Adding counts of a factor to a dataframe [duplicate]

Answer 1

using jmsigner's data you could do:

dt$count <- ave(dt$school, dt$school,  FUN = length)

Answer 2

You could try something like this:

dt <- data.frame(p=1:20, school=sample(1:5, 20, replace=T)) 
tbsch <- table(dt$school)

tbsch <- data.frame(tbsch)

merge(dt, tbsch, by.x="school", by.y="Var1")

Answer 3

You can also use plyr...and preserve the original order using this one liner

join(dt, count(dt, "school"))

Answer 4

This is a lot easier in data.table v1.8.1. := now works by group. Groups don't have to be contiguous and it retains the original order. And it's just one line:

library(data.table)

# set up data
set.seed(2)
npupils <- rpois(10, 20)
pupil <- unlist(lapply(npupils, seq_len))
school <- rep(seq_along(npupils), npupils)
dt <- data.table(school = school, pupil = pupil) # Create a data.table
dt <- dt[sample(seq_len(nrow(dt)))] # Mix it up

dt
     school pupil
  1:      5     2
  2:      6    13
  3:      2    14
  4:      5     3
  5:     10    14
 ---             
186:      3    11
187:      7     2
188:      8    12
189:      3     6
190:      7    10

(dt[, schoolSize := .N, by = school])

     school pupil schoolSize
  1:      5     2         16
  2:      6    13         18
  3:      2    14         15
  4:      5     3         16
  5:     10    14         24
 ---                        
186:      3    11         14
187:      7     2         28
188:      8    12         19
189:      3     6         14
190:      7    10         28

That has all the usual speed advantages of fast grouping, and assigns the new column by reference with no copy at all.

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Edit: Deleted an answer that was only relevant for data.table prior to version 1.8.1: (Thanks to Matthew for the update).