demos/more_examples/simple/MarvelTutorial.ipynb

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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "# ! pip install -q graphistry[igraph]"
      ],
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      "outputs": []
    },
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        "id": "6SqEpdRsrbdZ"
      },
      "source": [
        "# PyGraphistry Example: Graphing the Marvel Universe\n",
        "### Plots hero social network based on co-appearences between heroes\n",
        "\n",
        "*  Uses pandas, igraph, and PyGraphistry\n",
        "*  Combines comic book and hero data\n",
        "*  Near end, computes clusters and to avoid a hairball, weakens the edge weights between  nodes of different clusters\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gbjDG6Jerbdb"
      },
      "outputs": [],
      "source": [
        "import graphistry, igraph, pandas as pd\n",
        "\n",
        "# To specify Graphistry account & server, use:\n",
        "# graphistry.register(api=3, username='...', password='...')\n",
        "# For more options, see https://github.com/graphistry/pygraphistry#configure\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "21FWdvvDrbdc"
      },
      "source": [
        "# Load heroes, comics, appearences"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#characters_path = 'https://raw.githubusercontent.com/graphistry/pygraphistry/master/demos/data/characters.txt'\n",
        "characters_path = '../../data/characters.txt'\n",
        "\n",
        "heroes = pd.read_csv(characters_path, encoding='unicode_escape', names=['hero_name'])\n",
        "heroes['hero_id'] = heroes['hero_name'].str.extract(r'^Vertex ([0-9]+):')\n",
        "heroes['hero_name'] = heroes['hero_name'].str.extract(r'^Vertex [0-9]+: (.*)')\n",
        "heroes.sample(3)"
      ],
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          "height": 143
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        "id": "UkriDVRnsux3",
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            "text/plain": [
              "                                hero_name hero_id\n",
              "4387  PSI-LORD/FRANKLIN BENJAMIN RICHARDS    4388\n",
              "1968                            FORTUNATO    1969\n",
              "1105                                COFFY    1106"
            ],
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              "      <td>4388</td>\n",
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              "      <th>1968</th>\n",
              "      <td>FORTUNATO</td>\n",
              "      <td>1969</td>\n",
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              "    <tr>\n",
              "      <th>1105</th>\n",
              "      <td>COFFY</td>\n",
              "      <td>1106</td>\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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      "cell_type": "code",
      "source": [
        "#comics_path = 'https://raw.githubusercontent.com/graphistry/pygraphistry/master/demos/data/comics.txt'\n",
        "comics_path = '../../data/comics.txt'\n",
        "\n",
        "comics = pd.read_csv(comics_path, encoding='unicode_escape', names=['comic_name'])\n",
        "comics['comic_id'] = comics['comic_name'].str.extract(r'Vertex ([0-9]+):')\n",
        "comics['comic_name'] = comics['comic_name'].str.extract(r'Vertex [0-9]+: (.*)')\n",
        "comics"
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              "      comic_name comic_id\n",
              "0         AA2 35     6487\n",
              "1       M/PRM 35     6488\n",
              "2       M/PRM 36     6489\n",
              "3       M/PRM 37     6490\n",
              "4          WI? 9     6491\n",
              "...          ...      ...\n",
              "12937  BIZADV 33    19424\n",
              "12938    WI 25/2    19425\n",
              "12939     AA2 30    19426\n",
              "12940     AA2 20    19427\n",
              "12941     AA2 38    19428\n",
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              "      <td>AA2 38</td>\n",
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              "<p>12942 rows × 2 columns</p>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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    {
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      "source": [
        "#appearances_path = 'https://raw.githubusercontent.com/graphistry/pygraphistry/master/demos/data/appearances.txt'\n",
        "appearances_path = '../../data/appearances.txt'\n",
        "\n",
        "appearances = pd.read_csv(appearances_path, encoding='unicode_escape', names=['comic'])\n",
        "appearances = appearances[len(heroes) + len(comics) + 2:]\n",
        "appearances['hero'] = appearances.comic.str.extract(r'^([0-9]+) ')\n",
        "appearances['comic'] = appearances.comic.str.extract(r'^[0-9]+ (.*)')\n",
        "appearances['comic'] = appearances.comic.apply(lambda s: s.split(' '))\n",
        "appearances = appearances.explode('comic')\n",
        "appearances[:3]"
      ],
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          "height": 143
        },
        "id": "5SSKdLUEvP_V",
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      },
      "execution_count": null,
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          "data": {
            "text/plain": [
              "      comic hero\n",
              "19430  6487    1\n",
              "19431  6488    2\n",
              "19431  6489    2"
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c4991087-ad63-4a17-b061-8a0ee052f371 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c4991087-ad63-4a17-b061-8a0ee052f371');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OhK1em0Rrbdd"
