How to drop rows in R with almost the same column value?

I have a dataset with a column of names. I would like to drop rows with the lesser "P" value, if there exists one with a higher value. For example, in the dataset below, I would like to drop the row ID's 3 and 5 since there exists a 'Texas P5' and a 'North Dakota P9.' What is the best way to do this? Thanks in advance!

ID	Name	Score
1	Minnesota P2	342
2	Vermont P7	342
3	Texas P4	65
4	New Mexico	643
5	North Dakota P8	78
6	North Dakota P9	245
7	Texas P5	856
8	Minnesota LP	342

Solution

Here is a base R way. Use ave to split the data by Name excluding the numbers, and check which group element is equal to its greatest element. ave returns a vector of the same class as its input, in this case character. So coerce to logical and subset the original data frame.

x<-"
ID  Name    Score
1   'Minnesota P2'  342
2   'Vermont P7'    342
3   'Texas P4'  65
4   'New Mexico'    643
5   'North Dakota P8'   78
6   'North Dakota P9'   245
7   'Texas P5'  856
8   'Minnesota LP'  342"
df1 <- read.table(textConnection(x), header = TRUE)


i <- with(df1, ave(Name, sub("\\d+", "", Name), FUN = \(x){
  x == tail(sort(x), 1)
}))
df1[as.logical(i),]
#>   ID            Name Score
#> 1  1    Minnesota P2   342
#> 2  2      Vermont P7   342
#> 4  4      New Mexico   643
#> 6  6 North Dakota P9   245
#> 7  7        Texas P5   856
#> 8  8    Minnesota LP   342

^{Created on 2022-07-06 by the reprex package (v2.0.1)}