Learn RStudio IDE
Quick, Effective, and Productive Data Science
Seiten
2019
|
1st ed.
Apress (Verlag)
978-1-4842-4510-1 (ISBN)
Apress (Verlag)
978-1-4842-4510-1 (ISBN)
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 YouWill Learn
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
Who This Book Is For
Programmers who want to start doing data science, but don’t know what tools to focus on to get up to speed quickly.
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 YouWill Learn
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
Who This Book Is For
Programmers who want to start doing data science, but don’t know what tools to focus on to get up to speed quickly.
Matthew Campbell has worked on data visualization and dashboards with a data science team using RStudio. He got his start with technology after college when he learned SAS to do statistical programming at the Educational Testing Service (ETS). Learning this programming language kicked off a lifelong obsession with technology.
1. Installing RStudio.- 2. Hello World.- 3. RStudio Views.- 4. RStudio Projects.- 5. Repeatable Analysis.- 6. Essential R Packages: Tidyverse.- 7. Data Visualization.- 8. R Markdown.- 9. Shiny R Dashboards.- 10. Custom R Packages.- 11. Code Tools.- 12. R Programming.
| Erscheinungsdatum | 10.05.2019 |
|---|---|
| Zusatzinfo | 6 Illustrations, color; 82 Illustrations, black and white; IX, 153 p. 88 illus., 6 illus. in color. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge | |
| Schlagworte | Analysis • Analytics • Big Data • Code • Data Science • IDE • Integrated • programming • R • RStudio • Statistics • Tool |
| ISBN-10 | 1-4842-4510-5 / 1484245105 |
| ISBN-13 | 978-1-4842-4510-1 / 9781484245101 |
| Zustand | Neuware |
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