Vectors.md

Vectors

• All elements in a vector must have the same mode, which can be integer, numeric (floating-point number), character (string), logical (Boolean), complex, and so on. - The Art of R Programming
• R indeces begin at 1, not 0.
• Scalars are 1 element vectors.

Creating a vector

> x <- c(88, 5, 12, 13)

"We created a 4 element vector and assigned it to x"

The concatenate function, c, flattens vectors:

> x <- c(80, c(90, 100))
> x
[1] 80 90 100

Note that NULL values get removed:

> x <- c(NULL, 4)
> x
> [1] 4

Accessing elements in a vector

One value:

> x[1]
> [1] 88

Multiple sequential values:

> x[1:2]
> [1] 88 5

Multiple non-sequential values:

> x[c(1, 3)]
> [1] 88 12

Excluding elements from a vector

Use negative indeces:

> x[-1]
> [1] 5 12 13

Determining the length of a vector

> length(x)
[1] 4

All elements except the last

> x[1:length(x) - 1]
[1] 88  5 12

Adding vectors together

Functions will be applied element-wise:

> x <- c(1, 2, 4) + c(5, 0, -1)
[1] 6 2 3

Sequences

> seq(10)
 [1]  1  2  3  4  5  6  7  8  9 10

> seq(2, 10)
 [1]  2  3  4  5  6  7  8  9 10

> seq(2, 10, by = 2)
[1]  2  4  6  8 10

Generating a vector with repeating elements

> rep(5, 3)
[1] 5 5 5

Any and all

> x <- 1:10
> any(x > 8)
[1] TRUE
> any(x > 88)
[1] FALSE
> all(x > 88)
[1] FALSE
> all(x > 0)
[1] TRUE

Removing NA values

> x <- c(4, NA, 6)
> x[!is.na(x)]
[1] 4 6

Functions are vectorized

Meaning they are applied to each element individually:

> x <- c(1.4, 2.6)
> round(x)
[1] 1 3

Remember that scalars are actually just single-element vectors:

> x <- 4.2
> round(x)
[1] 4

Filtering

> x <- 1:3
> x[c(TRUE, FALSE, TRUE)]
[1] 1 3

> x >= 2
[1] FALSE TRUE TRUE
> x[x >= 2]
[1] 2 3

# Which is the same as the following because 2 is actually a vector and the elements are repeated when comparing them element-wise to the other vector:

> x[x >= c(2, 2, 2)]
[1] 2 3

# One more element-repeating example:

> x <- c(4, 5, 6, 7)
> x[x >= c(5, 6)]
[1] 6 7

# Which is the same as:

> x <- c(4, 5, 6, 7)
> x[x >= c(5, 6, 5, 6)]
[1] 6 7

We can also assign values to certain vector elements:

> x <- c(1,3,8,2,20)
> x[x > 3] <- 0
> x
[1] 1 3 0 2 0
```## Filtering with the `subset` function
`subset` doesn't return `NA` values:

x <- c(6, 1:3, NA, 12) x [1] 6 1 2 3 NA 12 x[x > 5] [1] 6 NA 12 subset(x, x > 5) [1] 6 12 ```## Finding indeces using the which function `which` returns the indeces of a vector that satisfy a certain condition:

> x <- c(1, 5, 10)
> which(x > 4)
[1] 2 3

The ifelse function

> x <- c(5, 2, 9, 12)
> ifelse(x > 6, 2 * x, 3 * x)
[1] 15 6 18 24

Vector element names

> grades <- c(80, 90, 100)
> names(grades) <- c("John", "Alex", "Tracy")
> grades
 John  Alex Tracy 
   80    90   100
> grades[1]
John 
  80 
> grades["John"]
 John 
  80 

Removing the names:

> names(grades) <- NULL
> grades
[1]  80  90 100

Counting how many elements are true

You can use sum:

> sum(c(TRUE, FALSE, TRUE))
[1] 2