Example: creating a graph
In this example we create a graph, assign a random label to the nodes, and sort the edges based on the label of their source node.
The function play_gnp() creates graphs directly through sampling of different attributes.
library(tidygraph)
graph <- tidygraph::play_gnp(n = 10, p = 0.2) %>%
activate(nodes) %>%
mutate(class = sample(letters[1:4], n(), replace = TRUE)) %>%
activate(edges) %>%
arrange(.N()$class[from])
graph## # A tbl_graph: 10 nodes and 19 edges
## #
## # A directed simple graph with 1 component
## #
## # Edge Data: 19 × 2 (active)
## from to
## <int> <int>
## 1 5 1
## 2 1 2
## 3 5 3
## 4 5 8
## 5 7 8
## 6 6 1
## 7 3 2
## 8 6 2
## 9 6 5
## 10 10 8
## 11 10 9
## 12 2 3
## 13 2 6
## 14 9 6
## 15 4 2
## 16 8 2
## 17 8 5
## 18 8 7
## 19 8 10
## #
## # Node Data: 10 × 1
## class
## <chr>
## 1 a
## 2 c
## 3 b
## # ℹ 7 more rowsConversion to tbl_graph
Convert data with as_tbl_graph(). A tbl_graph is a data structure for tidy graph manipulation. It converts a data frame encoded as an edgelist.
## from to year
## 1 1 14 1957
## 2 1 15 1957
## 3 1 21 1957
## 4 1 54 1957
## 5 1 55 1957
## 6 2 21 1957With as_tbl_graph() we get:
## # A tbl_graph: 70 nodes and 506 edges
## #
## # An undirected multigraph with 1 component
## #
## # Node Data: 70 × 0 (active)
## #
## # Edge Data: 506 × 3
## from to year
## <int> <int> <dbl>
## 1 1 13 1957
## 2 1 14 1957
## 3 1 20 1957
## # ℹ 503 more rows