Updated Spread, Table, Text, VectorField and VLine

examples/elements/bokeh/Spread.ipynb

@@ -32,6 +32,9 @@
    "source": [
     "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or assymetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Columnar Data tutorial](Columnar_Data.ipynb) for examples. \n",
     "\n",
+    "Note that as the ``Spread`` element is used to add information to a plot (typically a ``Curve``) the default alpha value is less that one, making it partially transparent. \n",
+    "\n",
+    "\n",
     "##### Symmetric"
    ]
   },

examples/elements/bokeh/Table.ipynb

@@ -83,7 +83,7 @@
    "outputs": [],
    "source": [
     "%%opts Table [height=140]\n",
-    "hv.Table((gender, age, weight, height), kdims = ['Gender', 'Age'],  vdims=['Weight', 'Height'])"
+    "table = hv.Table((gender, age, weight, height), kdims = ['Gender', 'Age'],  vdims=['Weight', 'Height'])"
    ]
   },
   {
@@ -133,9 +133,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:science]",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "conda-env-science-py"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {

examples/elements/matplotlib/Spread.ipynb

@@ -23,14 +23,16 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
-    "hv.notebook_extension('bokeh')"
+    "hv.notebook_extension()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or assymetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Columnar Data tutorial](Columnar_Data.ipynb) for examples. \n",
+    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or assymetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Columnar Data tutorial](Columnar_Data.ipynb) for examples.\n",
+    "\n",
+    "Note that as the ``Spread`` element is used to add information to a plot (typically a ``Curve``) the default alpha value is less that one, making it partially transparent. \n",
     "\n",
     "##### Symmetric"
    ]
@@ -78,7 +80,7 @@
    },
    "outputs": [],
    "source": [
-    "%%opts Spread (fill_color='indianred' fill_alpha=1)\n",
+    "%%opts Spread (facecolor='indianred' alpha=1)\n",
     "xs = np.linspace(0, np.pi*2, 20)\n",
     "hv.Spread((xs, np.sin(xs), 0.1+np.random.rand(len(xs)), 0.1+np.random.rand(len(xs))),\n",
     "          vdims=['y', 'yerrneg', 'yerrpos'])"

examples/elements/matplotlib/Table.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
-    "hv.notebook_extension('bokeh')"
+    "hv.notebook_extension()"
    ]
   },
   {
@@ -62,7 +62,6 @@
    },
    "outputs": [],
    "source": [
-    "%%opts Table [height=140]\n",
     "hv.Table({'Gender':gender, 'Age':age, 'Weight':weight, 'Height':height},\n",
     "         kdims = ['Gender', 'Age'],  vdims=['Weight', 'Height'])"
    ]
@@ -82,8 +81,8 @@
    },
    "outputs": [],
    "source": [
-    "%%opts Table [height=140]\n",
-    "hv.Table((gender, age, weight, height), kdims = ['Gender', 'Age'],  vdims=['Weight', 'Height'])"
+    "table = hv.Table((gender, age, weight, height), kdims = ['Gender', 'Age'],  vdims=['Weight', 'Height'])\n",
+    "table"
    ]
   },
   {
@@ -101,7 +100,6 @@
    },
    "outputs": [],
    "source": [
-    "%%opts Table [height=100]\n",
     "table.select(Gender='M') + table.select(Gender='M', Age=10)"
    ]
   },
@@ -133,9 +131,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:science]",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "conda-env-science-py"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {

examples/elements/matplotlib/Text.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
-    "hv.notebook_extension('bokeh')"
+    "hv.notebook_extension()"
    ]
   },
   {

examples/elements/matplotlib/VLine.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
-    "hv.notebook_extension('bokeh')"
+    "hv.notebook_extension()"
    ]
   },
   {
@@ -41,7 +41,7 @@
    },
    "outputs": [],
    "source": [
-    "%%opts VLine (color='red' line_width=6) Curve (color='#D3D3D3')\n",
+    "%%opts VLine (color='red' linewidth=6) Curve (color='#D3D3D3')\n",
     "xs = np.linspace(-5,5,100)\n",
     "ys = -(xs-2)**2\n",
     "hv.Curve((xs,ys)) * hv.VLine(xs[ys.argmax()])"

examples/elements/matplotlib/VectorField.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
-    "hv.notebook_extension('bokeh')"
+    "hv.notebook_extension()"
    ]
   },
   {
@@ -67,9 +67,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:science]",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "conda-env-science-py"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {