How to use the graphistry.plotter.Plotter._defaultNodeId function in graphistry

def _make_vgraph_dataset(self, edges, nodes, name):
        from . import vgraph

        (elist, nlist, encodings) = self._bind_attributes_v2(edges, nodes)
        nodeid = self._node or Plotter._defaultNodeId

        sources = elist[self._source]
        dests = elist[self._destination]
        elist.drop([self._source, self._destination], axis=1, inplace=True)

        # Filter out nodes which have no edges
        lnodes = pandas.concat([sources, dests], ignore_index=True).unique()
        lnodes_df = pandas.DataFrame(lnodes, columns=[nodeid])
        filtered_nlist = pandas.merge(lnodes_df, nlist, on=nodeid, how='left')

        # Create a map from nodeId to a continuous range of integer [0, #nodes-1].
        # The vgraph protobuf format uses the continous integer ranger as internal nodeIds.
        node_map = dict([(v, i) for i, v in enumerate(lnodes.tolist())])

        dataset = vgraph.create(elist, filtered_nlist, sources, dests, nodeid, node_map, name)
        dataset['encodings'] = encodings

(es2, vs2) = g.igraph2pandas(ig)
                g.nodes(vs2).bind(point_color='community').plot()
        """

        def get_edgelist(ig):
            idmap = dict(enumerate(ig.vs[self._node]))
            for e in ig.es:
                t = e.tuple
                yield dict({self._source: idmap[t[0]], self._destination: idmap[t[1]]},
                            **e.attributes())

        self._check_mandatory_bindings(False)
        if self._node is None:
            ig.vs[Plotter._defaultNodeId] = [v.index for v in ig.vs]
            self._node = Plotter._defaultNodeId
        elif self._node not in ig.vs.attributes():
            util.error('Vertex attribute "%s" bound to "node" does not exist.' % self._node)

        edata = get_edgelist(ig)
        ndata = [v.attributes() for v in ig.vs]
        nodes = pandas.DataFrame(ndata, columns=ig.vs.attributes())
        cols = [self._source, self._destination] + ig.es.attributes()
        edges = pandas.DataFrame(edata, columns=cols)
        return (edges, nodes)