Updated and Interactive Introduction to R

The most successful posts on my blog are my 30-part introduction to R and introduction to Python for data analysis, but data science, online learning and programming languages themselves evolve over time. I periodically receive message from readers regarding incompatibility issues with my guides versus current versions of programming languages and packages and my original guides don't have the level of interactivity that I've come to expect out of modern online learning, such as what is now available on MOOC platforms like Coursera and DataCamp. As a result, I've decided to update my R and Python guides, while simultaneously making them more interactive and less prone to comparability issues by converting them into a series of programming notebooks on Kaggle's kernel platform. As a series of programming notebooks, users who wish to interact with code or try exercises will be able to fork the lessons and experiment on their own in their browser in a consistent programming environment.


Although I have much of the structure and content of the guides already written, updating the guides for the Kaggle kernel environment will not be as simple as copying and pasting text and code. Some of the lessons and code need to be improved and updated for new packages and best practices. I also plan to add a handful of exercises to the end of each lesson, which will take time to formulate. In other words, while the guides won't be completely rewritten, they will need significant reformatting and additions to the point where the undertaking of updating and reworking them may take a similar amount of effort as writing them in the first place. This means that it will take some time before the updated guides are available in their entirety.


You can find the index to the updated R guide here. Thus far I have rewritten the first 3 lessons.


I haven't started the updated Python for data analysis guide yet; I will do that after I finish the updated R guide. I will edit this post and provide a link to the Python guide in the future.