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#' @name summarize_individual_rodents
#'
#' @title Return cleaned Portal rodent individual data
#'
#' @description This function cleans and subsets the data based on a number
#' of arguments. It returns stake number and individual level data.
#'
#' @inheritParams summarize_rodent_data
#'
#' @return a data.frame
#'
#' @export
#'
summarize_individual_rodents <- function(path = get_default_data_path(),
clean = TRUE, type = "Rodents",
length = "all", unknowns = FALSE, time = "period",
fillweight = FALSE, min_plots = 1, min_traps = 1,
download_if_missing = TRUE, quiet = FALSE)
{
#### Get Data ----
data_tables <- load_rodent_data(path, download_if_missing = download_if_missing,
clean = clean, quiet = quiet)
#### Do initial cleaning ----
rodents <- clean_rodent_data(data_tables$rodent_data,
data_tables$species_table,
fillweight, type,
unknowns)
#### Filter by length and add treatment types ----
trapping <- filter_plots(data_tables$trapping, length)
rodents <- join_trapping_to_rodents(rodents, trapping, data_tables$trapping,
min_plots, min_traps) %>%
join_plots(data_tables$plots_table) %>%
dplyr::select(c("period", "month", "day" = "day.x", "year",
"treatment", "plot", "stake", "species",
"sex", "reprod", "age", "testes", "vagina","pregnant", "nipples","lactation",
"hfl", "wgt", "tag", "note2", "ltag", "note3"))
#### use new moon number as time index if time == "newmoon" ----
return(add_time(rodents, data_tables$newmoons_table, time))
}
#' @rdname summarize_individual_rodents
#' @export
summarise_individual_rodents <- summarize_individual_rodents
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