{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "hide_input"
    ]
   },
   "source": [
    "# Make an Interactive Network Visualization with Bokeh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook includes code for creating interactive network visualizations with the Python libraries [NetworkX](https://networkx.github.io/) and [Bokeh](https://docs.bokeh.org/en/latest/index.html). The notebook begins with code for a basic network visualization then progressively demonstrates how to add more information and functionality, such as:\n",
    "\n",
    "- sizing and coloring nodes by degree\n",
    "- sizing and coloring nodes by modularity class\n",
    "- adding responsive highlighting when hovering over nodes and edges\n",
    "- adding node labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### *Game of Thrones*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<blockquote class=\"epigraph\" style=\" padding: 10px\">\n",
    "\n",
    "Lucky it might be, and red it certainly was, but Ygritte’s hair was such a tangle that Jon was tempted to ask her if she only brushed it at the changing of the seasons.\n",
    "\n",
    "-George R. R. Martin, *A Song of Ice and Fire*\n",
    "</blockquote>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import networkx\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install and Import Bokeh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install bokeh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To view interactive Bokeh visualizations in a Jupyter notebook, you need to run this cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1301\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  var JS_MIME_TYPE = 'application/javascript';\n  var HTML_MIME_TYPE = 'text/html';\n  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n  var CLASS_NAME = 'output_bokeh rendered_html';\n\n  /**\n   * Render data to the DOM node\n   */\n  function render(props, node) {\n    var script = document.createElement(\"script\");\n    node.appendChild(script);\n  }\n\n  /**\n   * Handle when an output is cleared or removed\n   */\n  function handleClearOutput(event, handle) {\n    var cell = handle.cell;\n\n    var id = cell.output_area._bokeh_element_id;\n    var server_id = cell.output_area._bokeh_server_id;\n    // Clean up Bokeh references\n    if (id != null && id in Bokeh.index) {\n      Bokeh.index[id].model.document.clear();\n      delete Bokeh.index[id];\n    }\n\n    if (server_id !== undefined) {\n      // Clean up Bokeh references\n      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n      cell.notebook.kernel.execute(cmd, {\n        iopub: {\n          output: function(msg) {\n            var id = msg.content.text.trim();\n            if (id in Bokeh.index) {\n              Bokeh.index[id].model.document.clear();\n              delete Bokeh.index[id];\n            }\n          }\n        }\n      });\n      // Destroy server and session\n      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n      cell.notebook.kernel.execute(cmd);\n    }\n  }\n\n  /**\n   * Handle when a new output is added\n   */\n  function handleAddOutput(event, handle) {\n    var output_area = handle.output_area;\n    var output = handle.output;\n\n    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n      return\n    }\n\n    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n\n    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n      // store reference to embed id on output_area\n      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n    }\n    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n      var bk_div = document.createElement(\"div\");\n      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n      var script_attrs = bk_div.children[0].attributes;\n      for (var i = 0; i < script_attrs.length; i++) {\n        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n      }\n      // store reference to server id on output_area\n      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n    }\n  }\n\n  function register_renderer(events, OutputArea) {\n\n    function append_mime(data, metadata, element) {\n      // create a DOM node to render to\n      var toinsert = this.create_output_subarea(\n        metadata,\n        CLASS_NAME,\n        EXEC_MIME_TYPE\n      );\n      this.keyboard_manager.register_events(toinsert);\n      // Render to node\n      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n      render(props, toinsert[toinsert.length - 1]);\n      element.append(toinsert);\n      return toinsert\n    }\n\n    /* Handle when an output is cleared or removed */\n    events.on('clear_output.CodeCell', handleClearOutput);\n    events.on('delete.Cell', handleClearOutput);\n\n    /* Handle when a new output is added */\n    events.on('output_added.OutputArea', handleAddOutput);\n\n    /**\n     * Register the mime type and append_mime function with output_area\n     */\n    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n      /* Is output safe? */\n      safe: true,\n      /* Index of renderer in `output_area.display_order` */\n      index: 0\n    });\n  }\n\n  // register the mime type if in Jupyter Notebook environment and previously unregistered\n  if (root.Jupyter !== undefined) {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  }\n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1301\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.0.min.js\": \"YobFyzPeVUsFQydHkJGsJL1kyfHnWxOlPc3EwaV22TmBaeGoXHLWx5aRRVPS9xlE\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.0.min.js\": \"NuAg9+TcTQQqvQCTtkCneRrpkTiMhhfiq0KHiBzx8ECiKiLWXHN6i6ia3q7b3eHu\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.0.min.js\": \"uMVqQc8JqHitD67bXTn9a06Mrk3EiHRaZ18EJENQenAKJ/KL71SakdXYomZQpGRr\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.0.min.js\": \"u+eGuEXC8aw0VSCm2mH+b/tQEAitUOYiR1H6SuIVEdUmXsf4vN8m/SmXpmjb7U/X\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1301\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));",
