This is a ggplot2 extension for alluvial plots.


The alluvial plots implemented here can be used to visualize frequency distributions over time or frequency tables involving several categorical variables. The design is inspired by the alluvial package, but the ggplot2 framework induced several conspicuous differences:

  • alluvial understands a variety of inputs (vectors, lists, data frames), whereas ggalluvial requires a single data frame;
  • alluvial uses each variable of these inputs as a dimension of the data, whereas ggalluvial requires the user to specify the dimensions, either as separate aesthetics or as key-value pairs;
  • alluvial produces both the alluvia, which link cohorts across multiple dimensions, and (what are here called) the strata, which partition the data along each dimension, in a single function; whereas ggalluvial relies on separate layers (stats and geoms) to produce strata, alluvia, and alluvial segments called lodes and flows.

Additionally, ggalluvial arranges these layers vertically without gaps, so that the secondary plotting axis indicates the cumulative values of the strata at each dimension.


The latest stable release can be installed from CRAN:


The cran branch will contain the version most recently submitted to CRAN.

The development version can be installed from GitHub:

remotes::install_github("corybrunson/ggalluvial", build_vignettes = TRUE)

Note that, in order to build the vignettes, the imported packages alluvial, ggfittext, and ggrepel must be installed. To skip this step, leave build_vignettes unspecified or set it to FALSE.

The optimization branch contains a development version with experimental functions to reduce the number or area of alluvial overlaps (see issue #6). Install it as follows:

remotes::install_github("corybrunson/ggalluvial", ref = "optimization")

Note, however, that this branch has not kept pace with the master branch or with recent upgrades on CRAN.



Here is how to generate an alluvial plot representation of the multi-dimensional categorical dataset of passengers on the Titanic:

The data is in “wide” format, but ggalluvial also recognizes data in “long” format and can convert between the two:


For detailed discussion of the data formats recognized by ggalluvial and several examples that illustrate its flexibility and limitations, read the technical vignette:

vignette(topic = "ggalluvial", package = "ggalluvial")

The documentation contains several examples; use help() to call forth examples of any layer (stat_* or geom_*) or of the conversion functions (to_*_form).



Development of this package benefitted from the use of equipment and the support of colleagues at UConn Health.


Issues and pull requests are more than welcome! Pretty much every fix and feature of this package derives from a problem or question posed by someone with datasets or design goals i hadn’t anticipated.


If you use ggalluvial-generated figures in publication, i’d be grateful to hear about it! You can also cite the package according to citation("ggalluvial").