Iterating on data collection practices for Pokemon Go

July 11, 2016

As I’m sure you can imagine (especially considering previous viz work I’ve done) the past couple of days have consisted of a lot of Pokemon Go for me.

Me walking around all weekend.

And like any good data nerd, a lot of my long poke-walks have been accompanied by thoughts about how to collect data on it. Apparently, I’m not the only one!

Okay, my fellow @Tableau #datarockstars. Please tell you are creating your own #PokemonGo data set as you play?


— Sean Miller (@kcmillersean) July 11, 2016

Go. When thinking through what the requirements should be I came up with this list:

I chose to go with an app I’ve used before for Quantified Self purposes, Nicholas Felton’s Reporter app for iPhone. The app has some really handy features like automatically geo-tagging reports, as well as adding step, weather, and photo data. You can totally customize what the questions the report asks and what kinds of answers you can give.

Adding a report

Initially, I set up questions to input which pokemon I caught and what their CP was. And, since it was just about time for my lunch break, I figured gong on a little walk and testing out my data collection couldn’t hurt. I’m glad I did because testing out my data collection process in the field helped me iterate on it and figure out what questions mattered.

All the pokemon I caught on my lunch break

As I walked, I hit a couple of Pokestops with lure modules on them. I was able to catch quite a few pokemon around them. I realized, that looking at the data, you would see a cluster of catches in this time period and might wonder why there were so many. So, I decided to add a question for if there was a lure module close by. At the same time, I realized that incense would have the similar effect, so I added a question for that, too.

I lure my pokemon like I do my interns, with lots of dranks and hella noms.

I continued my walk and hit another Pokestop where a Slowpoke was hanging out. I caught him and apparently his slowness spread to my phone, because upon catching him, my game froze. I’d estimate that around 40% of the time, the game freezes on me after I catch a pokemon. I’d like to be able to know an accurate percentage for that number. So, I added another question for if it froze or not while catching the pokemon.

“Wait….so did I actually catch that or nah?”

Going out in the real world and testing my data collection process helped me iterate on it and improve it. I was able to catch missing data earlier and it’ll lead to a more accurate dataset. The Reporter app makes it pretty easy to add new questions, so this whole experience really verified that it’s a good tool for the job. Unfortunately, Reporter is only for iOS, so if you have a suggestion for an app Android users could use, I’d love to hear it!

Now go out there and catch em all!

Pop Viz: Comparing Personality Traits on OkCupid

May 12, 2016

A couple days ago, I was thinking how it had been a while since I’ve made a new viz and I thought I’d head over to /r/datasets and see if I could find something interesting. What I ended up finding was the dataset of my dreams.

This dataset was compiled by some researchers from Denmark. It contains information on over 68k users and their question answers*. It’s pretty hefty and I’m still digging into it, but I wanted to throw something fun up here before I spend too much time falling down the rabbit hole. OkCupid is an incredibly rich source of data, as evidenced by their own data blog. Just to whet your appetite of things to come from this amazing dataset, I’ve made this exploratory viz to let you compare personality traits.

The main technology that drives OkCupid is it’s matching algorithm. It’s based on questions it asks you in which you choose your answer and how’d you like the other person to answer. These questions are all broken up into categories and also used to generate scores for different “personality traits.” For those who are curious here’s most of mine, minus some less safe for work ones. 😉

My OkCupid Personality traits

On that note, here’s the viz! More to come, I’m sure.

*Update: There’s been some controversy over the ethics of this dataset. The authors have since removed it from the linked website. I had already removed the user name column from the dataset because it was extraneous and I didn’t need it. I’ve now also updated my viz to not include as much potentially identifying information such as location. I don’t feel that looking at this data without that stuff is unethical, but if you have thoughts on the matter, I’d love to hear them.

Pop Viz: The Effects of Spotify’s Discover Weekly Playlist

April 11, 2016

If you are a fan of my blog, I’m going to bet you are also a fan of Peter Gilks’ blog and saw this excellent viz looking at his data. He does a great job laying out how to keep/get this data for yourself. And I liked his viz so much that I decided to rip it off entirely, down to the little pic of me wearing headphones:

Peter had some other cool visualizations analyzing his taste. He had some nice ones about genre, which I would totally do if I didn’t have 3,520 distinct artists to categorize. I did have some success using to scrape to get that information for my Festival Finder viz last year, so maybe if I have time I’ll take a crack at doing that. One thing I did finally learn a little more about is LOD calculations, which I used to find when the first/last date that I played an artist was. With that I was able to make this cool gantt chart of my Top 20 artists. Check out how one day of mourning David Bowie was enough to put him in my Top 20 for Q1.