      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Network From Pandas DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We read in a CSV file of *Game of Thrones* network data from Andrew Beveridge and Jie Shan's paper, [\"Network of Thrones.\"](https://www.maa.org/sites/default/files/pdf/Mathhorizons/NetworkofThrones%20%281%29.pdf)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{admonition} Pandas Review\n",
    ":class: pandasreview\n",
    " Do you need a refresher or introduction to the Python data analysis library Pandas? Be sure to check out <a href=\"https://melaniewalsh.github.io/Intro-Cultural-Analytics/Data-Analysis/Pandas-Basics-Part1.html\"> Pandas Basics (1-3) </a> in this textbook!\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "got_df = pd.read_csv('../data/got-edges.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Source</th>\n",
       "      <th>Target</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aemon</td>\n",
       "      <td>Grenn</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Aemon</td>\n",
       "      <td>Samwell</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Aerys</td>\n",
       "      <td>Jaime</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aerys</td>\n",
       "      <td>Robert</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aerys</td>\n",
       "      <td>Tyrion</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>Walder</td>\n",
       "      <td>Petyr</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>Walder</td>\n",
       "      <td>Roslin</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>Walton</td>\n",
       "      <td>Jaime</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>350</th>\n",
       "      <td>Ygritte</td>\n",
       "      <td>Qhorin</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351</th>\n",
       "      <td>Ygritte</td>\n",
       "      <td>Rattleshirt</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>352 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Source       Target  Weight\n",
       "0      Aemon        Grenn       5\n",
       "1      Aemon      Samwell      31\n",
       "2      Aerys        Jaime      18\n",
       "3      Aerys       Robert       6\n",
       "4      Aerys       Tyrion       5\n",
       "..       ...          ...     ...\n",
       "347   Walder        Petyr       6\n",
       "348   Walder       Roslin       6\n",
       "349   Walton        Jaime      10\n",
       "350  Ygritte       Qhorin       7\n",
       "351  Ygritte  Rattleshirt       9\n",
       "\n",
       "[352 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "got_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we make a network with `networkx.from_pandas_edgelist()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = networkx.from_pandas_edgelist(got_df, 'Source', 'Target', 'Weight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Network "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below shows how to make a basic network viz that includes Hover Tooltips (a text box that will display when a user hovers over nodes) as well as Zoom and Pan/Drag functionality.\n",
    "\n",
    "For more details about visualizing network graphs with Bokeh, see [the documentation](https://docs.bokeh.org/en/latest/docs/user_guide/graph.html?highlight=networks)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save\n",
    "from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import from_networkx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"b3019bfd-80f1-49ea-bad4-caf8514e76de\" data-root-id=\"1340\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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Application\",\"version\":\"2.1.0\"}};\n  var render_items = [{\"docid\":\"55fb56a7-2611-4018-a7e1-7935b9d8f88e\",\"root_ids\":[\"1340\"],\"roots\":{\"1340\":\"b3019bfd-80f1-49ea-bad4-caf8514e76de\"}}];\n  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    var attempts = 0;\n    var timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
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      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1340"
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     "output_type": "display_data"
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   ],
   "source": [
    "#Choose a title!\n",
    "title = 'Game of Thrones Network'\n",
    "\n",
    "#Establish which categories will appear when hovering over each node\n",
    "HOVER_TOOLTIPS = [(\"Character\", \"@index\")]\n",
    "\n",
    "#Create a plot — set dimensions, toolbar, and title\n",
    "plot = figure(tooltips = HOVER_TOOLTIPS,\n",
    "              tools=\"pan,wheel_zoom,save,reset\", active_scroll='wheel_zoom',\n",
    "            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)\n",
    "\n",
    "#Create a network graph object with spring layout\n",
    "# https://networkx.github.io/documentation/networkx-1.9/reference/generated/networkx.drawing.layout.spring_layout.html\n",
    "network_graph = from_networkx(G, networkx.spring_layout, scale=10, center=(0, 0))\n",
    "\n",
    "#Set node size and color\n",
    "network_graph.node_renderer.glyph = Circle(size=15, fill_color='skyblue')\n",
    "\n",
    "#Set edge opacity and width\n",
    "network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.5, line_width=1)\n",
    "\n",
    "#Add network graph to the plot\n",
    "plot.renderers.append(network_graph)\n",
    "\n",
    "show(plot)\n",
    "#save(plot, filename=f\"{title}.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network with Nodes Sized and Colored By Attribute (Degree)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below shows how to size and color nodes by degree."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Include Bokeh color palettes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save\n",
