This operator allows operators on the right hand side to be chained together. The intended use case is when you have a single object on which you want to perform several operations. For example, testing whether a variable is between 1 and 5 or equals special number 9, which might be used to indicate that someone responded to a question (i.e., its not missing per se) but that they preferred not to answer or did not know the answer.
Arguments
- e1
The values to be operated on, on the left hand side
- e2
A character string (it MUST be quoted) containing all the operators and their values to apply to `e1`. Note that in this character string, operators can be chained together using either `|` or `&`. Parentheses are also supported and work as expected. See examples for more information on how this function is used.
Details
` `is.na`, `!is.na`, `is.nan`, and `!is.nan`. These do not need any values supplied but they work as expected to add those logical assessments into the chain of operators.
Examples
## define a variable
sample_data <- c(1, 3, 9, 5, NA, -9)
## suppose that we expect that values should fall in [1, 10]
## unless they are special character, -9 used for unknown / refused
sample_data %c% "( >= 1 & <= 10 ) | == -9"
#> [1] TRUE TRUE TRUE TRUE NA TRUE
## we might expect some missing values and be OK as long as
## above conditions are met or values are missing
sample_data %c% "( >= 1 & <= 10 ) | == -9 | is.na"
#> [1] TRUE TRUE TRUE TRUE TRUE TRUE
## equally we might be expecting NO missing values
## and want missing values to come up as FALSE
sample_data %c% "(( >= 1 & <= 10 ) | == -9) & !is.na"
#> [1] TRUE TRUE TRUE TRUE FALSE TRUE
c(1, 3, 9, 5, NA, -9) %c% "is.na & (( >= 1 & <= 10 ) | == -9)"
#> [1] FALSE FALSE FALSE FALSE NA FALSE
## clean up
rm(sample_data)