compelling visuals. Yeah. That's so true. It's like democratizing data in a way. Yep.

But there's still a learning curve. Right? I mean, he mentions using a logarithmic scale for the color gradient. And I'll admit that one kinda went over my head. Oh, yeah.

That's a great question. And it highlights a really important concept in data visualization. Okay. So a logarithmic scale, it helps us visualize data that spans a really wide range of values. So think of it this way.

Instead of increasing linearly, the scale increases exponentially. Okay. So in this case, it helps him show both the subtle differences in traffic between, like, the low traffic counties and that huge spike at Mississippi State. Exactly. It's like, imagine you're, like, adjusting the contrast on a photo to reveal those hidden details.

Without it, the color differences might be too subtle to tell the full story. Oh, okay. That makes so much more sense now. Like, he's using the scale to highlight those nuances in the data. So what about the rest of the design, like, the colors?

Did he just use, like, the default color palette? He did not. Remember, this is someone who clearly cares about aesthetics. So he actually ditched the standard blue gradient that you might see in a lot of data visualizations. Instead, he used the, Grand Budapest 2 palette.

Okay. The what now? The Grand Budapest 2 palette. It's from the Wes Anderson package in r. Hold on.

Wes Anderson color palette. Yeah. Like, the filmmaker. The one and only. And I just I love that little detail.

It shows the level of detail and personality that he brought to this, and it's something that anyone can do with data visualization. Right? There's always room for creative expression even within these kind of technical aspects. That's so cool. I love that.

Okay. So we've got Wes Anderson color palettes. Yeah. We've got hidden dots that are like little Easter eggs. What else is there to uncover?

It's like he's taken data visualization Yeah. Like, beyond spreadsheets and charts, you know, and brought it into the real world. Totally. Yeah. He even talks about how we had to, like, really carefully choose the right font and placement for all the text on the cover, which I thought was interesting.

Oh, for sure. Because, yeah, even the typography can, like, make or break the design. Absolutely. And, like, he's using these specific tools, right, extra font and show text in art, to, like, meticulously position each word, like, from the book's title to his name, his affiliation. It's all about finding that sweet spot where the text complements the data visualization, but doesn't, like, overwhelm it.

You know? Yeah. Yeah. So it's like every little detail is intentional. Everything contributes to the overall impact.

Right. It's a great example of how data visualization, it's as much an art as it is a science. Totally. It reminds me of those, like, really intricate maps you see in museums sometimes. The ones with, like, beautiful calligraphy and illustrations.

They're not just conveying information. Right? They're telling a story. And that's the beauty of what he's done here. Right?

He's taken data, which, let's be honest, can often seem kind of dry and impersonal, and he's turned it into this, like, captivating visual narrative. Yeah. For sure. And, you know, it kinda makes you wonder, like, what other unexpected sources of data could we visualize? Like, I don't know.

Could we map out the emotions we experience throughout the day or, like, create a visual representation of our dreams? Now you're thinking outside the box. The possibilities are, like, truly endless. Imagine, like, visualizing the flow of conversations on social media or mapping the spread of ideas across different cultures. Woah.

Yeah. It's kinda wild to think about all that, like, hidden patterns and connections that we could uncover Mhmm. Even in seemingly unrelated areas just by visualizing the data. And that's what makes data visualization such a powerful tool for just, like, understanding the world around us. Right?

It allows us to see things from new perspectives, challenge our assumptions. It's really cool. Totally. But all this talk about the, like, possibilities of data visualization, it makes me wonder, like, what about the data itself? Didn't he have to gather information from all these different sources to make this happen?

Yeah. He did. He talks about how he started with his website traffic data, makes sense, right, from Google Analytics, but that only gave him part of the picture. Because Google Analytics wouldn't necessarily, like, break down the data by county. Exactly.

So he had to get creative. He supplemented his data with information from StatsAmerica. Okay. And what's StatsAmerica? So StatsAmerica, it's this great resource that provides demographic and statistical data at all these different geographical levels.

So he was able to find what he needed there. Oh, cool. So it sounds like he had to do some serious data wrangling to combine those sources. He did. He did.

What does that even entail? Like, what is data wrangling? Basically, it's the process of, you know, cleaning, transforming, and organizing data from different sources. Gotta get it all ready so you can actually analyze it and visualize it effectively. So it's like taking a jumbled jigsaw puzzle Mhmm.

And, like, meticulously sorting the pieces before you can even begin to see the bigger picture. Yeah. That's a great way to put it. And, honestly, it's a crucial step in so many data visualization projects. You rarely start with this perfectly clean and organized dataset.

Often, you really gotta roll up your sleeves and do some data wrangling to make sense of it all. It's kind of amazing, you know, when you think about it. Like, how much work actually goes on behind the scenes of a data visualization? Yeah. You don't always see the data wrangling and all the technical stuff, but it's, like, it's all so essential to the process.

Totally. It's like when you're, you know, building a house. You might be drawn to the, like, the beautiful facade, the way it looks, but it's the foundation, right, the framework that holds everything together. Yeah. That's such a good point.

This whole conversation, it's really got me thinking differently about data. It's not just, like, numbers on a spreadsheet. You know? It's a way of seeing the world, uncovering hidden stories, understanding ourselves and our communities better. That's what I find so exciting about data visualization.

It really does have this power to, like, make the invisible visible, connect seemingly, like, totally disparate ideas, and just spark new insights. And the best part, you don't need to be a data scientist, right, or a professional designer to tap into that power. Exactly. Like Eric's project, that's a perfect example. Even something as simple as a book cover, it could be this, like, canvas for data storytelling.

Totally. It's really cool. So I don't know. To our listener out there, I'd say just embrace your curiosity. Yeah.

Look around you. What data points, you know, exist in your daily life? What stories could they tell if you brought them to life through visualization? The possibilities really are kind of endless. Yeah.

It's such a good point to end on. This has been awesome. It's amazing to see how something as simple as a book cover can spark such a fascinating deep dive into data visualization, design, and even, like, the geography of Mississippi. Yeah. It's been fun.

So to our listeners, keep those creative sparks flying, and we'll catch you in our next deep dive.