    "from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import from_networkx\n",
    "from bokeh.palettes import Blues8, Reds8, Purples8, Oranges8, Viridis8, Spectral8\n",
    "from bokeh.transform import linear_cmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate degree for each node and add as node attribute**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "degrees = dict(networkx.degree(G))\n",
    "networkx.set_node_attributes(G, name='degree', values=degrees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Slightly adjust degree so that the nodes with very small degrees are still visible**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "number_to_adjust_by = 5\n",
    "adjusted_node_size = dict([(node, degree+number_to_adjust_by) for node, degree in networkx.degree(G)])\n",
    "networkx.set_node_attributes(G, name='adjusted_node_size', values=adjusted_node_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "  <div class=\"bk-root\" id=\"0ab88475-078c-4796-a773-234cf1e6226f\" data-root-id=\"1304\"></div>\n"
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    "#Choose attributes from G network to size and color by — setting manual size (e.g. 10) or color (e.g. 'skyblue') also allowed\n",
    "size_by_this_attribute = 'adjusted_node_size'\n",
    "color_by_this_attribute = 'adjusted_node_size'\n",
    "\n",
    "#Pick a color palette — Blues8, Reds8, Purples8, Oranges8, Viridis8\n",
    "color_palette = Blues8\n",
    "\n",
    "#Choose a title!\n",
    "title = 'Game of Thrones Network'\n",
    "\n",
    "#Establish which categories will appear when hovering over each node\n",
    "HOVER_TOOLTIPS = [\n",
    "       (\"Character\", \"@index\"),\n",
    "        (\"Degree\", \"@degree\")\n",
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    "\n",
    "#Create a plot — set dimensions, toolbar, and title\n",
    "plot = figure(tooltips = HOVER_TOOLTIPS,\n",
    "              tools=\"pan,wheel_zoom,save,reset\", active_scroll='wheel_zoom',\n",
    "            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)\n",
    "\n",
    "#Create a network graph object\n",
    "# https://networkx.github.io/documentation/networkx-1.9/reference/generated/networkx.drawing.layout.spring_layout.html\\\n",
    "network_graph = from_networkx(G, networkx.spring_layout, scale=10, center=(0, 0))\n",
    "\n",
    "#Set node sizes and colors according to node degree (color as spectrum of color palette)\n",
    "minimum_value_color = min(network_graph.node_renderer.data_source.data[color_by_this_attribute])\n",
    "maximum_value_color = max(network_graph.node_renderer.data_source.data[color_by_this_attribute])\n",
    "network_graph.node_renderer.glyph = Circle(size=size_by_this_attribute, fill_color=linear_cmap(color_by_this_attribute, color_palette, minimum_value_color, maximum_value_color))\n",
    "\n",
    "#Set edge opacity and width\n",
    "network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.5, line_width=1)\n",
    "\n",
    "plot.renderers.append(network_graph)\n",
    "\n",
    "show(plot)\n",
    "#save(plot, filename=f\"{title}.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network with Nodes Colored By Attribute (Community)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below shows how to size and color nodes by modularity class."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Include community module**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save\n",
    "from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import from_networkx\n",
    "from bokeh.palettes import Blues8, Reds8, Purples8, Oranges8, Viridis8, Spectral8\n",
    "from bokeh.transform import linear_cmap\n",
    "from networkx.algorithms import community"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate degree for each node and add as node attribute**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "degrees = dict(networkx.degree(G))\n",
    "networkx.set_node_attributes(G, name='degree', values=degrees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Slightly adjust degree so that the nodes with very small degrees are still visible**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "number_to_adjust_by = 5\n",
    "adjusted_node_size = dict([(node, degree+number_to_adjust_by) for node, degree in networkx.degree(G)])\n",
    "networkx.set_node_attributes(G, name='adjusted_node_size', values=adjusted_node_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate communities**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "communities = community.greedy_modularity_communities(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Add modularity class and color as attributes to network graph**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create empty dictionaries\n",
    "modularity_class = {}\n",
    "modularity_color = {}\n",
    "#Loop through each community in the network\n",
    "for community_number, community in enumerate(communities):\n",
    "    #For each member of the community, add their community number and a distinct color\n",
    "    for name in community: \n",
    "        modularity_class[name] = community_number\n",
    "        modularity_color[name] = Spectral8[community_number]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add modularity class and color as attributes from the network above\n",
    "networkx.set_node_attributes(G, modularity_class, 'modularity_class')\n",
