Chapter 1:
R for Advanced Analytics
Learning Objectives
By the end of this chapter, you will be able to:
- Explain advanced R programming constructs
- Print the summary statistics of a real-world dataset
- Read data from CSV, text, and JSON files
- Write R markdown files for code reproducibility
- Explain R data structures such as data.frame, data.table, lists, arrays, and matrices
- Implement the cbind, rbind, merge, reshape, aggregate, and apply functions
- Use packages such as dplyr, plyr, caret, tm, and many more
- Create visualizations using ggplot
In this chapter, we will set the foundation for programming with R and understand the various syntax and data structures for advanced analytics.
Introduction
R was one of the early programming languages ...
Get Applied Supervised Learning with R now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
