Why do we visualize data? There are many reasons, but we can split them into two main categories: analysis and presentation.
Analytical visualization is about exploration. In the 1970s, statistician John Tukey described exploratory data analysis, which is a stage in a traditional analysis where you use charts to understand a dataset. You don’t quite know what the data has to say yet, so you poke around and look at the data from various angles. You are both the maker and consumer of the charts.
Presentative visualization is about communication. You know what the data has to say, and you use charts to help others understand a dataset. You are the maker and your audience is the consumer of the charts.
This is an important distinction between the two categories. While you use similar geometries and visual methods for all visualization, a shift in purpose changes the process.
This course is about presentative visualization and the shifted process. It’s about how to visualize data to communicate to people.
This course is about how to provide clarity to an audience who otherwise wouldn’t know how or don’t have the time to read data in spreadsheet form.
You will learn about:
- Designing for an Audience
- Picking the Right Visualization
- Making Readable Graphics
- Bringing it Together
We take a tool-agnostic approach, so that you can learn regardless of the software that you use.
Who this Course is for
This course is for people who have made a chart or two but want to communicate data in a way that is more readable and less confusing.
You learn about the design process, which starts with the data, works through asking and answering questions, and finishes with a data graphic that provides readers with clarity.
With a greater emphasis on process, the course is tool-agnostic. Use the software (or paper and pencil) that you want. Use Excel. Use Tableau. Use Python. Use R. Use Illustrator.
The goal is to teach you how to make great charts for clarity, and the best way for you to learn is with the tools that you’re most comfortable with.
How to Use this Course
This course has a reading component and a practice component.
- You get practical advice in each section and I avoid straying off into too much theory. I want you to get better at making charts quick.
- Exercises help you apply principles and to practice making charts.
Suggested duration: 4 weeks. Read one main section per week, which gives time for the exercises. This changes depending on how fast you read and what exercises you work on.
Practice is the most important part. You have to make charts to get better at making charts.
When I first learned how to visualize data for an audience, I started with all of the popular books at the time. I just read and read and read.
But when it was time to actually make graphics, I felt like I had no idea what I was doing. There was an initial phase of confusion, but once I got over the hump, I felt like I could more easily apply what I learned from reading. My goal is to get you over that hump.
If you get stuck, post in the forums. Ask questions or share your work to get feedback. I check regularly.
Okay. Ready? Let’s go.