    "networkx.set_node_attributes(G, modularity_color, 'modularity_color')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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Arryn\"],\"start\":[\"Aemon\",\"Aemon\",\"Aemon\",\"Aemon\",\"Aemon\",\"Grenn\",\"Grenn\",\"Grenn\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Aerys\",\"Aerys\",\"Aerys\",\"Aerys\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Alliser\",\"Alliser\",\"Alliser\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Amory\",\"Oberyn\",\"Oberyn\",\"Oberyn\",\"Oberyn\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Anguy\",\"Beric\",\"Beric\",\"Beric\",\"Beric\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Gendry\",\"Gendry\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Rickon\",\"Rickon\",\"Rickon\",\"Rickon\",\"Roose\",\"Roose\",\"Roose\",\"Sandor\",\"Sandor\",\"Sandor\",\"Sandor\",\"Sandor\",\"Balon\",\"Balon\",\"Balon\",\"Loras\",\"Loras\",\"Loras\",\"Loras\",\"Loras\",\"Belwas\",\"Belwas\",\"Belwas\",\"Belwas\",\"Barristan\",\"Barristan\",\"Barristan\",\"Hodor\",\"Hodor\",\"Hodor\",\"Jojen\",\"Luwin\",\"Theon\",\"Brienne\",\"Brienne\",\"Brienne\",\"Bronn\",\"Podrick\",\"Podrick\",\"Lothar\",\"Lothar\",\"Lothar\",\"Lothar\",\"Walder\",\"Walder\",\"Walder\",\"Walder\",\"Walder\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Edmure\",\"Edmure\",\"Edmure\",\"Hoster\",\"Jeyne\",\"Lysa\",\"Lysa\",\"Lysa\",\"Lysa\",\"Lysa\",\"Petyr\",\"Petyr\",\"Robb\",\"Robb\",\"Robb\",\"Robb\",\"Robb\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Stannis\",\"Stannis\",\"Stannis\",\"Elia\",\"Ilyn\",\"Pycelle\",\"Shae\",\"Shae\",\"Varys\",\"Varys\",\"Craster\",\"Craster\",\"Daario\",\"Daario\",\"Daario\",\"Daario\",\"Drogo\",\"Drogo\",\"Drogo\",\"Irri\",\"Irri\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Jorah\",\"Rhaegar\",\"Davos\",\"Davos\",\"Davos\",\"Davos\",\"Renly\",\"Tommen\",\"Tommen\",\"Janos\",\"Kevan\",\"Dalla\",\"Qhorin\",\"Qhorin\",\"Rattleshirt\",\"Marillion\"]},\"selected\":{\"id\":\"1527\"},\"selection_policy\":{\"id\":\"1528\"}},\"id\":\"1458\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"end\":10.1,\"start\":-10.1},\"id\":\"1420\",\"type\":\"Range1d\"},{\"attributes\":{\"edge_renderer\":{\"id\":\"1459\"},\"inspection_policy\":{\"id\":\"1523\"},\"layout_provider\":{\"id\":\"1461\"},\"node_renderer\":{\"id\":\"1455\"},\"selection_policy\":{\"id\":\"1524\"}},\"id\":\"1452\",\"type\":\"GraphRenderer\"},{\"attributes\":{},\"id\":\"1514\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1526\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"data_source\":{\"id\":\"1454\"},\"glyph\":{\"id\":\"1462\"},\"hover_glyph\":null,\"muted_glyph\":null,\"view\":{\"id\":\"1456\"}},\"id\":\"1455\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1439\",\"type\":\"PanTool\"},{\"attributes\":{\"formatter\":{\"id\":\"1512\"},\"ticker\":{\"id\":\"1436\"}},\"id\":\"1435\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis\":{\"id\":\"1435\"},\"dimension\":1,\"ticker\":null},\"id\":\"1438\",\"type\":\"Grid\"},{\"attributes\":{\"graph_layout\":{\"Aegon\":[3.366666353965979,-9.237812087108317],\"Aemon\":[-0.8983311239186754,2.578358425528047],\"Aerys\":[2.3819633585681452,-0.3184754697730903],\"Alliser\":[-0.1079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Arryn\":[0.015396715866975677,-3.2882029339186154],\"Jorah\":[2.4635614898324643,-6.617528989311746],\"Karl\":[-4.143025299671663,8.811538872666992],\"Kevan\":[0.5773717031599852,-2.1510762109957122],\"Kraznys\":[2.5759866157710616,-9.118751598613068],\"Lancel\":[-0.26167268521058,-4.9625032533299285],\"Loras\":[0.09552493087007727,-1.2074221903985802],\"Lothar\":[-3.170565493645482,-0.5594663733711276],\"Luwin\":[-5.292145626783701,3.1427248838165736],\"Lysa\":[-0.505251095466495,-1.5692265377814367],\"Mace\":[3.452306786549256,-0.5707640170723922],\"Mance\":[-1.0725859546143355,5.486880893396424],\"Margaery\":[0.9787629714531395,-1.4248134844498654],\"Marillion\":[-1.3891420653518065,-2.757628028032004],\"Meera\":[-3.245808234686086,4.0093588181640305],\"Melisandre\":[-3.4533308165755847,2.33681418641795],\"Meryn\":[2.250387973873693,0.8096139867031555],\"Missandei\":[4.986814111169188,-7.958988648047092],\"Myrcella\":[1.255624780696211,-1.839228382666609],\"Nan\":[-5.159311682447407,3.7642299202867555],\"Oberyn\":[3.678873148401531,0.1362299045832502],\"Olenna\":[-0.7301313357039082,-2.703109313621338],\"Orell\":[-2.4525577126555547,6.849453405595615],\"Petyr\":[-0.7371201849356998,-0.7172235446503166],\"Podrick\":[1.9787165199020773,-1.2069928206642515],\"Pycelle\":[2.733862679540412,-0.8927783822023734],\"Qhorin\":[-1.6120697221590083,5.990776450468792],\"Qyburn\":[4.250147179455916,0.7551876395361692],\"Rakharo\":[4.932672049885687,-8.590618881502348],\"Ramsay\":[-4.499547617767683,0.11009569724035699],\"Rattleshirt\":[-1.1498413959078684,6.663486717735585],\"Renly\":[0.247059682613968,-0.8106325235841292],\"Rhaegar\":[2.3403840893653816,-4.190395434258183],\"Rickard\":[-3.7357215152001664,0.7254993442535437],\"Rickon\":[-1.1153994107112846,1.8740154784188423],\"Robb\":[-1.453066713491456,0.7595761407466439],\"Robert\":[0.8529922519211353,-0.831235050843262],\"Robert 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of Thrones 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Application\",\"version\":\"2.1.0\"}};\n  var render_items = [{\"docid\":\"2c295554-adde-4f52-ad4f-cea981f9b7f6\",\"root_ids\":[\"1422\"],\"roots\":{\"1422\":\"016275ad-bbf1-451b-9111-bcd7bd5785b6\"}}];\n  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    var attempts = 0;\n    var timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1422"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Choose attributes from G network to size and color by — setting manual size (e.g. 10) or color (e.g. 'skyblue') also allowed\n",
    "size_by_this_attribute = 'adjusted_node_size'\n",
    "color_by_this_attribute = 'modularity_color'\n",
    "#Pick a color palette — Blues8, Reds8, Purples8, Oranges8, Viridis8\n",
    "color_palette = Blues8\n",
    "#Choose a title!\n",
