I am trying to mutate a dataframes which are part of a list of dataframe all at the same time in R
Here are the functions I am running on the dataframe, this is able to mutate/group_by/summarise
ebird_tod_1 <- ebird_split[[1]] %>% #ebird_split is the df list.
mutate(tod_bins = cut(time_observations_started,
breaks = breaks,
labels = labels,
include.lowest = TRUE),
tod_bins = as.numeric(as.character(tod_bins))) %>%
group_by(tod_bins) %>%
summarise(n_checklists = n(),
n_detected = sum(species_observed),
det_freq = mean(species_observed))
This works superb for one dataframe in the list, however I have 45,And I rather not have pages of this coding to create the 45 variable. Hence I am lookingg for a method that would increase the "ebird_tod_1" variable to "ebird_tod_2" "ebird_tod_3" etc. At the same time that the dataframe on which the modification occur should change to "ebird_split[[2]]" "ebird_split[[3]]".
I have tried unsuccessfully to use the repeat and map function.
I hope that is all the info someone need to help, I am new at R,
Thank you.
As you provided no example data the following code is not tested. But a general approach would be to put your code inside a function and to use lapply
or purrr::map
to loop over your list of data frames and store the result in a list (instead of creating multiple objects):
myfun <- function(x) {
x %>%
mutate(tod_bins = cut(time_observations_started,
breaks = breaks,
labels = labels,
include.lowest = TRUE),
tod_bins = as.numeric(as.character(tod_bins))) %>%
group_by(tod_bins) %>%
summarise(n_checklists = n(),
n_detected = sum(species_observed),
det_freq = mean(species_observed))
}
ebird_tod <- lapply(ebird_split, myfun)