Add column with counts of another [duplicate]

Answer 1

You may try ave:

# first, convert 'gender' to class character
df$gender <- as.character(df$gender)

df$count <- as.numeric(ave(df$gender, df$gender, FUN = length))
df
#   gender age count
# 1      m  18     4
# 2      f  14     2
# 3      m  18     4
# 4      m  18     4
# 5      m  15     4
# 6      f  15     2

Update following @flodel's comment - thanks!

df <- transform(df, count = ave(age, gender, FUN = length))

Answer 2

And a data.table version for good measure.

library(data.table)
df <- as.data.table(df)

Once you have the data.table, it's then a simple operation:

df[,count := .N,by="gender"]
df

#   gender age count
#1:      m  18     4
#2:      f  14     2
#3:      m  18     4
#4:      m  18     4
#5:      m  15     4
#6:      f  15     2

Answer 3

You can set the counts and then do something like this, but that's not exactly elegant.

m.cnt <- length(which(df$gender == "m"))
f.cnt <- length(which(df$gender == "f"))

df$count <- NA
df$count[which(df$gender == "m")] <- m.cnt
df$count[which(df$gender == "f")] <- f.cnt

Alternatively you can use plyr but this results in recalculating the same thing over and over again, which might not be worth it since you only have 2 factors.

Answer 4

Since gender is a factor, you can use it to index the table output:

dat$count <- table(dat$gender)[dat$gender]

Or to avoid repeating dat$ too many times:

dat <- transform(dat, count = table(gender)[gender])

Answer 5

Using plyr:

library(plyr) 
ddply(dat,.(gender),transform,count=length(age))
  gender age count
1      f  14     2
2      f  15     2
3      m  18     4
4      m  18     4
5      m  18     4
6      m  15     4