Add a new column, based on data in between zeroes

Question

I have power data (Power) collected every second (Sample). My data.frame is therefore structured as follows:

Test <- data.frame(Sample = c(1:20), 
                


        

Answer 1

An option with base R:

indx1 = with(rle(Test$Power>0),rep(values,lengths))
indx2 = with(rle(Test$Power>0),rep(cumsum(values),lengths))
Test$Effort[indx1] = paste0("Effort",indx2[indx1])
Test$Effort[!indx1]="Rest"

Output:

   Sample Power  Effort
1       1     0    Rest
2       2     0    Rest
3       3     0    Rest
4       4     0    Rest
5       5     0    Rest
6       6    50 Effort1
7       7    67 Effort1
8       8   100 Effort1
9       9    92 Effort1
10     10     0    Rest
11     11     0    Rest
12     12     0    Rest
13     13    36 Effort2
14     14    89 Effort2
15     15    36 Effort2
16     16     0    Rest
17     17     0    Rest
18     18     0    Rest
19     19    89 Effort3
20     20    90 Effort3

About 0.0038 seconds for 3,000 rows ;) Hope this helps!

Answer 2

An option with dplyr from the tidyverse:

library(dplyr)
Test <- data.frame(Sample = c(1:20), 
                   Power = c(0,0,0,0,0,50,67,100,92,0,0,0,36,89,36,0,0,0,89,90))

Test_df <- Test %>%
  mutate(
    Marker = case_when(
      Power > 0 ~ "Effort",
      Power == 0 ~"Rest"),
    rleid = cumsum(Marker != lag(Marker, 1, default = "NA")), 
    Marker = case_when(
      Marker == "Effort" ~ paste0(Marker, rleid %/% 2),
      TRUE ~ "Rest"),
    rleid = NULL
  )

Test_df
#>    Sample Power  Marker
#> 1       1     0    Rest
#> 2       2     0    Rest
#> 3       3     0    Rest
#> 4       4     0    Rest
#> 5       5     0    Rest
#> 6       6    50 Effort1
#> 7       7    67 Effort1
#> 8       8   100 Effort1
#> 9       9    92 Effort1
#> 10     10     0    Rest
#> 11     11     0    Rest
#> 12     12     0    Rest
#> 13     13    36 Effort2
#> 14     14    89 Effort2
#> 15     15    36 Effort2
#> 16     16     0    Rest
#> 17     17     0    Rest
#> 18     18     0    Rest
#> 19     19    89 Effort3
#> 20     20    90 Effort3

---

An other option using a one-liner data.table :

library(data.table)
Test <- data.frame(Sample = c(1:20), 
                   Power = c(0,0,0,0,0,50,67,100,92,0,0,0,36,89,36,0,0,0,89,90))
setDT(Test)
Test[, Marker := ifelse(Power > 0, paste0("Effort", rleidv(Power > 0) %/% 2), "Rest")]
Test
#>     Sample Power  Marker
#>  1:      1     0    Rest
#>  2:      2     0    Rest
#>  3:      3     0    Rest
#>  4:      4     0    Rest
#>  5:      5     0    Rest
#>  6:      6    50 Effort1
#>  7:      7    67 Effort1
#>  8:      8   100 Effort1
#>  9:      9    92 Effort1
#> 10:     10     0    Rest
#> 11:     11     0    Rest
#> 12:     12     0    Rest
#> 13:     13    36 Effort2
#> 14:     14    89 Effort2
#> 15:     15    36 Effort2
#> 16:     16     0    Rest
#> 17:     17     0    Rest
#> 18:     18     0    Rest
#> 19:     19    89 Effort3
#> 20:     20    90 Effort3

Answer 3

An alternative base R version using cumsum:

mrk <- Test$Power==0
Test$New[!mrk] <- paste("effort", as.numeric(factor(cumsum(mrk)[!mrk])))
Test$New[mrk] <- "rest"

#   Sample Power   Marker      New
#1       1     0     Rest     rest
#2       2     0     Rest     rest
#3       3     0     Rest     rest
#4       4     0     Rest     rest
#5       5     0     Rest     rest
#6       6    50 Effort 1 effort 1
#7       7    67 Effort 1 effort 1
#8       8   100 Effort 1 effort 1
#9       9    92 Effort 1 effort 1
#10     10     0     Rest     rest
#11     11     0     Rest     rest
#12     12     0     Rest     rest
#13     13    36 Effort 2 effort 2
#14     14    89 Effort 2 effort 2
#15     15    36 Effort 2 effort 2
#16     16     0     Rest     rest
#17     17     0     Rest     rest
#18     18     0     Rest     rest
#19     19    89 Effort 3 effort 3
#20     20    90 Effort 3 effort 3