Chapter 6 Convert for common graph packages

6.1 {igraph}

In order to be converted into a graph object:

• The nodes should be a dataframe with the first column being a series of unique ID, understood as “names” by igraph - these are the ID columns from Neo4J. Other columns are considered attributes.

• relationships need a start and an end, i.e. startNode and endNode in the Neo4J results.

Here how to create a graph object from a {neo4r} result:

G <-"MATCH a=(p:Person {name: 'Tom Hanks'})-[r:ACTED_IN]->(m:Movie) RETURN a;" %>% 
  call_neo4j(con, type = "graph") 

library(dplyr)
library(purrr)
# Create a dataframe with col 1 being the ID, 
# And columns 2 being the names
G$nodes <- G$nodes %>%
  unnest_nodes(what = "properties") %>% 
  # We're extracting the first label of each node, but 
  # this column can also be removed if not needed
  mutate(label = map_chr(label, 1))
head(G$nodes)

## # A tibble: 6 x 7
##   id    label  tagline                     title      released  born name  
##   <chr> <chr>  <chr>                       <chr>         <int> <int> <chr> 
## 1 144   Movie  Houston, we have a problem. Apollo 13      1995    NA <NA>  
## 2 71    Person <NA>                        <NA>             NA  1956 Tom H…
## 3 67    Movie  At odds in life... in love… Youve Got…     1998    NA <NA>  
## 4 162   Movie  Once in a lifetime you get… A League …     1992    NA <NA>  
## 5 78    Movie  A story of love, lava and … Joe Versu…     1990    NA <NA>  
## 6 85    Movie  In every life there comes … That Thin…     1996    NA <NA>

We then reorder the relationnship table:

G$relationships <- G$relationships %>%
  unnest_relationships() %>%
  select(startNode, endNode, type, everything())
head(G$relationships)

## # A tibble: 6 x 5
##   startNode endNode type     id    roles    
##   <chr>     <chr>   <chr>    <chr> <list>   
## 1 71        144     ACTED_IN 202   <chr [1]>
## 2 71        67      ACTED_IN 84    <chr [1]>
## 3 71        162     ACTED_IN 234   <chr [1]>
## 4 71        78      ACTED_IN 98    <chr [1]>
## 5 71        85      ACTED_IN 110   <chr [1]>
## 6 71        111     ACTED_IN 146   <chr [1]>

graph_object <- igraph::graph_from_data_frame(
  d = G$relationships, 
  directed = TRUE, 
  vertices = G$nodes
)
plot(graph_object)

This can also be used with {ggraph} :

library(ggraph)
graph_object %>%
  ggraph() + 
  geom_node_label(aes(label = label)) +
  geom_edge_link() + 
  theme_graph()

## Using `nicely` as default layout

6.2 {visNetwork}

{visNetwork} expects the following format :

6.2.1 nodes

• “id” : id of the node, needed in edges information
• “label” : label of the node
• “group” : group of the node. Groups can be configure with visGroups
• “value” : size of the node
• “title” : tooltip of the node

6.2.2 edges

• “from” : node id of begin of the edge
• “to” : node id of end of the edge
• “label” : label of the edge
• “value” : size of the node
• “title” : tooltip of the node

(from ?visNetwork::visNetwork).

visNetwork is smart enough to transform a list column into several label, so we don’t have to worry too much about this one.

Here’s how to convert our {neo4r} result:

G <-"MATCH a=(p:Person {name: 'Tom Hanks'})-[r:ACTED_IN]->(m:Movie) RETURN a;" %>% 
  call_neo4j(con, type = "graph") 

# We'll just unnest the properties
G$nodes <- G$nodes %>%
  unnest_nodes(what = "properties")
head(G$nodes)  

# Turn the relationships :
G$relationships <- G$relationships %>%
  unnest_relationships() %>%
  select(from = startNode, to = endNode, label = type)
head(G$relationships)

visNetwork::visNetwork(G$nodes, G$relationships)