# Load packages

# Core
library(tidyverse)
library(tidyquant)

Functions

When should you write a function

# For Reproducible work
set.seed(1234)
# Create a data frame
df <- tibble::tibble(
  a = rnorm(10),
  b = rnorm(10),
  c = rnorm(10),
  d = rnorm(10)
)
# 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$a - min(df$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 0.332 0.153  0.782 0.765
##  2 0.765 0      0.473 0.897
##  3 1     0.0651 0.498 0.969
##  4 0     0.311  0.943 0.664
##  5 0.809 0.573  0.373 0.911
##  6 0.831 0.260  0     0.917
##  7 0.516 0.143  1     0.821
##  8 0.524 0.0255 0.210 0.824
##  9 0.519 0.0472 0.708 0.822
## 10 0.424 1      0.253 0.793
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 0.332 0.153  0.782 0.332
##  2 0.765 0      0.473 0.765
##  3 1     0.0651 0.498 1    
##  4 0     0.311  0.943 0    
##  5 0.809 0.573  0.373 0.809
##  6 0.831 0.260  0     0.831
##  7 0.516 0.143  1     0.516
##  8 0.524 0.0255 0.210 0.524
##  9 0.519 0.0472 0.708 0.519
## 10 0.424 1      0.253 0.424

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()
0 %>% detect_sign()
## [1] 0
# -1 %>% detect_sign()

Function arguements

?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_remover_na <- function(x, na.rm = TRUE, ...) {
    
    avg <- mean(x, na.rm = na.rm, ...)
    
    return(avg)
    
} 
x %>% mean_remover_na()
## [1] 14.09091
x %>% mean_remover_na(na.rm = FALSE)
## [1] NA
x %>% mean_remover_na(trim = 0.1)
## [1] 6

Two types of functions:

Return Values