Module 4: “Data Cleaning” has just been released.

While Module 3 explored how to import, explore, and summarize data using packages from the tidyverse, Module 4 covers the principles of cleaning and preparing your data for analysis. Specific topics covered, include:

• Data Cleaning: How can you explore, transform, and clean your data in R.
• Data Shapes and Tidy Data: Where we’ll explore how to get your data into a ‘tidy’ format to make analysis even simpler, particularly for packages from the tidyverse.
• Handling dates with the lubridate packages: To make working with dates and times easier in R.
• Binding and joining datasets: So you’re comfortable binding and joining data from different sources.
• Data Visualization Crash Course: Providing a quick introduction to producing plots with the ggplot2 package.
• An Introduction to Costing Policy Proposals: and how the ‘unit costing’ approach can be used to provide a ballpark estimate for the cost of a policy or program.

I’ve also been finding ways to improve the overall learning experience. I’m therefore proud to announce the introduction of the latest cutting-edge learning technology: animated GIFs:

We’re adding cutting-edge technology, like animated GIFs:

To reflect feedback from learners, I’ve also been busy rewriting content, correcting typos and adding additional videos to make progressing through the course as intuitive as possible.

As always, please feel free to reach out if you have any questions, comments or suggestions for improving the course.