Let's start from the very beginning, What exactly is R? You will have read a lot about it on data analysis and data science blogs and websites, but perhaps you are still not able to fix the concept in your mind. R is a high-level programming language. This means that by passing the kind of R scripts you are going to learn in this book, you will be able to order your PC to execute some desired computations and operations, resulting in some predefined output.Â
Programming languages are a set of predefined instructions that the computer is able to understand and react to, and R is one of them. You may have noticed that I referred to R as a high-level programming language. What does high-level mean? One way to understand it is by comparing it to typical industrial company structures. Within such companies, there is usually a CEO, senior managers, heads of departments, and so on, level by level until we reach the final group of workers.
What is the difference between those levels of a company hierarchy? The CEO makes the main strategical decisions, developing a strategical plan without taking care of tactical and operational details. From there, the lower you go in the hierarchy described, the more tactical and operational decisions become, until you reach the base worker, whose main duty is to execute basic operations, such as screwing and hammering.Â
It is the same for programming languages:
- High-level programming languages are like the CEO; they abstract from operational details, stating high-level sentences which will then be translated by lower-level languages the computer is able to understand
- Low-level programming languages are like the heads of departments and workers; they take sentences from higher-level languages and translate them into chunks of instructions needed to make the computer actually produce the output the CEO is looking for
To be precise, we should specify that it is also possible to directly write code using low-level programming languages. Nevertheless, since they tend to be more complex and wordy, their popularity has declined over time.
Now that we have a clear idea of what R is, let's move on and acquire a bit of knowledge about where R came from and when.