examples/gallery/demos/bokeh/nyc_airport_connections.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most examples work across multiple plotting backends, this example is also available for:\n",
    "\n",
    "* [Matplotlib NYC Taxi Connection](../matplotlib/nyc_taxi_connections.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import networkx as nx\n",
    "import holoviews as hv\n",
    "from holoviews import opts\n",
    "from holoviews import dim\n",
    "\n",
    "from holoviews.element.graphs import layout_nodes\n",
    "from bokeh.sampledata.airport_routes import routes, airports\n",
    "\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Declare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create dataset indexed by AirportID and with additional value dimension\n",
    "airports = hv.Dataset(airports, ['AirportID'], ['Name', 'IATA', 'City'])\n",
    "source_airports = list(airports.select(City='New York').data.AirportID)\n",
    "\n",
    "# Add connections count to routes then aggregate and select just routes connecting to NYC\n",
    "routes['connections'] = 1\n",
    "nyc_graph = hv.Graph((routes, airports), ['SourceID', \"DestinationID\"], ['connections'], label='NYC Airport Connections')\\\n",
    "    .aggregate(function=np.count_nonzero).select(SourceID=source_airports)\n",
    "\n",
    "# Lay out graph weighting and weight by the number of connections\n",
    "np.random.seed(14)\n",
    "graph = layout_nodes(nyc_graph, layout=nx.layout.fruchterman_reingold_layout, kwargs={'weight': 'connections'})\n",
    "labels = hv.Labels(graph.nodes, ['x', 'y'], ['IATA', 'City'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_labels = labels.select(City='New York').opts(\n",
    "    text_color='white', yoffset=0.05, text_font_size='16pt')\n",
    "\n",
    "other_labels = labels[labels['City']!='New York'].opts(\n",
    "    text_color='white', text_font_size='8pt')\n",
    "\n",
    "cmap = {3697: 'red', 3797: 'blue'}\n",
    "\n",
    "(graph * nyc_labels * other_labels).opts(\n",
    "    opts.Graph(bgcolor='gray', width=800, height=800,\n",
    "               edge_color=dim('SourceID').categorize(cmap, 'gray'),\n",
    "               node_color=dim('index').categorize(cmap, 'gray'),\n",
    "               title='NYC Airport Connections',\n",
    "               xaxis=None, yaxis=None)\n",
    ")"
   ]
  }
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