Data House of Horrors Followup!

October 20, 2014

Thanks to the lovely folks at import.io for showing a super fun time last Thursday at our Halloween special webinar! If you logged on, you probably caught some of our “fancy dress” but in case you weren’t, this happened:


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Getting ready to get spooky with data on our @importio webinar!

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If you didn’t make it, never fear! It was recorded and you can watch the whole thing here:

I wanted to go a little more into detail about how to build this dashboard, so I’ll break it down piece by piece so that you can recreate it!

Bar Chart

Building the first bar chart is pretty easy. To start, put [Costume Category] on rows. Since there are duplicate rows (due to having one row for every word in a title), instead of using [Number of Records] we are going to do a CountDistinct([Prod ID]). You can do this by right-click dragging [Prod ID] to the columns shelf and then selecting Count Distinct, or by clicking the drop down menu on the Prod ID pill and then going to Measure>Count(Distinct). This means Tableau is now only counting each costume once.

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Histogram

Making the price histogram was also very simple. All you have to do is select [Price] in the Measures pane and then hit the histogram button in Show Me.blog2

If the bins that your histogram selects are too big or small you can edit them by finding [Price(Bin)] in the Dimensions pane, clicking the drop down and clicking “Edit”. This will allow you to change your bins to whatever size you’d like.
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Lastly, instead of doing a count on price, which will make for duplicate rows because of the join with the words, switch out [CNT(Price)] on the Rows shelf with [CNTD(Prod Id)].

Word Cloud

To create the word cloud, drag the [Words] on to text and [Number of Records] on size. At first, you’ll get a treemap. This is a good point to filter out some of the words to keep them mucking out the word cloud. I filtered out words like costume, adult, the, of, etc. You can just over over a square and click “Exclude”. Once you do that, you can switch the marks card from “Automatic” to “Text” to get a word cloud.
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Another thing I wanted to do was filter to only the top 30 words; that way nothing is too small. Since we already filtered on [Words] when we excluded “adult” and “costume” and the like, we can create a duplicate field for words and filter on that. If you click the drop down menu on [Words] you will find the Duplicate option. Click on this and drag it to the Filters shelf. Once you are there, click the tab that says “Top” and choose “By field:” and set it to the Top 30 by [Number of Records].
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Table

The table is pretty simple. Drag [Item] to rows and [Price] to label. Easy peasy. I also put [Prod Id] on Detail in the Marks card (you’ll see why later) and [Description] in the tooltip.

Hover Help Ghost

This is a trick I use all the time as it’s a great way to add context to your dashboard without taking up too much space. It’s been well documented before so I won’t go into too much detail. The only real thing I did differently was change the shape to a custom shape that looks like a little ghost. Read more about utilizing custom shapes here.

The “Sexy” button

To create this, I first went through all the words and created groups so that words like “Babe” and “Flirty” fell into the “Sexy” group and all other words counted as “Everything else”
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With the groups created and renamed to [Sexy Words] I created the “Sexy” button by dragging out [Sexy Words] to the text on the marks card and then editing the label by clicking on the Text button and editing it to say “Click here to bring back”. Then I put [Sexy Words] on filter and filtered to only show words in the “Sexy” group. Then, I edited the formatting to have borders and colors to make it look button like.

Dashboard Interactions

Tableau Public is great for rapidly creating a lot of different charts types like we did above, but the real power comes in making these charts interact with each other. This is done through “Dashboard Actions.” Now that all of our sheets are created, we can create a new dashboard and drag everything onto it. Then we can create a series of dashboard actions by going to Dashboard>Actions in the menu. Here’s all the actions I created:

Design considerations

I wanted the theme to be really obvious, so I did a bit of design work to make everything match the Halloween theme. First, I set the background color to all of my sheets and the dashboard to black and set the other colors to fit a theme. I based everything off of this color scheme:

Trick_or_Treat
Color by COLOURlovers

I even created custom color palettes in Tableau so that I could use those colors as a gradient in the data.

Another thing I did was create a set of custom titles out of a custom font I found on DaFont called “Scary Halloween”
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I also added a little tombstone image to the dashboard for the costume picture to load on top of.

So, that’s basically it! Our finished product looks pretty neat:

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So, that’s it! I hope you enjoyed the webinar and the dashboard!

