Given a dataset with alluvial structure, stat_flow calculates the centroids (x and y) and weights (heights; ymin and ymax) of alluvial flows between each pair of adjacent axes.

stat_flow(mapping = NULL, data = NULL, geom = "flow",
  position = "identity", decreasing = NA, reverse = TRUE,
  aes.bind = FALSE, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE,
  ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot.

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

geom

The geometric object to use display the data; override the default.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

decreasing

Logical; whether to arrange the strata at each axis in the order of the variable values (NA, the default), in ascending order of total weight (largest on top, FALSE), or in descending order of total weight (largest on bottom, TRUE).

reverse

Logical; if decreasing is NA, whether to arrange the strata at each axis in the reverse order of the variable values, so that they match the order of the values in the legend. Ignored if decreasing is not NA. Defaults to TRUE.

aes.bind

Whether to prioritize aesthetics before axes (other than the index axis) when ordering the lodes within each stratum. Defaults to FALSE.

na.rm

Logical: if FALSE, the default, NA lodes are not included; if TRUE, NA lodes constitute a separate category, plotted in grey (regardless of the color scheme).

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.

...

Additional arguments passed to layer.

Aesthetics

stat_flow requires one of two sets of aesthetics:

  • x, alluvium, and (optionally) stratum

  • any number of axis[0-9]* (axis1, axis2, etc.)

Use x, alluvium, and stratum for data in lodes format and axis[0-9]* for data in alluvia format (see is_alluvial). Arguments to parameters inconsistent with the format will be ignored. Additionally, stat_flow accepts the following optional aesthetics:

  • weight

  • group

weight controls the vertical dimensions of the alluvia and are aggregated across equivalent observations. group is used internally; arguments are ignored.

See also

layer for additional arguments, geom_flow for the corresponding geom, and stat_stratum and geom_stratum for intra-axis boxes.

Examples

# illustrate positioning ggplot(as.data.frame(Titanic), aes(weight = Freq, axis1 = Class, axis2 = Sex, axis3 = Age, color = Survived)) + stat_stratum(geom = "errorbar") + geom_line(stat = "flow") + stat_flow(geom = "pointrange") + geom_text(stat = "stratum", label.strata = TRUE) + scale_x_continuous(breaks = 1:3, labels = c("Class", "Sex", "Age"))
# use of lode controls ggplot(as.data.frame(Titanic), aes(weight = Freq, axis1 = Class, axis2 = Sex, axis3 = Age)) + geom_flow(aes(fill = Survived), aes.bind = TRUE, reverse = FALSE) + geom_stratum(reverse = FALSE) + geom_text(stat = "stratum", label.strata = TRUE, reverse = FALSE) + scale_x_continuous(breaks = 1:3, labels = c("Class", "Sex", "Age"))
data(vaccinations) # rightward alluvial aesthetics for vaccine survey data ggplot(vaccinations, aes(x = survey, stratum = response, alluvium = subject, weight = freq, fill = response)) + geom_flow(stat = "alluvium", lode.guidance = "rightward") + geom_stratum(alpha = .5) + geom_text(aes(label = response), stat = "stratum")
# memoryless flows for vaccine survey data ggplot(vaccinations, aes(x = survey, stratum = response, alluvium = subject, weight = freq, fill = response)) + geom_flow() + geom_stratum(alpha = .5) + geom_text(aes(label = response), stat = "stratum")
# aesthetics that vary betwween and within strata data(vaccinations) vaccinations$subgroup <- LETTERS[1:2][rbinom( n = length(unique(vaccinations$subject)), size = 1, prob = .5 ) + 1][vaccinations$subject] ggplot(vaccinations, aes(x = survey, stratum = response, alluvium = subject, weight = freq, fill = response, label = response)) + geom_flow(aes(alpha = subgroup)) + scale_alpha_discrete(range = c(1/3, 2/3)) + geom_stratum(alpha = .5) + geom_text(stat = "stratum")
# can even set aesthetics that vary both ways ggplot(vaccinations, aes(x = survey, stratum = response, alluvium = subject, weight = freq, label = response)) + geom_flow(aes(fill = interaction(response, subgroup)), aes.bind = TRUE) + scale_alpha_discrete(range = c(1/3, 2/3)) + geom_stratum(alpha = .5) + geom_text(stat = "stratum")