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Decompose a netify object into edges and nodal data frames

decompose_netlet.Rd

decompose_netlet separates a netify object into its constituent parts: a data frame of edges and a data frame of nodal attributes. This function is particularly useful for preparing network data for analyses that require separate edge and node data sets.

Usage

decompose_netlet(netlet, remove_zeros = TRUE)

Arguments

netlet

A netify object to be decomposed.

remove_zeros

Logical. If TRUE, remove edges with zero values.

Value

A list containing two elements: edge_data and nodal_data. edge_data is a data frame of edges with attributes, and nodal_data is a data frame containing node attributes.

Author

Cassy Dorff, Shahryar Minhas

Examples

# load icews data
data(icews)

# choose attributes
nvars = c( 'i_polity2', 'i_log_gdp', 'i_log_pop' )
dvars = c( 'matlCoop', 'verbConf', 'matlConf' )

# create a netify object
netlet = netify(
    dyad_data=icews, actor1='i', actor2='j',
    time = 'year',
    symmetric=FALSE, weight='verbCoop',
    mode='unipartite', sum_dyads=FALSE,
    actor_time_uniform=TRUE, actor_pds=NULL,
    diag_to_NA=TRUE, missing_to_zero=TRUE,
    nodal_vars = nvars, 
    dyad_vars = dvars
)

# decompose the netify object
decomposed = decompose_netlet( netlet )

lapply(decomposed, head)
#> $edge_data
#>          from      to time verbCoop matlCoop verbConf matlConf
#> 1 Afghanistan Albania 2002        6        1        0        0
#> 2 Afghanistan Albania 2003        1        1        0        0
#> 3 Afghanistan Albania 2004       10        2        0        1
#> 4 Afghanistan Albania 2006        6        2        3       21
#> 5 Afghanistan Albania 2007        3        2        0        0
#> 6 Afghanistan Albania 2008        2        0        0        0
#> 
#> $nodal_data
#>          name time i_polity2 i_log_gdp i_log_pop
#> 1 Afghanistan 2002        NA  22.74550  16.86005
#> 2 Afghanistan 2003        NA  22.83014  16.93546
#> 3 Afghanistan 2004        NA  22.84418  16.97479
#> 4 Afghanistan 2005        NA  22.95061  17.01055
#> 5 Afghanistan 2006        NA  23.00280  17.05195
#> 6 Afghanistan 2007        NA  23.13230  17.06988
#>