R/value.R

In sharlagelfand/makeapp: A Shiny App Tracking Makeup Collection

#' @export
current_value <- function(collection) {
  collection %>%
    dplyr::filter(is.na(date_finished)) %>%
    dplyr::summarise(
      n = n(),
      value = sum(value)
    )
}

#' @export
current_value_by_category <- function(collection) {
  collection %>%
    dplyr::filter(is.na(date_finished)) %>%
    dplyr::left_join(product_categories, by = "category") %>%
    dplyr::group_by(main_category) %>%
    dplyr::summarise(
      n = n(),
      value = sum(value)
    )
}

#' @export
value_over_time <- function(collection) {
  added_and_finished <- collection %>%
    dplyr::select(date_added, date_finished, value) %>%
    tidyr::pivot_longer(
      cols = c(date_added, date_finished),
      names_to = "type",
      values_to = "date",
      names_prefix = "date_"
    ) %>%
    dplyr::filter(!is.na(date)) %>%
    dplyr::mutate(n = 1) %>%
    dplyr::mutate_at(dplyr::vars(value, n), ~ ifelse(type == "finished", .x * -1, .x))

  dates <- added_and_finished %>%
    dplyr::distinct(date) %>%
    dplyr::mutate_at(dplyr::vars(date), as.Date)

  dates %>%
    dplyr::mutate(
      data = purrr::map(
        date,
        ~ added_and_finished %>%
          dplyr::filter(date <= .x) %>%
          dplyr::summarise(
            value = sum(value),
            n = sum(n)
          ) %>%
          dplyr::select(value, n)
      ),
      value = purrr::map_dbl(data, "value"),
      n = purrr::map_dbl(data, "n")
    ) %>%
    dplyr::select(-data) %>%
    dplyr::arrange(date)
}