I have a dataframe that looks like this:
structure(list(Date = structure(c(1630544400, 1630548000, 1630551600,
1630555200, 1630558800, 1630562400, 1630566000, 1630569600, 1630573200,
1630576800, 1630580400, 1630630800, 1630634400, 1630638000, 1630641600,
1630645200, 1630648800, 1630652400, 1630656000, 1630659600), tzone = "America/Chicago", class = c("POSIXct",
"POSIXt")), daytime = c("Night", "Night", "Night", "Night", "Morning",
"Morning", "Morning", "Morning", "Morning", "Morning", "Morning",
"Night", "Night", "Night", "Night", "Morning", "Morning", "Morning",
"Morning", "Morning")), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
I would like to create another column to group the night and morning sequentially so the output would look like this:
Date daytime nightcount
<dttm> <chr> <dbl>
1 2021-09-01 20:00:00 Night 1
2 2021-09-01 21:00:00 Night 1
3 2021-09-01 22:00:00 Night 1
4 2021-09-01 23:00:00 Night 1
5 2021-09-02 00:00:00 Morning 1
6 2021-09-02 01:00:00 Morning 1
7 2021-09-02 02:00:00 Morning 1
8 2021-09-02 03:00:00 Morning 1
9 2021-09-02 04:00:00 Morning 1
10 2021-09-02 05:00:00 Morning 1
11 2021-09-02 06:00:00 Morning 1
12 2021-09-02 20:00:00 Night 2
13 2021-09-02 21:00:00 Night 2
14 2021-09-02 22:00:00 Night 2
15 2021-09-02 23:00:00 Night 2
16 2021-09-03 00:00:00 Morning 2
17 2021-09-03 01:00:00 Morning 2
18 2021-09-03 02:00:00 Morning 2
19 2021-09-03 03:00:00 Morning 2
20 2021-09-03 04:00:00 Morning 2
Is there an easy solution for this using dplyr?
>Solution :
You can create a logical value when "Morning" turns to "Night" and then use cumsum to sum these logical values across rows:
library(dplyr)
df |>
mutate(nightcount = cumsum(daytime == "Night" & lag(daytime, default = "Morning") == "Morning"))