      },
      "source": [
        "#Link heroes who co-appear"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 192
        },
        "id": "OEkcsN16rbdd",
        "outputId": "88eaeab4-e5d7-4cbc-f7ca-cdba7078be8c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "#edges 168267\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               counts\n",
              "hero_x hero_y        \n",
              "1999   1            1\n",
              "6459   1            1\n",
              "       1999         1"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fd5b160f-6ebd-43b4-9a1a-c56464e9bbdf\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>counts</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>hero_x</th>\n",
              "      <th>hero_y</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1999</th>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">6459</th>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1999</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fd5b160f-6ebd-43b4-9a1a-c56464e9bbdf')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fd5b160f-6ebd-43b4-9a1a-c56464e9bbdf button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fd5b160f-6ebd-43b4-9a1a-c56464e9bbdf');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "# You may need to install numexpr: pip install numexpr\n",
        "coappearances = (\n",
        "    appearances\n",
        "        .merge(appearances, on='comic')\n",
        "        .merge(comics, left_on='comic', right_on='comic_id')\n",
        "        [['hero_x', 'hero_y']]\n",
        "        .query('hero_x > hero_y')\n",
        ")\n",
        "\n",
        "unique_coappearances = coappearances.drop_duplicates(['hero_x', 'hero_y']).set_index(['hero_x', 'hero_y'])\n",
        "unique_coappearances['counts'] = coappearances.groupby(['hero_x', 'hero_y']).size()\n",
        "unique_coappearences = unique_coappearances.reset_index()\n",
        "\n",
        "print('#edges', len(unique_coappearances))        \n",
        "unique_coappearances[:3]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eqOzowZ3rbde"
      },
      "source": [
        "# Plot!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": true,
        "id": "VIJRkP1rrbde"
      },
      "outputs": [],
      "source": [
        "g = graphistry.edges(unique_coappearences, source='hero_x', destination='hero_y')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "bRaeh0lfrbde",
        "outputId": "4ad6d2c8-a15a-4e9d-bd05-87dc25550b87"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "            <iframe id=\"2f4a6587-25ff-43f8-ac7d-9129cd9e14d8\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=0622ae800f364ce28197dd21e5a24c33&type=arrow&viztoken=3b679533-00a4-4818-a4ef-16e6e39f93d1&usertag=b35944b5-pygraphistry-refs/pull/342/head&splashAfter=1651391257&info=true\"\n",
              "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
              "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
              "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
              "                    \n",
              "            >\n",
              "            </iframe>\n",
              "        \n",
              "            <script>\n",
              "                try {\n",
              "                  $(\"#2f4a6587-25ff-43f8-ac7d-9129cd9e14d8\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
              "                } catch (e) { console.error('exn catching scroll', e); }\n",
              "            </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "g.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0_Tzazfurbdf"
      },
      "source": [
        "# Label Nodes & Edges"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": true,
        "id": "rfKhseodrbdf"
      },
      "outputs": [],
      "source": [
        "# Here we are using two dataframes, one for edges and one for nodes\n",
        "g2 = (\n",
        "    g.nodes(heroes, 'hero_id')\n",
        "    .bind(point_title='hero_name')\n",
        "    .bind(edge_title='counts')\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "GUrWJq27rbdf",
        "outputId": "3d2fd382-f935-4501-eeec-eec503a99e53"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "            <iframe id=\"f902145f-fb74-4855-8837-0582540c6ebc\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=1e048ec60d2d40ed8cb051e5d847b960&type=arrow&viztoken=014dd435-42d4-4265-8c4a-4e640cf723ca&usertag=b35944b5-pygraphistry-refs/pull/342/head&splashAfter=1651391259&info=true\"\n",
              "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
              "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
              "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
              "                    \n",
              "            >\n",
              "            </iframe>\n",
              "        \n",
              "            <script>\n",
              "                try {\n",
              "                  $(\"#f902145f-fb74-4855-8837-0582540c6ebc\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
              "                } catch (e) { console.error('exn catching scroll', e); }\n",
              "            </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "g2.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DLT_SzUHrbdf"
      },
      "source": [
        "# Color using igraph infomap"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9aYittqYrbdf"
      },
      "source": [
        "### Infomap Community Detection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "cSgEZxfCrbdf",
        "outputId": "449e2ce3-e066-4fcd-cd8a-5f3edd99eadb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     hero_id  cluster hero_name\n",
              "4906    4907       81   SCHEELE\n",
