diff --git a/examples/gallery/demos/matplotlib/nyc_airport_connections.ipynb b/examples/gallery/demos/matplotlib/nyc_airport_connections.ipynb
index 8cb2dd811f..03277c0489 100644
--- a/examples/gallery/demos/matplotlib/nyc_airport_connections.ipynb
+++ b/examples/gallery/demos/matplotlib/nyc_airport_connections.ipynb
@@ -53,8 +53,6 @@
     "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",
-    "nyc_labels = \n",
-    "other_labels = "
    ]
   },
   {
diff --git a/examples/gallery/demos/matplotlib/nyc_taxi_connections.ipynb b/examples/gallery/demos/matplotlib/nyc_taxi_connections.ipynb
deleted file mode 100644
index 8dba44db9a..0000000000
--- a/examples/gallery/demos/matplotlib/nyc_taxi_connections.ipynb
+++ /dev/null
@@ -1,108 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Most examples work across multiple plotting backends, this example is also available for:\n",
-    "\n",
-    "* [Bokeh NYC Taxi Connection](../bokeh/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 dim\n",
-    "\n",
-    "from holoviews.element.graphs import layout_nodes\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": [
-    "# 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').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",
-    "nyc_labels = labels.select(City='New York')\n",
-    "other_labels = labels[labels['City']!='New York']"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Plot"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cmap={3697: 'red', 3797: 'blue'}\n",
-    "\n",
-    "plot = (\n",
-    "    graph.options(\n",
-    "        bgcolor='gray', edge_color=dim('SourceID').categorize(cmap, 'gray'), node_color=dim('index').categorize(cmap, 'gray'),\n",
-    "        xaxis=None, yaxis=None, xlim=(-1.2, 1.2), ylim=(-1.2, 1.2)\n",
-    "     ) *\n",
-    "     nyc_labels.options(color='white', yoffset=0.05, size=16) *\n",
-    "     other_labels.options(color='white', size=8)\n",
-    ")\n",
-    "\n",
-    "plot.relabel('NYC Airport Connections')"
-   ]
-  }
- ],
- "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": "3.6.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/examples/reference/elements/matplotlib/HLine.ipynb b/examples/reference/elements/matplotlib/HLine.ipynb
index ef7b40b2f1..8eba1348ad 100644
--- a/examples/reference/elements/matplotlib/HLine.ipynb
+++ b/examples/reference/elements/matplotlib/HLine.ipynb
@@ -44,8 +44,8 @@
     "points = hv.Points((xs,ys))\n",
     "\n",
     "(points * hv.HLine(ys.mean())).opts(\n",
-    "    opts.HLine(color='#D3D3D3')\n",
-    "    opts.Points(color='blue', linewidth=6))"
+    "    opts.HLine(color='blue', linewidth=6),\n",
+    "    opts.Points(color='#D3D3D3'))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Spline.ipynb b/examples/reference/elements/matplotlib/Spline.ipynb
index 14e5d003da..ebe6aac911 100644
--- a/examples/reference/elements/matplotlib/Spline.ipynb
+++ b/examples/reference/elements/matplotlib/Spline.ipynb
@@ -42,7 +42,7 @@
     "spline = hv.Spline((points, [1,4,4,4]))\n",
     "\n",
     "(spline * hv.Curve(points)).opts(\n",
-    "    opts.Curve(color='#D3D3D3')\n",
+    "    opts.Curve(color='#D3D3D3'),\n",
     "    opts.Spline(linewidth=6, edgecolor='green'))"
    ]
   },
diff --git a/examples/reference/elements/matplotlib/VLine.ipynb b/examples/reference/elements/matplotlib/VLine.ipynb
index a464e1e07c..bfd357da8c 100644
--- a/examples/reference/elements/matplotlib/VLine.ipynb
+++ b/examples/reference/elements/matplotlib/VLine.ipynb
@@ -45,7 +45,7 @@
     "\n",
     "(hv.Curve((xs,ys)) * vline).opts(\n",
     "    opts.Curve(color='#D3D3D3'),\n",
-    "    opts.Vline(color='red', linewidth=6)"
+    "    opts.VLine(color='red', linewidth=6))"
    ]
   },
   {
diff --git a/holoviews/plotting/plotly/renderer.py b/holoviews/plotting/plotly/renderer.py
index e98f80aad5..52f9964e5b 100644
--- a/holoviews/plotting/plotly/renderer.py
+++ b/holoviews/plotting/plotly/renderer.py
@@ -56,7 +56,7 @@ def __call__(self, obj, fmt='html', divuuid=None):
         if isinstance(plot, tuple(self.widgets.values())):
             return plot(), mime_types
         elif fmt in ('html', 'png', 'svg'):
-            return self._figure_data(plot, divuuid=divuuid), mime_types
+            return self._figure_data(plot, fmt, divuuid=divuuid), mime_types
         elif fmt == 'json':
             return self.diff(plot), mime_types