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## R Cheatsheet

### Overview

R is a programming language and environment for statistical computing and graphics. It is widely used in data analysis, machine learning, and scientific research. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand in 1993.

### Variables

R variables can store a variety of data types, including numeric, character, logical, and complex. Variables are assigned using the `<-` or `=` operator.

Numeric variable

x <- 3.14

Character variable

name <- "Alice"

Logical variable

is_female <- TRUE

Complex variable

z <- 1 + 2i

### Functions

R has a large number of built-in functions for common tasks such as data manipulation, statistical analysis, and plotting. Functions are called by name, with arguments in parentheses.

Data manipulation

mean(c(1, 2, 3, 4, 5)) # Returns 3

Statistical analysis

t.test(c(1, 2, 3, 4, 5), mu=3) # One-sample t-test

Plotting

plot(c(1, 2, 3, 4, 5), c(1, 4, 9, 16, 25), type="l")

### Loops

R has several types of loops, including `for`, `while`, and `repeat`. The `for` loop is used to iterate over a sequence of values, while the `while` and `repeat` loops are used to repeat a block of code while a condition is true or false.

For loop

for (i in 1:10) {

print(i)

}

While loop

i <- 1

while (i <= 10) {

print(i)

i <- i + 1

}

Repeat loop

i <- 1

repeat {

print(i)

i <- i + 1

if (i > 10) {

break

}

}

### Conditionals

R has several conditional statements, including `if`, `else if`, and `else`. These statements are used to control the flow of a program based on certain conditions.

If statement

age <- 30

if (age >= 18) {

print("You are an adult")

}

If-else statement

age <- 15

if (age >= 18) {

print("You are an adult")

} else {

print("You are a minor")

}

If-else if-else statement

age <- 25

if (age < 18) {

print("You are a minor")

} else if (age < 65) {

print("You are an adult")

} else {

print("You are a senior")

}

### File Manipulation

R provides several functions for manipulating files, including `read.csv`, `write.csv`, `file.rename`, and `file.remove`.

Read CSV file

data <- read.csv("data.csv")

Write CSV file

write.csv(data, "data_new.csv")

Rename file

file.rename("data.csv", "data_old.csv")

Remove file

file.remove("data_old.csv")

### Resources

- [R documentation](https://www.r-project.org/documentation/)
- [RStudio](https://www.rstudio.com/) (integrated development environment)
- [CRAN](https://cran.r-project.org/) (community repository)
- [R for Data Science](https://r4ds.had.co.nz/) (online book)