I’ve been using since 2006, so I have nearly a decade’s worth of music listening data to look through. I could probably create a whole blog just on my personal music listening habits, but I doubt that anyone would be all that interested in that besides me. However, I did start to scratch the surface of an interesting. About a year ago, Spotify started making these weekly curated playlists for their users called “Discover Weekly.” Spotify uses all kinds of sophisticated recommendation engines to determine what to add to each user’s individualized playlists. After giving them a try for a while, I learned that Spotify’s robots KNOW THEIR SHIT. So, I made the Discover Weekly playlist a part of my music listening routine. As such, I’ve seen a bit of a jump in the number of new-to-me artists I listen to, especially on Mondays, when the playlist comes out. Check it out in the story below:

This is just scratching the surface of the kinds of analysis I want to do about Discover Weekly. Coming up, I’m going to see how often they get things right, if what I’m currently listening to has an effect on what Spotify recommends me, and how much of their playlists are actual new artists to me and not just tracks I don’t listen to as much from artists I already love.

Exciting New Changes

April 7, 2016

It was over three years ago that I joined the Tableau Public team. I was just a fresh-faced kid fleeing a terrible, abusive first job, ready to take the data world by storm.

I didn’t know back then how much I would fall in love. With Tableau. With dataviz. With the wonderful community that we’ve built together. Together, you’ve helped take me from spending 2 days building this:

to spending 2 hours building this:

I feel honored and blessed to be a part of all it. I’ve worked with some amazingly talented, brilliant, creative, and just all around good people, both inside and outside of the Tableau Public team. I’ve learned so much from all of you. And while, I’ve greatly enjoyed helping grow this community and evangelizing Tableau Public, the time has come for a new challenge. I’m leaving the Tableau Public team.

Luckily, I’m not moving far. I’m staying with Tableau and starting a new role in our development organization as a Product Manager! I will be helping our team develop and improve Tableau’s storytelling features. And while it’s hard to leave behind my wonderful team of brilliant Tableau Publicans, I’m incredibly excited to be able to help make the product that I’ve grown to care for so much even better.

As I make this exciting move, I just want to say thank you to the community, to my team, and especially to Ben Jones. He’s really been the most wonderful and supportive manager and mentor I could ever dream of. It’s been an honor being your right-hand woman for the last 3 years and I’m going to miss working with you every day immensely.

I just want to reassure you, my lovely readers, that this does NOT mean I will stop vizzing, blogging, tweeting, or participating in the community. I plan to stay just as active, even as I make the transition from Marketing to Development. And yes, I will still be running Iron Viz, because you will have to pry that bell pepper out of my cold, dead hands.

Pop Viz: What Music Matters Most to KEXP- 2015 Edition

February 25, 2016

It’s finally here! My annual analysis of the greatest radio station in the world KEXP is done!

I gave the mobile-compatible story style another go and published it here. It’s pretty! Open it on a phone! I go in-depth on how I used to get the data and provide a lot of background on KEXP’s programming.

Since the story is made for mobile, there are a few of the exploratory style dashboards that I didn’t put since they don’t scale well. I’ll put them here instead:

Artist Exploration

DJ Exploration

Data Feed: 757 .csv Datasets

February 8, 2016

Make it rain (data)!

Click here to view the datasets.

Pop Viz: David Bowie Tour History

January 11, 2016

In case you haven’t heard, a great man and artist passed away last night, just days after his 69th birthday. That man was David Fucking Bowie. I’m devastated. And I’m mourning the only way I know how, with data. I threw together this visualization where you can track David Bowie’s tour history. I’ve also tried to hunt down a video from every tour on Youtube, so clicking on the tours in the bar chart below should open those up. I’m a little frustrated with the Path maps: it’s breaking up the paths by country. It also is showing a “*” for a lot of the dates and venues for when Mr. Bowie played a city multiple times, but adding those to the detail shelf messes up the path map even further. I’m guessing the solution is something having to do with LOD calcs, but I’m still experimenting. But, I wanted to get this out there so we can all start to heal.