    "title = 'Game of Thrones Network'\n",
    "\n",
    "#Establish which categories will appear when hovering over each node\n",
    "HOVER_TOOLTIPS = [\n",
    "       (\"Character\", \"@index\"),\n",
    "        (\"Degree\", \"@degree\"),\n",
    "         (\"Modularity Class\", \"@modularity_class\"),\n",
    "        (\"Modularity Color\", \"$color[swatch]:modularity_color\"),\n",
    "]\n",
    "\n",
    "#Create a plot — set dimensions, toolbar, and title\n",
    "plot = figure(tooltips = HOVER_TOOLTIPS,\n",
    "              tools=\"pan,wheel_zoom,save,reset, tap\", active_scroll='wheel_zoom',\n",
    "            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)\n",
    "\n",
    "#Create a network graph object\n",
    "# https://networkx.github.io/documentation/networkx-1.9/reference/generated/networkx.drawing.layout.spring_layout.html\n",
    "network_graph = from_networkx(G, networkx.spring_layout, scale=10, center=(0, 0))\n",
    "\n",
    "#Set node sizes and colors according to node degree (color as category from attribute)\n",
    "network_graph.node_renderer.glyph = Circle(size=size_by_this_attribute, fill_color=color_by_this_attribute)\n",
    "\n",
    "#Set edge opacity and width\n",
    "network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.5, line_width=1)\n",
    "\n",
    "plot.renderers.append(network_graph)\n",
    "\n",
    "show(plot)\n",
    "#save(plot, filename=f\"{title}.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network with Responsive Highlighting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below shows how to create responsive highlighting when a user hovers over nodes or edges, which you can read more about in [Bokeh's NetworkX Integration documentation](https://docs.bokeh.org/en/latest/docs/user_guide/graph.html?highlight=networks#interaction-policies). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Include  EdgesAndLinkedNodes, NodesAndLinkedEdges**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save\n",
    "from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine, EdgesAndLinkedNodes, NodesAndLinkedEdges\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import from_networkx\n",
    "from bokeh.palettes import Blues8, Reds8, Purples8, Oranges8, Viridis8, Spectral8\n",
    "from bokeh.transform import linear_cmap\n",
    "from networkx.algorithms import community"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate degree for each node and add as node attribute**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "degrees = dict(networkx.degree(G))\n",
    "networkx.set_node_attributes(G, name='degree', values=degrees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Slightly adjust degree so that the nodes with very small degrees are still visible**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "number_to_adjust_by = 5\n",
    "adjusted_node_size = dict([(node, degree+number_to_adjust_by) for node, degree in networkx.degree(G)])\n",
    "networkx.set_node_attributes(G, name='adjusted_node_size', values=adjusted_node_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate communities**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "communities = community.greedy_modularity_communities(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Add modularity class and color as attributes to network graph**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "# Create empty dictionaries\n",
    "modularity_class = {}\n",
    "modularity_color = {}\n",
    "#Loop through each community in the network\n",
    "for community_number, community in enumerate(communities):\n",
    "    #For each member of the community, add their community number and a distinct color\n",
    "    for name in community: \n",
    "        modularity_class[name] = community_number\n",
    "        modularity_color[name] = Spectral8[community_number]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "# Add modularity class and color as attributes from the network above\n",
    "networkx.set_node_attributes(G, modularity_class, 'modularity_class')\n",
    "networkx.set_node_attributes(G, modularity_color, 'modularity_color')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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Arryn\"],\"start\":[\"Aemon\",\"Aemon\",\"Aemon\",\"Aemon\",\"Aemon\",\"Grenn\",\"Grenn\",\"Grenn\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Samwell\",\"Aerys\",\"Aerys\",\"Aerys\",\"Aerys\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Jaime\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Robert\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tyrion\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Tywin\",\"Alliser\",\"Alliser\",\"Alliser\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Mance\",\"Amory\",\"Oberyn\",\"Oberyn\",\"Oberyn\",\"Oberyn\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Arya\",\"Anguy\",\"Beric\",\"Beric\",\"Beric\",\"Beric\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Bran\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Brynden\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Cersei\",\"Gendry\",\"Gendry\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Gregor\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Joffrey\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Jon\",\"Rickon\",\"Rickon\",\"Rickon\",\"Rickon\",\"Roose\",\"Roose\",\"Roose\",\"Sandor\",\"Sandor\",\"Sandor\",\"Sandor\",\"Sandor\",\"Balon\",\"Balon\",\"Balon\",\"Loras\",\"Loras\",\"Loras\",\"Loras\",\"Loras\",\"Belwas\",\"Belwas\",\"Belwas\",\"Belwas\",\"Barristan\",\"Barristan\",\"Barristan\",\"Hodor\",\"Hodor\",\"Hodor\",\"Jojen\",\"Luwin\",\"Theon\",\"Brienne\",\"Brienne\",\"Brienne\",\"Bronn\",\"Podrick\",\"Podrick\",\"Lothar\",\"Lothar\",\"Lothar\",\"Lothar\",\"Walder\",\"Walder\",\"Walder\",\"Walder\",\"Walder\