R Basics

Welcome to the R Basics section! This series of tutorials is designed to introduce you to the fundamentals of R programming, a powerful tool for data analysis, statistical computing, and graphics. Whether you are new to programming or transitioning from another language, these tutorials will guide you step-by-step through the essential concepts and techniques in R.

Contents

  • Introduction to R
    • Learn what R is, its history, and its applications in various fields.
  • Installing R and RStudio
    • Step-by-step instructions on how to install R and RStudio on your computer, making it easy to get started with R programming.
  • Basic R Syntax
    • An introduction to the basic syntax and structure of R code, including how to write and run simple R scripts.
  • Data Types in R
    • Explore the different types of data in R, such as numeric, character, and logical, and understand how to work with them.
  • Vectors
    • Learn about vectors, a fundamental data structure in R, and how to create, manipulate, and use them in various operations.
  • Matrices
    • Discover matrices in R, how to create them, and perform operations on matrix data.
  • Lists
    • Understand lists, a versatile data structure in R, including how to create, access, and manipulate list elements.
  • Data Frames
    • Get to know data frames, essential for storing tabular data in R, and learn how to work with them effectively.
  • Factors
    • Introduction to factors, which are used for handling categorical data in R, including how to create and use them.
  • Basic Operations
    • Learn about basic arithmetic, relational, and logical operations in R.
  • Functions in R
    • Discover how to define and use functions in R to encapsulate reusable code.
  • Control Structures
    • Understand control structures like if-else statements and loops, which are essential for controlling the flow of your R programs.
  • Importing Data
    • Learn how to import data into R from various sources, such as CSV and Excel files, to start your data analysis.
  • Data Cleaning
    • Techniques for cleaning and preparing your data in R to ensure it’s ready for analysis.
  • Data Manipulation with dplyr
    • Introduction to the dplyr package, which simplifies data manipulation tasks like filtering, selecting, and summarizing data.
  • String Manipulation
    • Learn how to manipulate and work with text data in R using various string functions.
  • Working with Dates
    • Discover how to handle date and time data in R, including parsing and formatting dates.
  • Descriptive Statistics
    • Learn how to calculate and interpret descriptive statistics, such as mean, median, and standard deviation, in R.
  • Introduction to Packages
    • Understand how to extend R’s functionality by installing and using packages from CRAN and other repositories.
  • Exporting Data
    • Learn how to export your data from R to various formats, such as CSV and Excel files, for sharing and reporting.

We hope you find these tutorials helpful as you embark on your journey to learn R programming. Let’s get started!