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Heatmap of standardised inputs and outputs

Source: R/plot-io-heatmap.R
plot_io_heatmap.Rd

Draws a DMU-by-variable heatmap of the input and output values, with DMUs on the y-axis and variables on the x-axis (inputs labelled I_, outputs O_). By default the values are standardised column-wise so they are comparable across variables.

Usage

plot_io_heatmap(
  x,
  scale = TRUE,
  labels = "all",
  max.overlaps.value = 10,
  transparency = 1,
  fade = TRUE,
  x_angle = NULL,
  subtitle = NULL,
  title = NULL,
  interactive = FALSE,
  ...
)

Arguments

x

A dea_data object, or a data frame coerced by as_dea_data.

scale

Logical; if TRUE (default) each variable is standardised (z-scored) before plotting.

labels

DMU tick labels: "all" (default) shows them, "none" hides them, and the name/id of a single DMU highlights that DMU's label(s) in colour.

max.overlaps.value

Accepted for API consistency; unused here (default 10).

transparency

Opacity of the markers/areas, a single number in [0, 1] (default 1).

fade

Controls the single-DMU focus view. When one DMU is given to labels, all other marks (and, for the network plots, everything outside that DMU's sub-network; for the panel biplot, the other trajectories) are faded so the chosen DMU stands out. TRUE (default) uses a sensible fade level; FALSE disables it; a single number in [0, 1] sets the alpha of the faded marks directly, where larger values fade them less (e.g. 0.4 leaves them more visible).

x_angle

Angle in degrees for the x-axis tick labels, useful when the input/output (or DMU) names on the x-axis are long and overlap. NULL (default) keeps the plot's standard orientation; for example x_angle = 45 tilts the labels to make them readable.

subtitle

Optional subtitle shown beneath the title.

title

Optional plot title.

interactive

Logical; static ggplot2 (default) or interactive plotly.

...

Additional arguments passed to geom_tile.

Value

A ggplot2 object, or a plotly object when interactive = TRUE.

See also

dea_data

Examples

df <- data.frame(
  dmu  = paste0("D", 1:6),
  i_x1 = c(4, 7, 8, 4, 2, 5),
  i_x2 = c(3, 3, 1, 2, 4, 2),
  o_y  = c(5, 8, 6, 7, 3, 9)
)
plot_io_heatmap(df)