CODEWITHSUNDEEP
rtidyverse
Stuart
Stuart

Reputation: 607

Assign sequential group ID given a group start indicator

I need to assign subgroup IDs given a group ID and an indicator showing the beginning of the new subgroup. Here's a test dataset:

group <- c(rep("A", 8), rep("B", 8))
x1 <- c(rep(0, 3), rep(1, 3), rep(0, 2))
x2 <- rep(0:1, 4)

df <- data.frame(group=group, indic=c(x1, x2))

Here is the resulting data frame:

 df
   group indic
1      A     0
2      A     0
3      A     0
4      A     1
5      A     1
6      A     1
7      A     0
8      A     0
9      B     0
10     B     1
11     B     0
12     B     1
13     B     0
14     B     1
15     B     0
16     B     1

indic==1 means that row is the beginning of a new subgroup, and the subgroup should be numbered 1 higher than the previous subgroup. Where indic==0 the subgroup should be the same as the previous subgroup. The subgroup numbering starts at 1. When the group variable changes, the subgroup numbering resets to 1. I would like to use the tidyverse framework. Here is the result that I want:

 df
   group indic subgroup
1      A     0        1
2      A     0        1
3      A     0        1
4      A     1        2
5      A     1        3
6      A     1        4
7      A     0        4
8      A     0        4
9      B     0        1
10     B     1        2
11     B     0        2
12     B     1        3
13     B     0        3
14     B     1        4
15     B     0        4
16     B     1        5

I would like to be able to give some methods that I've tried already but didn't work, but I haven't been able to find anything even close. Any help will be appreciated.

Upvotes: 1

Views: 62

Answers (1)

MrFlick
MrFlick

Reputation: 206187

You can just use

library(dplyr)
df %>% group_by(group) %>% 
  mutate(subgroup=cumsum(indic)+1)
#   group indic subgroup
#   <fct> <dbl>    <dbl>
#  1 A         0        1
#  2 A         0        1
#  3 A         0        1
#  4 A         1        2
#  5 A         1        3
#  6 A         1        4
#  7 A         0        4
#  8 A         0        4
#  9 B         0        1
# 10 B         1        2
# 11 B         0        2
# 12 B         1        3
# 13 B         0        3
# 14 B         1        4
# 15 B         0        4
# 16 B         1        5

We use dplyr to do the grouping and then we just use cumsum with takes the cumulative sum of the indic column so each time it sees a 1 it increases.

Upvotes: 1

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