As some of you may know, I identify as “new to data”. In short, I don’t know what I’m doing!!!
A little backstory about me: I’ve been a business analyst since 2016. Recently, I’ve changed course and now am working more in business intelligence. I am both excited and scared out of my mind about it because, while I get to do more of the stuff I love at work, I also feel like I have to skill up.
That’s why I started following the #datafam hashtag earlier this year and likewise began hanging out with the Data Visualization Society on Slack. I figured if I put myself in a room where everyone else knows more than me, I’m bound to learn something.
And learn, I have! What I love the most about the data communities is how openly everyone shares information, like how to do things! Every week I find myself saying, “Wow, look at that cool tutorial. I should try that.” Well, this is me trying that.
Welcome to Tutorial Tuesday! In what I hope will be a regular series, I, a total and utter data noob, pick a tutorial and try to get through it – and I’m inviting you to follow along! Key points I’ll be hitting:
- How hard it was for a total neophyte like me
- What skills I learned/improved
- Any tweaks I added to the viz afterward
Sound good? Alright, I’m excited! Let’s get into it!
Today’s Tutorial: CJ Maye’s Tackling Radar Charts
CJ’s always got excellent tutorials. His most recent post on Radar Charts will be my first official try at following along with one! You can check it out here:
Why this tutorial?
I’ve been looking for how to do radar charts in Tableau. I have a personal reason to make a good radar chart: my cat. He just came back from the vet. She says he’s overweight.
I don’t see it myself, but I’m not a vet! Anyway, I love my fur baby and I trust my vet, so I’m counting his calories, but I also want to track his macro nutrient intake. I found a research paper that investigated what macro nutrient proportions cats inherently prefer. Long story short, cats seem to prefer their energy to come from:
- 52% from protein (fun cat fact: they are consummate carnivores)
- 36% from fats
- 12% from carbs
Like I said, I’m no vet, but ours suggested a reduction in calories and keeping an eye on what he’s eating. Being able to see at-a-glance how his food stacks up to this ideal would be a pretty sweet way to do that, hence my desire for a radar chart. Let’s see how it goes!
What’s in the Tutorial?
This one was a great one, in that it had three new things for me to learn:
- Creating background charts in Python (optional);
- Creating a radar chart in Tableau, and;
- Creating arced labels in Figma.
Here’s how I’d describe my starting skill level with each:
How’d it go?
Even though CJ said the Python was optional, I wanted to give it a try anyway. As you can see from my stats, I have no Python knowledge. Nada, Zilch. Before the #datafam, I thought Python was a snake. I like languages, so I think I like this definition of Python better. I’ve also never done anything in Figma. Tableau, my only bastion of knowledge. But it looks so lonely. Let’s see if we can add some company!
I think it went well! I installed Python and imported libs and ran the script and that’s not bad for a first-timer! CJ’s explanations of the Python calculations were top-notch. I felt like I could read Python for the first time. Now, I did run into an error which I decided not to troubleshoot because doing the above was victory enough for me. Totally not the tutorial’s doing – that was all human error. I’ll try again later when I have more time – I’m coming for you Python!
The Tableau portion went much more smoothly for me – and it was the first time I really felt confident with a radial anything in Tableau. Props to the teacher, again, for his clear explanation of the calcs.
The Figma part also went well! I cheated a little bit here, where I basically took CJ’s original template and switched out the letters in the positions that I needed for a 3-section radar chart. The exercise was enough for me to get the gist of Figma as a first-timer. Feels a little bit like Photoshop – is that bad to say? Do the Figma people hate that comparison?
Anyway, here’s my viz on Tableau Public:
You’ll notice I tweaked the final product – I created multiple radar charts, one for every food my cat eats, as well as one that combines his total food intake and displays the macro nutrients for that against the target macros. Finally, I used parameters to switch between the charts.
It feels good to have made it through the whole tutorial! I now have a way to see what I’m feeding my cat, and I learned some things along the way.
What did you learn?
First, I learned Python isn’t that scary. For my second time around, I’ll probably install PyCharm like CJ was using, or Anaconda, so I can operate in a virtual environment. It’s just a good idea in general. Happy to take suggestions on the simplest way.
Also, if anyone else who’s a total noob needs some help figuring out how to install Python and download matplotlib and numpy, here’s the YouTube video I used for that. Also, here’s a great YouTube playlist on Python for beginners by Corey Scafer – a great place to start if you like hands-on programming language learning.
Second: I learned Figma is super cool! I can see why people are using it in their visualizations. I can see myself using it to make my vizzes look more unique – well, starting after this one, since right now this one looks an awful lot like CJ’s final product.
Finally, it appears I’ve got my cat on a low-carb diet. Catkins? Reminder: I am totally not a vet. Nothing I’m saying about his diet should be taken as any kind of veterinary advice. Go talk to yours if you have any concerns about the food your cat is eating. That’s how this journey into Radar Charts started, and I’m glad for it!
This tutorial brought me a long way. Here are my stats post-tutorial:
It did take me two whole hours to do, (which is why my health bar took a hit), but that was mostly because of my Python wrestling and tweaking at the end. But it was worth the energy burn. If anything, I wear that as a badge of pride that I, a total noob, can do something new without crashing and burning! Which means, all you other new-to-data folks should definitely give CJ’s tutorial a try.
There you have it! Super big thanks to CJ Mayes for making this tutorial available. I love the personable way he shares his knowledge and recommend this tutorial for any noob! Check out this tutorial and more of CJ’s work on his website:
And if you want to check out the main sites for the applications/language discussed in the tutorial, here they are:
Made it all the way down here? Let me know what you think! Leave a reply, or talk to me on Twitter about this! Which Python IDE do you use? Also: any feedback for the viz? Let me know!
Update: August 5, 2021 – CJ to the Rescue! Python Vanquished!
After posting this article, CJ tweeted the loveliest shoutout and we had a talk about Python. With his coaching, I actually got the code to run without errors!
- pip freeze tells me things about package versions
- PyCharm Community isn’t scary – can totally recommend!
- I have too many drives. Next time I’m paying attention to where I set up my project folder!
Again, huge thanks to CJ Mayes. I literally subscribe to his newsletter – and you should too!
Thanks to Catoro Pets for feeding my cat
One more acknowledgement: special thanks to Catoro Pets for helping me feed my cat! Catoro is a cat cafe and pet store, and more importantly, an advocate for cat rehabilitation and rescue. They help find homes for cats who need the help. I love these guys and get all my cat collateral from them.
If you’re wondering what cat food is referenced in my viz, here they are. Note: these are Catoro affiliate links to the products. I earn a commission with every purchase, and you’d be purchasing from Catoro. You’d also be supporting them, which is a worthy cause.
If you do choose to purchase from them, note they are in Vancouver, Canada, just like me!