Map the missing values in a data frame — missingness

Draws a tile map of the data frame with one column per variable and one row per observation, shading the cells that are missing. The variables are ordered by their proportion of missing values, and that proportion is shown in the axis labels, making it easy to spot variables and patterns that need attention before modelling.

Usage

missingness_map(
  data,
  cols = NULL,
  sort = TRUE,
  show_pct = TRUE,
  colours = c("grey85", depictr_accent()),
  legend_inside = FALSE,
  title = NULL
)

Arguments

data: A data frame.
cols: Optional character vector of columns to include (default: all).
sort: Whether to order variables by their proportion of missing values.
show_pct: Whether to append the percentage missing to each variable label.
colours: Length-2 vector: colours for present and missing cells. Defaults to a muted grey for present cells and the colourblind-safe depictr_palette() accent for missing cells.
legend_inside: When TRUE (and sort = TRUE), draw the legend inside the panel, in the top-right (where the most-complete columns put a solid "Present" block, so it hides no "Missing" mark) instead of in a right-hand margin. Defaults to FALSE.
title: Plot title.

Value

A ggplot2::ggplot object.

Examples

missingness_map(wellbeing_survey)