rec | R Documentation |
This function recodes numeric vectors, character vectors, or factors according to recode specifications.
rec(x, spec, as.factor = FALSE, levels = NULL, names = ".r", as.na = NULL,
table = FALSE, check = TRUE)
x |
a numeric vector, character vector, factor, matrix or data frame. |
spec |
a character string of recode specifications (see 'Details'). |
as.factor |
logical: if |
levels |
a character vector for specifying the levels in the returned factor. |
as.na |
a numeric vector indicating user-defined missing values,
i.e. these values are converted to |
names |
a character string or character vector indicating the names
of the recoded variables when specifying more than one variable.
By default, variables are named with the ending |
table |
logical: if |
check |
logical: if |
Recode specifications appear in a character string, separated by semicolons
(see the examples below), of the form input = output. If an input value satisfies
more than one specification, then the first (from left to right) applies. If
no specification is satisfied, then the input value is carried over to the
result. NA
is allowed in input and output. Several recode specifications
are supported:
- single value For example, 0 = NA
- vector of values For example, c(7, 8, 9) = 'high'
- range of values
For example, 7:9 = 'C'. The special values lo (lowest value) and hi (highest
value) may appear in a range. For example, lo:10 = 1
. Note that :
is not the R sequence operator. In addition you may not use :
with the
collect operator, e.g., c(1, 3, 5:7)
will cause an error.
- else
For example, else = NA
. Everything that does not fit a previous specification.
Note that else
matches all otherwise unspecified values on input, including
NA
.
Returns a numeric vector or data frame with the same length or same number of
rows as x
containing the recoded coded variable(s).
This function was adapted from the recode()
function in the car
package by John Fox and Sanford Weisberg (2019).
Takuya Yanagida takuya.yanagida@univie.ac.at
Fox, J., & Weisberg S. (2019). An R Companion to Applied Regression (3rd ed.). Thousand Oaks CA: Sage. URL: https://socialsciences.mcmaster.ca/jfox/Books/Companion/
item.reverse
#--------------------------------------
# Numeric vector
x.num <- c(1, 2, 4, 5, 6, 8, 12, 15, 19, 20)
# Recode 5 = 50 and 19 = 190
rec(x.num, "5 = 50; 19 = 190")
# Recode 1, 2, and 5 = 100 and 4, 6, and 7 = 200 and else = 300
rec(x.num, "c(1, 2, 5) = 100; c(4, 6, 7) = 200; else = 300")
# Recode lowest value to 10 = 100 and 11 to highest value = 200
rec(x.num, "lo:10 = 100; 11:hi = 200")
# Recode 5 = 50 and 19 = 190 and check recoding
rec(x.num, "5 = 50; 19 = 190", table = TRUE)
#--------------------------------------
# Character vector
x.chr <- c("a", "c", "f", "j", "k")
# Recode a to x
rec(x.chr, "'a' = 'X'")
# Recode a and f to x, c and j to y, and else to z
rec(x.chr, "c('a', 'f') = 'x'; c('c', 'j') = 'y'; else = 'z'")
# Recode a to x and coerce to a factor
rec(x.chr, "'a' = 'X'", as.factor = TRUE)
#--------------------------------------
# Factor
x.fac <- factor(c("a", "b", "a", "c", "d", "d", "b", "b", "a"))
# Recode a to x, factor levels ordered alphabetically
rec(x.fac, "'a' = 'x'")
# Recode a to x, user-defined factor levels
rec(x.fac, "'a' = 'x'", levels = c("x", "b", "c", "d"))
#--------------------------------------
# Multiple variables
dat <- data.frame(x1.num = c(1, 2, 4, 5, 6),
x2.num = c(5, 19, 2, 6, 3),
x1.chr = c("a", "c", "f", "j", "k"),
x2.chr = c("b", "c", "a", "d", "k"),
x1.fac = factor(c("a", "b", "a", "c", "d")),
x2.fac = factor(c("b", "a", "d", "c", "e")))
# Recode numeric vector and attach to 'dat'
dat <- cbind(dat,
rec(dat[, c("x1.num", "x2.num")], "5 = 50; 19 = 190"))
# Recode character vector and attach to 'dat'
dat <- cbind(dat,
rec(dat[, c("x1.chr", "x2.chr")], "'a' = 'X'"))
# Recode factor vector and attach to 'dat'
dat <- cbind(dat,
rec(dat[, c("x1.fac", "x2.fac")], "'a' = 'X'"))
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