Pop Viz: Barbie N-Grams

October 14, 2014

Several months ago, I was doing some Google searching to figure out what a Barbie Dream Boat is worth these days. The Barbie Dream Boat was basically my most prized possession as a kid. I got it for Christmas when I was 7. It came in a gigantic box. It had a pool that you could fill with water. AND IT HAD A BLENDER. I made so many virgin piña coladas in there.


In searching to see how much these go for these days, I stumbled upon BarbieValues.com. Being me, I was instantly excited about this repository of Barbie data. Unfortunately, my traditional methods of web scraping couldn’t handle this beast of a dataset. Thankfully, after pleading with the audience of my “Pokemon, Porn, and Pop Culture: Using data that doesn’t suck” session at this year’s Tableau Conference, a few super smart Tableau devs, specifically Charles Vaughn and Nathan Brandes, came to my rescue! This dataset is amazing and I have all kinds of plans on things to do with it. But for the first in my series of Barbie data vizzes, I created an n-gram search. You can use this to see occurrences of words or phrases in Barbie models and accessories over time. To create the n-gram search, I used a parameter method that Matt Francis recently blogged about. Check it out below:

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In future Barbie vizzes, we will figure out who her favorite friend is (Midge? Teresa? Skipper?) and explore the many, many careers she’s had.

Data House of Horrors: Halloween special with Tableau + import.io!

October 9, 2014

For those who don’t know, I’m on a bit of an extended trip working out of our London office right now. It’s been rad and one of the things I’m really excited about doing while I’m here is hanging out with my pals at Import.io. We are putting on a special Halloween edition webinar next Thursday, October 16th (my birthday!), to show how to scrape Buycostumes.com and build this viz in Tableau:

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You can use the viz above to find the perfect animal-ears-plus-lingerie combo, a la Mean Girls.

Hope to see you next Thursday!

Pop Viz: Pumpkin Spice Analytics

October 3, 2014

Fall is in full swing, so you know what that means: pumpkin spice lattes! Pumpkin spice muffins! Pumpkin spice doughnuts! Pumpkin spice bubble baths! And now… PUMPKIN SPICE ANALYTICS!

Also...PUMPKIN SPICE KITTIES!!!!

Making fun of the prominence of pumpkin spice seems to be the cool thing to do. The silly thing is, it seems that all this vitriol towards pumpkin spice is actually making it more popular. Take a look on my story below to see what I mean.

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Dataviz Coffee Talk

September 19, 2014

The purpose of this post is really just because I came up with a dataviz related “Coffee Talk” joke and needed to share it.

Treemaps are neither trees nor maps. Discuss. @tableau pic.twitter.com/gSAtaydlT2

— Jewel Loree (@jeweloree) September 19, 2014

If you have no idea why I find this hilarious, check out this classic SNL clip of Mike Myers’ classic character “Linda Richman.” One of my favorite sketches and characters from SNL ever.

If you have any other Coffee Talk jokes, tweet them to me!

EDIT: Just in case anyone actually wants to know the origins of the term “treemap” Iron Viz contestant and data genius Jeffrey Shaffer has us covered:

@jeweloree @tableau "the term treemap described the notion of turning a tree into a planar space-filling map." – Ben Shneiderman

— Jeffrey Shaffer (@HighVizAbility) September 19, 2014

#WJEAJDay2014 and Tableau

September 18, 2014

This morning I had the extreme pleasure of talking to a group of smart, talented high schoolers about data journalism. They were at the University of Washington for the Washington Journalism Education Association’s (WJEA) Journalism day. I’m excited to see what this creative group of young journalists will come up with in Tableau Public.

Here’s a viz we made together in about 15 minutes. I used data from Maxpreps on my high school football team. An interesting finding was that Mariner actually lost their highest scoring game of the last decade.

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Data Feed: New York Times APIs

September 17, 2014

If you were at Pimp My Viz, or at least read yesterday’s summary about it, then you may recall that I spoke a little bit about using the Spotify Web API to pull data into Google Spreadsheets. My partner (and author of this excellent tutorial about bring JSON into Google Spreadsheets) alerted me to the existence of these New York Times APIs yesterday. They have APIs for a number of different things but the ones I think you could get a LOT of interesting data out of are the Best Sellers API, Campaign Finance API, Congress API, Movie Reviews API, and Real Estate API.

Now go forth and do awesome things with data!

No, not that data!

#Data14- Pimp My Viz follow-up

September 16, 2014



I had SOOOOOO MUCH FUN being Xzibit for a day and getting to pimp some vizzes last week! Thanks to everyone who came and hung out with me. For those who missed it, here are the vizzes I pimped and some information about what I did with them.

