This function is equivalent to ggplot2::facet_grid() in that it allows for building a grid of small multiples where rows and columns correspond to a specific data value. While ggplot2::facet_grid() could be used it would lead to unexpected results as it is not possible to specify whether you are referring to a node or an edge attribute. Furthermore ggplot2::facet_grid() will draw edges in panels even though the panel does not contain both terminal nodes. facet_graph takes care of all of these issues, allowing you to define which data type the rows and columns are referencing as well as filtering the edges based on the nodes in each panel (even when nodes are not drawn).

  row_type = "edge",
  col_type = "node",
  margins = FALSE,
  scales = "fixed",
  space = "fixed",
  shrink = TRUE,
  labeller = "label_value",
  as.table = TRUE,
  switch = NULL,
  drop = TRUE



This argument is soft-deprecated, please use rows and cols instead.

row_type, col_type

Either 'node' or 'edge'. Which data type is being facetted in the rows and columns. Default is to facet on nodes column wise and on edges row wise.


Either a logical value or a character vector. Margins are additional facets which contain all the data for each of the possible values of the faceting variables. If FALSE, no additional facets are included (the default). If TRUE, margins are included for all faceting variables. If specified as a character vector, it is the names of variables for which margins are to be created.


Are scales shared across all facets (the default, "fixed"), or do they vary across rows ("free_x"), columns ("free_y"), or both rows and columns ("free")?


If "fixed", the default, all panels have the same size. If "free_y" their height will be proportional to the length of the y scale; if "free_x" their width will be proportional to the length of the x scale; or if "free" both height and width will vary. This setting has no effect unless the appropriate scales also vary.


If TRUE, will shrink scales to fit output of statistics, not raw data. If FALSE, will be range of raw data before statistical summary.


A function that takes one data frame of labels and returns a list or data frame of character vectors. Each input column corresponds to one factor. Thus there will be more than one with vars(cyl, am). Each output column gets displayed as one separate line in the strip label. This function should inherit from the "labeller" S3 class for compatibility with labeller(). You can use different labeling functions for different kind of labels, for example use label_parsed() for formatting facet labels. label_value() is used by default, check it for more details and pointers to other options.


If TRUE, the default, the facets are laid out like a table with highest values at the bottom-right. If FALSE, the facets are laid out like a plot with the highest value at the top-right.


By default, the labels are displayed on the top and right of the plot. If "x", the top labels will be displayed to the bottom. If "y", the right-hand side labels will be displayed to the left. Can also be set to "both".


If TRUE, the default, all factor levels not used in the data will automatically be dropped. If FALSE, all factor levels will be shown, regardless of whether or not they appear in the data.

See also

Other ggraph-facets: facet_edges(), facet_nodes()


gr <- as_tbl_graph(highschool) %>%
  mutate(popularity = as.character(cut(centrality_degree(mode = 'in'),
    breaks = 3,
    labels = c('low', 'medium', 'high')
ggraph(gr) +
  geom_edge_link() +
  geom_node_point() +
  facet_graph(year ~ popularity)
#> Using "stress" as default layout