I have a dataframe which includes grades of students per course. These grades, however, are in A-F format and need to be transformed to numerical grades (10-1). To do so, I generated random numbers that represent these A-F values.
A <- rnorm(nrow(Student_Data), 9.45, 0.2)
B <- rnorm(nrow(Student_Data), 7.95, 0.2)
C <- rnorm(nrow(Student_Data), 6.25, 0.2)
D <- rnorm(nrow(Student_Data), 4.75, 0.2)
F <- rnorm(nrow(Student_Data), 2, 0.2)
I also created a function which allows to replace the letters with numbers
courseGradesNumeric <- data.frame(lapply(courseGrades, function(x) {gsub("A", sample(A, 1), gsub("B", sample(B, 1), gsub("C", sample(C, 1), gsub("D", sample(D, 1), gsub("F", sample(F, 1), x)))))}))
This works quite well but the problem is that if there is an "A" (or any other letter) in a column, then this A in this specific column is replaced by a random number from vector A that is the same across the entire column.
To illustrate:
Current dataframe (ignore the NA's for now)
Student_ID ABC1000_Grade ABC1003_Grade
1 9000006 A B
2 9000014 A A
3 9000028 B C
4 9000045 <NA> <NA>
5 9000080 C <NA>
6 9000091 <NA> <NA>
The problem:
Student_ID ABC1000_Grade ABC1003_Grade
1 9000006 9.335523 8.231295
2 9000014 9.335523 9.462468
3 9000028 7.972959 6.394259
4 9000045 <NA> <NA>
5 9000080 6.257297 <NA>
6 9000091 <NA> <NA>
In the ABC1000_Grade column, the A was replaced by the same random number that was generated in an earlier step.
How can I make sure that all replaced values are different random numbers? Thus, the preferred result should be:
Student_ID ABC1000_Grade ABC1003_Grade
1 9000006 9.510445 8.231295
2 9000014 9.335523 9.462468
3 9000028 7.972959 6.394259
4 9000045 <NA> <NA>
5 9000080 6.257297 <NA>
6 9000091 <NA> <NA>
In your code, you are generating one random value to replace any given grade and that's why you are getting same values.
Here's a simpler way of getting your desired result using base::switch() with sapply and lastly dplyr package to modify all columns ending with "Grade" in one go -
library(dplyr)
replace_grade <- function(g) {
sapply(g, function(a) {
switch(a,
"A" = rnorm(1, 9.45, 0.2),
"B" = rnorm(1, 7.95, 0.2),
"C" = rnorm(1, 6.25, 0.2),
"D" = rnorm(1, 4.75, 0.2),
"F" = rnorm(1, 2, 0.2),
NA_real_
)
})
}
# function output for illustration
replace_grade(g = c("A", "B", "C", "D", "F", NA_character_))
A B C D F <NA>
9.229176 7.830536 6.239904 4.643644 2.146621 NA
# apply function to every column ending with "Grade"
df %>%
mutate_at(vars(ends_with("Grade")), replace_grade)
Student_ID ABC1000_Grade ABC1003_Grade
1 9000006 9.243239 7.946469
2 9000014 9.623083 9.072896
3 9000028 8.308868 6.177990
4 9000045 NA NA
5 9000080 6.336819 NA
6 9000091 NA NA
Data -
df <- read.table(text = "Student_ID ABC1000_Grade ABC1003_Grade
9000006 A B
9000014 A A
9000028 B C
9000045 <NA> <NA>
9000080 C <NA>
9000091 <NA> <NA>
", header= T, sep = "\t", stringsAsFactors = F)