UPDATE: My brilliant co-worker Richard Wesley had a super simple solution to my path map woes. Using Max([Country]) instead of [Country] still preserves all of the cities in places while also not using it as a dimension to divvy up the data. Thanks dude!!!!

Pop Viz: Neko Atsume and Trying a New Thing

December 11, 2015

Obviously, I like blogging about Tableau. I’ve held multiple panels on it, written articles, basically professed my love for it at every public opportunity I could get. However, there’s a lot not to love about it. Like:

Sure, I’ve had some success posting blog posts to Reddit every once in while, but the way people use the internet is different now. People want all of their content coming to them through one source, aggregators like Reddit, social media platforms like Facebook or Twitter, or curated content platforms like Medium. Content creators don’t want to deal with the hassle of maintaining a blog. And having a dedicated blog is a big commitment if you only have a couple ideas of things you want to make and talk about.

I still get a healthy amount of blog traffic from the Tableau community. But a big goal of my Pop Viz work (and my work on Tableau Public, in general) is to improve data literacy among the general populous. When I’m doing a Pop Viz post on something like music or Pokemon or whatever, I want fans of that thing to consume the viz. But fans of those things are confused when they come to my Tableau blog and there’s all this other weird content about graphs and data and what have you. To reach them, it’d be better to have these vizzes as standalone projects. I could always just send them to the viz homepage, but then I can’t add all the context that I want to. So, what should I do?

I’m experimenting with a new platform to solve just this problem. I want to make beautiful, responsive, Medium-like articles with data visualizations. Medium doesn’t allow for Tableau Public, but I found a tool that does. It’s called Atavist. It has a drag-and-drop interface to add different “Blocks” of content. One of the blocks you can add is and Embed code, and Tableau Public vizzes work there.

I’ve tested out this platform by making a little article about an iPhone game that all the women in my family have been obsessed with called “Neko Atsume”. So here it is, my article “Data Atsume”. Check it out and let me know what you think about this format! I think I might use it for projects like this where I’m making a bunch of vizzes on a very particular dataset and I want people to explore it. If any of you out there have avoided starting a blog for your data projects because of any of the pain points I listed at the start of this post, I encourage you to try to make a data story with this tool. And be sure to tweet it to me @jeweloree!

See my Neko Atsume Vizzes here!

P.S. It looks awesome on mobile.

Pop Viz: The Darth Jar Jar Theory

December 8, 2015

For the past couple weeks, every time I’m making small talk with someone and they mention their excitement for the new Star Wars movie, I quickly segue into “OMG. HAVE YOU HEARD THE DARTH JAR JAR THEORY?” Judging by some data analysis of Reddit that I’ve done; I’m not the only nerd doing this.


For those of a slightly less geeky nature, Jar Jar Binks is an incredibly unpopular character from Star Wars Episode 1: The Phantom Menace. As the title implies, someone in the film is supposed to be an unexpected bad guy. But, we never really find out who that is. By the end, we assume it’s Emperor Palpatine. However, some Star Wars super fans have posited that the Phantom Menace is an even more unexpected character: Jar Jar Binks. Check out this video to see the whole theory:

This theory really rose to prominence in a Reddit post last October. In the dashboard below, I used to scrape Reddit for any post containing “Jar Jar Binks”. You can see that prior to the theory becoming mainstream, the only people that routinely talked about Jar Jar were in the subreddit /r/whowouldwin, which pits all kinds of characters against each other and people debate who would win in that fight. After the theory, a whole subreddit on it /r/DarthJarJar because a popular place for people to suggest and discuss evidence for the theory of Jar Jar being a Sith lord.

Here’s the dashboard:

As for me…well:
I want to believe

#Data15: Pimp My Viz 2: Electric Boogaloo Follow-Up

October 26, 2015
10-26-2015 12-40-14 PM

I had a blast bringing back my weird point-of-view on making dashboards a little more fun to #Data15. Last year, I focused more on custom design and making things look as little like Tableau as possible. This year, I went a little more in the direction of doing some calculations and interactions that are a little more advanced. Let’s take a look at what I did!

But first, here’s the video I couldn’t get to play in my session:

Viz #1- Buzzfeed’s Most Viral Numbers

Ok, ok. Before you get too mad at me, yes. I admit it. I pimped my own viz. But it was out of desparation! All the vizzes submitted to me for Pimp My Viz were already too pimped out! Stop getting so good at Tableau, people! (Actually, don’t stop. It’s awesome.)

