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I have a data frame which tracks service involvement (srvc_inv 1, 0) for individual x (Bob) over a timeframe of interest (years 1900-1999).

library(tidyverse)

dat <- data.frame(name = rep("Bob", 100),
 day = seq(as.Date("1900/1/1"), as.Date("1999/1/1"), "years"),
 srvc_inv = c(rep(0, 25), rep(1, 25), rep(0, 25), rep(1, 25)))

As we can see, Bob has two service episodes: one episode between rows 26:50, and the other between rows 76:100.

If we want to determine any service involvement for Bob during the timeframe, we can use a simple max statement as shown below.

dat %>% 
 group_by(name) %>% 
 summarise(ever_inv = max(srvc_inv))

However, I would like to determine the number of service episodes that Bob had during the timeframe of interest (in this case, 2). A distinct service episode would be identified by a break in service involvement over consecutive dates. Anybody have any idea how to program this? Thanks!

One more solution based on base R rle

library(dplyr)
dat %>% group_by(name) %>% 
 summarise(ever_inv = length(with(rle(srvc_inv), lengths[values==1])))

# A tibble: 1 x 2
name ever_inv
 <fct> <int>
1 Bob 2

One possibility could be:

dat %>%
 group_by(name) %>%
 mutate(rleid = with(rle(srvc_inv), rep(seq_along(lengths), lengths))) %>%
 summarise(ever_inv = n_distinct(rleid[srvc_inv == 1]))

 name ever_inv
 <fct> <int>
1 Bob 2

Alternatively to rle() you can use diff():

dat %>%
 group_by(name) %>%
 summarise(ever_inv = sum(diff(c(0, srvc_inv)) > 0))

# A tibble: 1 x 2
# name ever_inv
# <fct> <int>
# 1 Bob 2

Assuming that srvc_inv is either 0 or 1, diff(srvc_inv) == 1 only when x_i is 1, and x_i-1 is 0. It turns into 0 or -1 otherwise. I added 0 before srvc_inv for a case when it starts from 1s run.

And with rle(), from my opinion, there is even simpler solution:

dat %>%
 group_by(name) %>%
 summarise(ever_inv = sum(rle(srvc_inv)$value))

# A tibble: 1 x 2
# name ever_inv
# <fct> <int>
# 1 Bob 2

Assuming that srvc_inv is either 0 or 1, that's enough just to sum values component of rle object, which returns the number of 1s runs.