Added gallery entries for Chord

holoviz · Jan 29, 2018 · b259ef3 · b259ef3
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diff --git a/examples/gallery/demos/bokeh/route_chord.ipynb b/examples/gallery/demos/bokeh/route_chord.ipynb
@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most examples work across multiple plotting backends equivalent, this example is also available for:\n",
+    "\n",
+    "* [Matplotlib - route_chord](../matplotlib/route_chord.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import holoviews as hv\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": [
+    "# Count the routes between Airports\n",
+    "route_counts = routes.groupby(['SourceID', 'DestinationID']).Stops.count().reset_index()\n",
+    "nodes = hv.Dataset(airports, 'AirportID', 'City')\n",
+    "chord = hv.Chord((route_counts, nodes), ['SourceID', 'DestinationID'], ['Stops'])\n",
+    "\n",
+    "# Select the 20 busiest airports\n",
+    "busiest = list(routes.groupby('SourceID').count().sort_values('Stops').iloc[-20:].index.values)\n",
+    "busiest_airports = chord.select(AirportID=busiest, selection_mode='nodes')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%opts Chord [edge_color_index='SourceID' label_index='City' color_index='AirportID' width=800 height=800]\n",
+    "%%opts Chord (cmap='Category20' edge_cmap='Category20')\n",
+    "busiest_airports"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/gallery/demos/matplotlib/route_chord.ipynb b/examples/gallery/demos/matplotlib/route_chord.ipynb
@@ -0,0 +1,90 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most examples work across multiple plotting backends equivalent, this example is also available for:\n",
+    "\n",
+    "* [Bokeh - route_chord](../bokeh/route_chord.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import holoviews as hv\n",
+    "from bokeh.sampledata.airport_routes import routes, airports\n",
+    "\n",
+    "hv.extension('matplotlib')\n",
+    "%output fig='svg' size=300"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Declare data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Count the routes between Airports\n",
+    "route_counts = routes.groupby(['SourceID', 'DestinationID']).Stops.count().reset_index()\n",
+    "nodes = hv.Dataset(airports, 'AirportID', 'City')\n",
+    "chord = hv.Chord((route_counts, nodes), ['SourceID', 'DestinationID'], ['Stops'])\n",
+    "\n",
+    "# Select the 20 busiest airports\n",
+    "busiest = list(routes.groupby('SourceID').count().sort_values('Stops').iloc[-20:].index.values)\n",
+    "busiest_airports = chord.select(AirportID=busiest, selection_mode='nodes')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%opts Chord [edge_color_index='SourceID' label_index='City' color_index='AirportID' width=800 height=800]\n",
+    "%%opts Chord (cmap='Category20' edge_cmap='Category20')\n",
+    "busiest_airports"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}