Recode Items, Factors and Numeric Vectors
recode.Rdrecode substitutes old values of a factor or a numeric
vector by new ones, just like the recoding facilities in some
commercial statistical packages.
Usage
recode(x,...,
copy=getOption("recode_copy",identical(otherwise,"copy")),
otherwise=NA)
# S4 method for class 'vector'
recode(x,...,
copy=getOption("recode_copy",identical(otherwise,"copy")),
otherwise=NA)
# S4 method for class 'factor'
recode(x,...,
copy=getOption("recode_copy",identical(otherwise,"copy")),
otherwise=NA)
# S4 method for class 'item'
recode(x,...,
copy=getOption("recode_copy",identical(otherwise,"copy")),
otherwise=NA)Arguments
- x
An object
- ...
One or more assignment expressions, each of the form
new.value <- old.values.new.valueshould be a scalar numeric value or character string. If one of thenew.values is a character string, the return value ofrecodewill be a factor and eachnew.valuewill be coerced to a character string that labels a level of the factor.Each
old.valuein an assignment expression may be a (numeric or character) vector. Ifxis numeric such an assignment expression may have the formnew.value <- range(lower,upper)In that case, values betweenlowerandupperare exchanged bynew.value. If one of the arguments torangeismin, it is substituted by the minimum ofx. If one of the arguments torangeismax, it is substituted by the maximum ofx.In case of the method for
labelledvectors, the tags of arguments of the formtag = new.value <- old.valueswill define the labels of the new codes.If the
old.valuesof different assignment expressions overlap, an error will be raised because the recoding is ambigous.- copy
logical; should those values of
xnot given an explicit new code copied into the resulting vector?- otherwise
a character string or some other value that the result may obtain. If equal to
NAor"NA", original codes not given an explicit new code are recoded intoNA. If equal to"copy", original codes not given an explicit new code are copied.
Details
recode relies on the lazy evaluation mechanism of R:
Arguments are not evaluated until required by the function they are given to.
recode does not cause arguments that appear in ... to be evaluated.
Instead, recode parses the ... arguments. Therefore, although
expressions like 1 <- 1:4 would cause an error action, if evaluated
at any place elsewhere in R, they will not cause an error action,
if given to recode as an argument. However, a call of the
form recode(x,1=1:4), would be a syntax error.
If John Fox' package "car" is installed, recode will also be callable
with the syntax of the recode function of that package.
Examples
x <- as.item(sample(1:6,20,replace=TRUE),
labels=c( a=1,
b=2,
c=3,
d=4,
e=5,
f=6))
print(x)
#> [1] d b c b d a f d e e d f f b d d a b e f
codebook(
recode(x,
a = 1 <- 1:2,
b = 2 <- 4:6))
#> Warning: recoding created 1 NAs
#> ================================================================================
#>
#> recode(x, a = 1 <- 1:2, b = 2 <- 4:6)
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Valid Total
#>
#> 1 'a' 6 31.6 30.0
#> 2 'b' 13 68.4 65.0
#> NA M 1 5.0
#>
codebook(
recode(x,
a = 1 <- 1:2,
b = 2 <- 4:6,
copy = TRUE))
#> ================================================================================
#>
#> recode(x, a = 1 <- 1:2, b = 2 <- 4:6, copy = TRUE)
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'a' 6 30.0
#> 2 'b' 13 65.0
#> 3 'c' 1 5.0
#>
# Note the handling of labels if the recoding rules are bijective
codebook(
recode(x,
1 <- 2,
2 <- 1,
copy=TRUE))
#> ================================================================================
#>
#> recode(x, 1 <- 2, 2 <- 1, copy = TRUE)
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'b' 4 20.0
#> 2 'a' 2 10.0
#> 3 'c' 1 5.0
#> 4 'd' 6 30.0
#> 5 'e' 3 15.0
#> 6 'f' 4 20.0
#>
codebook(
recode(x,
a = 1 <- 2,
b = 2 <- 1,
copy=TRUE))
#> ================================================================================
#>
#> recode(x, a = 1 <- 2, b = 2 <- 1, copy = TRUE)
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'a' 4 20.0
#> 2 'b' 2 10.0
#> 3 'c' 1 5.0
#> 4 'd' 6 30.0
#> 5 'e' 3 15.0
#> 6 'f' 4 20.0
#>
# A recoded version of x is returned
# containing the values 1, 2, 3, which are
# labelled as "A", "B", "C".
recode(x,
A = 1 <- range(min,2),
B = 2 <- 3:4,
C = 3 <- range(5,max), # this last comma is ignored
)
#>
#> Item (measurement: nominal, type: integer, length = 20)