So here’s some stuff I did to make this dashboard a little more pimpin’



Viz #2- Price of Gold Over Time

This is a pimped out version of a viz originally by former Tableau intern and wunderkind Quinn Schiller. You may remember him as the badass who figured out how to use pages to make animated gifs in Tableau. In honor of that, GIFs were one of the key features when I made over his Price of Gold dashboard (which has some excellent annotations and storytelling in it!). Here’s what I did:

OMG! A useful application for gifs?!?!?!

You’ve gotta be kitten me!

It’s true! I thought of a useful application for gifs! I know I’m not alone in lamenting that using animation on the Pages shelf in Tableau doesn’t not work once published to Tableau Public or Server. But, we can use gifs to work around this! Check it out:

How is this done? It’s actually pretty simple:

  1. Create the gif. I used Camtasia, which I have for recording training videos, but that’s a pretty hefty piece of software. There’s plenty of free tools to create screen capture GIFs, so pick whichever one works best for you.
  2. Host the gif online (again, Imgure FTW!) and embed it on your dashboard as a web object.
  3. Float the sheet that you are animating on top of the web object. What we are basically doing is a variation on this trick I wrote about last year, to leave your viewers with a message when filters make your vizzes disappear.
  4. Last, we need to create a button to make the viz disappear and show the animated gif behind it. To do this, I created a calculation that equals “Null” for everything. I made a button out of it by creating a sheet, putting the calc on text, and setting a square shape in the background. I edited the text label to say “See/Stop Animation”. I added to my dashboard with a dashboard action that effects the scatter plot on click and where clearing the filter excludes everything. This is what makes the chart disappear and the gif behind it reveal itself.

5 Easy Ways to Pimp Your Viz

To end the session, I gave a rapid fire list of 5 easy ways to Pimp Your Viz. This was based on a blog post I did earlier in the year, but here are those steps again, just if you need a refresher:

  1. Colors. Don’t be satisfied with the default Tableau blue! I like using sites like Colourlovers to choose color palettes that aren’t built into Tableau. I also like that they limit their palettes to 5 colors, which makes you really think about how you are using your color. Ryan Sleeper wrote a pretty fantastic blog post about color a couple years ago that is still a great resource.
  2. Marks Card Magic. Along with changing the color, there’s plenty you can do with the Marks card to pimp out your viz a bit. Make your bars fatter! Add labels! The stuff I did to the bars in the BuzzFeed viz above is a good example of how simple changes on the marks card can make a pretty strong impact when it comes to making a viz look custom.
  3. Add a banner. A good title for your viz is a MUST. And you might as well take that opportunity to make a banner. Banners are great because you can communicate what the theme of your dashboard is and set the tone for what people are about to see. My typical banner strategy is to find an image related to what the dashboard is about, crop it, blur it, and add the title in a custom font. I often use Adobe Illustrator for this, but a few people in the viz design community have confessed to me they just use Powerpoint for this and it gets the job done. For a web based solution where you can create some REALLY gorgeous graphics for your vizzes, I highly recommend Canva. It’s a web based drag-and-drop design tool that’s super intuitive and has stock images built right in for you to use. I actually use it all the time for designing gig posters for my band and am just now starting to use it for viz work. But I have a feeling it’s going to be my go-to from now on.
  4. Clean up the tooltips. SWEET MOTHER OF GOD JUST CLEAN UP YOUR TOOLTIPS, OK?!?! You should NEVER EVER EVER publish a viz with default tooltips. I assure you, they look like unreadable crap 100% of the time. In my session, I said that if you don’t clean up your tooltips, little fairies will fly into your bedroom at night and punch you in the face. I’m not joking. Although, the little fairy might be me in a tutu and fair wings, but I assure you, you’ll get punched. In the face. You don’t want that do you? So just clean up your tooltips, ok?
  5. Thoughtful Interaction. A dashboard without interaction is like pizza without cheese…. an ABOMINATION. Think through how people might want to interact with the data you are presenting them and try to make the order of operations make sense. Make the order that you click things go from left-to-right and top-to-bottom since people in the Western world read that way. Have a friend look at your dashboard and just watch what they try to click on and make those the areas where you put your interaction. The more people play with your viz, the more they’ll remember it!
  6. Finally, let’s wrap this up with some of my favorite tweets about my session.

    Need more pimping? You can also watch the original Pimp My Viz session from TC14 in Seattle and read the followup!

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