p1c4-data-structures.qmd

# Data Structure
In computer science, a data structure refers to the method which one uses to organize their data. Six basic data structures are commonly used in R:

- **Vectors** - Vectors contain ordered data of a single type.
- **Lists** - Lists are a collection of objects.
- **Matrices** - A matrix is a two-dimensional array where the data is all of the same type.
- **Factors** - Factors are used to designate levels within categorical data.
- **Data Frames** - A data frame contains two-dimensional data where the data can have different types.
- **Arrays** - Arrays are objects which have more than two dimensions (n-dimensional).

## Vectors

We can create a vector by using the "c" function to combine multiple values into a single vector. In the following example, we will combine four separate numbers into a single vector and the output the resulting vector to see what it looks like.

```{r}
x <- c(1, 3, 3, 7)

print(x)
```

## Lists

Lists are a collection of objects. This means that each element can be a different data type (unlike vectors). In the following example we'll create a list containing two character objects and one vector with the "list" function.

```{r}
first_name <- "John"
last_name <- "Smith"
favorite_numbers <- c(1, 3, 3, 7)

person <- list(first_name, last_name, favorite_numbers)

print(person)
```

## Matrices

A matrix is a two-dimensional array where the data is all of the same type. In the following example, we'll create a matrix with three rows and four columns.

```{r}
x <- matrix(
        c(1,3,3,7,1,3,3,7,1,3,3,7)
        , nrow = 3
        , ncol = 4
        , byrow = TRUE)

print(x)
```

## Factors

Factors are used to designate levels within categorical data. In the following example, we'll use the "factor" function on a vector of assorted color names to receive the "levels" which it contains.

```{r}
x <- c("Red", "Blue", "Red", "Yellow", "Yellow")

colors <- factor(x)

print(colors)
```

## Data Frames

A data frame contains two-dimensional data. Unlike the matrix data structure, each column of a data frame can contain data of a differing type (but within a column the data must be of the same type). 
The following example will create a data frame with two rows and two columns.

```{r}
people <- c("John", "Jane")
id <- c(1, 2)
df <- data.frame(id = id, person = people)

print(df)
```

## Arrays

Arrays are objects that can have more than two dimensions. This is sometimes referred to as being "n-dimensional". The dimensions of the following example are 1 x 4 x 3. You'll see that the data consist of one row and four columns spread out over a third dimension.

```{r}
x <- array(
        c(1,3,3,7,1,3,3,7,1,3,3,7)
        , dim = c(1,4,3))

print(x)
```

## Resources

- W3 Schools: <https://www.w3schools.com/r/r_vectors.asp>