R - Adding calculated columns to a table using existing names of a numeric vector and existing data-CodePudding

Hi I've got a table (data1) and a numeric vector(quantile) and trying to append calculated columns using the existing data (data1) and the vector(quantile).

such that:

newcol_20% = col1   col2   20%,
newcol_50% = col2   col3   50%, 
newcol_70% = col3   col4   70%

data1 and quantile and the desired output (out) are as below

>data1
ID       col1    col2   col3    col4
ABC124     10      15      6      15
ABC445      8       8     25      34
ABC550     10      15      5      12
---
ZZZ980     12      21     26      11
ZZZ999     22      19     11       8

> quantile
20%   50%   70%
 10    21    35

> out
ID       col1    col2   col3    col4   newcol_20%  newcol_50%  newcol_70%
ABC124     10      15      6      15           35          42          56
ABC445      8       8     25      34           26          54          94
ABC550     10      15      5      12           35          41          52
---
ZZZ980     12      21     26      11           43          68          72
ZZZ999     22      19     11       8           51          51          54

How could I perform above using base R? Any help, suggestions would be appreciated, thanks!

CodePudding user response：

A really simple and efficient way to do this is using the mutate() function from the dplyr package:

library(dplyr)
new_df <- df %>% mutate(new_col_20 = col1   col2   10,
                        newcol_50 = col2   col3   21, 
                        newcol_70 = col3   col4   35
                       )

However, if it needs to be using base R, you can just assign a new column using $:

df$new_col_20 <- df$col1   df$col2   10

And similarly for the other two columns.

PS. column names do not accept the '%' symbol.

CodePudding user response：

Here’s a base R solution that will generalize to any number of columns and vector elements:

src_cols <- data1[-1]
qnt_names <- names(quantile)

for (i in seq_along(src_cols)) {
  if (i < ncol(src_cols)) {
    data1[[paste0("newcol_", qnt_names[[i]])]] <- src_cols[[i]]   src_cols[[i   1]]   quantile[[i]]
  }
}

Result:

      ID col1 col2 col3 col4 newcol_20% newcol_50% newcol_70%
1 ABC124   10   15    6   15         35         42         56
2 ABC445    8    8   25   34         26         54         94
3 ABC550   10   15    5   12         35         41         52
4 ZZZ980   12   21   26   11         43         68         72
5 ZZZ999   22   19   11    8         51         51         54

CodePudding user response：

In base R you may use transform.

qs <- c(10, 21, 35)

dat <- transform(dat,
                 newcol_20=col1   col2   qs[1],
                 newcol_50=col2   col3   qs[2],
                 newcol_70=col3   col4   qs[3])
dat
#       ID col1 col2 col3 col4 newcol_20 newcol_50 newcol_70
# 1 ABC124   10   15    6   15        35        42        56
# 2 ABC445    8    8   25   34        26        54        94
# 3 ABC550   10   15    5   12        35        41        52
# 4 ZZZ980   12   21   26   11        43        68        72
# 5 ZZZ999   22   19   11    8        51        51        54

PS: Avoid special characters in names, check ?make.names to quickly learn about the rules of valid names.

dat <- structure(list(ID = c("ABC124", "ABC445", "ABC550", "ZZZ980", 
"ZZZ999"), col1 = c(10L, 8L, 10L, 12L, 22L), col2 = c(15L, 8L, 
15L, 21L, 19L), col3 = c(6L, 25L, 5L, 26L, 11L), col4 = c(15L, 
34L, 12L, 11L, 8L)), class = "data.frame", row.names = c(NA, 
-5L))