Got it, thanks. Here's a very ugly solution.
Je n'ai fait celle-ci plus longue que parce que je n'ai pas eu le loisir de la faire plus courte.
suppressPackageStartupMessages({
library(dplyr)
library(magrittr)
})
date_time <- c(
"Jan 29 2020 13:46:08",
"Jan 29 2020 13:42:53",
"Jan 29 2020 12:13:27",
"Jan 29 2020 12:11:19",
"Jan 29 2020 12:09:21",
"Jan 28 2020 12:22:26",
"Jan 27 2020 8:22:20",
"Jan 25 2020 14:34:22",
"Jan 25 2020 14:31:13",
"Jan 23 2020 12:16:16",
"Jan 23 2020 12:13:30",
"Jan 20 2020 12:12:59",
"Jan 20 2020 12:05:30",
"Jan 20 2020 12:01:54"
)
systol <- c(
132, 132, 118, 115, 110, 148, 120,
115, 117, 134, 136, 131, 132, 137
)
# df and data are also names of built-in functions
# Usually , other objects of the same names peacefully
# co-exist, but there are some operations in which
# the built-in takes precedence, so I avoid
DF <- data.frame(date_time, systol) %>%
mutate(dtetime = lubridate::mdy_hms(date_time)) %>%
arrange(dtetime)
# creates difftime object; no provision for DST
DF %<>% mutate(hiatus = dtetime - lag(dtetime,1))
# create a plug value for first row's hiatus
DF[1,4] <- (DF[2,4] - DF[2,4])
# identifiers for grouping, extend as needed
grp <- c(LETTERS,c(paste(LETTERS,LETTERS,sep = "")))
# codes whether a new group is starting and assign a group number
DF %<>% mutate(newone = ifelse(hiatus <= 10,0,1))
DF %<>% mutate(thegrp = cumsum(newone))
# assign a group name
DF %<>% mutate(thegrp = case_when(
thegrp == 0 ~ grp[1],
thegrp == 1 ~ grp[2],
thegrp == 2 ~ grp[3],
thegrp == 3 ~ grp[4],
thegrp == 4 ~ grp[5],
thegrp == 5 ~ grp[6],
thegrp == 6 ~ grp[7]
))
# cleanup
DF %<>% select(dtetime,systol,thegrp)
# group and summarize
DF %>%
group_by(thegrp) %>%
summarize(meansys = mean(systol))
#> # A tibble: 7 x 2
#> thegrp meansys
#> * <chr> <dbl>
#> 1 A 133.
#> 2 B 135
#> 3 C 116
#> 4 D 120
#> 5 E 148
#> 6 F 114.
#> 7 G 132
The %<>% operator is from the {magritte} package—it's just like %>% only it overwrites the left-hand expression.