Issue when using Mutate and Case_when in a loop - r

Question

I have a data frame with all the information from a racing yacht in that day (lg) and I wish to create variable that tells me what race the yacht was in. This race start and finish time are in a separate df (RaceInfo). I can filter by race time, but there is a changeable amount of races per day so it may need a loop.
Some Data
lg <- structure(list(Date = structure(c(18897, 18897, 18897, 18897,
18897, 18897, 18897, 18897, 18897, 18897), class = "Date"), Time = structure(c(1632725883,
1632725884, 1632725885, 1632725886, 1632725887, 1632725888, 1632725889,
1632725890, 1632725891, 1632725892), tzone = "", class = c("POSIXct",
"POSIXt")), Lat = c(43.2760531, 43.276059, 43.276065, 43.2760708,
43.2760766, 43.2760858, 43.276095, 43.2761, 43.276105, 43.2761095
), Lon = c(6.619109, 6.619136, 6.619163, 6.6191932, 6.6192235,
6.6192488, 6.619274, 6.6192988, 6.6193235, 6.6193532), Awa = c(-7.1,
-7.12, -7.15, -6.57, -6, -6.2, -6.4, -5.28, -4.15, 0.25), X = 1:10), row.names = c(NA,
-10L), class = "data.frame")
This is the yachts onboard data.
More Data
RaceInfo <- structure(list(date = structure(c(18897, 18896), class = "Date"),
RaceStartTime = structure(c(1632738480, 1632751560), tzone = "", class = c("POSIXct",
"POSIXt")), RaceNum = c("1", "2"), RaceFinishTime = structure(c(1632751520,
1632753000), tzone = "", class = c("POSIXct", "POSIXt"))), row.names = c("event.2",
"1"), class = "data.frame")
In the RaceInfo df it tells us the start and finish time of each race, as mentioned before there could be many races and I need to assign a new variable in the lg df as lg$RaceNum based on the times given in the RaceInfo df.
My closes attempt is this but loops are a weak point in my game.
for (i in RaceInfo$RaceNum){
lg <- lg %>%
mutate(Racenum = case_when(
lg$Time >= (subset(RaceInfo$RaceStartTime, RaceInfo$RaceNum == i)) &
lg$Time <= (subset(RaceInfo$RaceFinishTime, RaceInfo$RaceNum == i)) ~ i))
}
But this only returns the last number in the loop

Answer 1

The methods mutate and case_when are really to assign calculated columns within a data frame and not specifically for subsetting data frame itself.
Instead, consider dplyr::filter (similar to base::subset) even dplyr::between and collect your iteration results to build a data frame list. Then, rbind results at end. To subset by unique values, see by
df_list <- lapply(RaceInfo$RaceNum, function(i)
dplyr::filter(
lg,
dplyr::between(
Time,
RaceInfo$StartTime[RaceInfo$Racenum == i],
RaceInfo$RaceFinishTime[RaceInfo$Racenum == i]
)
)
)
final_df <- dplyr::bind_rows(df_list)
But as mentioned above, if your data is manageable with small set of distinct RaceInfo, consider a cross join with filter:
final_df <- dplyr::full_join(lg, RaceInfo, by = character()) %>%
filter(lg, between(
Time,
RaceInfo$StartTime[RaceInfo$Racenum == i],
RaceInfo$RaceFinishTime[RaceInfo$Racenum == i]
)
)