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Clustering nodes

Now, let's try to group nodes into clusters.


{
  "data": [
    {
      "name": "data",
      "url": "/data/blogs/network.csv",
      "format": {"type": "csv"}
    }
  ],

  "networks": [
    {
      "name": "network",
      "links": "data",
      "directed": true,
      "source_node": [ "id", "source" ],
      "target_node": [ "id",  "target" ],

       "transform": [
         {"type": "metric", "metric": "degree"}
         {"type": "filterNodes", "expression": "datum.degree > 2 "}

After filtering, we perform an additional transform to apply Louvain clustering.


         {"type": "cluster", "method": "louvain"}


       ]
    }
  ],

  "layouts": [
    {
      "name": "layout",
      "network": "network",
      "type": "d3-force"
    }
  ],

Define a caegorical color scale


  "scales": [
    {
      "name": "color",
      "type": "linear",
      "scheme": "category20",
      "domain": [0, 20]
    }
  ],



  "vis": [
    {
      "entries": "network.links",
      "layout": "layout",
      "mark": {
        "type": "linkpath",
        "start": "source",
        "end": "target"
      }
    },
    {
      "entries": "network.nodes",
      "layout": "layout",
      "mark": {
        "type": "circle",
        "area": 70,

Color each node based on the cluster number, using the color scale.


        "fill": {"field": "louvain", "scale": "color"}


      }
    }
  ]
}