Recode Numeric Values in R

Recode numeric values in R

This function does not work on numeric vector. If you want to use it, you can do as follows:

 x <- 1:10 # your numeric vector

 as.numeric(revalue(as.character(x), c("2" = "33", "4" = "88")))

 # [1]  1 33  3 88  5  6  7  8  9 10

How to recode a range of values in a variable and coerce it to a factor?

Using cut with labels:

df$education_recoded <- cut(df$education, breaks = c(0,3,5), 
                            labels = c("Up to secondary school", 
                                       "University studies or higher"))
# compare the values
table(df$education_recoded, df$education)
#                               1  2  3  4  5
# Up to secondary school       21 24 24  0  0
# University studies or higher  0  0  0 15 16

Or using pipes:

library(dplyr)  

df %>% 
  mutate(education_recoded = cut(education, breaks = c(0,3,5), 
                                 labels = c("Up to secondary school", 
                                            "University studies or higher")))

Recode Numeric To Character

The 'v1' can be used as an index as it is a sequence of values from 1. So, if we pass the new vector to rename in the order we want, then 'pass' will replace whereever there is 1 value in 'v1', 'arb' for 2 and 'rtk' for 3

library(data.table)
setDT(have)[, v1 := c('pass', 'arb', 'rtk')[v1]]

Another option is using a named vector to do the match

nm1 <- setNames(c('pass', 'arb', 'rtk'),  1:3)
setDT(have)[, v1 := nm1[as.character(v1)]]

---

Or do this with a factor label option

setDT(have)[, v1 := as.character(factor(v1, levels = 1:3, 
           labels = c('pass', 'arb', 'rtk')))]

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In the OP's code, the recode is using comparison operator (==), instead it would be =. Also, for values that are numeric, wrap with backquote

setDT(have)[, v1  := dplyr::recode(v1, `1` = "pass", `2`="arb", `3`="rtk")]

How do I recode multiple variables from string to numeric?

The following method seems to have worked for my issue (recoding string variables to numeric in multiple columns):

For_Analysis <- data.frame(Q11_1=c("Never", "Often", "Sometimes"),
 Q11_2=c("Sometimes", "Often", "Never"), Q11_3=c("Never", "Never", "Often"))

New_Values <- c(1, 2, 3, 4, 5)
Old_Values <- unique(For_Analysis$Q11_1)

For_Analysis[1:3] <- as.data.frame(sapply(For_Analysis[1:3],
                     mapvalues, from = Old_Values, to = New_Values))

Thanks for the help!

Recode a range of values into one number using 'recode()' in tidyverse

It may be easier with case_when

library(dplyr)
case_when(var %in% 10:30 ~ 4,
               var %in% 6:9 ~ 3, 
               var %in% 3:5 ~ 2,
               var %in% 1:2 ~ 1, 
                var == 0 ~ 0)

---

Or another option is cut

as.integer(cut(var, breaks = c(-Inf, 0, 2, 5, 9, 30, Inf)))

NOTE: change the include.lowest and right option in cut to adjust

data

set.seed(24)
var <- sample(0:35, 50, replace = TRUE)

Recode character IDs into numeric IDs

library(dplyr)
library(stringr)
df %>%
  mutate(
    group = str_extract(id, "[0-9]+")
  ) %>%
  group_by(group) %>%
  mutate(id = as.numeric(paste0(group, if(n() > 1) row_number() else ""))) %>%
  ungroup() %>%
  select(-group)
# # A tibble: 10 × 2
#      id Grade
#   <dbl> <dbl>
# 1    11     3
# 2    21     3
# 3    22     3
# 4   331     4
# 5   332     4
# 6   333     4
# 7   351     5
# 8   352     5
# 9   353     5
#10   354     5

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