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Overview of Extended Binary Operators for Data Manipulation

James J Balamuta

2025-05-27

Source: vignettes/rops.Rmd
rops.Rmd

Overview

When writing functions or simply perform data analyses, sometimes you may wish for just that one additional operator or equality check that speeds up the process greatly. The goal behind this package is to provide such operators with as minimal an overhead as possible.

Package Installation

To install the package, please type:

Using the package

To use the package, please load it into the R session by typing:

Coalescing Operators

Null coalescing operator 

# Null value
x = NULL

# Before
y = if(is.null(x)){ "Unset" } else { x }

# After
y = x %??% "Unset"

y
## [1] "Unset"

Missing value (NA) coalescing operator

To impute values when “missingness” is detected, the ifna() provides a convenient interface.

x = c(1:5, NA, NA, 8, NA, 10)
y = 1:10

# Before
ifelse(is.na(x), x, y)
##  [1]  1  2  3  4  5 NA NA  8 NA 10
ifelse(is.na(x), x, 3)
##  [1]  3  3  3  3  3 NA NA  3 NA  3
# After
ifna(x, y)
##  [1]  1  2  3  4  5  6  7  8  9 10
ifna(x, 3)
##  [1]  1  2  3  4  5  3  3  8  3 10

Equality Operators

Checking for exact equivalence in object can be done using an infix operator instead of relying upon identical().

NB There are cases where checking with all.equal() is preferred.

x = y = 1:5
x2 = x + 1

# Before
identical(x, y)
## [1] TRUE
identical(x2, y)
## [1] FALSE
# After
x %==% y
## [1] TRUE
x2 %==% y
## [1] FALSE
# Before
!identical(x, y)
## [1] FALSE
!identical(x2, y)
## [1] TRUE
# After
x %!=% y
## [1] FALSE
x2 %!=% y
## [1] TRUE

Whole Numbers

Previously, using is.integer() would yield a check on the type of vector. Here, the is_whole() function seeks to check the state of all numbers individually in the vector regardless of whether they are numeric or integer.

x = c(1, 2, 3, 8.5)
y = c(1L, 2L, 3L)

# Before
is.integer(x)
## [1] FALSE
## [1] TRUE
# After
is_whole(x)
## [1]  TRUE  TRUE  TRUE FALSE
## [1] TRUE TRUE TRUE

Safe Sequence Generation

The colon operator (:) does not perform a check on whether the increment should be positive or negative. This leads to issues when iterating over an empty vector or data.frame using 1:length(obj). To avoid this, safe sequences %:% performs a check to make sure the sequence is positive. If it is not, then an empty integer vector is created to avoid having a loop run.

x = NULL

# Before
1:length(x)
## [1] 1 0
# After
1 %:% length(x)
## integer(0)

Not in Set

The not in set operator is a negation of the %in% operator that checks for whether an element belongs to the set.

x = 1:5
set = 3:10

# Before
!(x %in% set)
## [1]  TRUE  TRUE FALSE FALSE FALSE
# After
x %notin% set
## [1]  TRUE  TRUE FALSE FALSE FALSE