Alluvial positions

Given a dataset with alluvial structure, stat_alluvium calculates the centroids (x and y) of the lodes, the intersections of the alluvia with the strata, together with their weights (heights; ymin and ymax). It leverages the group aesthetic for plotting purposes (for now).

stat_alluvium(mapping = NULL, data = NULL, geom = "alluvium",
  position = "identity", decreasing = NA, reverse = TRUE,
  aggregate.wts = FALSE, lode.guidance = "zigzag", lode.ordering = NULL,
  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.
aggregate.wts	Whether to aggregate weights across otherwise equivalent rows before computing lode and flow positions. Set to TRUE to group observations into cohorts. Warning: This is currently an expensive operation.
lode.guidance	The function to prioritize the axis variables for ordering the lodes within each stratum. Options are "zigzag", "rightleft", "leftright", "rightward", and "leftward" (see lode-guidance-functions).
lode.ordering	A list (of length the number of axes) of integer vectors (each of length the number of rows of data) or NULL entries (indicating no imposed ordering), or else a numeric matrix of corresponding dimensions, giving the preferred ordering of alluvia at each axis. This will be used to order the lodes within each stratum by sorting the lodes first by stratum and then by the provided vectors.
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_alluvium 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_alluvium 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_alluvium 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 = "alluvium") +
  stat_alluvium(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), stat = "alluvium",
            aes.bind = TRUE, lode.guidance = "rightward") +
  geom_stratum() + geom_text(stat = "stratum", label.strata = TRUE) +
  scale_x_continuous(breaks = 1:3, labels = c("Class", "Sex", "Age"))

# use of lode ordering
lode_ord <- replicate(n = 3, expr = sample(x = 32), simplify = FALSE)
ggplot(as.data.frame(Titanic),
       aes(weight = Freq,
           axis1 = Class, axis2 = Sex, axis3 = Age)) +
  geom_flow(aes(fill = Survived), stat = "alluvium",
            lode.ordering = lode_ord) +
  geom_stratum() + geom_text(stat = "stratum", label.strata = TRUE) +
  scale_x_continuous(breaks = 1:3, labels = c("Class", "Sex", "Age"))

data(majors)

# omit missing lodes and incident flows
ggplot(majors,
       aes(x = semester, stratum = curriculum, alluvium = student,
           label = curriculum)) +
  geom_alluvium(fill = "darkgrey", na.rm = TRUE) +
  geom_stratum(aes(fill = curriculum), color = NA, na.rm = TRUE) +
  theme_bw()

# diagram with outlined alluvia and forward-colored flows
ggplot(majors,
       aes(x = semester, stratum = curriculum, alluvium = student,
           fill = curriculum, label = curriculum)) +
  geom_flow(stat = "alluvium", lode.guidance = "rightleft",
            color = "black") +
  geom_stratum()
# same diagram with alluvium aggregation enabled,
# so that students are aggregated into cohorts
ggplot(majors,
       aes(x = semester, stratum = curriculum, alluvium = student,
           fill = curriculum, label = curriculum)) +
  geom_flow(stat = "alluvium", lode.guidance = "rightleft",
            color = "black", aggregate.wts = TRUE) +
  geom_stratum()

# NOT RUN {
  data(babynames, package = "babynames")
  # a discontiguous alluvium
  bn <- dplyr::filter(babynames,
                      prop >= .01 & sex == "F" &
                        year > 1962 & year < 1968)
  ggplot(data = bn,
         aes(x = year, alluvium = name, weight = prop)) +
    geom_alluvium(aes(fill = name, color = name == "Tammy"),
                  decreasing = TRUE, show.legend = FALSE) +
    scale_color_manual(values = c("#00000000", "#000000"))
  # filling in missing zeros
  bn2 <- merge(bn,
               expand.grid(year = unique(bn$year), name = unique(bn$name)),
               all = TRUE)
  bn2$prop[is.na(bn2$prop)] <- 0
  ggplot(data = bn2,
         aes(x = year, alluvium = name, weight = prop)) +
    geom_alluvium(aes(fill = name, color = name == "Tammy"),
                  decreasing = TRUE, show.legend = FALSE) +
    scale_color_manual(values = c("#00000000", "#000000"))
# }