Create columns containing the quantile() function output

Question

I'm looking for a way to create multiple columns based on the quantile() function output. I actually want the quantile of each rows containing womens and mens value.

Example for line 1 : I want quantile(c(4.6, 5.8)) Which give :

  0%  25%  50%  75% 100% 
 4.6  4.9  5.2  5.5  5.8 

Here is a sample of data and the output I want :

data :

  code  womens  mens
1: 01    4.6    5.8
2: 02    5.0    4.6
3: 03    4.1    5.3
4: 04    5.2    3.0
5: 05    4.6    5.4
6: 06    2.3    3.4

what I want :

  code  womens  mens  0%  25%  50%  75% 100%
1: 01    4.6    5.8  4.6  4.9  5.2  5.5  5.8 
2: 02    5.0    4.6  4.6  4.7  4.8  4.9  5.0   
3: 03    4.1    5.3  4.1  4.4  4.7  5.0  5.3
4: 04    5.2    3.0  3.0  3.5  4.1  4.6  5.2 
5: 05    4.6    5.4  4.6  4.8  5.0  5.2  5.4 
6: 06    2.3    3.4  2.3  2.6  2.8  3.1  3.4

I already tried with lapply() and some for loop without results. The result I had was always the same 4.6 4.9 5.2 5.5 5.8 for every rows.

Thanks everyone

Answer 1

cbind(d, do.call(rbind, lapply(1:NROW(d), function(i){
    quantile(d[i, c("womens", "mens")])
})))
#   code womens mens  0%   25%  50%   75% 100%
#1:    1    4.6  5.8 4.6 4.900 5.20 5.500  5.8
#2:    2    5.0  4.6 4.6 4.700 4.80 4.900  5.0
#3:    3    4.1  5.3 4.1 4.400 4.70 5.000  5.3
#4:    4    5.2  3.0 3.0 3.550 4.10 4.650  5.2
#5:    5    4.6  5.4 4.6 4.800 5.00 5.200  5.4
#6:    6    2.3  3.4 2.3 2.575 2.85 3.125  3.4

DATA

d = structure(list(code = 1:6,
                   womens = c(4.6, 5, 4.1, 5.2, 4.6, 2.3),
                   mens = c(5.8, 4.6, 5.3, 3, 5.4, 3.4)),
              class = "data.frame",
              row.names = c("1:", "2:", "3:", "4:", "5:", "6:"))

Answer 2

If it is a data.table, one option in base R, would be to convert to data.frame (setDF), then loop through the rows with apply (MARGIN = 1), get the quantiles and assign new columns

library(data.table)
setDF(df1)
df1[c("0%", "25%", "50%", "75%", "100%")] <- t(apply(df1[, 2:3], 1, 
           quantile, na.rm = TRUE))

data

df1 <- structure(list(code = 1:6, womens = c(4.6, 5, 4.1, 5.2, 4.6, 
2.3), mens = c(5.8, 4.6, 5.3, 3, 5.4, 3.4)), class = c("data.table", 
"data.frame"), row.names = c(NA, -6L))