# Data Types

Want to learn more? I recommend working through: R for Data Science, R Cookbook, and R Graphics Cookbook.

## Vectors

### Vectors could best be described as rows of information.

### Create a row containing five values x <- c(1,2,3,4,5)

## Factors

### Factors are best thought about as categories, and each individual category is represented by a name and a numerical identifying value.

### Create a factor that represents a variable with three categories y <- factor(c("yes", "no", "maybe"))

## Matrix

### A matrix is a great of numbers, but no text strings

### Create a matrix of some data k <- matrix(data = 1:15, nrow = 5, ncol = 5, byrow = T)

## Arrays

### An array is like a matrix, but in 3D (like a time series)

### Create an array z <- array(1:27,dim=c(3,3,3))

## Lists

### A list is a list of R objects, any objects

### Create variables of three different data types f <- c(1:4) j <- FALSE u <- matrix(c(1:4),nrow=2,ncol=2) ### Combine them into a list m <- list(f,j,u)

## Dataframes

### Data frames are like excel spreadsheets, all types of data in a big grid

s <- 1:5 d <- c(T,T,F,F,T) df <- data.frame(s,d)