Cumulative sequence of occurrences of values [duplicate]
Try this:
dataset <- data.frame(out = c("a","b","c","a","d","b","c","a","d","b","c","a"))with(dataset, ave(as.character(out), out, FUN = seq_along))# [1] "1" "1" "1" "2" "1" "2" "2" "3" "2" "3" "3" "4"
Of course, you can assign the output to a column in your data.frame
using something like out$asNumbers <- with(dataset, ave(as.character(out), out, FUN = seq_along))
Update
The "dplyr" approach is also quite nice. The logic is very similar to the "data.table" approach. An advantage is that you don't need to wrap the output with as.numeric
which would be required with the ave
approach mentioned above.
dataset %>% group_by(out) %>% mutate(count = sequence(n()))# Source: local data frame [12 x 2]# Groups: out# # out count# 1 a 1# 2 b 1# 3 c 1# 4 a 2# 5 d 1# 6 b 2# 7 c 2# 8 a 3# 9 d 2# 10 b 3# 11 c 3# 12 a 4
A third option is to use getanID
from my "splitstackshape" package. For this particular example, you just need to specify the data.frame
name (since it's a single column), however, generally, you would be more specific and mention the column(s) that presently serve as "ids", and the function would check whether they are unique or whether a cumulative sequence is required to make them unique.
library(splitstackshape)# getanID(dataset, "out") ## Example of being specific about column to usegetanID(dataset)# out .id# 1: a 1# 2: b 1# 3: c 1# 4: a 2# 5: d 1# 6: b 2# 7: c 2# 8: a 3# 9: d 2# 10: b 3# 11: c 3# 12: a 4
Update:
As Ananda pointed out, you can use the simpler:
DT[, counts := sequence(.N), by = "V1"]
(where DT
is as below)
You can create a "counts" column, initialized to 1, then tally the cumulative sum, by factor.below is a quick implementation with data.table
# Called the column V1dataset<-data.frame(V1=c("a","b","c","a","d","b","c","a","d","b","c","a"))library(data.table)DT <- data.table(dataset)DT[, counts := 1L]DT[, counts := cumsum(counts), by=V1]; DT# V1 counts# 1: a 1# 2: b 1# 3: c 1# 4: a 2# 5: d 1# 6: b 2# 7: c 2# 8: a 3# 9: d 2# 10: b 3# 11: c 3# 12: a 4