Chapter 20: Vectors

Introduction

Vector basics

Important types of automic vector

Using atomic vectors

sample(10) + 10
##  [1] 16 14 18 12 15 11 19 20 13 17
1:10 + 1:2
##  [1]  2  4  4  6  6  8  8 10 10 12
1:10 + 1:3
## Warning in 1:10 + 1:3: longer object length is not a multiple of shorter object
## length
##  [1]  2  4  6  5  7  9  8 10 12 11
data.frame(a = 1:10, b = 1:2)
##     a b
## 1   1 1
## 2   2 2
## 3   3 1
## 4   4 2
## 5   5 1
## 6   6 2
## 7   7 1
## 8   8 2
## 9   9 1
## 10 10 2
 # data.frame(a = 1:10, b = 1:3)
# Giving names
    set_names(1:3, c("a", "b", "c"))
## a b c 
## 1 2 3
x <- sample(10)
x
##  [1] 10  9  5  8  7  2  6  3  1  4
x[c(5, 7)]
## [1] 7 6
x [x>5]
## [1] 10  9  8  7  6

Recursive vectors

x1 <- list(c(1, 2), c(3, 4))
x2 <- list(list(1, 2), list(3, 4))
x3 <- list(1, list(2, list(3)))

x1
## [[1]]
## [1] 1 2
## 
## [[2]]
## [1] 3 4
x2
## [[1]]
## [[1]][[1]]
## [1] 1
## 
## [[1]][[2]]
## [1] 2
## 
## 
## [[2]]
## [[2]][[1]]
## [1] 3
## 
## [[2]][[2]]
## [1] 4
x3
## [[1]]
## [1] 1
## 
## [[2]]
## [[2]][[1]]
## [1] 2
## 
## [[2]][[2]]
## [[2]][[2]][[1]]
## [1] 3
a <- list(a = 1:3, b = "a string", c = pi, d = list(-1, -5))
a
## $a
## [1] 1 2 3
## 
## $b
## [1] "a string"
## 
## $c
## [1] 3.141593
## 
## $d
## $d[[1]]
## [1] -1
## 
## $d[[2]]
## [1] -5
a[1:2]
## $a
## [1] 1 2 3
## 
## $b
## [1] "a string"
a[[4]]
## [[1]]
## [1] -1
## 
## [[2]]
## [1] -5
a[[4]][2]
## [[1]]
## [1] -5
a[[4]][[2]]
## [1] -5

Attributes

Augmented vectors

 # Factors
x <- factor(c("ab", "cd", "ab"), levels = c("ab", "cd", "ef"))
x
## [1] ab cd ab
## Levels: ab cd ef

Chapter 21: Iteration

Introduction

For loops

 # Example from cheatsheet - https://iqss.github.io/dss-workshops/R/Rintro/base-r-cheat-sheet.pdf
for (i in 1:4){
    j <- i + 10
    print(j)
}
## [1] 11
## [1] 12
## [1] 13
## [1] 14
 # Example 1: numeric calculation - adding 10
x <- 11:15

for (i in seq_along(x)){
    j <- x[i] + 10
    print(j)
}
## [1] 21
## [1] 22
## [1] 23
## [1] 24
## [1] 25
 # Save output
y <- vector("integer", length(x))

for (i in seq_along(x)){
    y[i] <- x[i] + 10
    print(y[i])
}
## [1] 21
## [1] 22
## [1] 23
## [1] 24
## [1] 25
 # Output
y
## [1] 21 22 23 24 25
 # Example 2: String operation - extrect first letter
x <- c("abc", "xyz")

y <- vector("character", length(x))

for (i in seq_along(x)){
    y[i] <- x[i] %>% str_extract("[a-z]")
    print(y[i])
}
## [1] "a"
## [1] "x"

For loop variations

For loops vs. functionals

The map functions

 # Example 1: numeric calculation - adding 10
x <- 11:15

y <- vector("integer", length(x))

for (i in seq_along(x)){
    y[i] <- x[i] + 10
    print(y[i])
}
## [1] 21
## [1] 22
## [1] 23
## [1] 24
## [1] 25
 # Output
y
## [1] 21 22 23 24 25
 # Using map function
x
## [1] 11 12 13 14 15
map(.x = x, .f = ~.x + 10)
## [[1]]
## [1] 21
## 
## [[2]]
## [1] 22
## 
## [[3]]
## [1] 23
## 
## [[4]]
## [1] 24
## 
## [[5]]
## [1] 25
map_dbl(.x = x, .f = ~.x + 10)
## [1] 21 22 23 24 25
add_10 <- function(x) {x + 10}
11 %>% add_10()
## [1] 21
map_dbl(.x = x, .f = add_10)
## [1] 21 22 23 24 25

Dealing with failure