Book Image

Data Analysis with R, Second Edition - Second Edition

Book Image

Data Analysis with R, Second Edition - Second Edition

Overview of this book

Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

The data.table package


One of the morals that I hope came across manifest in the previous chapter is that R is capable of much better performance than many expect. And, outside of calling low-level code and using parallelization, it is very widely agreed that there is no single best approach (taking personal preference and the largely subjective concept of readability out of the equation) to high-performance R than to learn how to properly wield data.table.

Many would be amazed at what previously intractable problems could be solved using this package. Often, problems that the uninitiated are keen to tackle with powerful remote servers, industrial databases, andtrendy tools can be handled quite easily and gracefully by data.table. And, with every update, data.table keeps getting faster and faster.

Before, we jump right into the code, it would behoove us to discuss what the data.table package gives us.

Note

Note that we will be using the made up variable, DT, to refer to a data.table in a generic...