Introduction to R Programming for Beginners

Overview

• R Programming Language: Popular language for data science, statistical computing, and data mining
• Comparison with Python: R is ranked higher than Python in data mining among experts
• Open Source: Free to use and has a large community with over 9000 packages
• Optimization: Especially beneficial for vector operations

Features of R

• Free and Open Source: No licensing costs
• Easy to Learn: Suitable for both coders and non-coders
• Integration: Works with languages such as C, C++, Java, and Python
• Packages: Comes with built-in packages and datasets for easier data analysis and reporting

Setting Up R

1. Download from R Project: Visit r-project.org
2. Choose CRAN Mirror: Preferably use zero cloud mirror for fast download
3. Select OS: Windows, Mac, or Linux
4. Install Base R and R Studio: Base R is required; RStudio is optional but recommended
5. Workspace: RStudio provides a better interface to work with R

Working With R Studio

• Installation: Download and install from the RStudio website
• Interface: Includes console, scripts editor, environment variables, and plots section
• Loading Data: Load built-in datasets using functions like data() and summary()
• Basic Commands: control + enter to run scripts, data manipulation, and plotting

Basics of R Programming

Variables

• Declaration: Store data values like numbers, characters, etc.
• Assignment Operator: <- to assign values
• Naming Conventions: Use letters, digits, periods, and underscores
• Case Sensitivity: Variable names are case-sensitive

e.g., model1 <-