R
Data Analysis and Statistics
R is a programming language designed for data analysis and statistical computing. It is widely used by data scientists, statisticians, and researchers for various purposes.
Why R?
For developers, R offers several advantages over other programming languages:
- R has a focus on data analysis and statistical computing, with a range of built-in functions and libraries for these tasks.
- It provides a high-level interface for data manipulation and visualization, making it easy to explore and analyze complex data sets.
- R has a large and active community of users and contributors, with many resources and tutorials available.
R Syntax
- R has a simple and intuitive syntax, with a focus on data manipulation and analysis.
- It supports various data types, including vectors, matrices, data frames, and lists.
- R has built-in support for statistical functions and libraries.
Free Resources for Learning R
- R Project: The official R website, with downloads, documentation, and resources.
- R Tutorial: A comprehensive tutorial for learning R, covering the basics of data analysis and visualization.
- R for Data Science: A book by Hadley Wickham and Garrett Grolemund, covering the fundamentals of data science with R.
- Coursera: Various online courses on R programming and data science.
R Frameworks and Libraries
- R has a large and diverse ecosystem of libraries and packages, catering to various data science use cases such as data manipulation, visualization, machine learning, and more.
- Popular R libraries include ggplot2, dplyr, tidyr
File Extensions
- .R