Most frequent value (mode) by group [duplicate]

Answer 1

We could get the 'Mode' of 'b' grouped by 'a' using ave

 Mode <- function(x) {
 ux <- unique(x)
 ux[which.max(tabulate(match(x, ux)))]
}

df$c <-  with(df, ave(b, a, FUN=Mode))
df$c
#[1] 2 2 2 2 3 3 3 1 1

Or using data.table

library(data.table)
setDT(df)[, c:= Mode(b), by=a][]

Answer 2

Building on Davids comments your solution is the following:

Mode <- function(x) {
  ux <- unique(x)
  ux[which.max(tabulate(match(x, ux)))]
}

library(dplyr)
df %>% group_by(a) %>% mutate(c=Mode(b))

Notice though that for the tie when df$a is 3 then the mode for b is 1.

Answer 3

Here is a base R method that uses table to calculate a cross tab, max.col to find the mode per group, and rep together with rle to fill in the mode across groups.

# calculate a cross tab, frequencies by group
myTab <- table(df$a, df$b)
# repeat the mode for each group, as calculated by colnames(myTab)[max.col(myTab)] 
# repeating by the number of times the group ID is observed
df$c <- rep(colnames(myTab)[max.col(myTab)], rle(df$a)$length)

df
  a b c
1 1 2 2
2 1 2 2
3 1 1 2
4 1 2 2
5 2 3 3
6 2 3 3
7 2 1 3
8 3 1 2
9 3 2 2

Note that this assumes the data has been sorted by group. Also, the default of max.col is to break ties (mulitple modes) at random. If you want the first or last value to be the mode, you can set this using the ties.method argument.