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
One non-empty character string (it MUST be quoted) containing the operators and values to apply to `e1`. Operators can be chained together using either `|` or `&`; these connectors must appear between complete conditions, not at the start or end of the string, and cannot be doubled. 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)