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Catelyn\",\"Edmure\",\"Edmure\",\"Edmure\",\"Hoster\",\"Jeyne\",\"Lysa\",\"Lysa\",\"Lysa\",\"Lysa\",\"Lysa\",\"Petyr\",\"Petyr\",\"Robb\",\"Robb\",\"Robb\",\"Robb\",\"Robb\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Sansa\",\"Stannis\",\"Stannis\",\"Stannis\",\"Elia\",\"Ilyn\",\"Pycelle\",\"Shae\",\"Shae\",\"Varys\",\"Varys\",\"Craster\",\"Craster\",\"Daario\",\"Daario\",\"Daario\",\"Daario\",\"Drogo\",\"Drogo\",\"Drogo\",\"Irri\",\"Irri\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Daenerys\",\"Jorah\",\"Rhaegar\",\"Davos\",\"Davos\",\"Davos\",\"Davos\",\"Renly\",\"Tommen\",\"Tommen\",\"Janos\",\"Kevan\",\"Dalla\",\"Qhorin\",\"Qhorin\",\"Rattleshirt\",\"Marillion\"]},\"selected\":{\"id\":\"1801\"},\"selection_policy\":{\"id\":\"1802\"}},\"id\":\"1691\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1800\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1671\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1727\",\"type\":\"NodesAndLinkedEdges\"},{\"attributes\":{\"source\":{\"id\":\"1691\"}},\"id\":\"1693\",\"type\":\"CDSView\"},{\"attributes\":{\"end\":10.1,\"start\":-10.1},\"id\":\"1656\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"1664\",\"type\":\"LinearScale\"},{\"attributes\":{\"fill_color\":{\"value\":\"white\"},\"line_width\":{\"value\":2},\"size\":{\"field\":\"adjusted_node_size\",\"units\":\"screen\"}},\"id\":\"1700\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"1667\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis\":{\"id\":\"1666\"},\"ticker\":null},\"id\":\"1669\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1788\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"line_width\":{\"value\":2}},\"id\":\"1720\",\"type\":\"MultiLine\"},{\"attributes\":{},\"id\":\"1790\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"axis\":{\"id\":\"1670\"},\"dimension\":1,\"ticker\":null},\"id\":\"1673\",\"type\":\"Grid\"},{\"attributes\":{\"formatter\":{\"id\":\"1788\"},\"ticker\":{\"id\":\"1671\"}},\"id\":\"1670\",\"type\":\"LinearAxis\"},{\"attributes\":{\"end\":10.1,\"start\":-10.1},\"id\":\"1655\",\"type\":\"Range1d\"},{\"attributes\":{\"line_width\":{\"value\":2}},\"id\":\"1715\",\"type\":\"MultiLine\"},{\"attributes\":{\"graph_layout\":{\"Aegon\":[-9.736578549595755,2.4551524791204815],\"Aemon\":[-0.9641327269341058,1.933880742475836],\"Aerys\":[1.5549341148945812,0.44466866964031454],\"Alliser\":[-2.0728121938872497,3.6181820829886826],\"Amory\":[9.278518551370082,0.4513325616300485],\"Anguy\":[1.4981971796792988,-6.096085830428933],\"Arya\":[1.0550224396316725,-2.297304508155613],\"Balon\":[1.5178921989770446,-0.7999094896826283],\"Barristan\":[-3.4116943041546675,1.0929421901680332],\"Belwas\":[-6.5117965020960655,3.879886089933734],\"Beric\":[1.63413909418989,-4.311752795509046],\"Bowen\":[-2.650314474046977,4.361687052203272],\"Bran\":[-1.610133538627098,-1.7486653090478221],\"Brienne\":[2.1821321699263017,-3.33460400877845],\"Bronn\":[5.462032383600556,-1.4213357991731237],\"Brynden\":[0.482694067589055,-3.925590216253667],\"Catelyn\":[1.048276390299474,-2.905509501375289],\"Cersei\":[2.7016814915897784,-1.2654953716636907],\"Chataya\":[5.151153698939468,2.2297796227924516],\"Craster\":[-4.011558006487563,3.2626381753672966],\"Cressen\":[1.1616085282180681,9.760407427032009],\"Daario\":[-8.12368540242754,3.672329266677181],\"Daenerys\":[-6.498320311805836,1.712562021611107],\"Dalla\":[-0.2795958271145115,4.335079694921948],\"Davos\":[1.4647102736799593,6.570556639727358],\"Doran\":[7.025085784256067,-0.616461558680161],\"Drogo\":[-8.377327653944647,2.9614974527901645],\"Eddard\":[0.43564360888018394,-1.6183285476315752],\"Eddison\":[-3.651256671178694,2.5426144693682717],\"Edmure\":[0.40173588326961446,-4.562510265067255],\"Elia\":[0.6339550504947277,-0.3344850988099604],\"Ellaria\":[6.640864375103008,0.7508188506756995],\"Gendry\":[2.405183362654342,-4.627823537877247],\"Gilly\":[-3.10362566831514,3.5029464120024083],\"Gregor\":[3.4390448690383777,-1.3443600269958604],\"Grenn\":[-2.7385271768301496,2.7315594361721174],\"Hodor\":[-2.936386701472608,-2.364813052076333],\"Hoster\":[2.251180604950789,-5.414515512005032],\"Illyrio\":[-8.585145513406614,6.533126396214826],\"Ilyn\":[4.3837649756159545,-2.195261712030537],\"Irri\":[-9.095230745479473,3.7107397923687655],\"Jaime\":[1.600712351535427,-1.730906820871945],\"Janos\":[-0.4004544436934228,2.626581246293481],\"Jeyne\":[0.14148253812820685,-5.437860191301003],\"Joffrey\":[3.175842143361009,-1.0211092837599236],\"Jojen\":[-3.737032010273222,-0.8672867303665799],\"Jon\":[-1.201863455267384,1.5291083074443357],\"Jon Arryn\":[2.2745608979421044,0.4166306128202194],\"Jorah\":[-6.193312007635978,2.4429045706203967],\"Karl\":[-7.0558510908323795,3.427029794501847],\"Kevan\":[4.658044223539629,0.789664051942429],\"Kraznys\":[-9.719467585771836,1.1550402169297451],\"Lancel\":[7.522864664831109,3.0151186942322776],\"Loras\":[3.277285636710373,-2.0058589418731896],\"Lothar\":[-0.9308802668065704,-4.908407877924546],\"Luwin\":[-4.674531777239774,-3.6362376446227818],\"Lysa\":[3.2649591099926427,-2.744817366495416],\"Mace\":[5.298712791560464,0.764541216563428],\"Mance\":[-1.5906121754219709,3.7019169690925215],\"Margaery\":[4.225770600214854,-0.7759750381784082],\"Marillion\":[5.129091215588785,-4.069009357411789],\"Meera\":[-3.027046050922315,-0.34318016167624565],\"Melisandre\":[0.18279784690791134,3.7455908031507663],\"Meryn\":[3.818833176865053,-2.1678055092382307],\"Missandei\":[-9.718473727151672,3.2906787899952046],\"Myrcella\":[5.054476569377251,-0.7656005017535602],\"Nan\":[-4.252427761796653,-4.211953133273512],\"Oberyn\":[5.692612941689448,-0.1539745329599889],\"Olenna\":[4.614084545175451,-3.8081007107100167],\"Orell\":[-4.629328002126954,1.352998256959741],\"Petyr\":[1.946811079155582,-2.6720151713598295],\"Podrick\":[4.8580889735529595,-1.636617529701165],\"Pycelle\":[4.51102620809468,0.12197013265055609],\"Qhorin\":[-1.8580711444005418,4.229464734269308],\"Qyburn\":[4.132010050722387,-5.060661565165408],\"Rakharo\":[-10.0,1.8187413971154789],\"Ramsay\":[-2.086301954233508,-5.664831151804152],\"Rattleshirt\":[-1.1402424522399197,4.957867679038363],\"Renly\":[2.342668555800091,-0.13019504664310494],\"Rhaegar\":[-3.3965538469224823,0.7011948658080965],\"Rickard\":[-0.4524000722790566,-6.082178447574117],\"Rickon\":[-0.5225092727137945,-2.286023716814553],\"Robb\":[0.23900345959093003,-2.495378868233665],\"Robert\":[-0.23522306809331978,-0.2638251478456975],\"Robert