Mat Hughes’ music dashboard

/r/tableau regular, Mr. Mat Hughes, sent me this great little dashboard of his music listening as tracked by last.fm. I wanted to make it more obnoxiously obvious that it was about music, so when I was done, it looked like this:

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Here’s some of the stuff I did:

Lari’s Disney Dashboard

The story behind this dashboard is that Lari McEdward, Tableau instructional video extraordinaire, and her sister were trying to choose a Disney movie to watch and resolved to make the decision by choosing the movie with the best songs. They judged all the songs and created this pretty-in-pink viz. Here’s my pimped version:

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Here’s some of the stuff I did:

Tweet me if you want more info on any of this. Hopefully you picked up some fun tricks that’ll make your dashboards a little more pimpin! To close, here’s some tweets:

“In case you were wondering what my data skirt was saying today…” @jeweloree explaining her music data on her skirt! HA! #data14 #datanerd

— Kristie Bauer (@kristiekbauer) September 10, 2014

@jeweloree teaching a valuable lesson – “what is pimping?” #data14 pic.twitter.com/ibGIz0fL9a

— Graeme Crawford (@n1jimmy) September 11, 2014

@jeweloree has fun ways of showing filter fails. #data14 #tableau pic.twitter.com/RiG1Wv0LTW

— Kristie Bauer (@kristiekbauer) September 10, 2014

@jeweloree this is BY FAR my favorite text I’ve received at #data14 pic.twitter.com/tpyUQQ2anO

— Mat Hughes (@MatHughesTweets) September 10, 2014

#Data14: Porn, Pokemon, and Pop Culture Follow-Up


Huge thanks to everyone who came out to see me, Peter, and Andy for our blogger panel last week. We all had a blast. It was great to get a chance to goof around with y’all and show you the fun side of data! As promised, here’s some of the resources I promised to round up for you.

Scraping tools:

Quantified Self Apps:

Other references:

And here’s a little of the Twitter action from the session:

Just been told that the Porn and Pokeman session will have live demos whoop whoop! @jeweloree @tableau #data14

— Paul Chapman (@cheeky_chappie) September 10, 2014

.@jeweloree ,@VizWizBI , @pgilks talking about data that doesn’t suck! #data14 Its a gif factory up here! pic.twitter.com/mqO911P1BQ — Dan Montgomery (@DanRMonty) September 10, 2014

@jeweloree @VizWizBI @pgilks Wooooo. Porn. Pokemon. Priceless. pic.twitter.com/jFZQPa5B8H

— James Young (@DataJimnast) September 10, 2014

Learned a new word from @jeweloree, “vizzer.” #data14 — David Carnes (@David_Carnes) September 10, 2014

@jeweloree wins most engaging session at #data14 #tmi

— Ryan Wagner (@WagsRyan) September 10, 2014

Boy this sesh has gone below the belt a few times! *blushes*.Awesome stuff with @jeweloree @pgilks @VizWizBI #data14 pic.twitter.com/aR32QSEotF — Paul Banoub (@paulbanoub) September 10, 2014

Pop Viz: Seattle Music Venues

August 19, 2014

In case you missed it, I made this viz for our Destination Data countdown. Every week a different Tableau employee will share their insider knowledge of things to do in Seattle. You may have gathered as much by now, but I am a bit of a music fanatic. I go to at least 1 live show a week. In fact, just this past weekend, I was in Portland for Musicfest NW where I saw awesome bands like HAIM, Spoon, Tuneyards, and Man Man. Even with a lineup like that, the part of the weekend I was most excited for was an after party show at a tiny club with my local heroes Tacocat and my newest obsession, Tijuana Panthers. I’m not exaggerating when I’m saying that I was fangirling pretty hard. I’ve got data to back up my claim:

I've been listening to them A LOT.

I mean, just look how excited I was to take a picture with two-thirds of them.

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I love live music culture and am so devoted to the scene that I considered (well, really I’m still considering) getting a tattoo of something like this on my inside right wrist:

place stamp here

(because when you go to shows in clubs they usually stamp your wrist so that you can get in and out.)

I’ve highlighted some of my favorite venues in the viz below. I tend to like smaller, more intimate places. A lot of fantastic acts come through the bigger venues like Paramount and the Showbox and they are beautiful buildings, but I just don’t feel it as much in those places. Not to mention that I’m often too short to see anything at those venues if I’m in the pit. Here’s the dashboard if you’d like to explore!

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