For example if I have this:
n = c(2, 3, 5)
s = c("aa", "bb", "cc")
b = c(TRUE, FALSE, TRUE)
df = data.frame(n, s, b)
n s b
1 2 aa TRUE
2 3 bb FALSE
3 5 cc TRUE
Then how do I combine the two columns n
and s
into a new column named x
such that it looks like this:
n s b x
1 2 aa TRUE 2 aa
2 3 bb FALSE 3 bb
3 5 cc TRUE 5 cc
This question is related to
r
dataframe
multiple-columns
r-faq
We can use paste0:
df$combField <- paste0(df$x, df$y)
If you do not want any padding space introduced in the concatenated field. This is more useful if you are planning to use the combined field as a unique id that represents combinations of two fields.
There are other great answers, but in the case where you don't know the column names or the number of columns you want to concatenate beforehand, the following is useful.
df = data.frame(x = letters[1:5], y = letters[6:10], z = letters[11:15])
colNames = colnames(df) # could be any number of column names here
df$newColumn = apply(df[, colNames, drop = F], MARGIN = 1, FUN = function(i) paste(i, collapse = ""))
As already mentioned in comments by Uwe and UseR, a general solution in the tidyverse
format would be to use the command unite
:
library(tidyverse)
n = c(2, 3, 5)
s = c("aa", "bb", "cc")
b = c(TRUE, FALSE, TRUE)
df = data.frame(n, s, b) %>%
unite(x, c(n, s), sep = " ", remove = FALSE)
Instead of
paste
(default spaces), paste0
(force the inclusion of missing NA
as character) or unite
(constrained to 2 columns and 1 separator), I'd suggest an alternative as flexible as paste0
but more careful with NA
: stringr::str_c
library(tidyverse)
# check the missing value!!
df <- tibble(
n = c(2, 2, 8),
s = c("aa", "aa", NA_character_),
b = c(TRUE, FALSE, TRUE)
)
df %>%
mutate(
paste = paste(n,"-",s,".",b),
paste0 = paste0(n,"-",s,".",b),
str_c = str_c(n,"-",s,".",b)
) %>%
# convert missing value to ""
mutate(
s_2=str_replace_na(s,replacement = "")
) %>%
mutate(
str_c_2 = str_c(n,"-",s_2,".",b)
)
#> # A tibble: 3 x 8
#> n s b paste paste0 str_c s_2 str_c_2
#> <dbl> <chr> <lgl> <chr> <chr> <chr> <chr> <chr>
#> 1 2 aa TRUE 2 - aa . TRUE 2-aa.TRUE 2-aa.TRUE "aa" 2-aa.TRUE
#> 2 2 aa FALSE 2 - aa . FALSE 2-aa.FALSE 2-aa.FALSE "aa" 2-aa.FALSE
#> 3 8 <NA> TRUE 8 - NA . TRUE 8-NA.TRUE <NA> "" 8-.TRUE
Created on 2020-04-10 by the reprex package (v0.3.0)
extra note from str_c
documentation
Like most other R functions, missing values are "infectious": whenever a missing value is combined with another string the result will always be missing. Use
str_replace_na()
to convertNA
to"NA"
Using dplyr::mutate
:
library(dplyr)
df <- mutate(df, x = paste(n, s))
df
> df
n s b x
1 2 aa TRUE 2 aa
2 3 bb FALSE 3 bb
3 5 cc TRUE 5 cc
Some examples with NAs and their removal using apply
n = c(2, NA, NA)
s = c("aa", "bb", NA)
b = c(TRUE, FALSE, NA)
c = c(2, 3, 5)
d = c("aa", NA, "cc")
e = c(TRUE, NA, TRUE)
df = data.frame(n, s, b, c, d, e)
paste_noNA <- function(x,sep=", ") {
gsub(", " ,sep, toString(x[!is.na(x) & x!="" & x!="NA"] ) ) }
sep=" "
df$x <- apply( df[ , c(1:6) ] , 1 , paste_noNA , sep=sep)
df
Use paste
.
df$x <- paste(df$n,df$s)
df
# n s b x
# 1 2 aa TRUE 2 aa
# 2 3 bb FALSE 3 bb
# 3 5 cc TRUE 5 cc
For inserting a separator:
df$x <- paste(df$n, "-", df$s)
Source: Stackoverflow.com