Introduction to R and Python

Learn how to set up R and RStudio on your machine. We will also demonstrate how to install R packages from CRAN, and install the tidyverse package.

Welcome

This tutorial introduces both R and Python programming, covering fundamental topics such as data types, variables, operators, and loops. Use the tabs below to switch between R and Python content.

Data Types in R

  • Integer: Whole numbers (e.g., 42, -3)
  • Double/Floating Point: Decimal numbers (e.g., 3.14, -2.718)
  • Character (String): Text in quotes (e.g., "Hello World")
  • Logical (Boolean): TRUE, FALSE
  • Missing Values: NA, NaN
# Examples of Data Types in R
x <- 42   # Integer
y <- 3.14 # Floating point
z <- "Hello, R!"  # String
is_valid <- TRUE   # Boolean
print(c(x, y, z, is_valid))

Variables in R

a <- 10
b <- 5
c <- a + b  # Addition
print(c)    # Output: 15

Data Types in Python

  • Integer: Whole numbers (42, -3)
  • Float: Decimal numbers (3.14, -2.718)
  • String: Text in quotes ("Hello World")
  • Boolean: True, False
# Examples of Data Types in Python
x = 42   # Integer
y = 3.14 # Float
z = "Hello, Python!"  # String
is_valid = True   # Boolean
print(x, y, z, is_valid)

Variables in Python

a = 10
b = 5
c = a + b  # Addition
print(c)   # Output: 15

Loops

Loops allow us to execute a block of code multiple times, reducing repetition and making our programs more efficient. The two most common types of loops are:

  • For loops: Used when we know how many times we need to iterate.
  • While loops: Used when we repeat execution until a condition is met.

Below are examples of loops in R and Python:

R

Python