Pop Viz: Gotta Viz Em All

November 6, 2013

Screenshot of Pokemon Dashboard

This is the first of hopefully many Pokemon dashboards. Originally, I put the cart before the horse a bit and instantly wanted to do some really complicated probability dashboards. Turns out I’m not good enough at math and database structures to figure out what needs to happen to do that yet. I still want to, so if any Pokemon statisticians out there want to help, I’d be much obliged.

This is what I looked like trying to write SQL to connect the pokedex to the type multipliers table.

In the mean time, I thought I’d whet my appetite with a basic Pokemon dashboard. On this dashboard, you can use the buttons at the top to select the type of Pokemon you want to see. You can use the dropdowns below the buttons to choose which metrics you want to see. Your options are Attack, Defense, Speed, and HP (Hit Points). I’ve put reference lines at the averages so that we have kind of a quadrant chart going on. Explore it yourself:

Learn About Tableau

UPDATE: Some folks on Reddit were asking for a larger version, so here it is!

Dealing with 718 Pokemon Shapes in Tableau

October 30, 2013

Yesterday, we published an awesome blog post on the Tableau Public blog by the always hilarious Ryan Robitaille. When describing the importance of effective visual communication he joked “it would be a shame for your detailed Pokemon analysis to go unnoticed.”

Yay! Ryan makes jokes aimed at my generation!

I chuckled at that for a good, long while. And then I asked myself, “Wait… why haven’t I done a detailed Pokemon analysis yet?” I was able to find a couple of examples of Pokemon dashboards in Tableau, but nothing that knocked my socks off. It almost seems silly that there hasn’t been tons of Pokemon dashboards, considering that it is a game based entirely on math and statistics. And there just happens to be TONS of data out there for it.

OMG!!! SO MUCH DATA!!!!!!!!

So, I have been exploring some ideas using a variety of different Pokemon datasets I found. The very first thing I thought to do was import all the sprites as shapes so that I could make an awesome scatter plot of attack points versus defense points. There’s just one problem…there are 718 Pokemon. Anyone who has ever really dealt with custom shapes in Tableau before probably looks like this right now:
718 shapes?!?! Can we just viz the original 151?

Tableau doesn’t make it super easy to assign shapes to things. Really, the only dialog you have is this box:

Yeah, this is the actual size of this window.

There isn’t a list view. There actually isn’t any way of viewing the names of the images at all. All you can do is look at the tiny little image and try to match it up with the appropriate Pokemon on the left. As you can imagine, that would take FOREVER. Especially with 718 Pokemon. Especially since I really have no idea what 567 of those Pokemon look like.

Luckily, I realized something today that is going to really simplify this entire process. When Tableau brings custom shape files into the above dialog, it does so alphabetically! So, since my sprites are already numbered, they should all come into Tableau perfectly, right? I can totally just hit “assign shapes” and everything will work out! Please?

Not quite. I ran into a couple snags. First, despite the fact that all of my Pokemon sprites were already named by their numbers, the way alphabetical sorting works makes anything start with a 1 go before anything with a 2 and so on. So instead of going 1,2,3 the order is 1,10,100,11, etc. Luckily, this is really only a problem for the first 100 Pokemon, so I went through the files and added zeros so that the order would be preserved.

The second problem is that the Pokemon are in alphabetical order by name. But that’s easily fixed by sorting the names. However, it’s a little weird. I have a field for number, which I can use to put the names in order. However, when you sort by a field you have to aggregate it somehow. It’s a little strange. Luckily, sorting by either minimum or maximum basically just takes that one number anyway.

Sort sort sort, sort sort sort, sort your dimensions.

(As I’m writing this, I’m just now realizing I probably just could’ve put # on shape and saved me that last step. Silly me!)

Once I got those issues out of the way, assigning my sprites was as easily as clicking “Assign Palette”! So, the moral of the story here is if you are going to be using a crap ton of shape files, name them in a way that matches up with the dimension you are assigning to them and it’ll be WAAAAYYYYY easier to deal with.

