Creating igraph graphs from data frames or vice-versa

This function creates an igraph graph from one or two data frames containing the (symbolic) edge list and edge/vertex attributes.

Usage

as_data_frame(x, what = c("edges", "vertices", "both"))

graph_from_data_frame(d, directed = TRUE, vertices = NULL)

from_data_frame(...)

Arguments

x

An igraph object.

what

Character constant, whether to return info about vertices, edges, or both. The default is ‘edges’.

d

A data frame containing a symbolic edge list in the first two columns. Additional columns are considered as edge attributes. Since version 0.7 this argument is coerced to a data frame with as.data.frame.

directed

Logical scalar, whether or not to create a directed graph.

vertices

A data frame with vertex metadata, or NULL. See details below. Since version 0.7 this argument is coerced to a data frame with as.data.frame, if not NULL.

...

Passed to graph_from_data_frame().

Value

An igraph graph object for graph_from_data_frame(), and either a data frame or a list of two data frames named edges and vertices for as.data.frame.

Details

graph_from_data_frame() creates igraph graphs from one or two data frames. It has two modes of operation, depending whether the vertices argument is NULL or not.

If vertices is NULL, then the first two columns of d are used as a symbolic edge list and additional columns as edge attributes. The names of the attributes are taken from the names of the columns.

If vertices is not NULL, then it must be a data frame giving vertex metadata. The first column of vertices is assumed to contain symbolic vertex names, this will be added to the graphs as the ‘name’ vertex attribute. Other columns will be added as additional vertex attributes. If vertices is not NULL then the symbolic edge list given in d is checked to contain only vertex names listed in vertices.

Typically, the data frames are exported from some spreadsheet software like Excel and are imported into R via read.table(), read.delim() or read.csv().

All edges in the data frame are included in the graph, which may include multiple parallel edges and loops.

as_data_frame() converts the igraph graph into one or more data frames, depending on the what argument.

If the what argument is edges (the default), then the edges of the graph and also the edge attributes are returned. The edges will be in the first two columns, named from and to. (This also denotes edge direction for directed graphs.) For named graphs, the vertex names will be included in these columns, for other graphs, the numeric vertex ids. The edge attributes will be in the other columns. It is not a good idea to have an edge attribute named from or to, because then the column named in the data frame will not be unique. The edges are listed in the order of their numeric ids.

If the what argument is vertices, then vertex attributes are returned. Vertices are listed in the order of their numeric vertex ids.

If the what argument is both, then both vertex and edge data is returned, in a list with named entries vertices and edges.

Note

For graph_from_data_frame() NA elements in the first two columns ‘d’ are replaced by the string “NA” before creating the graph. This means that all NAs will correspond to a single vertex.

NA elements in the first column of ‘vertices’ are also replaced by the string “NA”, but the rest of ‘vertices’ is not touched. In other words, vertex names (=the first column) cannot be NA, but other vertex attributes can.

See also

graph_from_literal() for another way to create graphs, read.table() to read in tables from files.

Other conversion: as.matrix.igraph(), as_adj_list(), as_adjacency_matrix(), as_biadjacency_matrix(), as_directed(), as_edgelist(), as_graphnel(), as_long_data_frame(), graph_from_adj_list(), graph_from_graphnel()

Other biadjacency: graph_from_biadjacency_matrix()

Author

Gabor Csardi csardi.gabor@gmail.com

Examples

## A simple example with a couple of actors
## The typical case is that these tables are read in from files....
actors <- data.frame(
  name = c(
    "Alice", "Bob", "Cecil", "David",
    "Esmeralda"
  ),
  age = c(48, 33, 45, 34, 21),
  gender = c("F", "M", "F", "M", "F")
)
relations <- data.frame(
  from = c(
    "Bob", "Cecil", "Cecil", "David",
    "David", "Esmeralda"
  ),
  to = c("Alice", "Bob", "Alice", "Alice", "Bob", "Alice"),
  same.dept = c(FALSE, FALSE, TRUE, FALSE, FALSE, TRUE),
  friendship = c(4, 5, 5, 2, 1, 1), advice = c(4, 5, 5, 4, 2, 3)
)
g <- graph_from_data_frame(relations, directed = TRUE, vertices = actors)
print(g, e = TRUE, v = TRUE)
#> IGRAPH f33cbbf DN-- 5 6 -- 
#> + attr: name (v/c), age (v/n), gender (v/c), same.dept (e/l),
#> | friendship (e/n), advice (e/n)
#> + edges from f33cbbf (vertex names):
#> [1] Bob      ->Alice Cecil    ->Bob   Cecil    ->Alice David    ->Alice
#> [5] David    ->Bob   Esmeralda->Alice

## The opposite operation
as_data_frame(g, what = "vertices")
#>                name age gender
#> Alice         Alice  48      F
#> Bob             Bob  33      M
#> Cecil         Cecil  45      F
#> David         David  34      M
#> Esmeralda Esmeralda  21      F
as_data_frame(g, what = "edges")
#>        from    to same.dept friendship advice
#> 1       Bob Alice     FALSE          4      4
#> 2     Cecil   Bob     FALSE          5      5
#> 3     Cecil Alice      TRUE          5      5
#> 4     David Alice     FALSE          2      4
#> 5     David   Bob     FALSE          1      2
#> 6 Esmeralda Alice      TRUE          1      3