Add new column to dataframe with duplicated values pasted together [duplicate] - r

Question

This question already has answers here:
Collapse / concatenate / aggregate a column to a single comma separated string within each group
(6 answers)
Closed 3 years ago.
I have a df looking like this:
ID Country
55 Poland
55 Romania
55 France
98 Spain
98 Portugal
98 UK
65 Germany
67 Luxembourg
84 Greece
22 Estonia
22 Lithuania
Where some ID are repeated because they belong to the same group. What I want to do is to paste together all Country with the same ID, to have an output like this.
So far, I tried with
ifelse(df[duplicated(df$ID) | duplicated(df$ID, fromLast = TRUE),], paste('Countries', df$Country), NA) but this is not retrieving the expected output.

Answer 1

Using data.table
library(data.table)
setDT(df)[, New_Name := c(paste0(Country, collapse = " + ")[1L], rep(NA, .N -1)), by = ID]
#df
#ID Country New_Name
#1: 55 Poland Poland + Romania + France
#2: 55 Romania <NA>
#3: 55 France <NA>
#4: 98 Spain Spain + Portugal + UK
#5: 98 Portugal <NA>
#6: 98 UK <NA>
#7: 65 Germany Germany
#8: 67 Luxembourg Luxembourg
#9: 84 Greece Greece
#10: 22 Estonia Estonia + Lithuania
#11: 22 Lithuania <NA>

Answer 2

Using base R,
replace(v1 <- with(df, ave(as.character(Country), ID, FUN = toString)), duplicated(v1), NA)
#[1] "Poland, Romania, France" NA NA "Spain, Portugal, UK" NA NA "Germany" "Luxembourg" "Greece" "Estonia, Lithuania"
#[11] NA

Answer 3

Using dplyr, one way would be
library(dplyr)
df %>%
group_by(ID) %>%
mutate(new_name = paste0(Country,collapse = " + "),
new_name = replace(new_name, duplicated(new_name), NA))
# ID Country new_name
# <int> <fct> <chr>
# 1 55 Poland Poland + Romania + France
# 2 55 Romania NA
# 3 55 France NA
# 4 98 Spain Spain + Portugal + UK
# 5 98 Portugal NA
# 6 98 UK NA
# 7 65 Germany Germany
# 8 67 Luxembourg Luxembourg
# 9 84 Greece Greece
#10 22 Estonia Estonia + Lithuania
#11 22 Lithuania NA
However, to get your exact expected output we might need
df %>%
group_by(ID) %>%
mutate(new_name = if (n() > 1)
paste0("Countries ", paste0(Country,collapse = " + ")) else Country,
new_name = replace(new_name, duplicated(new_name), NA))
# ID Country new_name
# <int> <fct> <chr>
# 1 55 Poland Countries Poland + Romania + France
# 2 55 Romania NA
# 3 55 France NA
# 4 98 Spain Countries Spain + Portugal + UK
# 5 98 Portugal NA
# 6 98 UK NA
# 7 65 Germany Germany
# 8 67 Luxembourg Luxembourg
# 9 84 Greece Greece
#10 22 Estonia Countries Estonia + Lithuania
#11 22 Lithuania NA

Answer 4

Using aggregate and then matching back for the first time only:
flat <- function(x) paste("Countries:", paste(x,collapse=", "))
tmp <- aggregate(Country ~ ID, data=dat, FUN=flat)
dat$Country <- NA
dat$Country[match(tmp$ID, dat$ID)] <- tmp$Country
# ID Country
#1 55 Countries: Poland, Romania, France
#2 55 <NA>
#3 55 <NA>
#4 98 Countries: Spain, Portugal, UK
#5 98 <NA>
#6 98 <NA>
#7 65 Countries: Germany
#8 67 Countries: Luxembourg
#9 84 Countries: Greece
#10 22 Countries: Estonia, Lithuania
#11 22 <NA>

Answer 5

With purrr and dplyr:
df %>%
nest(-ID) %>%
mutate(new_name = map_chr(data, ~ paste0(.x$Country, collapse = " + "))) %>%
unnest()
Table:
ID new_name Country
55 Poland + Romania + France Poland
55 Poland + Romania + France Romania
55 Poland + Romania + France France
98 Spain + Portugal + UK Spain
98 Spain + Portugal + UK Portugal
98 Spain + Portugal + UK UK
65 Germany Germany
67 Luxembourg Luxembourg
84 Greece Greece
22 Estonia + Lithuania Estonia
22 Estonia + Lithuania Lithuania