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Learn RStudio IDE

Quick, Effective, and Productive Data Science

  • Matthew¬†Campbell

Table of contents

  1. Front Matter
    Pages i-ix
  2. Matthew Campbell
    Pages 1-13
  3. Matthew Campbell
    Pages 15-27
  4. Matthew Campbell
    Pages 29-38
  5. Matthew Campbell
    Pages 39-48
  6. Matthew Campbell
    Pages 49-62
  7. Matthew Campbell
    Pages 63-72
  8. Matthew Campbell
    Pages 73-85
  9. Matthew Campbell
    Pages 87-97
  10. Matthew Campbell
    Pages 99-112
  11. Matthew Campbell
    Pages 113-124
  12. Matthew Campbell
    Pages 125-136
  13. Matthew Campbell
    Pages 137-149
  14. Back Matter
    Pages 151-153

About this book

Introduction

Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data from diverse sources such as SAS files, CSV files, and JSON. You will map out the features in RStudio so that you will be able to customize RStudio to fit your own style of coding.

Finally, you will see how to save a ton of time by adopting best practices and using packages to extend RStudio. Learn RStudio IDE is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects.


You will:
  • Quickly, effectively, and productively use RStudio IDE for building data science applications
  • Install RStudio and program your first Hello World application
  • Adopt the RStudio workflow 
  • Make your code reusable using RStudio
  • Use RStudio and Shiny for data visualization projects
  • Debug your code with RStudio 
  • Import CSV, SPSS, SAS, JSON, and other data

Keywords

RStudio R data science tool IDE Integrated programming big data analytics statistics analysis code

Authors and affiliations

  • Matthew¬†Campbell
    • 1
  1. 1.YardleyUSA

Bibliographic information

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