Create a column with a count of occurrences in R [duplicate]

Answer 1

You should be good with something like that (suppose df is your data):

df.agr=aggregate(Product~Customer,data=df, FUN=function(x) length(unique(x)))
df=cbind(df, Count=apply(df, MARGIN=1, FUN=function(r) df.agr$Product[match(r[1],df.agr$Customer)]))

It won't be blazing fast, but definitely faster than for.

Answer 2

I use plyr for anything that involves split-apply-combine. In this case, we split the data by Customer and apply the length-unique function on Product, then combine the results

require(plyr)
ddply(df, .(Customer), transform, num.products = length(unique(Product)))

  Customer   Product num.products
1        1 Chocolate            3
2        1     Candy            3
3        1      Soda            3
4        2 Chocolate            1
5        2 Chocolate            1
6        2 Chocolate            1
7        3   Insulin            2
8        3     Candy            2

Bonus in case you want a smaller summary dataframe out of this.

ddply(df, .(Customer), summarize, num.products = length(unique(Product)))

  Customer num.products
1        1            3
2        2            1
3        3            2

Answer 3

In base R I would suggest ave:

within(mydf, {
    count = ave(Product, Customer, FUN = function(x) length(unique(x)))
})
##   Customer   Product count
## 1        1 Chocolate     3
## 2        1     Candy     3
## 3        1      Soda     3
## 4        2 Chocolate     1
## 5        2 Chocolate     1
## 6        2 Chocolate     1
## 7        3   Insulin     2
## 8        3     Candy     2

---

You could also try the "data.table" package:

library(data.table)
as.data.table(mydf)[, count := length(unique(Product)), by = Customer][]
##    Customer   Product count
## 1:        1 Chocolate     3
## 2:        1     Candy     3
## 3:        1      Soda     3
## 4:        2 Chocolate     1
## 5:        2 Chocolate     1
## 6:        2 Chocolate     1
## 7:        3   Insulin     2
## 8:        3     Candy     2