R/plot_record_by_season.R

In FRBCesab/forcis: An R Client to Access the FORCIS Database

#' Plot sample records by season
#'
#' @description
#' This function produces a barplot of FORCIS sample records by season.
#'
#' @param data a `tibble` or a `data.frame`, i.e. a FORCIS dataset.
#'
#' @return A `ggplot` object.
#'
#' @export
#'
#' @examples
#' # Attach the package ----
#' library("forcis")
#'
#' # Import example dataset ----
#' file_name <- system.file(file.path("extdata", "FORCIS_net_sample.csv"),
#'                          package = "forcis")
#'
#' net_data <- read.table(file_name, dec = ".", sep = ";")
#'
#' # Plot data by year (example dataset) ----
#' plot_record_by_season(net_data)

plot_record_by_season <- function(data) {
  ## Check data object ----

  check_if_df(data)
  check_field_in_data(data, "sample_id")
  check_field_in_data(data, "site_lat_start_decimal")

  ## Extract month ----

  if (get_data_type(data) == "Sediment trap") {
    check_field_in_data(data, "sample_date_time_start")
    data$"sampling_month" <- as.numeric(sub(
      "^\\d{2}/(\\d{2})/\\d{4}$",
      "\\1",
      data$"sample_date_time_start"
    ))
  } else {
    check_field_in_data(data, "profile_date_time")
    data$"sampling_month" <- as.numeric(sub(
      "^\\d{2}/(\\d{2})/\\d{4}$",
      "\\1",
      data$"profile_date_time"
    ))
  }

  ## Identify season ----

  data$"season" <- ifelse(
    data$"site_lat_start_decimal" > 0 &
      data$"sampling_month" %in% c(6, 7, 8, 9),
    "Summer",
    ifelse(
      data$"site_lat_start_decimal" < 0 &
        data$"sampling_month" %in% c(12, 1, 2),
      "Summer",
      ifelse(
        data$"site_lat_start_decimal" < 0 &
          data$"sampling_month" %in% c(6, 7),
        "Winter",
        ifelse(
          data$"site_lat_start_decimal" > 0 &
            data$"sampling_month" %in% c(12, 1, 2, 3),
          "Winter",
          ifelse(
            data$"site_lat_start_decimal" > 0 &
              data$"sampling_month" %in% c(3, 4, 5),
            "Spring",
            ifelse(
              data$"site_lat_start_decimal" > 0 &
                data$"sampling_month" %in% c(9, 10, 11),
              "Fall",
              ifelse(
                data$"site_lat_start_decimal" < 0 &
                  data$"sampling_month" %in% c(3, 4, 5),
                "Fall",
                ifelse(
                  data$"site_lat_start_decimal" < 0 &
                    data$"sampling_month" %in% c(9, 10, 11),
                  "Spring",
                  "Unknown"
                )
              )
            )
          )
        )
      )
    )
  )

  ## Get distinct values ----

  data <- data[, c("sample_id", "season")]
  data <- data[!duplicated(data), ]

  data <- table(data$"season") |>
    data.frame()

  colnames(data) <- c("season", "count")

  ## Ensure to have all months ----

  season <- data.frame(
    "season" = c("Fall", "Winter", "Spring", "Summer", "Unknown")
  )

  data <- merge(data, season, by = "season", all = TRUE)

  data$"count" <- ifelse(is.na(data$"count"), 0, data$"count")

  ## Trick for ggplot2 ----

  data$"season" <- factor(
    x = data$"season",
    levels = c("Fall", "Winter", "Spring", "Summer", "Unknown")
  )

  ## Plot ----

  ggplot(data, aes(x = .data$season, y = .data$count)) +
    geom_bar(width = 0.7, col = "black", stat = "identity") +
    theme_classic() +
    xlab(label = "Season") +
    ylab(label = "Number of FORCIS samples")
}