R/GenTimeTrend.R

In conoroheocha/NBSVisTool: Visualisation and mapping for datasets from systematic reviews and maps

#' Create Histogram from dataset
#' @param idata dataset from eviatlas
#' @param hist_col column used for histogram
#' @param axis_txt_lim character limit for label text in axis
#' @keywords internal

GenTimeTrend <- function(idata, hist_col, axis_txt_lim = 60) {
  UseMethod("GenTimeTrend", object = idata[hist_col][[1]])
}

#' Create Histogram from dataset - default method
#' @method GenTimeTrend default
#' @export
#' @keywords internal
GenTimeTrend.default <- function(idata, hist_col, axis_txt_lim = 60) {
  gttmp <- ggplot2::ggplot(idata, ggplot2::aes_string(x = hist_col)) +
    ggplot2::geom_bar(
      alpha = 0.9,
      stat = "count",
      fill = "dodger blue"
    ) +
    ggplot2::labs(y = "Studies") +
    ggplot2::scale_x_discrete(
      name = paste(hist_col),
      labels = function(x) substr(x, 1, axis_txt_lim)
    ) +
    ggplot2::theme_bw() +
    ggplot2::theme(
      axis.line = ggplot2::element_line(colour = "black"),
      panel.background = ggplot2::element_blank(),
      plot.title = ggplot2::element_text(hjust = .5),
      text = ggplot2::element_text(size = 13)
    )

  # Rotate xaxis label if too many categories
  if (dplyr::n_distinct(idata[hist_col]) > 15) {
    gttmp <- gttmp + ggplot2::theme(
      axis.text.x = ggplot2::element_text(
        angle = 40,
        hjust = 0.95,
        size = 12
      )
    )
  }
  gttmp
}

#' Create Histogram from dataset - numeric column
#' @method GenTimeTrend numeric
#' @export
#' @keywords internal

GenTimeTrend.numeric <- function(idata, hist_col, axis_txt_lim = 60) {
  ggplot2::ggplot(idata, ggplot2::aes_string(x = hist_col)) +
    ggplot2::geom_bar(
      alpha = 0.9,
      stat = "count",
      fill = "dodger blue"
    ) +
    ggplot2::labs(y = "Studies") +
    ggplot2::theme_bw() +
    ggplot2::theme(
      axis.line = ggplot2::element_line(colour = "black"),
      panel.background = ggplot2::element_blank(),
      plot.title = ggplot2::element_text(hjust = .5),
      text = ggplot2::element_text(size = 13)
    )
}