Holoviews Bokeh crossfilter example

holoview_crossfilter_example.ipynb

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   "source": [
    "import os\n",
    "import urllib\n",
    "\n",
    "import holoviews as hv\n",
    "\n",
    "from bokeh.resources import INLINE\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.layouts import row, widgetbox\n",
    "from bokeh.models import Select\n",
    "from bokeh.plotting import curdoc\n",
    "from bokeh.sampledata.autompg import autompg\n",
    "from bokeh.io import show\n",
    "\n",
    "\n",
    "output_notebook(INLINE, hide_banner=True)\n",
    "\n",
    "\n",
    "def jupyter_proxy_url(notebook_url, port):\n",
    "    base_url = os.environ['EXTERNAL_URL']\n",
    "    service_url_path = os.environ['JUPYTERHUB_SERVICE_PREFIX']\n",
    "    proxy_url_path = 'proxy/%d' % port\n",
    "    user_url = urllib.parse.urljoin(base_url, service_url_path)\n",
    "    full_url = urllib.parse.urljoin(user_url, proxy_url_path)\n",
    "    return full_url\n",
    "\n",
    "\n",
    "def crossfilter(doc):\n",
    "    df = autompg.copy()\n",
    "\n",
    "    SIZES = list(range(6, 22, 3))\n",
    "    ORIGINS = ['North America', 'Europe', 'Asia']\n",
    "\n",
    "    # data cleanup\n",
    "    df.cyl = [str(x) for x in df.cyl]\n",
    "    df.origin = [ORIGINS[x-1] for x in df.origin]\n",
    "\n",
    "    df['year'] = [str(x) for x in df.yr]\n",
    "    del df['yr']\n",
    "\n",
    "    df['mfr'] = [x.split()[0] for x in df.name]\n",
    "    df.loc[df.mfr=='chevy', 'mfr'] = 'chevrolet'\n",
    "    df.loc[df.mfr=='chevroelt', 'mfr'] = 'chevrolet'\n",
    "    df.loc[df.mfr=='maxda', 'mfr'] = 'mazda'\n",
    "    df.loc[df.mfr=='mercedes-benz', 'mfr'] = 'mercedes'\n",
    "    df.loc[df.mfr=='toyouta', 'mfr'] = 'toyota'\n",
    "    df.loc[df.mfr=='vokswagen', 'mfr'] = 'volkswagen'\n",
    "    df.loc[df.mfr=='vw', 'mfr'] = 'volkswagen'\n",
    "    del df['name']\n",
    "\n",
    "    columns = sorted(df.columns)\n",
    "    discrete = [x for x in columns if df[x].dtype == object]\n",
    "    continuous = [x for x in columns if x not in discrete]\n",
    "    quantileable = [x for x in continuous if len(df[x].unique()) > 20]\n",
    "\n",
    "    renderer = hv.renderer('bokeh')\n",
    "    options = hv.Store.options(backend='bokeh')\n",
    "    options.Points = hv.Options('plot', width=800, height=600, size_index=None,)\n",
    "    options.Points = hv.Options('style', cmap='rainbow', line_color='black')\n",
    "\n",
    "    def create_figure():\n",
    "        label = \"%s vs %s\" % (x.value.title(), y.value.title())\n",
    "        kdims = [x.value, y.value]\n",
    "\n",
    "        opts, style = {}, {}\n",
    "        opts['color_index'] = color.value if color.value != 'None' else None\n",
    "        if size.value != 'None':\n",
    "            opts['size_index'] = size.value\n",
    "            opts['scaling_factor'] = (1./df[size.value].max())*200\n",
    "        points = hv.Points(df, kdims=kdims, label=label).opts(plot=opts, style=style)\n",
    "        return renderer.get_plot(points).state\n",
    "\n",
    "    def update(attr, old, new):\n",
    "        layout.children[1] = create_figure()\n",
    "\n",
    "    x = Select(title='X-Axis', value='mpg', options=quantileable)\n",
    "    x.on_change('value', update)\n",
    "\n",
    "    y = Select(title='Y-Axis', value='hp', options=quantileable)\n",
    "    y.on_change('value', update)\n",
    "\n",
    "    size = Select(title='Size', value='None', options=['None'] + quantileable)\n",
    "    size.on_change('value', update)\n",
    "\n",
    "    color = Select(title='Color', value='None', options=['None'] + quantileable)\n",
    "    color.on_change('value', update)\n",
    "\n",
    "    controls = widgetbox([x, y, color, size], width=200)\n",
    "    layout = row(controls, create_figure())\n",
    "\n",
    "    doc.add_root(layout)\n",
    "    doc.title = \"Crossfilter\"\n",
    "  \n",
    "show(crossfilter, proxy_url_func=jupyter_proxy_url)"
   ]
  }
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