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#' Visualise the value of data values
#'
#' Visualise all of the values in the data on a 0 to 1 scale. Only works on
#' numeric data - see examples for how to subset to only numeric data.
#'
#' @param data a data.frame
#' @param na_colour a character vector of length one describing what colour
#' you want the NA values to be. Default is "grey90"
#' @param viridis_option A character string indicating the colormap option to
#' use. Four options are available: "magma" (or "A"), "inferno" (or "B"),
#' "plasma" (or "C"), "viridis" (or "D", the default option) and "cividis"
#' (or "E").
#'
#' @return a ggplot plot of the values
#' @export
#'
#' @examples
#'
#' vis_value(airquality)
#' vis_value(airquality, viridis_option = "A")
#' vis_value(airquality, viridis_option = "B")
#' vis_value(airquality, viridis_option = "C")
#' vis_value(airquality, viridis_option = "E")
#' \dontrun{
#' library(dplyr)
#' diamonds %>%
#' select_if(is.numeric) %>%
#' vis_value()
#'}
vis_value <- function(data,
na_colour = "grey90",
viridis_option = "D") {
test_if_all_numeric(data)
purrr::map_dfr(data, scale_01) %>%
vis_gather_() %>%
dplyr::mutate(
value = vis_extract_value_(data),
value = as.numeric(value),
valueType = as.numeric(valueType)
) %>%
vis_create_() +
# change the limits etc.
ggplot2::guides(fill = ggplot2::guide_legend(title = "Value")) +
# add info about the axes
ggplot2::scale_x_discrete(position = "top") +
ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0)) +
ggplot2::scale_fill_viridis_c(option = viridis_option,
na.value = na_colour)
}
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