Recode.RdCombining or rearranging a factor can be tedious if it has many levels. Recode supports this step by
accepting a direct definition of new levels by enumerating old levelnames as argument and adding an "elselevel" option. If new levels are given as integer values they will be translated in the according levels.
Recode(x, ..., elselevel = NA, use.empty = FALSE, num = FALSE)the factor whose levels are to be altered. If x is character it will be factorized (using factor defaults).
the old levels (combined by c() if there are several) named with the new level:newlevel_a=c("old_a", "old_b"), newlevel_b=c("old_c", "old_d")
See examples.
the value for levels, which are not matched by newlevel list.
If this is set to NULL, the elselevels will be left unchanged.
If set to NA (default) non matched levels will be set to NA.
logical. Defines how a new level, which can't be found in x, should be handled. Should it be left in the level's list or be dropped? The default is FALSE,
which drops empty levels.
logical. If set to TRUE the result will be numeric.
the factor having the new levels applied.
set.seed(1984)
x <- factor(sample(1:15, 20, replace=TRUE))
levels(x) <- paste("old", levels(x), sep="_")
y <- Recode(x,
"new_1" = c("old_1","old_4","old_5"),
"new_2" = c("old_6","old_10","old_11"),
"new_3" = c("old_12","old_13"),
elselevel = "other")
data.frame(x=x, y=y)
#> x y
#> 1 old_8 other
#> 2 old_14 other
#> 3 old_4 new_1
#> 4 old_10 new_2
#> 5 old_1 new_1
#> 6 old_5 new_1
#> 7 old_14 other
#> 8 old_3 other
#> 9 old_15 other
#> 10 old_8 other
#> 11 old_1 new_1
#> 12 old_13 new_3
#> 13 old_4 new_1
#> 14 old_8 other
#> 15 old_1 new_1
#> 16 old_4 new_1
#> 17 old_6 new_2
#> 18 old_15 other
#> 19 old_13 new_3
#> 20 old_13 new_3
# Coding NAs, NA is recoded to new_1
x[5:6] <- NA
x <- x[1:7]
data.frame(
x,
RecodeNA = Recode(x,
"new_1" = c("old_4","old_8", NA),
elselevel = "other"),
# NAs remain untouched
NoRecodeNA = Recode(x,
"new_1" = c("old_4","old_8"),
elselevel = "other")
)
#> x RecodeNA NoRecodeNA
#> 1 old_8 new_1 new_1
#> 2 old_14 other other
#> 3 old_4 new_1 new_1
#> 4 old_10 other other
#> 5 <NA> new_1 <NA>
#> 6 <NA> new_1 <NA>
#> 7 old_14 other other
x <- factor(letters[1:6])
z1 <- Recode(x, AB=c("a","b"), CD=c("c","d"), elselevel="none of these")
z2 <- Recode(x, AB=c("a","b"), CD=c("c","d"), elselevel=NA)
z3 <- Recode(x, AB=c("a","b"), CD=c("c","d"), elselevel=NULL)
z4 <- Recode(x, AB=c("a","b"), GH=c("g","h"), elselevel=NA, use.empty=TRUE)
z5 <- Recode(x, AB=c("a","b"), GH=c("g","h"), elselevel=NA, use.empty=FALSE)
data.frame(z1, z2, z3, z4, z5)
#> z1 z2 z3 z4 z5
#> 1 AB AB AB AB AB
#> 2 AB AB AB AB AB
#> 3 CD CD CD <NA> <NA>
#> 4 CD CD CD <NA> <NA>
#> 5 none of these <NA> e <NA> <NA>
#> 6 none of these <NA> f <NA> <NA>
lapply(data.frame(z1, z2, z3, z4, z5), levels)
#> $z1
#> [1] "AB" "CD" "none of these"
#>
#> $z2
#> [1] "AB" "CD"
#>
#> $z3
#> [1] "AB" "CD" "e" "f"
#>
#> $z4
#> [1] "AB" "GH"
#>
#> $z5
#> [1] "AB"
#>
# empty level GH exists in z4...
table(z4, useNA="ifany")
#> z4
#> AB GH <NA>
#> 2 0 4
# and is dropped in z5
table(z5, useNA="ifany")
#> z5
#> AB <NA>
#> 2 4
# use integers to define the groups to collapse
set.seed(1972)
(likert <- factor(sample(1:10, size=15, replace=TRUE),
levels=1:10, labels=gettextf("(%s)", 1:10)))
#> [1] (4) (10) (9) (1) (3) (7) (10) (7) (8) (10) (1) (6) (9) (10) (5)
#> Levels: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Recode(likert, det=1:6, pas=7:8, pro=9:10)
#> [1] det pro pro det det pas pro pas pas pro det det pro pro det
#> Levels: det pas pro
# or directly turned to numeric
Recode(likert, "1"=1:6, "2"=7:8, "5"=9:10, num=TRUE)
#> [1] 1 5 5 1 1 2 5 2 2 5 1 1 5 5 1