4th and 5th Grade Girls Help #VisualizeNoMalaria

4th and 5th Grade Girls Help #VisualizeNoMalaria

Over the last couple of months, I was fortunate to have the opportunity to meet with the 4th and 5th Grade Girls Club at a San Francisco school and get them excited about all things data visualization and mapping. In a couple lunches and after school workshops we learned about cartography, map construction, and design, built our own outrageously fun custom maps of San Francisco using Mapbox, and finally contributed to the #VisualizeNoMalaria project by tracing buildings for Humanitarian OpenStreetMap.  My presentation for all the lessons, as well as the instructions for the building tracing are below.   My hope is to help data viz and map practitioners to get involved with children in their local schools to inspire the #DataKids of tomorrow.  Get Mapping!

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Consumed - A study of consumptive malaise

Introduction

I think of this viz as a dystopian Harold and the Purple Crayon.  Harold had the power to create a world by simply drawing it.  In this viz, my consumptive malaise draws the world around me.  By sifting through the pile, I discover meaning and conflict in the mountain of banal objects that I interact with daily, and ponder why I use so many things.

The idea was simple - to log every “thing” that I used throughout the course of the day and visualize the “pile”.  Then, categorize and group all the things and see what story they tell.

I’m a lucky girl.  I get to work with Noah Salvaterra.  He’s ridiculous, which means I can say things like “I need a waterfall of sexy transactional data, pooling into lakes of ever increasing ROI based on risk mitigation,” and Noah makes it happen.  This time the request was, “I have a bunch of cartoon drawings of all crap that I use.  I want to build up a mountain of it over time”.  As usual, Noah made it so with his math Bedazzler.

 

Wants vs. Needs

Looking at the pile dissected by “Wants” vs. “Needs” requires a few assumptions to be made.  My needs were more than water, food and shelter.  To live in SF in 2017 and be in my line of work, I classified my phone and laptop as needs, as were standard furniture items like a desk and chair to work at.  Wants were more along the line of a Manhattan every day at 5 pm, or using 3 bowls throughout the day, instead of just having one and reusing it.  Most wants came out of cosmetics, and food items beyond just basic meals.  You may not agree with my categorizations of Wants vs. Needs, but in the end it is my viz, and I got to make the distinctions.  Only about 43% of the items I used were needs.  I wanted to dig in and understand the drivers of the wants.

 

Intersection of Female Specific items and Wants

The biggest shock in my consumption analysis was my categorization of 88% of the “Female Specific” being wants, compared to the “gender neutral” items which were almost a 50% split.  I use, what I would consider, a normal amount of makeup and hair products, and yet I categorized them mostly all as wants.  I would be hard pressed to give them up and feel like “Anya”, or even presentable outside my home.  Would most women consider mascara and lipstick a want or a need?  Why do I want them?  I am angered by the time suck and money drain these products represent, but I can’t imagine not using them. 

I had a conversation about labeling things female specific, and was asked; “Why I did not label things male specific?”  I asked, “What would some examples of that be?”.  “A jock strap and cigars” was the tentative response.   Well, I didn’t use those.

 

 

 

Cartoon Representations of All the Things vs. Standard Viz Mark Type

We are always representing things in bars and lines, so I wanted a chance to explore using representative objects to convey each item as a data point. I hired doodle artist Maeve Tan to create cartoon images, and found using a pile of cartoons a much more compelling representation of the story I wanted to tell.  Would the viz carry the same message if standard chart marks were used?  Where is the line in the sand between accuracy and speed of data consumption, vs better storytelling?  Is my desire to “tell a story” skewing the presentation of my consumption behavior?

Well, after all this, am I going to change my consumption behavior?

One of the most tedious parts of the project was going through the list of items and writing a description and where each was bought.  I discovered that I have either no real attachment, nor had not given much thought to the products I use day after day.  I bought them for the most part because they were easy to buy, on sale, part of a routine, an impulse buy, etc.

I had started a version of this viz a long time ago, when I was married and living in a nicer house, in a nicer neighborhood, and everything was from a hipster boutique or high end store.  As I looked through the current day version of my pile, I was a bit ashamed that it was all now from Costco and Target.  People will know I use Pantene!  But I was more shamed by how much I still bought and used.  It had taken a big life change to alter my pattern of consumption.  Yet faced with the question of what would I consume differently now, without an impetus, or conscious effort, I am likely continue to behave the same.  

