使用NA分配组内的值的等级

Question

I have such a data frame(df) which is just a sapmle:

group value
1     12.1
1     10.3
1     NA
1     11.0
1     13.5
2     11.7
2     NA
2     10.4
2     9.7

Namely,

df<-data.frame(group=c(1,1,1,1,1,2,2,2,2), value=c(12.1, 10.3, NA, 11.0, 13.5, 11.7, NA, 10.4, 9.7))

Desired output is:

group value  order
1     12.1    3
1     10.3    1
1     NA      NA
1     11.0    2
1     13.5    4
2     11.7    3
2     NA      NA
2     10.4    2
2     9.7     1

Namely, I want to find the

• rank of the "value"s from starting from the smallest value
• within the "group"s.

How can I do that with R? I will be very glad for any help Thanks a lot.

Answer 1

We could use ave from base R to create the rank column ("order1") of "value" by "group". If we need to have NAs for corresponding NA in "value" column, this can be done ( df$order[is.na(..)] )

 df$order1 <- with(df, ave(value, group, FUN=rank))
 df$order1[is.na(df$value)] <- NA

Or using data.table

 library(data.table)
 setDT(df)[, order1:=rank(value)* NA^(is.na(value)), by = group][]
 #    group value order1
 #1:     1  12.1      3
 #2:     1  10.3      1
 #3:     1    NA     NA
 #4:     1  11.0      2
 #5:     1  13.5      4
 #6:     2  11.7      3
 #7:     2    NA     NA
 #8:     2  10.4      2
 #9:     2   9.7      1

Answer 2

You can use the rank() function applied to each group at a time to get your desired result. My solution for doing this is to write a small helper function and call that function in a for loop. I'm sure there are other more elegant means using various R libraries but here is a solution using only base R.

df <- read.table('~/Desktop/stack_overflow28283818.csv', sep = ',', header = T)

#helper function
    rankByGroup <- function(df = NULL, grp = 1)
                {
                rank(df[df$group == grp, 'value'])
                }


# Remove NAs
df.na <- df[is.na(df$value),]
df.0  <- df[!is.na(df$value),]

# For loop over groups to list the ranks
for(grp in unique(df.0$group))
    {
    df.0[df.0$group == grp, 'order'] <- rankByGroup(df.0, grp) 
    print(grp)
    }

# Append NAs
df.na$order <- NA
df.out <- rbind(df.0,df.na)

#re-sort for ordering given in OP (probably not really required)
df.out <- df.out[order(as.numeric(rownames(df.out))),]

This gives exactly the output desired, although I suspect that maintaining the position of the NAs in the data may not be necessary for your application.

> df.out
  group value order
1     1  12.1     3
2     1  10.3     1
3     1    NA    NA
4     1  11.0     2
5     1  13.5     4
6     2  11.7     3
7     2    NA    NA
8     2  10.4     2
9     2   9.7     1