Custom shapes aren’t as scary as I once thought! But, the experience could still definitely be improved. Here’s an idea from the Community site about labeling the icons with their file names, which would definitely make things way easier. So now that I have my super awesome shapes in place, I can get cracking at making something cool. Here’s a sneak peak of my shapes in action:

pokemonscatter

Pop Viz: US Top Baby Names Since 1910 and #JAWS2013

October 26, 2013

I’m here in beautiful Essex, Vermont hanging out with some awesome women at the 2013 Journalism and Women Symposium (JAWS) Camp. I did a panel today, sharing the spotlight with Kathy Kiely from the Sunlight Foundation. They do some really awesome work making political data more accessible. I was especially tickled with the premise of their project politicalpartytime.org, which crowdsources and maps out political fundraising events.

I’m excited for tomorrow, when I will hold an hour-long Tableau Public training here at JAWS Camp. Learning how to use a new piece of software is already hard enough, so I like to use datasets that are more on the fun side, to make things a little more interesting. I also like to avoid datasets that are too specialized (e.g. economic datasets) because I don’t want to have to spend too much time explaining what all the data is. For this training, I was inspired by this cool map that Jezebel published about the top girl’s names by state since 1910. The gif action is cool, but I really wished I could’ve paused it and explored things for a second. The whole dataset from the SSA actually contains way more than just the top name in each state; it has every name with more than 5 occurrences in a state. That dataset ends up being over 5.5 million rows; too big for Tableau Public (but it is fun stuff to play with), so I filtered the data down to just the top names for boys and girls. I whipped up a little dashboard on the flight over yesterday that is pretty fun to play with:

Learn About Tableau

Findings:

Also: If you are interested in how I built this viz, you can take a look at the tutorial I built for JAWS attendees.

Pop Viz: Spooky or Sexy? Halloween Costumes Dashboard

October 18, 2013

Happy October, dear readers! If you still haven’t picked a Halloween costume, don’t fret! I’ve made a little dashboard based on data I scraped from Buycostumes.com via Import.io. You can use it to explore costumes that are “sexy” versus “spooky”. And once you decide what you are going to be for Halloween, you can fill out my costume survey, which I will turn into a viz sometime next week!

Here’s the dashboard:

Learn About Tableau

A few findings:

On the Tableau Public blog: Creating and Utilizing Custom Shapes

October 7, 2013

Want to learn how to do awesome stuff like use Game of Thrones sigils to make sweet lollipop charts?

Game of Thrones Lollipop chart

Check out my post on the Tableau Public blog on creating and utilizing custom shapes! If you haven’t been following the Tableau Public blog, we are one week into Design Month and we’ve already got tons of great content! Peter Gilks wrote a great post about the design thought that went into his viz about New York City Skyscrapers. Iron Viz champion Ryan Sleeper also came up with a great post about color theory. And if YOU post your tips, tricks, and thoughts on design in Tableau on your blog, you can win a DATA hoodie! Check it out and stay tuned to the blog all month. We’ve got lots of exciting stuff lined up for you over there!

Behind the scenes: Making the author profile finder

September 27, 2013

Recommended Authors

If you haven’t seen it already, I made a little application to find author profiles on Tableau Public. I was pretty happy with the way it turned out. It’s crazy how a few simple shapes and some custom fonts can really make a dashboard look a lot more organized. A few people have asked me how I did some of the custom styling on the dashboard, so I thought I’d make a little tutorial here.

I use GIMP for most of my design work, mostly because I was a poor college student when I was first teaching myself graphics and couldn’t afford Photoshop, and now I’m used to it. It’s a great tool, being free and all, but I know there’s a bit of a learning curve. But, everything I made for this dashboard was totally easy and beginner friendly.

I designed the basic sheets and dashboard interaction before I touched any images. It may look complicated but when you remove all the custom images, my dashboard is really just 2 tables and 4 sheets. The images of the featured authors are laid out in a table with their pictures set as custom shapes. The other table just a text table with a wildcard quickfilter on the field for “display name.” The name, description, profile link, and featured viz are all each their own sheet being filtered to only show information for the last person clicked on. If you take away all the images, this what you are left with.

dashboard without any images

 

I wanted away to separate sections but at the same time make everything fit together a little more, so that’s how the module idea came about. Plus, all the rounded rectangles reminded me of pills on the column/row shelves so I thought it looked mildly Tableau looking. As you can see in the image above, I had already been working a particular color scheme in mind. It’s a bright, fun palette I found on colourlovers called “Ocean Five”

Ocean_Five
Color by COLOURlovers

I had also decided that I wanted the titles to have a more decorative font, so I used one called “Qlassik” that I found on dafont.com. Since I had already basically placed things on the dashboard, I knew about what sizes I needed all the shapes to be. I used SnagIt to measure the size each of the boxes needed to be so that I could make my shapes fit nicely.

