Comparing results from different approaches at http://stackoverflow.com/questions/26761849/count-rows-between-nas

SO26761849.R

dat1 <- data.frame(time = seq(10, 90, 10), 
                   value = c(NA, 0, 1, NA, NA, 30, 68, 0, NA))
dat2 <- data.frame(time = seq(10, 90, 10), 
                   value = c(0, NA, 1, NA, NA, 30, 68, 0, NA))

RStudent <- function(indf) {
  aux <- rle(as.numeric((!is.na(indf[, 2]))))
  cbind(TIME = indf[cumsum(aux$lengths)[which(aux$values == 1)] - 
                   aux$lengths[aux$values == 1] +1, 1],
        Result = rle(is.na(indf$value))$lengths[!rle(is.na(indf$value))$values])
}

RStudent(dat1)
#      TIME Result
# [1,]   20      2
# [2,]   60      3
RStudent(dat2)
#      TIME Result
# [1,]   10      1
# [2,]   30      1
# [3,]   60      3

beginneR <- function(indf) {
  indf %>%
    group_by(m = cumsum(is.na(value))) %>% 
    summarise(n = n() -1, time = first(time[!is.na(value)])) %>%
    ungroup() %>%
    filter(n > 0 & m > 0) %>% 
    select(-m)
}

beginneR(dat1)
# Source: local data frame [2 x 2]
# 
#   n time
# 1 2   20
# 2 3   60
beginneR(dat2)
# Source: local data frame [2 x 2]
# 
#   n time
# 1 1   30
# 2 3   60

AM <- function(indf) {
  na.omit(data.table(TIME = indf$time, Val = TrueSeq(
    !is.na(indf$value), zero2NA = TRUE)))[, list(TIME = TIME[1], .N), by = Val]
}

AM(dat1)
#    Val TIME N
# 1:   1   20 2
# 2:   2   60 3
AM(dat2)
#    Val TIME N
# 1:   1   10 1
# 2:   2   30 1
# 3:   3   60 3

konvas <- function(indf) {
  res <- data.frame(
    time = na.omit(indf$time[which(is.na(indf$value)) + 1]),
    result = diff(which(is.na(indf$value))) - 1
  )
  res[res$result != 0, ]
}

konvas(dat1)
#   time result
# 1   20      2
# 3   60      3
konvas(dat2)
#   time result
# 1   30      1
# 3   60      3