Create a new level column based on unique row sets - r

Question

I want to create a new column with new variables (preferably letters) to count the frequency of each set later on.
Lets say I have a data frame called datatemp which is like:
datatemp = data.frame(colors=rep( c("red","blue"), 6), val = 1:6)
colors val
1 red 1
2 blue 2
3 red 3
4 blue 4
5 red 5
6 blue 6
7 red 1
8 blue 2
9 red 3
10 blue 4
11 red 5
12 blue 6
And I can see my unique row sets where colors and val columns have identical inputs together, such as:
unique(datatemp[c("colors","val")])
colors val
1 red 1
2 blue 2
3 red 3
4 blue 4
5 red 5
6 blue 6
What I really want to do is to create a new column in the same data frame where each unique set of row above has a level, such as:
colors val freq
1 red 1 A
2 blue 2 B
3 red 3 C
4 blue 4 D
5 red 5 E
6 blue 6 F
7 red 1 A
8 blue 2 B
9 red 3 C
10 blue 4 D
11 red 5 E
12 blue 6 F
I know that's very basic, however, I couldn't come up with an useful idea for a huge dataset.
So make the question more clear, I am giving another representation of desired output below:
colA colB newcol
10 11 A
12 15 B
10 11 A
13 15 C
Values in the new column should be based on uniqueness of first two columns before it.

Answer 1

www's solution maps the unique values in your value column to letters in freq column. If you want to do create a factor variable for each unique combination of colors and val, you could do something along these lines:
library(plyr)
datatemp = data.frame(colors=rep( c("red","blue"), 6), val = 1:6)
datatemp$freq <- factor(paste(datatemp$colors, datatemp$val), levels=unique(paste(datatemp$colors, datatemp$val)))
datatemp$freq <- mapvalues(datatemp$freq, from = levels(datatemp$freq), to = LETTERS[1:length(levels(datatemp$freq))])
I first create a new factor variable for each unique combination of val and colors, and then use plyr::mapvalues to rename the factor levels to letters.

Answer 2

We can concatenate the val and color column and create it as factor, then we can change the factor level by letters.
datatemp$Freq <- as.factor(paste(datatemp$val, datatemp$colors, sep = "_"))
levels(datatemp$Freq) <- LETTERS[1:length(levels(datatemp$Freq))]
datatemp
# colors val Freq
# 1 red 1 A
# 2 blue 2 B
# 3 red 3 C
# 4 blue 4 D
# 5 red 5 E
# 6 blue 6 F
# 7 red 1 A
# 8 blue 2 B
# 9 red 3 C
# 10 blue 4 D
# 11 red 5 E
# 12 blue 6 F