Node- and group-level metrics are available as tidy data frames via
as.data.frame.
Usage
# S3 method for class 'cooccurrence'
summary(object, ...)Details
For a network built with split_by, the returned frame stacks one
network per group, so a node pair can occur once per group. Pooled
simple-graph metrics (density, mean_degree,
possible_edges) are undefined in that case and reported as
NA; the per-group table carries the correct values.
Examples
res <- cooccurrence(list(c("A","B","C"), c("B","C"), c("A","C")))
summary(res)
#> cooccurrence network
#> ------------------------------
#> Nodes : 3
#> Edges : 3
#> Possible edges : 3
#> Density : 1.0000
#> Mean degree : 2.0000
#> Isolates : 0
#> Transactions : 3
#> Similarity : none
#> Counting : full
#> Weight range : [1, 2]
#> Weight mean : 1.667
#> Count range : [1, 2]
#> Count mean : 1.667
#> Top nodes : C(2, 4), A(2, 3), B(2, 3)
# Node-level metrics as a tidy data frame
as.data.frame(summary(res))
#> cooccurrence network
#> ------------------------------
#> Nodes : 3
#> Edges : 3
#> Possible edges : 3
#> Density : 1.0000
#> Mean degree : 2.0000
#> Isolates : 0
#> Transactions : 3
#> Similarity : none
#> Counting : full
#> Weight range : [1, 2]
#> Weight mean : 1.667
#> Count range : [1, 2]
#> Count mean : 1.667
#> Top nodes : C(2, 4), A(2, 3), B(2, 3)
#> node degree strength count_strength frequency
#> 1 C 2 4 4 3
#> 2 A 2 3 3 2
#> 3 B 2 3 3 2