R: Simplifying code to convert letter grades to numeric grades

Question

I have written a function in R that will convert a data frame containing letter grades into numeric grades. I then use sapply() on each column of the data frame. Is there a simpler way to do this that doesn't require three separate calls of sapply? Is there a way to apply a function to every element of a data frame instead of every row or column? The source data, "grades", looks like this: ``` grades <- read.table("Grades.txt", header = TRUE) head(grades) final_exam quiz_avg homework_avg 1 C A A 2 C- B- A 3 D+ B+ A 4 B+ B+ A 5 F B+ A 6 B A- A ``` My "`convert_grades`" function looks like this: ``` convert_grades <- function(x) { if (x == "A+") { x <- 4.3 } else if (x == "A") { x <- 4 } else if (x == "A-") { x <- 3.7 } else if (x == "B+") { x <- 3.3 } else if (x == "B") { x <- 3 } else if (x == "B-") { x <- 2.7 } else if (x == "C+") { x <- 2.3 } else if (x == "C") { x <- 2 } else if (x == "C-") { x <- 1.7 } else if (x == "D+") { x <- 1.3 } else if (x == "D") { x <- 1 } else if (x == "D…

Accepted Answer

I would rewrite your `convert_grades` function as follows:

```
convert_grades <- function(x) {
  A <- factor(x, levels=c("A+", "A", "A-",
                     "B+", "B", "B-",
                     "C+", "C", "C-",
                     "D+", "D", "D-", "F"))
  values <- c(4.3, 4, 3.7, 
              3.3, 3, 2.7,
              2.3, 2, 1.7,
              1.3, 1, 0.7, 0)
  values[A]
}
```

Then, I would do the conversion like this:

```
num_grades <- grades
num_grades[] <- lapply(num_grades, convert_grades)
num_grades
  final_exam quiz_avg homework_avg
1        2.0      4.0            4
2        1.7      2.7            4
3        1.3      3.3            4
4        3.3      3.3            4
5        0.0      3.3            4
6        3.0      3.7            4
```

R: Simplifying code to convert letter grades to numeric grades

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