              "2700    2701       81      KALE\n",
              "4116    4117      159        OZ"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9ef1861a-981b-45ad-be7e-5cc10c5d90aa\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hero_id</th>\n",
              "      <th>cluster</th>\n",
              "      <th>hero_name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4906</th>\n",
              "      <td>4907</td>\n",
              "      <td>81</td>\n",
              "      <td>SCHEELE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2700</th>\n",
              "      <td>2701</td>\n",
              "      <td>81</td>\n",
              "      <td>KALE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4116</th>\n",
              "      <td>4117</td>\n",
              "      <td>159</td>\n",
              "      <td>OZ</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9ef1861a-981b-45ad-be7e-5cc10c5d90aa')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9ef1861a-981b-45ad-be7e-5cc10c5d90aa button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9ef1861a-981b-45ad-be7e-5cc10c5d90aa');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "#Warning: slow\n",
        "ig = g2.to_igraph(directed=False)\n",
        "ig.vs['cluster'] = ig.community_infomap().membership\n",
        "\n",
        "# load just the desired attributes: reuse original edges, and enrich with just cluster\n",
        "g3a = g2.from_igraph(ig, load_edges=False, node_attributes=['hero_id', 'cluster'])\n",
        "g3a._nodes.sample(3)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "g3b = g3a.nodes(\n",
        "    g3a._nodes.assign(color=g3a._nodes['cluster'].apply(lambda x: x % 9).astype('int32'))\n",
        ")\n",
        "g3 = g3b.encode_point_color('color').bind(edge_weight='counts')\n",
        "\n",
        "g3._nodes.sample(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Pa-295p0a0uY",
        "outputId": "ffd1aacd-3aee-4c4e-c02b-321391a2f1fb"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     hero_id  cluster               hero_name  color\n",
              "2707    2708        5                KAMIKAZE      5\n",
              "4727    4728        8  ROGUE | MUTANT X-VERSE      8\n",
              "4166    4167       15               PARTRIDGE      6"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9c6acb45-d053-4734-acac-d950eadbada9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hero_id</th>\n",
              "      <th>cluster</th>\n",
              "      <th>hero_name</th>\n",
              "      <th>color</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2707</th>\n",
              "      <td>2708</td>\n",
              "      <td>5</td>\n",
              "      <td>KAMIKAZE</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4727</th>\n",
              "      <td>4728</td>\n",
              "      <td>8</td>\n",
              "      <td>ROGUE | MUTANT X-VERSE</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4166</th>\n",
              "      <td>4167</td>\n",
              "      <td>15</td>\n",
              "      <td>PARTRIDGE</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9c6acb45-d053-4734-acac-d950eadbada9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9c6acb45-d053-4734-acac-d950eadbada9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9c6acb45-d053-4734-acac-d950eadbada9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "EsPvIYIGrbdg",
        "outputId": "953fb249-8897-4990-a953-6c087816feaf"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "            <iframe id=\"cfdd28ca-3669-44cf-b9c2-3e87ac9370bc\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=957342a731554205a6f43d6ad1f03d4a&type=arrow&viztoken=248a6ed5-ba3e-456b-ad15-c1c9fb81b573&usertag=b35944b5-pygraphistry-refs/pull/342/head&splashAfter=1651391292&info=true\"\n",
              "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
              "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
              "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
              "                    \n",
              "            >\n",
              "            </iframe>\n",
              "        \n",
              "            <script>\n",
              "                try {\n",
              "                  $(\"#cfdd28ca-3669-44cf-b9c2-3e87ac9370bc\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
              "                } catch (e) { console.error('exn catching scroll', e); }\n",
              "            </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "g3.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_oJ-C9hJrbdg"
      },
      "source": [
        "# Restrict to biggest communities"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "gdKjHaaprbdg",
        "outputId": "840fc524-7bae-4924-c618-74e465878f44"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# big clusters 10\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   cluster  cluster_size\n",
              "0        1          1354\n",
              "1        2           198\n",
              "2        5           836"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-153733cc-aba4-4655-be45-34f9df65076f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cluster</th>\n",
              "      <th>cluster_size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5</td>\n",
              "      <td>836</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-153733cc-aba4-4655-be45-34f9df65076f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-153733cc-aba4-4655-be45-34f9df65076f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-153733cc-aba4-4655-be45-34f9df65076f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "big_clusters = (g3._nodes\n",
        "    .pivot_table(index=['cluster'], aggfunc=lambda x: len(x.unique()))\n",
