How to get rows with min values in one column, grouped by other column, while keeping other columns?

Question

I have the following data:

df <- data.frame(A = c(1,2,3,4,5,6), B=c(\"P\",\"P\",\"P\",\"Q\",\"Q\",\"Q\"), C=c(\"a\",\"b\",\"c\",\"d\",\"e\",\"f\"))
df
##              


        

Answer 1

You can try

library(dplyr)
df %>% 
    group_by(B) %>%
    filter(A==min(A))
#  A B C
#1 1 P a
#2 4 Q d

Or

library(data.table)
setDT(df)[, .SD[A==min(A)], B]

Or using base R

 df[with(df, ave(A, B, FUN=min)==A),]
 #  A B C
 #1 1 P a
 #4 4 Q d

Answer 2

you can also use the split-apply technique:

# split `df` on the field 'b' 
tmp <- split(df,df$B)

# reduce to the row with the minimum value of A
tmp  <-  lapply(tmp,function(x)
                x[x$A == min(x$A),])

# bind the rows together
do.call(rbind,tmp)


#>   A B C
#> P 1 P a
#> Q 4 Q d