Book description
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.
The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youâ??ve learned, and concludes with exercises, most of which involve writing R code.
- Write a simple R program, and discover what the language can do
- Use data types such as vectors, arrays, lists, data frames, and strings
- Execute code conditionally or repeatedly with branches and loops
- Apply R add-on packages, and package your own work for others
- Learn how to clean data you import from a variety of sources
- Understand data through visualization and summary statistics
- Use statistical models to pass quantitative judgments about data and make predictions
- Learn what to do when things go wrong while writing data analysis code
Table of contents
- Learning R
- Preface
-
I. The R Language
- 1. Introduction
- 2. A Scientific Calculator
- 3. Inspecting Variables and Your Workspace
- 4. Vectors, Matrices, and Arrays
- 5. Lists and Data Frames
- 6. Environments and Functions
- 7. Strings and Factors
- 8. Flow Control and Loops
- 9. Advanced Looping
- 10. Packages
- 11. Dates and Times
-
II. The Data Analysis Workflow
- 12. Getting Data
- 13. Cleaning and Transforming
- 14. Exploring and Visualizing
- 15. Distributions and Modeling
- 16. Programming
- 17. Making Packages
- III. Appendixes
- E. Bibliography
- Index
- About the Author
- Colophon
- Copyright
Product information
- Title: Learning R
- Author(s):
- Release date: September 2013
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781449357108
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