Making the shapes is super easy. This was the process:

  1. Create a new file that is the dimensions I need the shape to be.
  2. Use the paint bucket to fill it with the desired color. Use the text tool to add the title.Creating an image
  3. In the Menu go to Filters>Decor>Round Corners… Selecting Rounded Corners
  4. Uncheck “Add drop-shadow”
  5. You now how a nice little container to float your sheets on top of.

Feature Viz Box

 

 

Repeat the process a couple times and there you have it! If you like easy design tips like this, you are going to love October on the Tableau Public website because it is design month! I know that I’m excited to share all my design tips with you and I can’t wait to hear some of yours!

Pop Viz: Hello Etsy aka The Cutest Viz EVER

September 17, 2013

Oh man guys, I had some fun with this one. What you are about to feast your eyes on is data scraped from Etsy using IFTTT, which is quickly becoming my favorite set-it-and-forget-it data tool. I scraped anything tagged “Hello Kitty” from August 14th to September 17th.

I didn’t expect any crazy revelations in the data besides that there is A LOT of Hello Kitty crap on Etsy. And most of it is under $5 it seems! I really wanted to do this because I knew it would be a blast to design. And oh man it was.

To start with, I used an adorable color palette I found on colorlouvers.com:

(◕〝◕)
Color by COLOURlovers

I followed the instructions to add colors to my preferences file. Originally, I had this in as a “regular” palette, meaning that it was meant for discrete data. But, it looks pretty continuous to me, and all my data was continuous, so I made it an ordered diverging palette! Weee! Isn’t this fun already?!

Next, I wanted the text to be just as adorable as the colors. I switched pretty much everything to Comic Sans (I know… boo! hiss! but John Maeda said it was ok at his TCC13 Keynote!). I also downloaded a sweet font off of dafont.com called “Loveness Three”

I grabbed a vector image of Hello Kitty and blew it up really big to make the header. I felt it was a particular stroke of genius to put the hover help menu (my signature trick!) in her bow. How nifty!

I’ll go into more detail about the design work behind this viz next month, since it will be Design month at Tableau Public! Without further ado, here’s a dashboard with more hot pink than you will ever see on Tableau Public ever again:

Learn About Tableau

P.S. If you hover around a little bit, you may find a little Easter egg. Tweet me a screenshot of it by 5pm PST on 9/18/2013 to be entered in a random drawing for the Tableau t-shirt of your choice!

Top Picks for TCC13 Breakout Sessions

September 8, 2013
Here to help with all of your session-picking needs!

Here to help with all of your session-picking needs!

I’m here at TCC13 doing my duties as a Content Guru! As such, I’ve got the low-down on all the breakout sessions and have rounded up the sessions I think will be the most valuable to Tableau Public publishers.

Monday:

08:30am-09:30am: How to Create a Viz that Demands Attention with Anya A’Hearn, Kelly Martin, Ryan Sleeper, Ramon Martinez and Ben Jones, Woodrow Wilson A
09:45am-10:45am: Rapid-Fire Tips & Ticks with Kelly Martin, Anya A’Hearn, Ray Randall, Michael Kovner and Dan Hom, Woodrow Wilson A
09:45am-10:45am: Making Flow Happen: Dashboard that Persuade, Inform & Engage with Jeff Pettiross, Chesapeake 1-3
11:00am-12:00pm: Actions Get Reactions with Ray Randall and Guilherme Bronner, Maryland B
11:00am-12:00pm: Let’s Talk About Text Baby: Do More with Your Titles, Labels, Tooltips with James Baker, Cheasapeake 1-3
11:00am-12:00pm: Extreme Viz Makeover with Jock Mackinlay, Erin Easter, and Ben Jones, Woodrow Wilson A
04:00pm-05:00pm: Rapid-Fire Tips & Tricks with Ryan Sleeper, Craig Bloodworth, Mike Klacyznski, Jewel Loree, and Dan Hom, Woodrow Wilson A

Tuesday:

