Chapter 5 Transforming data
Anyone regularly working with data is aware that transforming data (aka. “data munging” or “data wrangling”) is an essential pre-requisite for any successful data analysis.
Key topics (and corresponding R packages) of this chapter are:
All these sections and packages are designed for manipulating data structures (mostly vectors or tables) into other data structures.
If transforming data is viewed as a challenge and a task, our main goal is to gain insights into the contents of our data. From this perspective, tidy data becomes an intermediate goal — a way of representing our data so that it can be processed more easily and rapidly.
Recommended readings for this chapter include:
Before reading, please take some time to reflect upon the following questions:
Assuming we had all the data required for answering our question, which additional obstacles would we face?
The same data can be stored in different data structures. Which ones? (Think in terms of different data types and their data structures or shapes.)
Does it matter how data is stored? Why or why not?