#>
#> [1:20] B A B A B A C B C C B C C A B B A A C C
# This causes an error action: the sets
# of original values overlap.
try(recode(x,
A = 1 <- range(min,2),
B = 2 <- 2:4,
C = 3 <- range(5,max)
))
#> Error in recode(x, A = 1 <- range(min, 2), B = 2 <- 2:4, C = 3 <- range(5, :
#> recoding request is ambiguous
recode(x,
A = 1 <- range(min,2),
B = 2 <- 3:4,
C = 3 <- range(5,6),
D = 4 <- 7
)
#> Warning: recoding 4 <- 7 has no consequences
#>
#> Item (measurement: nominal, type: integer, length = 20)
#>
#> [1:20] B A B A B A C B C C B C C A B B A A C C
# This results in an all-missing vector:
recode(x,
D = 4 <- 7,
E = 5 <- 8
)
#> Warning: recodings 4 <- 7, 5 <- 8 have no consequences
#> Warning: recoding created 20 NAs
#>
#> Item (measurement: nominal, type: integer, length = 20)
#>
#> [1:20] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
f <- as.factor(x)
x <- as.integer(x)
recode(x,
1 <- range(min,2),
2 <- 3:4,
3 <- range(5,max)
)
#> [1] 2 1 2 1 2 1 3 2 3 3 2 3 3 1 2 2 1 1 3 3
# This causes another error action:
# the third argument is an invalid
# expression for a recoding.
try(recode(x,
1 <- range(min,2),
3:4,
3 <- range(5,max)
))
#> Error in recode(x, 1 <- range(min, 2), 3:4, 3 <- range(5, max)) :
#> invalid recoding request
# The new values are character strings,
# therefore a factor is returned.
recode(x,
"a" <- range(min,2),
"b" <- 3:4,
"c" <- range(5,6)
)
#> [1] b a b a b a c b c c b c c a b b a a c c
#> Levels: a b c
recode(x,
1 <- 1:3,
2 <- 4:6
)
#> [1] 2 1 1 1 2 1 2 2 2 2 2 2 2 1 2 2 1 1 2 2
recode(x,
4 <- 7,
5 <- 8,
otherwise = "copy"
)
#> Warning: recodings 4 <- 7, 5 <- 8 have no consequences
#> [1] 4 2 3 2 4 1 6 4 5 5 4 6 6 2 4 4 1 2 5 6
recode(f,
"A" <- c("a","b"),
"B" <- c("c","d"),
otherwise="copy"
)
#> [1] B A B A B A f B e e B f f A B B A A e f
#> Levels: A B e f
recode(f,
"A" <- c("a","b"),
"B" <- c("c","d"),
otherwise="C"
)
#> [1] B A B A B A C B C C B C C A B B A A C C
#> Levels: A B C
recode(f,
"A" <- c("a","b"),
"B" <- c("c","d")
)
#> Warning: recoding created 7 NAs
#> [1] B A B A B A <NA> B <NA> <NA> B <NA> <NA> A B
#> [16] B A A <NA> <NA>
#> Levels: A B
DS <- data.set(x=as.item(sample(1:6,20,replace=TRUE),
labels=c( a=1,
b=2,
c=3,
d=4,
e=5,
f=6)))
print(DS)
#> x
#> 1 e
#> 2 d
#> 3 a
#> 4 e
#> 5 a
#> 6 c
#> 7 e
#> 8 e
#> 9 d
#> 10 b
#> 11 a
#> 12 f
#> 13 c
#> 14 f
#> 15 a
#> 16 d
#> 17 a
#> 18 a
#> 19 b
#> 20 a
DS <- within(DS,{
xf <- recode(x,
"a" <- range(min,2),
"b" <- 3:4,
"c" <- range(5,6)
)
xn <- x@.Data
xc <- recode(xn,
"a" <- range(min,2),
"b" <- 3:4,
"c" <- range(5,6)
)
xc <- as.character(x)
xcc <- recode(xc,
1 <- letters[1:2],
2 <- letters[3:4],
3 <- letters[5:6]
)
})
DS
#>
#> Data set with 20 observations and 5 variables
#>
#> x xf xn xc xcc
#> 1 e c 5 e 3
#> 2 d b 4 d 2
#> 3 a a 1 a 1
#> 4 e c 5 e 3
#> 5 a a 1 a 1
#> 6 c b 3 c 2
#> 7 e c 5 e 3
#> 8 e c 5 e 3
#> 9 d b 4 d 2
#> 10 b a 2 b 1
#> 11 a a 1 a 1
#> 12 f c 6 f 3
#> 13 c b 3 c 2
#> 14 f c 6 f 3
#> 15 a a 1 a 1
#> 16 d b 4 d 2
#> 17 a a 1 a 1
#> 18 a a 1 a 1
#> 19 b a 2 b 1
#> 20 a a 1 a 1
DS <- within(DS,{
xf <- recode(x,
"a" <- range(min,2),
"b" <- 3:4,
"c" <- range(5,6)
)
x1 <- recode(x,
1 <- range(1,2),
2 <- range(3,4),
copy=TRUE
)
xf1 <- recode(x,
"A" <- range(1,2),
"B" <- range(3,4),
copy=TRUE
)
})
DS
#>
#> Data set with 20 observations and 7 variables
#>
#> x xf xn xc xcc x1 xf1
#> 1 e c 5 e 3 e e
#> 2 d b 4 d 2 b B
#> 3 a a 1 a 1 a A
#> 4 e c 5 e 3 e e
#> 5 a a 1 a 1 a A
#> 6 c b 3 c 2 b B
#> 7 e c 5 e 3 e e
#> 8 e c 5 e 3 e e
#> 9 d b 4 d 2 b B
#> 10 b a 2 b 1 a A
#> 11 a a 1 a 1 a A
#> 12 f c 6 f 3 f f
#> 13 c b 3 c 2 b B
#> 14 f c 6 f 3 f f
#> 15 a a 1 a 1 a A
#> 16 d b 4 d 2 b B
#> 17 a a 1 a 1 a A
