This graph-specific join method makes a full join on the nodes data and updates the edges in the joining graph so they matches the new indexes of the nodes in the resulting graph. Node and edge data is combined using dplyr::bind_rows() semantic, meaning that data is matched by column name and filled with NA if it is missing in either of the graphs.

graph_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"),
  ...)

Arguments

x

A tbl_graph

y

An object convertible to a tbl_graph using as_tbl_graph()

by

a character vector of variables to join by. If NULL, the default, *_join() will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they're right (to suppress the message, simply explicitly list the variables that you want to join).

To join by different variables on x and y use a named vector. For example, by = c("a" = "b") will match x.a to y.b.

copy

If x and y are not from the same data source, and copy is TRUE, then y will be copied into the same src as x. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.

suffix

If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.

...

other parameters passed onto methods, for instance, na_matches to control how NA values are matched. See join.tbl_df for more.

Value

A tbl_graph containing the merged graph

Examples

gr1 <- create_notable('bull') %>% activate(nodes) %>% mutate(name = letters[1:5]) gr2 <- create_ring(10) %>% activate(nodes) %>% mutate(name = letters[4:13]) gr1 %>% graph_join(gr2)
#> Joining, by = "name"
#> # A tbl_graph: 13 nodes and 15 edges #> # #> # A directed acyclic simple graph with 1 component #> # #> # Node Data: 13 x 1 (active) #> name #> <chr> #> 1 a #> 2 b #> 3 c #> 4 d #> 5 e #> 6 f #> # … with 7 more rows #> # #> # Edge Data: 15 x 2 #> from to #> <int> <int> #> 1 1 2 #> 2 1 3 #> 3 2 3 #> # … with 12 more rows