Chapter 20 Vectors

Introduction

Vector Basics

Important types of atomic vector

Using atomic vectors

sample(10) + 10
##  [1] 19 17 15 12 14 18 16 20 11 13
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)
x <- sample(10)
x
##  [1]  4  5  3  6 10  8  9  7  2  1
x[c(5, 7)]
## [1] 10  9
x[x>5]
## [1]  6 10  8  9  7

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)))
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

Chapter 21 Interation

Introduction

For loops

# example from the cheat sheet
for(i in 1:4) {
    j <- i + 10
    print(j)
}
## [1] 11
## [1] 12
## [1] 13
## [1] 14
# example 1: numeric calculation - add 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 - extract 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"
# output
y
## [1] "a" "x"

For loop variations

For loops vs fuctionals

The map functions

# example 1: numeric calculation - add 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
df <- tibble(
  a = rnorm(10),
  b = rnorm(10),
  c = rnorm(10),
  d = rnorm(10))

median(df$a)
## [1] -0.7798424
median(df$b)
## [1] 0.04230232
median(df$c)
## [1] 0.02292061
median(df$d)
## [1] 0.5437188
map_dbl(df, mean)
##           a           b           c           d 
## -0.55322329 -0.07684597  0.01101724  0.07115537
map_dbl(df, median)
##           a           b           c           d 
## -0.77984240  0.04230232  0.02292061  0.54371880
map_dbl(df, sd)
##         a         b         c         d 
## 0.6894449 0.7372814 0.9488514 1.4366086