Take a P2P network query and implement the Louvain community detection method. The 'igraph' implementation of the Louvain method is used.
network_louvain(
data,
hrvar = "Organization",
bg_fill = "#000000",
font_col = "#FFFFFF",
node_alpha = 0.8,
algorithm = "mds",
path = "network_p2p_louvain",
desc_hrvar = c("Organization", "LevelDesignation", "FunctionType"),
return = "plot-louvain",
size_threshold = 5000
)See return.
Data frame containing a person-to-person query.
String containing the label for the HR attribute.
String to specify background fill colour.
String to specify font and link colour.
A numeric value between 0 and 1 to specify the transparency of the nodes. Defaults to 0.7.
String to specify the node placement algorithm to be used.
Defaults to "mds" for the deterministic multi-dimensional scaling of
nodes. See
https://rdrr.io/cran/ggraph/man/layout_tbl_graph_igraph.html for a full
list of options.
File path for saving the PDF output. Defaults to a timestamped path based on current parameters.
Character vector of length 3 containing the HR attributes
to use when returning the "describe" output. See network_describe().
String specifying what output to return. Defaults to "plot-louvain". Valid return options include:
'plot-louvain': return a network plot coloured by Louvain communities,
saving a PDF to path.
'plot-hrvar': return a network plot coloured by HR attribute, saving a
PDF to path.
'plot-sankey': return a sankey plot combining communities and HR
attribute.
'table': return a vertex summary table with counts in communities and
HR attribute.
'data': return a vertex data file that matches vertices with
communities and HR attributes.
'describe': return a list of data frames which describe each of the
identified communities. The first data frame is a summary table of all the
communities.
'network': return 'igraph' object.
Numeric value representing the maximum number of edges
before network_leiden() switches to use a more efficient, but less
elegant plotting method (native igraph). Defaults to 5000. Set as 0 to
coerce to a fast plotting method every time, and Inf to always use the
default plotting method (with 'ggraph').
Other Network:
external_network_plot(),
g2g_data,
internal_network_plot(),
network_describe(),
network_g2g(),
network_leiden(),
network_p2p(),
network_summary(),
p2p_data_sim()
# Simulate a small person-to-person dataset
p2p_data <- p2p_data_sim(size = 50)
# Return louvain, console, plot
p2p_data %>%
network_louvain(path = NULL,
return = "plot")
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