Week 12: Code along 11

R Data Science CHAPTER 12 Functions

# Load packages

# Core
library(tidyverse)
library(tidyquant)

Functions

When should you write a function?

# Create 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$d - min(df$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 0.363  0.300  0      0.185 
##  2 0.730  1      0.512  0.295 
##  3 0.563  0.566  0.0889 0.0950
##  4 0.0860 0.296  0.717  0.402 
##  5 0      0.831  0.428  0.120 
##  6 0.263  0      0.282  0.0645
##  7 0.288  0.0308 1      0.487 
##  8 0.438  0.252  0.333  0.399 
##  9 0.0952 0.699  0.724  1     
## 10 1      0.768  0.516  0

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 0.363  0.300  0      0.185 
##  2 0.730  1      0.512  0.295 
##  3 0.563  0.566  0.0889 0.0950
##  4 0.0860 0.296  0.717  0.402 
##  5 0      0.831  0.428  0.120 
##  6 0.263  0      0.282  0.0645
##  7 0.288  0.0308 1      0.487 
##  8 0.438  0.252  0.333  0.399 
##  9 0.0952 0.699  0.724  1     
## 10 1      0.768  0.516  0

Conditional execution

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()

## [1] 3

0 %>% detect_sign()

## [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