Arryn\":[5.411649413401012,-3.4578300585028754],\"Roose\":[1.0716954970720438,-4.606231675865614],\"Roslin\":[-0.5764747296893034,-5.51488798174124],\"Salladhor\":[2.8260428515790665,9.428354013373582],\"Samwell\":[-2.090269547496069,1.916983599627054],\"Sandor\":[2.301558826491978,-2.3336411894126186],\"Sansa\":[2.3554820758561448,-1.586974449897159],\"Shae\":[3.829441691576815,0.9965566675224344],\"Shireen\":[2.016457275802533,9.741653605962993],\"Stannis\":[0.890303332393286,0.9416570868525894],\"Styr\":[-2.589575487646443,4.981344980165904],\"Theon\":[-1.7610932733643991,-1.1812764077081552],\"Thoros\":[1.092412228992107,-3.422236554329554],\"Tommen\":[4.468276068764826,-1.3020248605776998],\"Tyrion\":[2.9196224083879585,-0.4284550441551017],\"Tywin\":[2.51024496110785,-0.7532643725055251],\"Val\":[0.6389829979896674,2.585224129121012],\"Varys\":[3.8342425564186633,0.510584154248076],\"Viserys\":[-2.1844174690060125,0.5990733442323114],\"Walder\":[0.20164610693733465,-3.640557524809852],\"Walton\":[3.4557561329143454,-5.493564268895024],\"Worm\":[-9.474537271718285,0.4531098042671703],\"Ygritte\":[-1.7379331903223316,5.089595726518109]}},\"id\":\"1694\",\"type\":\"StaticLayoutProvider\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":{\"id\":\"1675\"},\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1674\"},{\"id\":\"1675\"},{\"id\":\"1676\"},{\"id\":\"1677\"},{\"id\":\"1678\"}]},\"id\":\"1679\",\"type\":\"Toolbar\"},{\"attributes\":{\"fill_color\":{\"field\":\"modularity_color\"},\"size\":{\"field\":\"adjusted_node_size\",\"units\":\"screen\"}},\"id\":\"1695\",\"type\":\"Circle\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"Character\",\"@index\"],[\"Degree\",\"@degree\"],[\"Modularity Class\",\"@modularity_class\"],[\"Modularity Color\",\"$color[swatch]:modularity_color\"]]},\"id\":\"1678\",\"type\":\"HoverTool\"},{\"attributes\":{},\"id\":\"1674\",\"type\":\"PanTool\"},{\"attributes\":{\"data_source\":{\"id\":\"1687\"},\"glyph\":{\"id\":\"1695\"},\"hover_glyph\":{\"id\":\"1700\"},\"muted_glyph\":null,\"selection_glyph\":{\"id\":\"1705\"},\"view\":{\"id\":\"1689\"}},\"id\":\"1688\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1675\",\"type\":\"WheelZoomTool\"}],\"root_ids\":[\"1657\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.0\"}};\n  var render_items = [{\"docid\":\"8d0880b8-07db-41a3-8b27-98c567a35576\",\"root_ids\":[\"1657\"],\"roots\":{\"1657\":\"73368388-480e-4389-8064-05f8c079a5cd\"}}];\n  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    var attempts = 0;\n    var timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1657"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.models import EdgesAndLinkedNodes, NodesAndLinkedEdges\n",
    "\n",
    "#Choose colors for node and edge highlighting\n",
    "node_highlight_color = 'white'\n",
    "edge_highlight_color = 'black'\n",
    "\n",
    "#Choose attributes from G network to size and color by — setting manual size (e.g. 10) or color (e.g. 'skyblue') also allowed\n",
    "size_by_this_attribute = 'adjusted_node_size'\n",
    "color_by_this_attribute = 'modularity_color'\n",
    "\n",
    "#Pick a color palette — Blues8, Reds8, Purples8, Oranges8, Viridis8\n",
    "color_palette = Blues8\n",
    "\n",
    "#Choose a title!\n",
    "title = 'Game of Thrones Network'\n",
    "\n",
    "#Establish which categories will appear when hovering over each node\n",
    "HOVER_TOOLTIPS = [\n",
    "       (\"Character\", \"@index\"),\n",
    "        (\"Degree\", \"@degree\"),\n",
    "         (\"Modularity Class\", \"@modularity_class\"),\n",
    "        (\"Modularity Color\", \"$color[swatch]:modularity_color\"),\n",
    "]\n",
    "\n",
    "#Create a plot — set dimensions, toolbar, and title\n",
    "plot = figure(tooltips = HOVER_TOOLTIPS,\n",
    "              tools=\"pan,wheel_zoom,save,reset\", active_scroll='wheel_zoom',\n",
    "            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)\n",
    "\n",
    "#Create a network graph object\n",
    "# https://networkx.github.io/documentation/networkx-1.9/reference/generated/networkx.drawing.layout.spring_layout.html\n",
    "network_graph = from_networkx(G, networkx.spring_layout, scale=10, center=(0, 0))\n",
    "\n",
    "#Set node sizes and colors according to node degree (color as category from attribute)\n",
    "network_graph.node_renderer.glyph = Circle(size=size_by_this_attribute, fill_color=color_by_this_attribute)\n",
    "#Set node highlight colors\n",
    "network_graph.node_renderer.hover_glyph = Circle(size=size_by_this_attribute, fill_color=node_highlight_color, line_width=2)\n",
    "network_graph.node_renderer.selection_glyph = Circle(size=size_by_this_attribute, fill_color=node_highlight_color, line_width=2)\n",
    "\n",
    "#Set edge opacity and width\n",
    "network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.5, line_width=1)\n",
    "#Set edge highlight colors\n",
    "network_graph.edge_renderer.selection_glyph = MultiLine(line_color=edge_highlight_color, line_width=2)\n",
    "network_graph.edge_renderer.hover_glyph = MultiLine(line_color=edge_highlight_color, line_width=2)\n",
    "\n",
    "    #Highlight nodes and edges\n",