        "    .rename(columns={'hero_id': 'cluster_size'})\n",
        "    .query('cluster_size > 100')\n",
        "    .reset_index()[['cluster', 'cluster_size']]\n",
        ")\n",
        "print('# big clusters', len(big_clusters))\n",
        "big_clusters[:3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "Yr0r6i0Krbdh",
        "outputId": "2840238b-6b5f-4243-ffd1-81ecef41b6df"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# nodes 3711\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  hero_id  cluster                                   hero_name  color  \\\n",
              "0       2        1  3-D MAN/CHARLES CHANDLER & HAROLD CHANDLER      1   \n",
              "1      10        1                    ABOMINATION/EMIL BLONSKY      1   \n",
              "2      18        1                                        ACBA      1   \n",
              "\n",
              "   cluster_size  \n",
              "0          1354  \n",
              "1          1354  \n",
              "2          1354  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-04944ac5-29f8-47a7-ba60-5f7d7ec5791d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hero_id</th>\n",
              "      <th>cluster</th>\n",
              "      <th>hero_name</th>\n",
              "      <th>color</th>\n",
              "      <th>cluster_size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3-D MAN/CHARLES CHANDLER &amp; HAROLD CHANDLER</td>\n",
              "      <td>1</td>\n",
              "      <td>1354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>ABOMINATION/EMIL BLONSKY</td>\n",
              "      <td>1</td>\n",
              "      <td>1354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>ACBA</td>\n",
              "      <td>1</td>\n",
              "      <td>1354</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-04944ac5-29f8-47a7-ba60-5f7d7ec5791d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-04944ac5-29f8-47a7-ba60-5f7d7ec5791d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-04944ac5-29f8-47a7-ba60-5f7d7ec5791d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "good_nodes = g3._nodes.merge(big_clusters, on='cluster')\n",
        "print('# nodes', len(good_nodes))\n",
        "good_nodes[:3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "OTf_LDq3rbdh",
        "outputId": "9449a1f2-dd16-4282-e7c4-d2a46b8dd545"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# edges 118318\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  hero_x hero_y  counts\n",
              "0   2186      2       3\n",
              "1   2555      2       3\n",
              "2   3491      2       3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-55d5ef2d-addf-42be-b468-df047b82313c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hero_x</th>\n",
              "      <th>hero_y</th>\n",
              "      <th>counts</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2186</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2555</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3491</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-55d5ef2d-addf-42be-b468-df047b82313c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-55d5ef2d-addf-42be-b468-df047b82313c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-55d5ef2d-addf-42be-b468-df047b82313c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ],
      "source": [
        "good_edges = unique_coappearences\\\n",
        "    .merge(good_nodes, left_on='hero_x', right_on='hero_id')\\\n",
        "    .merge(good_nodes, left_on='hero_y', right_on='hero_id')\\\n",
        "    [['hero_x', 'hero_y', 'counts']]\n",
        "print('# edges', len(good_edges))\n",
        "good_edges[:3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "ayFTeZIArbdh",
        "outputId": "13819fe4-829e-43f6-e360-bd78480045c9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "            <iframe id=\"5543fd91-4c28-41a7-871d-b35dee30e272\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=a0e1210f79344b3a838f23772ca3f5e8&type=arrow&viztoken=0a21a400-d421-49c5-906c-45e5b8bcae0b&usertag=b35944b5-pygraphistry-refs/pull/342/head&splashAfter=1651391531&info=true\"\n",
              "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
              "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
              "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
              "                    \n",
              "            >\n",
              "            </iframe>\n",
              "        \n",
              "            <script>\n",
              "                try {\n",
              "                  $(\"#5543fd91-4c28-41a7-871d-b35dee30e272\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
              "                } catch (e) { console.error('exn catching scroll', e); }\n",
              "            </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ],
      "source": [
        "g4 = g3.edges(good_edges).nodes(good_nodes)\n",
        "\n",
        "g4.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kaf1Qgzrrbdh"
      },
      "source": [
        "# Seperate communities\n",
        "### Treat intra-community edges as strong edge weights, and inter-community as weak edge weight"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "E0ZPz9a7rbdh",
        "outputId": "5acbac74-636b-459e-c25b-9fbc41a71952"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  hero_x hero_y  counts  is_inner  weight\n",
              "0   2186      2       3      True      10\n",
              "1   2555      2       3      True      10\n",
              "2   3491      2       3      True      10"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fbbbc779-b944-46a3-b0bf-389dcae92146\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hero_x</th>\n",
