Pb when mutating melted data : i got numbers instead the group name

user_10945401 0
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Assume we have the following melted data :

melted=structure(list(Var1 = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L), variable = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L), .Label = c("Sensitivity", 
"Specificity", "Pos Pred Value", "Neg Pred Value", "Precision", 
"Recall", "F1", "Prevalence", "Detection Rate", "Detection Prevalence", 
"Balanced Accuracy "), class = "factor"), value = c(0, 0.701244813278008, 
0.701244813278008, 0.705394190871369, 0.711297071129707, 0.711297071129707, 
0.7125, 0.714876033057851, 0, 0.295454545454545, 0.295454545454545, 
0.318181818181818, 0.347826086956522, 0.347826086956522, 0.355555555555556, 
0.372093023255814, 0, 0.845, 0.845, 0.85, 0.85, 0.85, 0.855, 
0.865, 0, 0.152941176470588, 0.152941176470588, 0.164705882352941, 
0.188235294117647, 0.188235294117647, 0.188235294117647, 0.188235294117647, 
0, 0.845, 0.845, 0.85, 0.85, 0.85, 0.855, 0.865, 0, 0.701244813278008, 
0.701244813278008, 0.705394190871369, 0.711297071129707, 0.711297071129707, 
0.7125, 0.714876033057851, 0, 0.766439909297052, 0.766439909297052, 
0.770975056689342, 0.774487471526196, 0.774487471526196, 0.777272727272727, 
0.782805429864253, 0, 0.845614035087719, 0.845614035087719, 0.845614035087719, 
0.83859649122807, 0.83859649122807, 0.842105263157895, 0.849122807017544, 
0, 0.592982456140351, 0.592982456140351, 0.596491228070175, 0.596491228070175, 
0.596491228070175, 0.6, 0.607017543859649, 0, 0.701754385964912, 
0.701754385964912, 0.701754385964912, 0.701754385964912, 0.701754385964912, 
0.701754385964912, 0.701754385964912, 0, 0.498349679366277, 0.498349679366277, 
0.511788004526594, 0.529561579043114, 0.529561579043114, 0.534027777777778, 
0.543484528156833)), class = "data.frame", row.names = c(NA, 
-88L))

I need to add another column based in the following condition :

g=ifelse(melted[,"Var1"]==8,melted[,"variable"],NA)

However , i get numbers instead of the variable column in the dataset. For example :

print(g[1:16])
[1] NA NA NA NA NA NA NA  1 NA NA NA NA NA NA NA  2

But the output should be :

[1] NA NA NA NA NA NA NA  Sensitivity NA NA NA NA NA NA NA  Specificity.

To explain the pb in another way , Consider :

melted <- mutate(melted, Label = variable)

I need to replace Label with NA whenever Var1 !=8.

So again i tried :

melted <- mutate(melted, Label = ifelse(Var1!=8,NA,variable))
   print(melted[1:16,])

Then i got :

   Var1    variable     value Label
1     1 Sensitivity 0.0000000    NA
2     2 Sensitivity 0.7012448    NA
3     3 Sensitivity 0.7012448    NA
4     4 Sensitivity 0.7053942    NA
5     5 Sensitivity 0.7112971    NA
6     6 Sensitivity 0.7112971    NA
7     7 Sensitivity 0.7125000    NA
8     8 Sensitivity 0.7148760     1
9     1 Specificity 0.0000000    NA
10    2 Specificity 0.2954545    NA
11    3 Specificity 0.2954545    NA
12    4 Specificity 0.3181818    NA
13    5 Specificity 0.3478261    NA
14    6 Specificity 0.3478261    NA
15    7 Specificity 0.3555556    NA
16    8 Specificity 0.3720930     2

However the expected result should be :

   Var1    variable     value Label
1     1 Sensitivity 0.0000000    NA
2     2 Sensitivity 0.7012448    NA
3     3 Sensitivity 0.7012448    NA
4     4 Sensitivity 0.7053942    NA
5     5 Sensitivity 0.7112971    NA
6     6 Sensitivity 0.7112971    NA
7     7 Sensitivity 0.7125000    NA
8     8 Sensitivity 0.7148760    Sensitivity
9     1 Specificity 0.0000000    NA
10    2 Specificity 0.2954545    NA
11    3 Specificity 0.2954545    NA
12    4 Specificity 0.3181818    NA
13    5 Specificity 0.3478261    NA
14    6 Specificity 0.3478261    NA
15    7 Specificity 0.3555556    NA
16    8 Specificity 0.3720930    Specificity
dplyr r
2 Answers

The issue is that the column 'variable' is factor and thus ifelse converts it to integer storage mode. An option would be to use this in case_when with the reverse logic and not specify the TRUE so that the default will be NA.

library(dplyr)
melted <- melted %>%
      mutate(Label = case_when(Var1 == 8 ~ variable))

-output

head(melted, 16)
Var1    variable     value       Label
1     1 Sensitivity 0.0000000        <NA>
2     2 Sensitivity 0.7012448        <NA>
3     3 Sensitivity 0.7012448        <NA>
4     4 Sensitivity 0.7053942        <NA>
5     5 Sensitivity 0.7112971        <NA>
6     6 Sensitivity 0.7112971        <NA>
7     7 Sensitivity 0.7125000        <NA>
8     8 Sensitivity 0.7148760 Sensitivity
9     1 Specificity 0.0000000        <NA>
10    2 Specificity 0.2954545        <NA>
11    3 Specificity 0.2954545        <NA>
12    4 Specificity 0.3181818        <NA>
13    5 Specificity 0.3478261        <NA>
14    6 Specificity 0.3478261        <NA>
15    7 Specificity 0.3555556        <NA>
16    8 Specificity 0.3720930 Specificity

If we are okay with changing the column type i.e. factor to character, then ifelse can be made to work

melted <- mutate(melted, Label = ifelse(Var1!=8,NA, as.character(variable)))
user_37322710

Based on @akrun remark , i had found another possible solution :

melted <- mutate(melted, Label = ifelse(melted$Var1!=8,NA,melted$variable))

#print(unique(melted$variable)[melted$Label])

melted$Label=unique(melted$variable)[melted$Label]  # we substract from melted$variable levels since melted$Label contains just integers 



print(melted[1:16,])  # print some rows to check 

11 Levels: Sensitivity Specificity Pos Pred Value Neg Pred Value ... Balanced Accuracy 
   Var1    variable     value       Label
1     1 Sensitivity 0.0000000        <NA>
2     2 Sensitivity 0.7012448        <NA>
3     3 Sensitivity 0.7012448        <NA>
4     4 Sensitivity 0.7053942        <NA>
5     5 Sensitivity 0.7112971        <NA>
6     6 Sensitivity 0.7112971        <NA>
7     7 Sensitivity 0.7125000        <NA>
8     8 Sensitivity 0.7148760 Sensitivity
9     1 Specificity 0.0000000        <NA>
10    2 Specificity 0.2954545        <NA>
11    3 Specificity 0.2954545        <NA>
12    4 Specificity 0.3181818        <NA>
13    5 Specificity 0.3478261        <NA>
14    6 Specificity 0.3478261        <NA>
15    7 Specificity 0.3555556        <NA>
16    8 Specificity 0.3720930 Specificity
user_109454010
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