Getting good at Tableau should not be your goal. In fact, let’s forget about goals altogether. We are going to construct a system that works. While we’re at it let’s forget about motivation too. Our interest in doing the thing ebbs and flows. I wouldn’t want you to put the fate of acquiring Tableau skills on your temperamental interest level. Show up consistently and give the task whatever you have at the moment.
If you are new to the Simple Chart series and would like to get some clarity on what this is about please go check out the intro. Otherwise, move right along to this simple bar chart walkthrough. This is what your bar chart should look like when you are done. One of the old faithful chart types. Bar charts do a great job comparing different categories to one another along a shared axis.
MakeoverMonday was an especially special event this week as the digital gathered together at the Tableau Customer Conference for a live makeover in Vegas. As you can imagine this is an exciting opportunity to meet fellow #MakeoverMonday regulars and newbies in real life, but also a challenge yourself to create something presentable within an hour while Andy and Eva looking over your shoulder. Personally, I would rather spend days wondering how I am going to visualize the dataset of the week, play with the numbers a bit and iterate far longer than any sane person.
This post is the first in a series of interviews with Data Visualization folks. In these posts, I will be interviewing friends, former colleagues, and others whose work I find inspiring. It will be interesting to see how differently everyone approaches their craft, found themselves practicing data visualization and any other unique quality they would like to share. Like many practicing data visualization, Kristin Henry can’t define easily. Kristin currently describes herself as a generative artist.
The United Nations (UN) has a few ambitious goals up their globe spanning sleeves. In this post I’ll be writing specifically about the MY World 2030 survey. The United Nations MY World 2030 survey is gathering people’s views on the state of poverty, inequality and climate change, based on where you live. Data will be gathered to build up a picture of progress over the next fifteen years. The survey is a simple series of three questions:
One of my data viz friends, who arguably has THE most enviable domain name, dataviz.love, recently introduced me to a fun sketching project. In the project Giorgia Lupi, master of pretty, personalized data visualizations and more, shares a step-by-step approach we can follow to draw selfies. Now, don’t let the lightheartedness of sketching, obscure the deeper point. Giorgia has far more meaningful motives than helping you attract more Insta followers ❤️
What works Lines are clearly differentiated It is intuitive What could be improved I’ll work on the title Remove the legend (test for color blindness) Right align the y-axis labels Remove vertical grid line Add full years Add annotations at points where lines intersect Research proper x-axis / y-axis ratios A few fun tips Spectrum I use Spectrum to test for colorblindness. You can see the original colors work well, buuut I decided to go with some different colors anyway.
Read the full post to find out what the insight from this chart and Michael Phelps have in common. If you are finding this series for the first time visit P1 and P2 to see what has lead us to this point. There is so much I want to say about the value of makeovers, but that’s a topic for an entirely different post. It’s my honest opinion that participating in exercises such as these the best way to learn short from having a great team to push you every day.
In part 1 of this storytelling with data redesign series, we simply set the stage. In this post, we walk through the cleanup process. WHAT’S OUR OBJECTIVE? Most people are going to jump straight into the cleanup process as you might with a messy room. What’s out of place and where can I put it, so the room looks tidy again? No surprises here. I am going to approach the visual clean up the same way.
Cole, of storytelling with data, doesn’t host public redesigns often. This is a rare opportunity to practice with a master. Cole has been busily globetrotting for years teaching people at almost any company you can think of how to better tell stories with their data. She finds particular value in the power of storytelling, which you can learn more about by reading her book or attending her public workshops.
There are plenty of ways one can go about analyzing the rich recesses in Trumps Twitter archives. Tim, and I wanted to see if sentiment analysis would turn up anything useful. In this short post, we share what was found. In April 2016, the media repeatedly reported on Trump’s warning of a rough July. Trump went so far as to say there could be riots at the Republican National Convention if things didn’t go his way.
This project was inspired by Andy Kirk’s Chart Maker Directory. Each post in this series will cover the basics of building chart a from Andy’s list with D3. What better way to learn than by building a chart or… 49. We will start with the most widely used chart types and slowly explore the more esoteric. This way you’re sure to get more utility out of these tutorials as well.
WHAT’S A LIFT? A lift is my way improving a visualization by isolating one feature that hinders our perception in some way. Data visualization is complex, but that doesn’t mean there aren’t informed approaches anyone can take to make more accessible visualizations. I hope by sharing these bite-size improvements we can learn how to avoid common missteps and better defend our design decisions. LET’S GET AFTER IT! Week 39 of Makeover Monday had us makeover a chart type I have started noticing more and more in the wild.