How to replace specific values in a column with other values?

I have a data frame and want to add a new column to it based on another column and then replace its values.

For example column ID_old is what I have:

df1 <- structure(list(ID.old=c(1,1,1,  2,2,  3,3,3,3,  4,4,  5,5,5,5,5,  6,6,6,  7,7,7,7,  8,8,  9, 10,10,10, 11,11,  12,12,12, 13,13,  14,14,14,14, 15,15,  16, 17,17, 18, 19,19,19, 20,20,20)),
                 class = "data.frame", row.names = c(NA,-52L))

and now column ID_new is what I need:

df2 <- structure(list(ID.old=c(1,1,1,  2,2,  3,3,3,3,  4,4,  5,5,5,5,5,  6,6,6,  7,7,7,7,  8,8,  9, 10,10,10, 11,11,  12,12,12, 13,13,  14,14,14,14, 15,15,  16, 17,17, 18, 19,19,19, 20,20,20),
                      ID.new=c('a1','a1','a1', 'a2','a2', 'a3','a3','a3','a3', 'a4','a4', 'a5','a5','a5','a5','a5', 'a1','a1','a1', 'a2','a2','a2','a2', 'a3','a3', 'a4', 'a5','a5','a5', 'a1','a1', 'a2','a2','a2', 'a3','a3', 'a4','a4','a4','a4', 'a5','a5', 'a1', 'a2','a2', 'a3', 'a4','a4','a4', 'a5','a5','a5')),
                 class = "data.frame", row.names = c(NA,-52L))

I thought that I can use str_replace_all from stringer, but it produces something different,

library(stringr)
df1<- df1 %>% 
  mutate(ID.new = ID.old)
replace = c("1"="a1", "2"="a2", "3"="a3", "4"="a4", "5"="a5",
            "6"="a1", "7"="a2", "8"="a3", "9"="a4", "10"="a5",
            "11"="a1", "12"="a2", "13"="a3", "14"="a4", "15"="a5",
            "16"="a1", "17"="a2", "18"="a3", "19"="a4", "20"="a5")

df1$ID.new<- str_replace_all(df1$ID.new, replace)

in my original data frame, I have many rows, and specifically, I need wherever it is 1,6,11,16 to be "a1".

2,7,12,17 to be "a2" etc.

How can I get a column like what we have in df2 ID.new
Thanks

>Solution :

stringr::str_replace_all is based on regex. For example, with your ‘replace’ dictionnary, it replaces every 1 it encounters with "a1", so the number ’11’ is replaced by "a1a1", as it contains two successive 1. Since you have already designed a dictionary, you should simply add ‘start’ (^) and end ($) regex tags, as I suggest below:

1. Simply add this line of code after the creation of your actual ‘replace’ dictionnary:

names(replace) = paste0("^", names(replace), "$")

2. And know the replacement is correct if you proceed again df1$ID.new<- str_replace_all(df1$ID.new, replace)