09:45am-10:45am: The Art & Science of the Zen Masters, Jesse Gebhardt and Ryan Robataille, Woodrow Wilson A
09:45am-10:45am: Visual Storytelling in the Age of Data, Robert Kosara, Chesapeake A-C
11:00am-12:00pm: Using Design & Emotion to Create an Impactful Data Visualization, Anya A’Hearn, National Harbor 6-7
03:00pm-04:00pm: Hands-On Visual Best Practices, Amanda Pype and Molly Monsey, Woodrow Wilson A
03:00pm-04:00pm: Making Art with Tableau: How I Made the Kraken, Andy Cotgreave, Chesapeake 7-9
03:00pm-05:15pm: Building Better Dashboards, Michael Carpenter and Alexandria Skrivanich, Maryland C
04:15pm-05:15pm: Effective Data Storytelling with Tableau, Robert Kosara, Chesapeake 4-6

Wednesday:

09:45am-10:45am: 3rd Annual Iron Viz Championship, Woodrow Wilson A
11:00am-12:00pm: Advanced Social Media with Tableau, Mike Klacynski, Chesapeake 7-9
03:30pm-06:30pm: Fanalytics: Feed Your Passion for Data, Ben Jones, Adam McCann, Craig Bloodworth, Ramon Martinez, National Harbor 4

I’ll be floating around the different answers desks, as well as presenting in the second Rapid-Fire Tips & Tricks sessions and co-hosting Iron Viz. If you see me, don’t forget to hi!

Pop Viz: Rating Pac12 Professors

September 5, 2013

It’s Fall and school is starting all over the country. I put together a little viz to help current college students see what they are up against this semester and current high school seniors pick a school for themselves. This one is limited to the Pac12, but I’ll probably throw together the same thing for all the Division I schools.

The data is all scraped from Ratemyprofessors.com. My fellow Tableau Public data analyst, Mike Klacyznski, turned me on to a pretty awesome tool called Import.io.If you’d like to know a little more about how it works, check out Mike’s awesome blog post about using it.

Here’s the viz!

Learn About Tableau

Findings

What my most viewed viz ever taught me last week: The Internet is for Porn.

September 3, 2013

So, last week, I reached accidental internet stardom for a very silly reason. I opened up Twitter and saw this Tweet:

Pornhub’s US Average Visit Duration and Top 3 Search Terms by State http://t.co/uW25FuD7Zh via @tableau

— ALONZEAU (@ALONZEAU972) August 26, 2013

 

Which led to a viz that at the time looked like this:
Original Pornhub Viz

The original viz was created by a mysterious group (for which I have no contact information so please stop asking!) called the “Pornhub Stats Division.” What you are looking at is the average duration on the website Pornhub and the top 3 searches in each state.The data was so intriguing, but it was apparent that whoever made this was new to Tableau and was missing some of the finishing touches. I wanted to give it a quick facelift so that it the information would be more digestable, so I did. I liked what they did with the formatting of the bar chart on the original. It matched their logo and it really popped. So, I went ahead and changed the map to a dark map (From the menu: Map>Map Options>Style>Dark) and changed the dashboard formatting to a black background (Dashboard>Format>Shading>Default). I also got rid of the table at the side since I didn’t feel it added much. I used duration to color the states and had the top search display as text. I also cleaned up the tool tips a bit. If I had been feeling like spending a little more time on it, I would’ve floated Alaska and Hawaii under the U.S. so that you could easily see them too. If I had felt like spending a lot more time, I would’ve reformatted the data so that you could click on a search term and see all the states that had that in their top 3 searches. But, it felt kind of weird to have it say certain words all over my monitor at work. Anyway, this is how it turned out.

Learn About Tableau

I was really happy to see that they later made similar design changes. I still think they should change the dashboard formatting to be black though. 😉

Naturally, I posted it to Reddit. Then all hell broke loose. The viz was reposted in it’s original form across several subreddits and made a few more as a static image.

Whoa, guys, wait. Reddit likes porn?

It then made it’s way to a number of blogs, starting with Jezebel, then Gizmodo, Business Insider, a variety of local news blogs, and finally the crème de la crème of internet journalism, Cracked.com (in list form of course!)

The tweets were (and still are) pouring in. I was getting random emails from friends and colleagues about the viz. It started gaining thousands of views an hour. I permalinked the original behind mine, as to not steal the original author’s thunder. Now both vizzes are pushing 300k views. It was definitely the top viewed viz last week.

A couple of thoughts:

If I was Pornhub, this is how I would follow up:

In closing, what did last week teach us, boys and girls? As the good folks at Avenue Q so eloquently put it:

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