Learn RStudio IDE (e-bog) af Campbell, Matthew
Campbell, Matthew (forfatter)

Learn RStudio IDE e-bog

288,10 DKK (inkl. moms 360,12 DKK)
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 ...
E-bog 288,10 DKK
Forfattere Campbell, Matthew (forfatter)
Forlag Apress
Udgivet 17 april 2019
Genrer Probability and statistics
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781484245118
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.What You Will LearnQuickly, effectively, and productively use RStudio IDE for building data science applicationsInstall RStudio and program your first Hello World applicationAdopt the RStudio workflow Make your code reusable using RStudioUse RStudio and Shiny for data visualization projectsDebug your code with RStudio Import CSV, SPSS, SAS, JSON, and other dataWho This Book Is ForProgrammers who want to start doing data science, but don't know what tools to focus on to get up to speed quickly.