Intro

When to Write a Function

set.seed(1234)

df <- tibble::tibble(
  a = rnorm(10),
  b = rnorm(10),
  c = rnorm(10),
  d = rnorm(10)
)
# Rescale Colums
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$b, na.rm = TRUE) - min(df$a, 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))
rescale <- function(x){
    #body
    x<- (x - min(x, na.rm = TRUE)) / 
  (max(x, na.rm = TRUE) - min(x, na.rm = TRUE))
    #retun values
    return(x)}
df$a <- rescale(df$a)
df$b <- rescale(df$b)
df$c <- rescale(df$c)
df$d <- rescale(df$d)

Functions for Humans & 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 can be accepted")
    } else {
        stop("vale is negitive, function must stop")
    }
}
3%>% detect_sign()
## value is positive
## [1] 3
0%>% detect_sign()
## Warning in detect_sign(.): value is not positive, but can be accepted
#-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 * one that takes tvector as the input * another that takes a data frame as the inupt

Return Values