Error in `.rowNamesDF<-`(x, value = value) : 'row.names' duplicate are not allowed. In-CodePudding

I have the following dataframe total_authority

structure(list(country = c("Albania", "Algeria", "American Somoa", 
"Angola", "Anguilla", "Antigua", "Argentina", "Armenia", "Aruba", 
"Australia"), `1994` = c(0.0000000000000000312250225675825, 0.0000000000000000312250225675825, 
0.0000000000000000312250225675825, 0.0000000000000000312250225675825, 
0.0000000000000000312250225675825, 0.0000000000000000312250225675825, 
0.00289122132708816, 0.0000000000000000312250225675825, 0.00000528966979389429, 
0.00622391681538348), country.1 = c("Albania", "Algeria", "American Somoa", 
"Angola", "Anguilla", "Antigua", "Argentina", "Armenia", "Aruba", 
"Australia"), `1995` = c(0.00000320558770721281, 0.0000000000000000277555756156289, 
0.0000000000000000277555756156289, 0.0000000000000000277555756156289, 
0.0000000000000000277555756156289, 0.0000000000000000277555756156289, 
0.0224538010858487, 0.0000000000000000277555756156289, 0.0000000000000000277555756156289, 
0.407633483379219)), row.names = c(NA, 10L), class = "data.frame")

which I would like to rearrange in such a way the first column contains the countries, the second denotes the year and the third the value scored by the countries in that year.

Visually, the dataframe total_authority is now

          country                      1994      country.1                      1995
1         Albania 0.00000000000000003122502        Albania 0.00000320558770721280500
2         Algeria 0.00000000000000003122502        Algeria 0.00000000000000002775558
3  American Somoa 0.00000000000000003122502 American Somoa 0.00000000000000002775558
4          Angola 0.00000000000000003122502         Angola 0.00000000000000002775558
5        Anguilla 0.00000000000000003122502       Anguilla 0.00000000000000002775558
6         Antigua 0.00000000000000003122502        Antigua 0.00000000000000002775558
7       Argentina 0.00289122132708816148572      Argentina 0.02245380108584869860433
8         Armenia 0.00000000000000003122502        Armenia 0.00000000000000002775558
9           Aruba 0.00000528966979389429437          Aruba 0.00000000000000002775558
10      Australia 0.00622391681538347896208      Australia 0.40763348337921861963551

The desired result is instead:

         country                     score  year
         Albania 0.00000000000000003122502  1994
         Algeria 0.00000000000000003122502  1994
  American Somoa 0.00000000000000003122502  1994
          Angola 0.00000000000000003122502  1994
        Anguilla 0.00000000000000003122502  1994
         Antigua 0.00000000000000003122502  1994
       Argentina 0.00289122132708816148572  1994
         Armenia 0.00000000000000003122502  1994
           Aruba 0.00000528966979389429437  1994
      Australia 0.00622391681538347896208   1994
         Albania 0.00000320558770721280500  1995
         Algeria 0.00000000000000002775558  1995
  American Somoa 0.00000000000000002775558  1995
          Angola 0.00000000000000002775558  1995
        Anguilla 0.00000000000000002775558  1995
         Antigua 0.00000000000000002775558  1995
       Argentina 0.02245380108584869860433  1995
         Armenia 0.00000000000000002775558  1995
           Aruba 0.00000000000000002775558  1995
      Australia 0.40763348337921861963551   1995

This is my attempt (count index of the for loop ranges between 1 and 2 but it is just an example):

actors<-c("Albania", "Algeria", "American Somoa", "Angola", "Anguilla", "Antigua", "Argentina", "Armenia", "Aruba", "Australia")

final_output<-data.frame()
for (count in 1:2) {
  df <- data.frame(country=actors)
  df$year=rep(names(total_authority)[2*count],nrow(df))
  df$authority<-total_authority[2*count]
  final_output <- rbind(final_output, df)
}

Anyway, I obtained the following error:

Error in `.rowNamesDF<-`(x, value = value) : 
  'row.names' duplicate are not allowed.
In addition: Warning message:
non-unique values when setting 'row.names': ‘1’, ‘10’, ‘2’, ‘3’, ‘4’, ‘5’, ‘6’, ‘7’, ‘8’, ‘9’

CodePudding user response：

We don't need a for loop here. Just index the data.frame to subset the columns, unlist and construct data.frame directly

out <-  data.frame(country = unlist(total_authority[c(1,3)]), 
         score = unlist(total_authority[c(2,4)]),
       year = rep(names(total_authority)[c(2,4)], each = nrow(total_authority)))
row.names(out) <- NULL

-output

> out
          country                     score year
1         Albania 0.00000000000000003122502 1994
2         Algeria 0.00000000000000003122502 1994
3  American Somoa 0.00000000000000003122502 1994
4          Angola 0.00000000000000003122502 1994
5        Anguilla 0.00000000000000003122502 1994
6         Antigua 0.00000000000000003122502 1994
7       Argentina 0.00289122132708816018468 1994
8         Armenia 0.00000000000000003122502 1994
9           Aruba 0.00000528966979389429013 1994
10      Australia 0.00622391681538347982944 1994
11        Albania 0.00000320558770721281009 1995
12        Algeria 0.00000000000000002775558 1995
13 American Somoa 0.00000000000000002775558 1995
14         Angola 0.00000000000000002775558 1995
15       Anguilla 0.00000000000000002775558 1995
16        Antigua 0.00000000000000002775558 1995
17      Argentina 0.02245380108584869860433 1995
18        Armenia 0.00000000000000002775558 1995
19          Aruba 0.00000000000000002775558 1995
20      Australia 0.40763348337921900821357 1995

Regarding the error with duplicate row.names, it occurs because the authority created is a data.frame with a single column ([), instead, we need a vector by extracting the column ([[)

final_output<-data.frame()
for (count in 1:2) {
   df <- data.frame(country=actors)
   df$year=rep(names(total_authority)[2*count],nrow(df))
   df$authority<-total_authority[[2*count]]
   final_output <- rbind(final_output, df)
 }

-output

> final_output
          country year                 authority
1         Albania 1994 0.00000000000000003122502
2         Algeria 1994 0.00000000000000003122502
3  American Somoa 1994 0.00000000000000003122502
4          Angola 1994 0.00000000000000003122502
5        Anguilla 1994 0.00000000000000003122502
6         Antigua 1994 0.00000000000000003122502
7       Argentina 1994 0.00289122132708816018468
8         Armenia 1994 0.00000000000000003122502
9           Aruba 1994 0.00000528966979389429013
10      Australia 1994 0.00622391681538347982944
11        Albania 1995 0.00000320558770721281009
12        Algeria 1995 0.00000000000000002775558
13 American Somoa 1995 0.00000000000000002775558
14         Angola 1995 0.00000000000000002775558
15       Anguilla 1995 0.00000000000000002775558
16        Antigua 1995 0.00000000000000002775558
17      Argentina 1995 0.02245380108584869860433
18        Armenia 1995 0.00000000000000002775558
19          Aruba 1995 0.00000000000000002775558
20      Australia 1995 0.40763348337921900821357