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Reorder observations for a path geom

Source: R/stat_ordered_path.R
stat_ordered_path.Rd

stat_ordered_path() reorders observations along each path using a user-supplied ordering aesthetic (order_by) before drawing the path. The statistic can be used to ensure that paths are drawn in a consistent order even when the input data are not pre-sorted. This is equivalent to reordering the data before passing it to geom_path().

Usage

stat_ordered_path(
  mapping = NULL,
  data = NULL,
  geom = "path",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  decreasing = TRUE,
  na_method = c("drop_na", "drop_group"),
  ...
)

StatOrderedPath

Format

An object of class StatOrdered (inherits from Stat, ggproto, gg) of length 4.

Arguments

mapping

Set of aesthetic mappings created by ggplot2::aes(). Must at least supply x, y, and order_by. The group aesthetic can be used to define separate paths.

data

Data frame to be used for this layer. If NULL, the default, the data is inherited from the plot.

geom

The geometric object to use to draw the paths. Defaults to "path".

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

show.legend

Logical or NA. Should this layer be included in the legends? NA, the default, includes the layer if any aesthetics are mapped.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

decreasing

Logical. If TRUE, paths are ordered in decreasing order of order_by. If FALSE (default), ordering is increasing.

na_method

Character string specifying how to handle missing values in order_by. One of:

  • "drop_na" (default): drop only rows where order_by is NA;

  • "drop_group": drop entire groups that contain any NA in order_by.

...

Additional parameters passed on to the underlying geom.

Value

A ggplot2 layer that can be added to a plot object.

Details

The statistic expects an order_by aesthetic that supplies the variable used to order observations within each group.

Missing values order_by are handled according to na_method. If na_method is "drop_na", missing values are dropped from the data, and the path is still drawn, but might skipping steps due to missing values. If na_method is "drop_group", the entire group whose missing values belong is dropped from the data, and the path is not drawn.

Ties in order_by are allowed but trigger a warning and preserve the original row order for tied values.

Duplicates in order_by are dropped and a warning is issued.

Grouping is controlled via the usual group aesthetic. If a group column is present in the data, reordering is performed independently within each group; otherwise, the entire data is treated as a single path.

Aesthetics

stat_ordered_path() understands the following aesthetics (required are in bold).

Examples

library(ggplot2)
library(dplyr)
# Data prep
input_df <- prefviz:::aecdop22_widen |> 
   filter(DivisionNm %in% c("Higgins", "Monash"))
tern22 <- as_ternable(input_df, ALP:Other)

# Base plot
p <- get_tern_data(tern22, plot_type = "2D") |> 
  ggplot(aes(x = x1, y = x2)) +
  add_ternary_base() +
  geom_ternary_region(
    aes(fill = after_stat(vertex_labels)),
    vertex_labels = tern22$vertex_labels,
    alpha = 0.3, color = "grey50",
    show.legend = FALSE
  ) +
  geom_point(aes(color = ElectedParty)) +
  add_vertex_labels(tern22$simplex_vertices) +
  scale_color_manual(
    values = c("ALP" = "red", "LNP" = "blue", "Other" = "grey70"),
    aesthetics = c("fill", "colour")
  )

# Add ordered paths
p + 
  stat_ordered_path(
    aes(group = DivisionNm, order_by = CountNumber, color = ElectedParty))