              "      <th>hero_y</th>\n",
              "      <th>counts</th>\n",
              "      <th>is_inner</th>\n",
              "      <th>weight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2186</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>True</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2555</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>True</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3491</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>True</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fbbbc779-b944-46a3-b0bf-389dcae92146')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fbbbc779-b944-46a3-b0bf-389dcae92146 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fbbbc779-b944-46a3-b0bf-389dcae92146');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "#label edges whether they stay inside a cluster or connect nodes in different clusters\n",
        "good_edges2 = good_edges\\\n",
        "        .merge(\\\n",
        "                 good_nodes[['cluster', 'hero_id']].rename(columns={'cluster': 'cluster_x'}),\\\n",
        "                 left_on='hero_x', right_on='hero_id')\\\n",
        "        .merge(\\\n",
        "                 good_nodes[['cluster', 'hero_id']].rename(columns={'cluster': 'cluster_y'}),\\\n",
        "                 left_on='hero_y', right_on='hero_id')\n",
        "good_edges2['is_inner'] = good_edges2.apply(lambda x: x['cluster_x'] == x['cluster_y'], axis=1)\n",
        "\n",
        "#bind to edge_weight\n",
        "good_edges2['weight'] = good_edges2.apply(lambda x: 10 if x['is_inner'] else 8, axis=1)\n",
        "good_edges2 = good_edges2[['hero_x', 'hero_y', 'counts', 'is_inner', 'weight']]\n",
        "good_edges2[:3]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aHHd1zf3rbdh"
      },
      "source": [
        "### Plot; control the edge weight in the settings panel"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "scrolled": false,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "ToMe-BkErbdi",
        "outputId": "715e734a-9702-4a90-a33e-586f61a19f3a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "            <iframe id=\"ed4f92c1-82f7-4af0-8ce4-50054586ccfb\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=06365bd491574eecab13aef5b8971415&type=arrow&viztoken=10d09787-a1bf-4955-b5d0-6ebc10643f45&usertag=b35944b5-pygraphistry-refs/pull/342/head&splashAfter=1651391583&info=true&edgeInfluence=0.7&edgeOpacity=0.5\"\n",
              "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
              "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
              "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
              "                    \n",
              "            >\n",
              "            </iframe>\n",
              "        \n",
              "            <script>\n",
              "                try {\n",
              "                  $(\"#ed4f92c1-82f7-4af0-8ce4-50054586ccfb\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
              "                } catch (e) { console.error('exn catching scroll', e); }\n",
              "            </script>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ],
      "source": [
        "g5 = (g4\n",
        "      .bind(edge_weight='weight')\n",
        "      .edges(good_edges2)\n",
        "      .settings(url_params={'edgeInfluence': 0.7, 'edgeOpacity': 0.5})\n",
        ")\n",
        "\n",
        "g5.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GLJDGwokrbdi"
      },
      "source": [
        "# Filter by k-core shell"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0orzmEl8rbdi",
        "outputId": "7b489d91-f1e7-47a6-ac1c-215d303dd858"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "#shells 95\n"
          ]
        }
      ],
      "source": [
        "ig5 = g5.to_igraph()\n",
        "ig5.vs['shell'] = g5.to_igraph().shell_index()\n",
        "print('#shells', str(len(list(set(ig5.vs['shell'])))))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "g5._edges"
      ],
      "metadata": {
        "id": "R4ZkQ-Ydkt74",
        "outputId": "dc96f156-8d98-47e8-e6ca-22f332cb4fa7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       hero_x hero_y  counts  is_inner  weight\n",
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              "2        3491      2       3      True      10\n",
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              "4         859      2       3      True      10\n",
              "...       ...    ...     ...       ...     ...\n",
              "113111   3493    335       1      True      10\n",
              "113112    993    991       1      True      10\n",
              "113113    805   6394       1      True      10\n",
              "113114    818   4670       1      True      10\n",
              "113115    758    677       1      True      10\n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LVZ6J7dOrbdi"
      },
      "source": [
        "### Plot: Use the histogram tool to filter for the smaller shells"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#update just the attributes we want\n",
        "g5.from_igraph(ig5, node_attributes=['shell', 'hero_id'], load_edges=False).plot()"
      ],
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        "id": "TPIUpYpCjFQL",
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        "colab": {
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          "height": 543
        }
      },
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      "outputs": [
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          },
          "metadata": {},
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    {
      "cell_type": "code",
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