You can go a long way in R doing data science using functions built into the base language or available in packages, but sooner or later you'll probably need to write custom code to perform an operation that is not available in a prepackaged function. In this lesson and the next, we'll learn the basic programming constructs in R so that you can create your own custom code and functions.
This is lesson 11 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below:
Introduction to R: Control Flow https://www.kaggle.com/hamelg/intro-to-r-part-11-control-flow
This guide does not assume any prior exposure to R, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn R.
I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can fork and edit each lesson so that you can follow along and run code yourself.
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Introduction to R Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rDjk9tSOIUZJU4s5NpEyYtE
