Learning data visualization beyond the spreadsheet is a challenge when you first start out.
There are countless applications and services to help visualize your data, and they all seem to promise ultimate insights and beautiful graphics.
But as it turns out, the automated way is not always best. It rarely is.
Visualization in Practice
Learn with real data and concrete examples, all in one place.
The best way to learn how to visualize data is to start doing it now. Look at real data to see how visual forms work and how to negotiate between more efficient and more visually compelling chart types.
Improvement comes with experience.
And this is how I approach FlowingData courses and tutorials.
I explain how a method works, provide you the tools — which includes source code in R and d3.js — to get your stuff done, and then provide you with a wrap-up so you can apply what you learn to your own data.
The advice in the how-tos are based on my own experiences as a statistician and on projects for both web and print.
Who Should Join
Where there is data, there is a need for someone to understand it and to communicate.
The list goes on. Data is everywhere these days, and there is a growing need to understand it. If you can visualize data, your skills will be in high demand in a lot of places.
No programming experience? Not a problem. While the resources on FlowingData are code-centric, tutorials are written with beginners in mind, and if you get stuck, there are places to ask questions.
The Benefits of Membership
Here’s what you gain access to when you join.
Practical how-tos with source code and data.
Course: Visualization in R
The four-week course takes you from beginner to advanced with practical instruction and end-of-week exercises.
Visualizing Time Series Data in R
The weekender for those in a rush to see patterns over time.
Full Archive Search
Quickly access thousands of posts and links on FlowingData, public and members-only.
Members-only links and guides focused on the how of visualization.
Ask questions and leave comments at the end of tutorials or in the forum.
You also get ad-free reading for a more focused experience and a warm fuzzy feeling from supporting an independently-run FlowingData.
Who I Am
My name is Nathan Yau, and I’ve been running this place since 2007. I have a PhD in statistics from the University of California, Los Angeles, and I have a background in programming and information design. I’ve written two best-selling books on visualization — Visualize This and Data Points.
I strive to help people understand data in both their personal and professional lives. Hopefully they have fun in the process.
Follow step-by-step examples to make the data graphics you want for reports, presentations, and analyses.
Learn to make beautiful and useful visualizations.
There are currently over 80 in-depth tutorials — with more every month — amounting to hundreds of hours of learning. Mostly in R and d3.js, the tutorials walk you through step-by-step so that you can make a countless number of data graphics for reports, presentations, and analysis. Tutorials include data to work with, source code downloads, and examples to work off of.
If you get stuck, there’s a section at the end of each tutorial to ask questions and see previous answers.
Learning to visualize data is a process that doesn’t happen overnight. It takes time. It takes iteration. It takes practice. You will have questions along the way. So in addition to the comment areas at the end of tutorials, which I monitor continuously, you also gain access to the forum to ask questions and get advice. I answer questions every Monday and Wednesday.
Start with the basics. Advance.
If you don’t have a specific visualization in mind, and instead, are just eager to learn, these guided courses are for you. There are currently two.
Work with the suggested schedule or move at your own pace.
Visualization in R, From Beginner to Advanced
This is a four-week course that starts with the basics and walks through more complex methods. Create basic charts, make use of visualization packages, map geographic data, and create custom graphics to use with your own data.
Each section provides exercises to hone your skills.
Visualizing Time Series Data in R
Everything you need to know to see and show patterns over time, from basic chart types to the more advanced.
Mapping Geographic Data in R
Make maps that allow you to see spatial patterns across regions and are great for presentation and communication.