Introduction

# Create a data frame
df <- tibble::tibble(
    a = rnorm(10),
    b = rnorm(10),
    c = rnorm(10),
    d = rnorm(10)
)
# For reproducible work
set.seed(1234)

# Rescale each column

df$a <- (df$a - min(df$a, na.rm = TRUE)) /
    (max(df$a, na.rm = TRUE) - min(df$a, na.rm = TRUE))
df$b <- (df$b - min(df$b, na.rm = TRUE)) /
    (max(df$b, na.rm = TRUE) - min(df$b, na.rm = TRUE))
df$c <- (df$c - min(df$c, na.rm = TRUE)) /
    (max(df$c, na.rm = TRUE) - min(df$c, na.rm = TRUE))
 df$d <- (df$d - min(df$d, na.rm = TRUE)) /
    (max(df$d, na.rm = TRUE) - min(df$d, na.rm = TRUE))
 
 df
## # A tibble: 10 × 4
##         a     b     c     d
##     <dbl> <dbl> <dbl> <dbl>
##  1 0.0176 0.381 0.978 0    
##  2 0      1     0.364 0.333
##  3 0.962  0.889 0.983 0.405
##  4 0.336  0     1     0.403
##  5 0.940  0.204 0     0.549
##  6 0.798  0.295 0.258 1    
##  7 0.559  0.601 0.548 0.440
##  8 1      0.436 0.694 0.952
##  9 0.594  0.557 0.141 0.218
## 10 0.0655 0.456 0.115 0.120
rescale <- function(x) {
    
    # body
    x <- (x - min(x, na.rm = TRUE)) /
        (max(x, na.rm = TRUE) - min(x, na.rm = TRUE))
    
    # return values
    return(x)
}
df$a <- rescale(df$a)
df$b <- rescale(df$b)
df$c <- rescale(df$c)
df$d <- rescale(df$d)

df
## # A tibble: 10 × 4
##         a     b     c     d
##     <dbl> <dbl> <dbl> <dbl>
##  1 0.0176 0.381 0.978 0    
##  2 0      1     0.364 0.333
##  3 0.962  0.889 0.983 0.405
##  4 0.336  0     1     0.403
##  5 0.940  0.204 0     0.549
##  6 0.798  0.295 0.258 1    
##  7 0.559  0.601 0.548 0.440
##  8 1      0.436 0.694 0.952
##  9 0.594  0.557 0.141 0.218
## 10 0.0655 0.456 0.115 0.120

Functions are for humans and computers

Conditional execution

detect_sign <- function(x) {
    
    
    if(x > 0) {
        message("Value is positive")
        print(x)
    } else if(x == 0) {
        warning("Value is not positive, but it can be accepted")
        print(x)
    } else {
        stop("Value is negative, the function must stop")
        print(x)
    }
}

3 %>% detect_sign()
## Value is positive
## [1] 3
0 %>% detect_sign()
## Warning in detect_sign(.): Value is not positive, but it can be accepted
## [1] 0
# -1 %>% detect_sign()

Function arguments

?mean

x <- c(1:10, 100, NA)
x
##  [1]   1   2   3   4   5   6   7   8   9  10 100  NA
x %>%mean()
## [1] NA
x %>%mean(na.rm = TRUE)
## [1] 14.09091
x %>%mean(na.rm = TRUE, trim = 0.1)
## [1] 6
mean_remove_na <- function(x, na.rm = TRUE, ...) {
    
    avg <- mean(x, na.rm = na.rm, ...)
    
    return(avg)
}

x %>% mean_remove_na()
## [1] 14.09091
x %>% mean_remove_na(na.rm = FALSE)
## [1] NA
x %>% mean_remove_na(trim = 0.1)
## [1] 6

two types of functions