recode  R Documentation 
recode
change, rearrange or consolidate the values of an existing
variable based on conditions. Design of this function inspired by RECODE from
SPSS. Sequence of recodings provided in the form of formulas. For example,
1:2 ~ 1 means that all 1's and 2's will be replaced with 1. Each value will be
recoded only once. In the assignment form recode(...) = ...
of this
function values which doesn't meet any condition remain unchanged. In case of
the usual form ... = recode(...)
values which doesn't meet any
condition will be replaced with NA. One can use values or more sophisticated
logical conditions and functions as a condition. There are several special
functions for usage as criteria  for details see criteria. Simple
common usage looks like: recode(x, 1:2 ~ 1, 3 ~ 0, 1:2 ~ 1, 99 ~ NA)
.
For more information, see details and examples.
The ifs
function checks whether one or more conditions are met and
returns a value that corresponds to the first TRUE condition. ifs
can
take the place of multiple nested ifelse
statements and is much
easier to read with multiple conditions. ifs
works in the same manner
as recode
 e. g. with formulas. But conditions
should be only logical and it doesn't operate on multicolumn objects.
recode( x, ..., with_labels = FALSE, new_label = c("all", "range", "first", "last") ) rec(x, ..., with_labels = TRUE, new_label = c("all", "range", "first", "last")) recode(x, with_labels = FALSE, new_label = c("all", "range", "first", "last")) < value rec(x, with_labels = TRUE, new_label = c("all", "range", "first", "last")) < value ifs(...) lo hi copy(x) from_to(from, to) values %into% names
x 
vector/matrix/data.frame/list 
... 
sequence of formulas which describe recodings. They are used when

with_labels 
logical. FALSE by default for 'recode' and TRUE for 'rec'. Should we also recode value labels with the same recodings as variable? 
new_label 
one of "all", "range", "first", or "last". If we recode value labels ('with_labels = TRUE') how we will combine labels for duplicated values? "all" will use all labels, "range" will use first and last labels. See examples. 
value 
list with formulas which describe recodings in assignment form
of function/ 
from 
list of conditions for values which should be recoded (in the same format as LHS of formulas). 
to 
list of values into which old values should be recoded (in the same format as RHS of formulas). 
values 
object(s) which will be assigned to 
names 
name(s) which will be given to 
An object of class numeric
of length 1.
An object of class numeric
of length 1.
Input conditions  possible values for lefthand side (LHS) of formula or
element of from
list:
vector/single value All values in x
which equal to elements of the
vector in LHS will be replaced with RHS.
function Values for which function gives TRUE will be replaced with RHS. There are some special functions for the convenience  see criteria.
single logical value TRUE
It means all other unrecoded values
(ELSE in SPSS RECODE). All other unrecoded values will be changed to RHS of the
formula or appropriate element of to
.
Output values  possible values for righthand side (RHS) of formula or
element of to
list:
value replace elements of x
. This value will be
recycled across rows and columns of x
.
vector values of this vector will replace values in the corresponding
position in rows of x
. Vector will be recycled across columns of
x
.
function This function will be applied to values of x
which
satisfy recoding condition. There is a special auxiliary function copy
which just returns its argument. So, in the recode
it just copies old
value (COPY in SPSS RECODE). See examples.
%into%
tries to mimic SPSS 'INTO'. Values from lefthand side will
be assigned to righthand side. You can use %to%
expression in the
RHS of %into%
. See examples.
lo
and hi
are shortcuts for Inf
and Inf
. They
can be useful in expressions with %thru%
, e. g. 1 %thru%
hi
.
