Week 2 Building on your foundations: going further with R
In the last chapter, we got to grips with the basics of R. Hopefully after completing the basic introduction, you feel more comfortable with the key concepts of R. Don’t worry if you feel like you haven’t understood everything - this is common and perfectly normal! Learning R is very much like learning a real language in that it takes time and practice to feel ‘fluent’. Even if you do feel comfortable in the language, there is no shame in asking for help or looking for more information to develop your understanding. As regular R users, we still look things up constantly and there are one or two basics which we still forget, even with over a decade of experience of using the R environment! With this in mind, a goal of these R tutorials is to re-emphasise and reinforce basic concepts throughout. We will introduce concepts but through the practical demonstrations of code, we will underline them again and again.
In future chapters, we will be using a similar approach to reinforce the evolutionary genetic concepts you have encountered in the book. However, for this chapter we remain solely in the R environment and will instead switch our focus to more advanced features of R. Advanced does not necessarily mean more complicated - but it does mean that you need to have at least been introduced to the basic concepts. We will first ‘level-up’ our approach to handling and manipulating data. For this, we will be borrowing heavily from the tidyverse - a collection of packages and principles for data science in R. We will also introduce you to more advanced plotting, comparing the two most popular apporaches for plots - base and ggplot.