CodeToLive

Introduction to R

R is a programming language and environment for statistical computing and graphics. It is widely used for data analysis, machine learning, and data visualization. R provides a rich ecosystem of packages for various statistical and graphical techniques.

Key Features of R:

• Statistical Computing: R is designed for statistical analysis and data manipulation.
• Data Visualization: R provides powerful tools for creating graphs and plots.
• Extensive Libraries: R has a vast collection of packages for various tasks.
• Open Source: R is free to use and has a large community of contributors.

Example: Hello World in R

# R Hello World Program
print("Hello, World!")
      

This program uses the print function to display "Hello, World!" on the screen.

Installing R

To get started with R, you need to install it on your computer. You can download R from the official website: CRAN (Comprehensive R Archive Network).

RStudio

RStudio is an integrated development environment (IDE) for R. It provides a user-friendly interface for writing and executing R code. You can download RStudio from: RStudio Download.

Basic R Syntax

R syntax is straightforward and easy to learn. Here are some basic examples:

# Assigning values to variables
x <- 10
y <- 20

# Performing arithmetic operations
sum <- x + y
print(sum)

# Creating a vector
numbers <- c(1, 2, 3, 4, 5)
print(numbers)
      

In the above example, we assign values to variables, perform arithmetic operations, and create a vector.

Data Structures in R

R supports various data structures such as vectors, matrices, lists, and data frames. Here's an example of a data frame:

# Creating a data frame
df <- data.frame(
  Name = c("Alice", "Bob", "Charlie"),
  Age = c(25, 30, 35),
  Gender = c("Female", "Male", "Male")
)

# Displaying the data frame
print(df)
      

Data frames are commonly used for storing and manipulating tabular data.