Explore missing values in a dataset — explore

Primarily a visual tool, but also can tabulate the same, which allows exploration of the amount of missingness in a dataset. The visual shows the amount of missing data in each column.

Usage

explore_na(
  df,
  return = "plot",
  probabilities = TRUE,
  keep_all = FALSE,
  colour_thresholds = c(0.1, 0.3),
  zoom_in = FALSE,
  reference_lines = TRUE
)

Arguments

df: dataset, of the class data.frame
return: Either "plot" or "table", depending what you want the function to return
probabilities: Do you want the amount missing reported in absolute (nrow) or relative (percentage)terms
keep_all: Whether to include the columns which are not missing anything ie n_missing = 0
colour_thresholds: The visuals give a RAG rating for the missingness depending on these thresholds
zoom_in: Should the amount missing axis max out at 100 percent or the greatest non-zero amount missing?
reference_lines: Should reference lines be drawn on the visual to show the thresholds used for the colours

Value

A ggplot object

Examples

my_data <- data.frame(
  x0 = 1:11
  , x1 = c(NA, 1:10)
  , x2 = c(rep(NA, 2), 1:9)
  , x3 = c(rep(NA, 3), 1:8)
  , x4 = c(rep(NA, 4), 1:7)
)
my_data |> explore_na()
#> Rows: 11

my_data |> explore_na(keep_all = TRUE)
#> Rows: 11

my_data |> explore_na(zoom_in = TRUE)
#> Rows: 11