object of the same form as x
with recoded values
# examples from SPSS manual # RECODE V1 TO V3 (0=1) (1=0) (2, 3=1) (9=9) (ELSE=SYSMIS) v1 = c(0, 1, 2, 3, 9, 10) recode(v1) = c(0 ~ 1, 1 ~ 0, 2:3 ~ 1, 9 ~ 9, TRUE ~ NA) v1 # RECODE QVAR(1 THRU 5=1)(6 THRU 10=2)(11 THRU HI=3)(ELSE=0). qvar = c(1:20, 97, NA, NA) recode(qvar, 1 %thru% 5 ~ 1, 6 %thru% 10 ~ 2, 11 %thru% hi ~ 3, TRUE ~ 0) # the same result recode(qvar, 1 %thru% 5 ~ 1, 6 %thru% 10 ~ 2, ge(11) ~ 3, TRUE ~ 0) # RECODE STRNGVAR ('A', 'B', 'C'='A')('D', 'E', 'F'='B')(ELSE=' '). strngvar = LETTERS recode(strngvar, c('A', 'B', 'C') ~ 'A', c('D', 'E', 'F') ~ 'B', TRUE ~ ' ') # recode in place. Note that we recode only first six letters recode(strngvar) = c(c('A', 'B', 'C') ~ 'A', c('D', 'E', 'F') ~ 'B') strngvar # RECODE AGE (MISSING=9) (18 THRU HI=1) (0 THRU 18=0) INTO VOTER. age = c(NA, 2:40, NA) voter = recode(age, NA ~ 9, 18 %thru% hi ~ 1, 0 %thru% 18 ~ 0) voter # the same result with '%into%' recode(age, NA ~ 9, 18 %thru% hi ~ 1, 0 %thru% 18 ~ 0) %into% voter2 voter2 # recode with adding labels voter = recode(age, "Refuse to answer" = NA ~ 9, "Vote" = 18 %thru% hi ~ 1, "Don't vote" = 0 %thru% 18 ~ 0) voter # recoding with labels ol = c(1:7, 99) var_lab(ol) = "Liking" val_lab(ol) = num_lab(" 1 Disgusting 2 Very Poor 3 Poor 4 Soso 5 Good 6 Very good 7 Excellent 99 Hard to say ") recode(ol, 1:3 ~ 1, 5:7 ~ 7, TRUE ~ copy, with_labels = TRUE) # 'rec' is a shortcut for recoding with labels. Same result: rec(ol, 1:3 ~ 1, 5:7 ~ 7, TRUE ~ copy) # another method of combining labels recode(ol, 1:3 ~ 1, 5:7 ~ 7, TRUE ~ copy, with_labels = TRUE, new_label = "range") # example with from/to notation # RECODE QVAR(1 THRU 5=1)(6 THRU 10=2)(11 THRU HI=3)(ELSE=0). list_from = list(1 %thru% 5, 6 %thru% 10, ge(11), TRUE) list_to = list(1, 2, 3, 0) recode(qvar, from_to(list_from, list_to)) list_from = list(NA, 18 %thru% hi, 0 %thru% 18) list_to = list("Refuse to answer" = 9, "Vote" = 1, "Don't vote" = 0) voter = recode(age, from_to(list_from, list_to)) voter # 'ifs' examples a = 1:5 b = 5:1 ifs(b>3 ~ 1) # c(1, 1, NA, NA, NA) ifs(b>3 ~ 1, TRUE ~ 3) # c(1, 1, 3, 3, 3) ifs(b>3 ~ 1, a>4 ~ 7, TRUE ~ 3) # c(1, 1, 3, 3, 7) ifs(b>3 ~ a, TRUE ~ 42) # c(1, 2, 42, 42, 42) # advanced usage #' # multiple assignment with '%into%' set.seed(123) x1 = runif(30) x2 = runif(30) x3 = runif(30) # note nessesary brackets around RHS of '%into%' recode(x1 %to% x3, gt(0.5) ~ 1, other ~ 0) %into% (x_rec_1 %to% x_rec_3) fre(x_rec_1) # the same operation with characters expansion i = 1:3 recode(x1 %to% x3, gt(0.5) ~ 1, other ~ 0) %into% text_expand('x_rec2_{i}') fre(x_rec2_1) # factor recoding a = factor(letters[1:4]) recode(a, "a" ~ "z", TRUE ~ copy) # we get factor # example with function in RHS data(iris) new_iris = recode(iris, is.numeric ~ scale, other ~ copy) str(new_iris) set.seed(123) a = rnorm(20) # if a<(0.5) we change it to absolute value of a (abs function) recode(a, lt(0.5) ~ abs, other ~ copy) # the same example with logical criteria recode(a, when(a<(.5)) ~ abs, other ~ copy)
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