Go ahead and be a voyeur. Then look at what’s in your pile.

PS. Most of us are voracious consumers, and if you are reading this, most likely of consumers of data visualizations as well.  Before you quickly swipe right of left, based on a casual glance at the aesthetics as a viz pops into your twitter feed, take a minute to have a read and maybe a think, or you may find your viz in Allan Walker’s idea to make a “tinder” type app for viz’s to satirize the velocity in which people consume data viz.

 

 

To Animate or Not To Animate

To Animate or Not To Animate

Context

Previously I wrote this post around analyzing the predictions generated by 538 during March Madness each year. At the end of the post, I briefly discuss the possibility of telling the same story using animation in place of vertically scrolling through a static set of charts. I believe that, if used correctly, the ability to animate from one chart to the next can greatly assist the reader in understanding your analysis process. 

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Building SVG Paths in Alteryx + Tableau

Building SVG Paths in Alteryx + Tableau

Background

Recently my family watched Disney’s Moana for the first time. We all really enjoyed the movie, especially my two young daughters. After the movie was over, my five-year-old noticed the spiral in the title on the movie case and asked me whether I could build it on the computer. I figured this was as good an opportunity as any to show her the power and possibilities of math. 

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Analyzing 538's March Madness Win Probabilities with Alteryx and Tableau

Analyzing 538's March Madness Win Probabilities with Alteryx and Tableau

Story:

The concept for the story comes from visually comparing these two games (and several others like them). As I followed the early rounds of the 2017 tournament and tracked the games via 538’s predictions site, it seemed, more often then not that Men’s tournament games were closer then the Women’s.

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Building towards d3.js “plugins” for Tableau

Building towards d3.js “plugins” for Tableau

This post is a follow up to my Vizception post from a few months back. We are still building off the technique described in detail within that effort. Here we will look at two additional implementations leveraging the capabilities available within d3.js (thank you Mike Bostock!).

The first of the two implementations looks at leveraging d3.js mapping projectionsTamas Foldi and I presented this example during a recent Think Data Thursday. Here we will leverage the referenced d3.js code and adapt it for use with our Tableau integration method. This will allow us to build choropleth maps in Tableau with access to the d3 projection library which provides just a few more options in addition to your standard Web Mercator (the Tableau default).

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Telling a Story in Tableau

This short post is around trying to create an article like structure with in-line visualizations all within Tableau. Inspiration for this pulls from sites like 538 and polygraph as well as several authors from the Tableau Public community (like the one noted below, this recent VotD).

There have been many examples across the Tableau Public community showing the data storytelling capabilities of Tableau. These include leveraging additional JS libraries (via API/embed) like reveal.js (thank you Jeff Shaffer!), but others that caught my eye recently where examples of building out an entire story in a long form Tableau dashboard. Here is one example that Rob Radburn posted recently that got me thinking. Note: there are several others, this one by Rob is just a single recent example. 

I decided to see just how much work it is to do something like this, all within Tableau. The answer... not all that much. Like every tool, Tableau makes some hard things easy and some easy things hard. This type of visualization is a great example of the former and demonstrates the creativity that Tableau can empower it's Desktop users with. The viz story is just a simple collection of visualization sheets and text boxes, you can download the workbook to see how I went about laying out the story. The viz below is best viewed in landscape, hope you like it! 

3D "Printing" in Mapbox, Alteryx, and Tableau: "I've got big balls!"

3D "Printing" in Mapbox, Alteryx, and Tableau:  "I've got big balls!"

While starting to work on a new viz project, I came up with the idea to create empathy by putting the user inside of a 3D map with the data happening around them like a virtual reality movie.  Yes, the DataBlick crazy-town express train is starting to chug out of the station again.  This post shows some of my initial explorations into jumping in a viz.

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Rose Curves in Tableau

Rose Curves in Tableau

I love when people get creative and come up with visuals like these, if you want to see more, check out Shirley Wu’s project with Nadieh Bremer at datasketch.es for starters. Techniques like these (or using things like the rose curve) to encode data will definitely require a more engaged user base. Readers will need to take some time to understand what each rose petal/shape is and then it will take them time to compare the petals across the visual. This type of technique is probably not the best choice to visualize your data when granular differences between your marks need to be analyzed by your reader.

