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. 😉
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.
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 Last.fm/Spotify 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 import.io to scrape Allmusic.com 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 Last.fm 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.
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.
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!!!!
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:
Having to build a website
Having to fight spam
Feeling pressured to keep it updated
Spending hours editing blog posts
Tinkering with my WordPress theme only to get frustrated eventually
Trying to get new readers when no one really reads personal blogs anymore
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!
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 import.io 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.
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’
I figured out what color red Buzzfeed uses using the Colorzilla Chrome App. I then applied this color all over the dashboard. The charts themselves are pretty simple and didn’t need a lot of different colors. That’s actually great because it allows us to really solidify this theme with the BuzzFeed red.
I made a banner to try to emulate the header on the BuzzFeed website. I poked around on FontSquirrel for a while until I found a font that was a close approximation. FontSquirrel is great because every font on there is free to download and licensed for commercial use.
I cleaned up the bar chart by hiding the header for titles and instead moving the title onto label. I like doing this a lot to bar charts because it allows you to use the maximum amount of space showing the data and you get to have long labels without them getting cut-off.
First: it was already in the viz before I started pimping it, but you’ll notice I have a parameter in the corner to switch between the different kinds of reactions. If you don’t already know how to use a parameter to switch between measures, here’s a helpful walk through from Nelson Davis. It’s definitely a trick every viz pimp should know!
Next to the parameter chooser, I put little emojis that reflect what the reactions are. Why emojis? Because it’s BuzzFeed and I’m a millennial and I don’t know how else to communicate emotions. Making the emojis had two parts. First, you have to create a folder of custom shapes. Then, you have to make a Case calculation, like what you make for switching variables with a parameter, but this time, you just say “WHEN Broken Heart THEN ‘Broken Heart'” as a way to get all the different options into one variable. The annoying thing is that only one parameter can be selected at a time, so you’ll have to go through and select every option in the parameter to change the emoji for it.
Under the BuzzFeed header, we have a little fake article headline written in the style of a BuzzFeed listicle. This took a couple steps.
I wanted to title to be based on whatever number in the histogram had the most reactions. So first I created a Rank calculation based on my parameter measure.
I made a table that had the measure [Number in Title] along rows and displayed labels. I set up the labels to say “ articles that prove that item listicles elict the most “” reactions”
I hid the header of [Number in Title]. Finally, I needed to hid everything but the number 1 ranked number. I used a Lookup calculation based on rank: “Lookup([Rank],0” to filter out anything that was ranked higher than zero. Now the only thing left is the number one ranked [Number in Title] and it dynamically changes with the parameter.
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:
Figure out how many coins you’ll need by determining how much one coin stands for. I went for each coin representing $19, as that was pretty much steadily the price of gold up until the 1960’s. I made a calculation called [Coin Count] which is quite simply the [Close] measure (closing price of gold) divided by 19.
Next, figure out what is the maximum number of coins you’ll need by visualizing the [Coin Count] measure. The tallest stack in my dataset was 2012, with 88 coins.
This part is tedious, so I recommend you do what I did and rewatch old episodes of “Gilmore Girls” while doing this part (especially in preparation for NEW EPISODES ON NETFLIX!!). We need to create a calculation for every possible coin in the stack, meaning 88 calculations. These calcs look something like this: “if sum([Coin Count]) > 1 then 1 end”. Repeat 88 times. This is what draws each of our coins on our chart.
Now we put [Measure Values] on Rows with [Year] on Columns and make sure that all 88 of our coin calcs are in the Measure Values window.
Lastly, we need a little flat coin custom shape. I found an image of coins stacked on top of each other on Google (remember, I’m not an artist…just a Google images curator) and cut out the top coin shape using the scissors tool in GIMP.
Some small design stuff: I changed the colors of the bubbles to reflect the Gold theme and added Scrooge McDuck diving into the piles of coins. I pointed out in my session, that although he’s totally useless here, using images with transparent parts can be used to do some cool things, for example this dashboard by Ancestry.com which uses a transparent house layered on top of a bar chart to make it look like the house is filling up with data.
Lastly, what kind of dashboard about gold doesn’t have BLING?!?! I created some glitter text using this glitter text generator. I then hosted the images on Imgur instead of linking directly to the images created by the generator. Why? Because Imgur supports HTTPS, which is crucial if you want your URLs to actually appear on the Tableau Public webpage. I added the glitter text gifs as web objects instead of as pictures because animated GIFs aren’t supported as images. Besides making this viz look ridiculous, the gifs don’t really add that much. But I thought of a borderline useful use-case for them!
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:
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.
Host the gif online (again, Imgure FTW!) and embed it on your dashboard as a web object.
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.
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:
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.
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.
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.
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?
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!
Finally, let’s wrap this up with some of my favorite tweets about my session.
I want to make sure we have as many amazing dancers as we can have, so I’m extending the deadline to submit #WatchMeViz videos to October 4th! So if you have time this weekend to do some sweet dance moves, please send them to me! Check out some of the current awesome submissions below: