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What is R Programming?
R is a programming language and software environment for statistical computing and graphics. It is widely used among statisticians and data miners for developing statistical software and data analysis. R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. R is an open-source software, and users can write new R functions, and can easily access the functionality of R packages contributed by others. R is also a popular choice for data visualization and reporting.
Here are some popular tools and libraries used in R programming:
- RStudio: An integrated development environment (IDE) for R, which makes it easier to write and run R code.
- ggplot2: A data visualization library that allows users to create highly customizable and expressive graphics.
- dplyr: A data manipulation library that provides a simple and efficient way to manipulate data frames.
- tidyr: A library for tidying messy data, making it easy to reshape and restructure data for analysis.
- caret: A library for training and evaluating machine learning models.
- Shiny: A web application framework for building interactive web applications using R.
- lubridate: A library for working with dates and times in R.
- stringr: A library for working with strings, providing a number of useful functions for manipulating and searching strings.
- MASS: A library for fitting and analyzing statistical models, including linear and nonlinear models.
- tidyr: A library for reshaping data, making it easy to reshape and restructure data for analysis.
These are some of the popular R tools, but there are many more available, catering to a wide range of use cases and applications.