Introducing a New Course on Mapping Geographic Data in R, with ggplot2

I’m happy to announce a new course on mapping geographic data in R, using the ggplot2 package. The course is by data journalist and visualization consultant Maarten Lambrechts, and it’s available immediately to FlowingData members.

If you’re not a member yet, now is a great time to join. You get instant access to this course, plus four others and over a hundred in-depth visualization tutorials.

For those who’ve read FlowingData for a while probably know that I’m not much of ggplot2 user. It’s not that I don’t like it. I just never worked it into my workflow, and what I’m using now hasn’t stalled my work yet.

But when it comes to visualizing data, I’m a firm believer in learning a wide array of tools. A flexible toolset lets you visualize data in the way that you want. The tool shouldn’t be the limiting factor.

Hence, this course.

I worked through the course myself, and I’ll tell you first-hand that it’s fun, practical, and will get you up to speed quick. There’s real data, concrete examples, and you’ll be making beautiful maps with your own data in no time.

Check it out now.

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Audit advanced data science course online

Jeff Leek and Roger Peng started their course Advanced Data Science at Johns Hopkins University. It’s meant for JHU students, but you can learn from the weekly course material for free:

The class is not designed to teach a set of statistical methods or packages – there are a ton of awesome classes, books, and tutorials about those things out there! Rather the goal is to help you to organize your thinking around how to combine the things you have learned about statistics, data manipulation, and visualization into complete data analyses that answer important questions about the world around you.

So you know the methods and tools (or how to learn them on your own), but you want to learn more about putting it all together.

Nice. I could probably use a refresher.

You can get the weekly updates here.

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✚ Charting for Others (The Process 086)

There's a new tool-agnostic course now available for members. Check it out now. Read More

Johns Hopkins providing course on using epidemiology to understand the Covid-19 numbers

The numbers are fuzzy. You take them at face value, and you end up with fuzzy interpretations. Starting at the end of this month, Johns Hopkins is providing a two-week epidemiology course on understanding these numbers better:

This free Teach-Out is for anyone who has been curious about how we identify and measure outbreaks like the COVID-19 epidemic and wants to understand the epidemiology of these infections.

The COVID-19 epidemic has made many people want to understand the science behind pressing questions like: “How many people have been infected?” “How do we measure who is infected?” “How infectious is the virus?” “What can we do?” Epidemiology has the tools to tell us how to collect and analyze the right data to answer these questions.

Yes.

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Introducing a Course for Mapping in R

Mapping geographic data in R can be tricky, because there are so many ways to complete separate tasks. It’s a jumble of options and you have to figure out how to put the pieces together. This course walks you through the steps so that the process isn’t so jumbley.

FlowingData members can access the course right now. Learn how to load geographic data, draw boundaries, map locations, and make data-driven maps that are publication-ready. Then refine the process and learn how you can apply it to your own data.

Not a member yet? Join now, and gain instant access to this course and others, along with the full visualization tutorials collection.

Membership details.

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