    "network_graph.selection_policy = NodesAndLinkedEdges()\n",
    "network_graph.inspection_policy = NodesAndLinkedEdges()\n",
    "\n",
    "plot.renderers.append(network_graph)\n",
    "\n",
    "show(plot)\n",
    "#save(plot, filename=f\"{title}.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network with Labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below shows how to create node labels, which you can read more about in [Bokeh's label documentation](https://docs.bokeh.org/en/latest/docs/user_guide/annotations.html#labels)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Include  LabelSet**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show, save\n",
    "from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine, EdgesAndLinkedNodes, NodesAndLinkedEdges, LabelSet\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.plotting import from_networkx\n",
    "from bokeh.palettes import Blues8, Reds8, Purples8, Oranges8, Viridis8, Spectral8\n",
    "from bokeh.transform import linear_cmap\n",
    "from networkx.algorithms import community"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate degree for each node and add as node attribute**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "degrees = dict(networkx.degree(G))\n",
    "networkx.set_node_attributes(G, name='degree', values=degrees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Slightly adjust degree so that the nodes with very small degrees are still visible**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "number_to_adjust_by = 5\n",
    "adjusted_node_size = dict([(node, degree+number_to_adjust_by) for node, degree in networkx.degree(G)])\n",
    "networkx.set_node_attributes(G, name='adjusted_node_size', values=adjusted_node_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Calculate communities**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "communities = community.greedy_modularity_communities(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Add modularity class and color as attributes to network graph**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "# Create empty dictionaries\n",
    "modularity_class = {}\n",
    "modularity_color = {}\n",
    "#Loop through each community in the network\n",
    "for community_number, community in enumerate(communities):\n",
    "    #For each member of the community, add their community number and a distinct color\n",
    "    for name in community: \n",
    "        modularity_class[name] = community_number\n",
    "        modularity_color[name] = Spectral8[community_number]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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    "#Choose colors for node and edge highlighting\n",
    "node_highlight_color = 'white'\n",
    "edge_highlight_color = 'black'\n",
    "\n",
    "#Choose attributes from G network to size and color by — setting manual size (e.g. 10) or color (e.g. 'skyblue') also allowed\n",
    "size_by_this_attribute = 'adjusted_node_size'\n",
    "color_by_this_attribute = 'modularity_color'\n",
    "\n",
    "#Pick a color palette — Blues8, Reds8, Purples8, Oranges8, Viridis8\n",
    "color_palette = Blues8\n",
    "\n",
    "#Choose a title!\n",
    "title = 'Game of Thrones Network'\n",
    "\n",
    "#Establish which categories will appear when hovering over each node\n",
    "HOVER_TOOLTIPS = [\n",
    "       (\"Character\", \"@index\"),\n",
    "        (\"Degree\", \"@degree\"),\n",
    "         (\"Modularity Class\", \"@modularity_class\"),\n",
    "        (\"Modularity Color\", \"$color[swatch]:modularity_color\"),\n",
    "]\n",
    "\n",
    "#Create a plot — set dimensions, toolbar, and title\n",
    "plot = figure(tooltips = HOVER_TOOLTIPS,\n",
    "              tools=\"pan,wheel_zoom,save,reset\", active_scroll='wheel_zoom',\n",
    "            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)\n",
    "\n",
    "#Create a network graph object\n",
    "# https://networkx.github.io/documentation/networkx-1.9/reference/generated/networkx.drawing.layout.spring_layout.html\n",
    "network_graph = from_networkx(G, networkx.spring_layout, scale=10, center=(0, 0))\n",
    "\n",
    "#Set node sizes and colors according to node degree (color as category from attribute)\n",
    "network_graph.node_renderer.glyph = Circle(size=size_by_this_attribute, fill_color=color_by_this_attribute)\n",
    "#Set node highlight colors\n",
    "network_graph.node_renderer.hover_glyph = Circle(size=size_by_this_attribute, fill_color=node_highlight_color, line_width=2)\n",
    "network_graph.node_renderer.selection_glyph = Circle(size=size_by_this_attribute, fill_color=node_highlight_color, line_width=2)\n",
    "\n",
    "#Set edge opacity and width\n",
    "network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.3, line_width=1)\n",
    "#Set edge highlight colors\n",
    "network_graph.edge_renderer.selection_glyph = MultiLine(line_color=edge_highlight_color, line_width=2)\n",
    "network_graph.edge_renderer.hover_glyph = MultiLine(line_color=edge_highlight_color, line_width=2)\n",
    "\n",
    "#Highlight nodes and edges\n",
    "network_graph.selection_policy = NodesAndLinkedEdges()\n",
    "network_graph.inspection_policy = NodesAndLinkedEdges()\n",
    "\n",
    "plot.renderers.append(network_graph)\n",
    "\n",
    "#Add Labels\n",
    "x, y = zip(*network_graph.layout_provider.graph_layout.values())\n",
    "node_labels = list(G.nodes())\n",
    "source = ColumnDataSource({'x': x, 'y': y, 'name': [node_labels[i] for i in range(len(x))]})\n",
    "labels = LabelSet(x='x', y='y', text='name', source=source, background_fill_color='white', text_font_size='10px', background_fill_alpha=.7)\n",
    "plot.renderers.append(labels)\n",
    "\n",
    "show(plot)\n",
    "#save(plot, filename=f\"{title}.html\")"
   ]
  }
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