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

Chapter 17. Reproducibility and Best Practices

At the close of some programming texts, the user, now knowing the intricacies of the subject of the text, is nevertheless bewildered on how to actually get started with some serious programming. Very often, discussion of the tooling, environment, and the like - the things that inveterate programmers of language x take for granted - are left for the reader to figure out on their own.

Take R, for example: when you click on the R icon on your system, a rather Spartan window with a text-based interface appears, imploring you to enter commands interactively. Are you to program R in this manner? By typing commands one at a time into this window? This was more or less permissible up until this point in the book, but it just won't cut it when you're out there on your own. For any kind of serious work, for example, requiring the rerunning of analyses with modifications, and so on, you need knowledge of the tools and typical workflows that professional...