#> 18 a a 1 a 1 a A
#> 19 b a 2 b 1 a A
#> 20 a a 1 a 1 a A
codebook(DS)
#> ================================================================================
#>
#> x
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'a' 7 35.0
#> 2 'b' 2 10.0
#> 3 'c' 2 10.0
#> 4 'd' 3 15.0
#> 5 'e' 4 20.0
#> 6 'f' 2 10.0
#>
#> ================================================================================
#>
#> xf
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'a' 9 45.0
#> 2 'b' 5 25.0
#> 3 'c' 6 30.0
#>
#> ================================================================================
#>
#> xn
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: interval
#>
#> Min: 1.000
#> Max: 6.000
#> Mean: 3.050
#> Std.Dev.: 1.830
#>
#> ================================================================================
#>
#> xc
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: character
#> Measurement: nominal
#>
#> Min: "a"
#> Max: "f"
#>
#> ================================================================================
#>
#> xcc
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 '1' 9 45.0
#> 2 '2' 5 25.0
#> 3 '3' 6 30.0
#>
#> ================================================================================
#>
#> x1
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'a' 9 45.0
#> 2 'b' 5 25.0
#> 5 'e' 4 20.0
#> 6 'f' 2 10.0
#>
#> ================================================================================
#>
#> xf1
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Measurement: nominal
#>
#> Values and labels N Percent
#>
#> 1 'A' 9 45.0
#> 2 'B' 5 25.0
#> 5 'e' 4 20.0
#> 6 'f' 2 10.0
#>
DF <- data.frame(x=rep(1:6,4,replace=TRUE))
DF <- within(DF,{
xf <- recode(x,
"a" <- range(min,2),
"b" <- 3:4,
"c" <- range(5,6)
)
x1 <- recode(x,
1 <- range(1,2),
2 <- range(3,4),
copy=TRUE
)
xf1 <- recode(x,
"A" <- range(1,2),
"B" <- range(3,4),
copy=TRUE
)
xf2 <- recode(x,
"B" <- range(3,4),
"A" <- range(1,2),
copy=TRUE
)
})
DF
#> x xf2 xf1 x1 xf
#> 1 1 A A 1 a
#> 2 2 A A 1 a
#> 3 3 B B 2 b
#> 4 4 B B 2 b
#> 5 5 5 5 5 c
#> 6 6 6 6 6 c
#> 7 1 A A 1 a
#> 8 2 A A 1 a
#> 9 3 B B 2 b
#> 10 4 B B 2 b
#> 11 5 5 5 5 c
#> 12 6 6 6 6 c
#> 13 1 A A 1 a
#> 14 2 A A 1 a
#> 15 3 B B 2 b
#> 16 4 B B 2 b
#> 17 5 5 5 5 c
#> 18 6 6 6 6 c
#> 19 1 A A 1 a
#> 20 2 A A 1 a
#> 21 3 B B 2 b
#> 22 4 B B 2 b
#> 23 5 5 5 5 c
#> 24 6 6 6 6 c
codebook(DF)
#> ================================================================================
#>
#> x
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#>
#> Min: 1.000000
#> Max: 6.000000
#> Mean: 3.500000
#> Std.Dev.: 1.707825
#>
#> ================================================================================
#>
#> xf2
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Factor with 4 levels
#>
#> Levels and labels N Valid
#>
#> 1 'B' 8 33.3
#> 2 'A' 8 33.3
#> 3 '5' 4 16.7
#> 4 '6' 4 16.7
#>
#> ================================================================================
#>
#> xf1
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Factor with 4 levels
#>
#> Levels and labels N Valid
#>
#> 1 'A' 8 33.3
#> 2 'B' 8 33.3
#> 3 '5' 4 16.7
#> 4 '6' 4 16.7
#>
#> ================================================================================
#>
#> x1
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: double
#>
#> Min: 1.000000
#> Max: 6.000000
#> Mean: 2.833333
#> Std.Dev.: 1.950783
#>
#> ================================================================================
#>
#> xf
#>
#> --------------------------------------------------------------------------------
#>
#> Storage mode: integer
#> Factor with 3 levels
#>
#> Levels and labels N Valid
#>
#> 1 'a' 8 33.3
#> 2 'b' 8 33.3
#> 3 'c' 8 33.3
#>