inst/doc/nicer_roperators.R

In roperators: Additional Operators to Help you Write Cleaner R Code

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
require(roperators)
# require(magrittr)

iris_data <- iris

## -----------------------------------------------------------------------------
require(roperators)
my_string <- 'using infix (%) operators ' %+% 'R can do simple string addition'
print(my_string)

## -----------------------------------------------------------------------------
my_string %-% 'R can do simple string addition'

## -----------------------------------------------------------------------------
my_a <- 'a'
my_a %s*% 3
# If a is an unnamed vector, the original value is saved as the element name(s)
# just to make it easier to undo by my_a <- names(my_a)

## -----------------------------------------------------------------------------
# How many times does the letter a appear in the string
'an apple a day keeps the malignant spirit of Steve Jobs at bay' %s/% 'a' 

## -----------------------------------------------------------------------------
# How many times is Steve Jobs or apple mentioned?
'an apple a day keeps the malignant spirit of Steve Jobs at bay' %s/% 'Steve Jobs|apple' 

## ---- eval = FALSE------------------------------------------------------------
#  iris_data$Sepal.Length <- iris_data$Sepal.Length + 1

## -----------------------------------------------------------------------------
iris_data$Sepal.Length[iris_data$Species == 'setosa'] <- iris_data$Sepal.Length[iris_data$Species == 'setosa'] + 1
# ...which may not even fit on the page. 

## ---- eval = FALSE------------------------------------------------------------
#  iris_data$Sepal.Length %+=% 1

## -----------------------------------------------------------------------------
iris_data$Sepal.Length[iris_data$Species == 'setosa'] %+=% 1
# ...which is ike a breath of fresh air

## -----------------------------------------------------------------------------
x <- c("a1b", "b1", "c", "d0")
# Replace digits with the letter x
x %regex=% c("\\d+", "i")
 # x is now c("aib", "bi", "c", "di")
print(x)

## -----------------------------------------------------------------------------
x <- c(NA, 1, 2, 3)
x %na<-% 0
print(x)

## -----------------------------------------------------------------------------
x <- c("aib", "bi", "c", "di")
x %regex<-% c('i', '[redacted]')
print(x)

## -----------------------------------------------------------------------------
x <- c(NA, 'foo', 'foo', NA)
y <- c(NA, 'foo', 'bar', 'bar')

x %==% y

## -----------------------------------------------------------------------------
x == y

## ---- eval=FALSE--------------------------------------------------------------
#  (0.1 * 3) == 0.3  # FALSE
#  (0.1 * 5) == 0.5  # TRUE
#  (0.1 * 7) == 0.7  # FALSE
#  (0.1 * 11) == 1.1 # TRUE
#  
#  (0.1 * 3) >= 0.3 # TRUE
#  (0.1 * 3) <= 0.3 # FALSE

## ---- eval=FALSE--------------------------------------------------------------
#  (0.1 * 3)  %~=% 0.3  # TRUE
#  (0.1 * 5)  %~=% 0.5  # TRUE
#  (0.1 * 7)  %~=% 0.7  # TRUE
#  (0.1 * 11) %~=% 1.1  # TRUE
#  
#  (0.1 * 3) %>~% 0.3 #TRUE
#  (0.1 * 3) %<~% 0.3 #TRUE

## ---- eval=FALSE--------------------------------------------------------------
#  isTRUE(all.equal(0.1 * 3, 0.3))  # TRUE
#  isTRUE(all.equal(0.1 * 5, 0.5))  # TRUE
#  isTRUE(all.equal(0.1 * 7, 0.7))  # TRUE
#  isTRUE(all.equal(0.1 * 11, 1.1))  # TRUE
#  
#  
#  isTRUE(all.equal(0.1 * 3, 0.3)) | ((0.1 * 3) > 0.3)
#  isTRUE(all.equal(0.1 * 3, 0.3)) | ((0.1 * 3) < 0.3)
#  # I feel dirty even typing that as an example.

## -----------------------------------------------------------------------------
5 %><% c(1, 10)  # TRUE
1 %><% c(1, 10)  # FALSE
1 %>=<% c(1, 10) # TRUE

# note that due to my simple mindedness, at the time of writing, 5 %><% c(10, 1) is FALSE

## -----------------------------------------------------------------------------
!1 %in% c(2,3,4)

## -----------------------------------------------------------------------------
1 %ni% c(2,3,4)

## ---- eval=FALSE--------------------------------------------------------------
#  if((a|b) & xor(y, z))

## ---- eval=FALSE--------------------------------------------------------------
#  if((a|b) & (y %xor% z))

## ---- eval=FALSE--------------------------------------------------------------
#  if((a*2 == b+2) %aon% (x^2 == y*10))
#  # Compared to
#  if((a*2 == b+2) == (x^2 == y*10))
#  # which takes my brain a little bit more time to read

## -----------------------------------------------------------------------------
x <- c('TRUE', 'FALSE', 'TRUE', 'TRUE')

percent_true <- paste0(sum(as.integer(as.logical(x))) / length(x)*100, '%')
print(percent_true)


## -----------------------------------------------------------------------------
percent_true <- (sum(int(bool(x))) / length(x) * 100) %+% '%'
print(percent_true)

## -----------------------------------------------------------------------------
foo <- 204
as.class(foo, "roman")

## ---- eval=FALSE--------------------------------------------------------------
#  if(is.atomic(x) & (length(x) >= 1) & !is.na(x) & !is_nan(x) & !is.na(as.numeric(x)) & !is.factor(x) & !is.infinite(x) ){
#    ...
#  }

## ---- eval = FALSE------------------------------------------------------------
#  if(!is.bad_for_calcs(x)){
#    ...
#  }

## ---- eval=FALSE--------------------------------------------------------------
#  my_stuff <- c(1:10, 10, 5)
#  
#  # These are straight forward
#  get_1st(my_stuff)    # 1
#  get_nth(my_stuff, 3) # 3
#  get_last(my_stuff)   # 5
#  
#  # Returns numeric vector of mode(s) if x is numeric
#  get_most_frequent(my_stuff) # c(10, 5)
#  
#  # Else it returns a character vector
#  my_chars <- c("a", "b", "b", "a", "g", "o", "l", "d")
#  get_most_frequent(my_chars) # c("a", "b")
#  
#  # can collapse into a single string (for convienience)
#  get_most_frequent(my_chars, collapse = " & ") # "a & b"
#  

## ---- eval=FALSE--------------------------------------------------------------
#  generic_string <- "Who's A good boy? Winston's a good boy!"
#  
#  get_1st_word(generic_string)    # Who's
#  get_nth_word(generic_string, 3) # good
#  get_last_word(generic_string)   # boy!
#  
#  # default ignores case and punctuation
#  get_most_frequent_word(generic_string) # c("a", "boy", "good")
#  
#  # can change like so:
#  get_most_frequent_word(generic_string, ignore.case = FALSE, ignore.punct = FALSE)
#  # "good"
#