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Sensor vs. Simulated IED: Max's Science Fair Project using Tableau for Image Analysis

Sensor vs. Simulated IED:  Max's Science Fair Project using Tableau for Image Analysis

This is a post by Max, Anya's 12-year-old son.  It was his Science / Engineering Fair project where he used Tableau to visualize his results.  Thank you, Adam McCann and Merlijn Buit for your posts on color analysis that were used by Max for this project.

Each year many people die of bombs and other explosive devices. Some examples are the Boston Marathon and the recent bombing in Manhattan. In many modern wars, thousands of soldiers die due to IEDs (Improvised Explosive Devices). In my project, I will use an infrared sensor to find a cell phone (in place of an IED) in different temperature environments. Judging by how easy it is to see the cell phone, we can tell where infrared would work best, as well as where it would not work.  Using this information we can know when to use infrared sensors to save lives.

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The 3D Tableau Full Monty

The 3D Tableau Full Monty

Recently DataBlick had a client project dealing with analyzing parts on a car during manufacturing and transport, and the client wanted something like Noah's Tesla.  We all want a Tesla, right?  Well, now you can have one (in Tableau at least).  In this post, I'll walk you through how to find a 3D model and get it into Tableau.  The next post will show how to trick it out a little bit as well as "explode" parts in a 3D tool before bringing them into Tableau so you can highlight and interact with them on your dashboard.

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X, Y and a bit of Z - Cheater 3D Orthographic Views & Making everything "Spatial"

X, Y and a bit of Z - Cheater 3D Orthographic Views & Making everything "Spatial"

Anya must have pinged me 10 times over the course of the last week asking me questions about rendering 3d cars in Tableau. I figured it must have something to do with curing malaria. My reply was a bit ironic given the fact that I’ve done my own 3d car. I did it for fun though… I don’t like being told I can’t do stuff. it just doesn’t work as part of a production workbook. Well… from a performance standpoint maybe we will get there soon. But for now my suggestion was to pick a good angle and then drive a steamroller over it and just make it into polygons. I really should have seen the next question coming, but she asked how to do that. I was stumped. My best idea was, hire a graphic artist to trace it for you…

Last night she told me she solved it using QGIS… mind explosion! Of course! Why not use mapping software for this? Geography isn’t the only thing spatial. Why shouldn’t you use QGIS to map your car, your plane, the shelves of your supermarket, what have you. I always thought background images were misplaced in Tableau, I wonder if this is what they were thinking when they put it under maps. Latitude and Longitude are just a special name for x and y (or is it the other way around?). Why not hijack Tableau’s mapping capabilities and import your polygons as custom shapes?

I’ve gone to great lengths to hack multiple layers onto maps, so I was excited to hear multi-layered maps will be coming to Tableau, but this opens the door to hacking that feature into all sorts of things. Someone once told me that everything in Tableau is a scatterplot but I’m starting to think maybe everything should be a map. Oh… I am going to crash that Beta so hard!

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#Data16 Twitter Network Project

#Data16 Twitter Network Project

For this year’s conference I undertook a project with Keith Helfrich to harvest tweets tagged with #data16.  We collected the tweets regularly throughout the week, and updated a view of high level summaries and detailed network visualizations.  This post details some of the highs and lows that we came across, and provides access to the workbook so you can do your own analysis and review as well. Please also be sure to check out Keith’s post on the same subject here.

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On the topic of community: & being friends and mentors.

On the topic of community:  & being friends and mentors.

First - sign up and sign up for Emily Kunde's Mentor Match program, and have a chance to win an hour of help with either Allan or Anya as well as other prizes to be announced on Emily's site soon.  

This friendship started with a Tweet:  March 5th, 2014 Tweet to @AllanWalkerIT help…..!  ? "Since you are the king of Tableau Maps, I wanted to see if you had any suggestions?"  For over two years now, we have worked together on many collaborations.   We hope with a quick review of how we have expanded our skills by working together, you can learn from our take-aways and find friends and mentors to work with. 

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