Beginning Data Science in R 4 : Data Analysis, Visualization, and Modelling for the Data Scientist

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist.Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning.You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models.This requires computational methods and programming, and R is an ideal programming language for this.Modern data analysis requires computational skills and usually a minimum of programming.After reading and using this book, you'll have what you need to get started with R programming with data science applications. Source code will be available to support your next projects as well. Source code is available at github.com/Apress/beg-data-science-r4. What You Will LearnPerform data science and analytics using statistics and the R programming languageVisualize and explore data, including working with large data sets found in big dataBuild an R packageTest and check your codePractice version controlProfile and optimize your codeWho This Book Is ForThose with some data science or analytics background, but not necessarily experience with the R programming language.