Mutate all columns into one row (without naming each input column)-CodePudding

I am looking to mutate data into one column seperated by ","

I can do this if I name each input column, but is there a way to do it without having to type out each V1...V11?

input = mtcars
colnames(input) = c('V1','V2','V3','V4','V5','V6','V7','V8','V9','V10','V11')
joined = mutate(output11, join = paste(V1,V2,V3,V4,V5,V6,V7,V8,V9,V10,V11, sep = ","))
output = select(joined, join)

CodePudding user response：

Couple of options -

Use tidyr::unite -

tidyr::unite(input, join, dplyr::everything(), sep = ",")

#                                                       join
#Mazda RX4               21,6,160,110,3.9,2.62,16.46,0,1,4,4
#Mazda RX4 Wag          21,6,160,110,3.9,2.875,17.02,0,1,4,4
#Datsun 710            22.8,4,108,93,3.85,2.32,18.61,1,1,4,1
#Hornet 4 Drive      21.4,6,258,110,3.08,3.215,19.44,1,0,3,1
#Hornet Sportabout    18.7,8,360,175,3.15,3.44,17.02,0,0,3,2
#Valiant              18.1,6,225,105,2.76,3.46,20.22,1,0,3,1
#Duster 360           14.3,8,360,245,3.21,3.57,15.84,0,0,3,4
#Merc 240D              24.4,4,146.7,62,3.69,3.19,20,1,0,4,2
#Merc 230             22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2
#Merc 280            19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4
#...
#...

Base R using do.call paste

input$join <- do.call(paste, c(input, sep = ","))

CodePudding user response：

Here is a combination of rowwise and c_across along with building a list:

library(dplyr)
library(tidyr)

mtcars %>% 
  rowwise() %>% 
  transmute(join = list(paste(c_across(everything()), collapse = ","))) %>% 
  unnest(join)

  join                                   
   <chr>                                  
 1 21,6,160,110,3.9,2.62,16.46,0,1,4,4    
 2 21,6,160,110,3.9,2.875,17.02,0,1,4,4   
 3 22.8,4,108,93,3.85,2.32,18.61,1,1,4,1  
 4 21.4,6,258,110,3.08,3.215,19.44,1,0,3,1
 5 18.7,8,360,175,3.15,3.44,17.02,0,0,3,2 
 6 18.1,6,225,105,2.76,3.46,20.22,1,0,3,1 
 7 14.3,8,360,245,3.21,3.57,15.84,0,0,3,4 
 8 24.4,4,146.7,62,3.69,3.19,20,1,0,4,2   
 9 22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2 
10 19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4
# ... with 22 more rows
# i Use `print(n = ...)` to see more rows