R is one of the most popular programming languages used in computation statistics, data visualization, and data science. With the increasing number of companies becoming data-driven, the user base of R is also increasing fast. R is supported by over two million users worldwide.
In this book, you will learn how to use R to load data from different sources, carry out fundamental data manipulation techniques, extract the hidden patterns in data through exploratory data analysis, and build complex predictive as well as forecasting models. Finally, you will learn to visualize and communicate the data analysis to the audience. This book is aimed at beginners and intermediate users of R, taking them through the most important techniques in data science that will help them start their data scientist journey.
In this chapter, we will be covering the basic concepts of R such as reading data from different sources, understanding the data format, learning about the preprocessing techniques, and performing basic arithmetic and string operations.
The objective of this chapter is to first help the reader get a hold on to programming in R and know about the basic operations that will be useful for any analysis. In this chapter, we will essentially be exploring the standard techniques that will be used to convert the raw data into a usable format.
The following topics will be covered in this chapter:
Reading data from different sources
Discussing data types in R
Discussing data preprocessing techniques
Performing arithmetic operations on the data
Performing string operations on the data
Discussing control structures in R
Bringing the data into a usable format