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#' Plot which variables contain a missing value
#'
#' This plot produces a set of rectangles indicating whether there is a missing
#' element in a column or not. A default minimal theme is used, which can be
#' customised as normal for ggplot.
#'
#' @param x a dataframe
#'
#' @return a ggplot object of which variables contains missing values
#'
#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
#'
#' @export
#'
#' @examples
#'
#' gg_miss_which(airquality)
gg_miss_which <- function(x){
col_na <- colSums(is.na(x)) == 0
col_na_val <- dplyr::if_else(col_na, "complete", "missing")
# tell us which columns have missing data
ggobject <- tibble::tibble(variable = names(col_na),
value = col_na_val) %>%
dplyr::mutate(nheight = 1) %>%
ggplot(data = .,
aes(x = variable,
y = nheight,
fill = factor(value))) +
geom_tile(colour = "white") +
theme_minimal() +
scale_fill_grey(name = "") +
scale_x_discrete(limits = names(x)) +
theme(legend.position = "none") +
scale_y_discrete(breaks = c(""),
labels = c("")) +
labs(y = " ",
x = " ") +
coord_flip()
return(ggobject)
}
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