Transformations with Base R
In the last three chapters of this book, our intent was to lay the foundations of the main data types you will find when working on a real-life project. Once a dataset is opened, it is likely you will find strings, numbers, and dates and times as variables. Knowing what they are, how they can be created, and some popular functions to manipulate them will keep us moving during exploratory data analysis.
The next two chapters are focused on transformations of data, what I consider the core of data wrangling. I say that because the main part of what needs to be done during the data wrangling phase of a project will be related to transformations of data. Then, another good chunk of the work is on data visualization, and the final piece will be modeling and evaluating the results.
In this chapter, we will study the most common transformations that can be done in a dataset:
- Slicing and filtering: These tasks allow us to focus on a specific part of...
