Bokeh.ipynb

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.io import output_notebook, push_notebook\n",
    "from bokeh.models import ColumnDataSource, CustomJS, DataRange1d, LinearAxis, Range1d\n",
    "from bokeh.models.widgets import DataTable, TableColumn\n",
    "\n",
    "from ipywidgets import interact\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "ix = pd.date_range('2016-01-01', '2017-01-01', freq='d', name='date')\n",
    "srs = pd.Series(np.random.randint(0, 300, size=len(ix)), index=ix, name='volume')\n",
    "srs2 = pd.Series(np.random.randint(0, 1000, size=len(ix)), index=ix, name='size')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_data(freq='MS'):\n",
    "    return pd.DataFrame(srs.groupby(pd.Grouper(freq=freq)).sum())\n",
    "\n",
    "def get_data2(freq='MS'):\n",
    "    return pd.DataFrame(srs2.groupby(pd.Grouper(freq=freq)).sum())\n",
    "\n",
    "def get_data3(freq='MS'):\n",
    "    return pd.DataFrame(srs2.groupby(pd.Grouper(freq=freq)).mean())\n",
    "\n",
    "source = ColumnDataSource(data=ColumnDataSource.from_df(get_data()))\n",
    "source2 = ColumnDataSource(data=ColumnDataSource.from_df(get_data2()))\n",
    "\n",
    "def get_width():\n",
    "    mindate = min(source.data['date'])\n",
    "    maxdate = max(source.data['date'])\n",
    "    return 0.8 * (maxdate-mindate).total_seconds() * 1000 / len(source.data['date'])\n",
    "\n",
    "f = figure(plot_width=550, plot_height=400, x_axis_type=\"datetime\", y_range=Range1d(0, max(source.data['volume']), bounds='auto'))\n",
    "f.x_range.bounds='auto'\n",
    "\n",
    "f.extra_y_ranges = {\n",
    "    \"size\": Range1d(bounds='auto', start=0, end=max(source2.data['size'])),\n",
    "}\n",
    "\n",
    "f.add_layout(LinearAxis(y_range_name='size'), 'right')\n",
    "r = f.vbar(source=source, top='volume', x='date', width=get_width())\n",
    "f.line(source=source2, x='date', y='size', color='red', y_range_name='size')\n",
    "f.tools[2].dimensions = 'width'\n",
    "\n",
    "handle = show(f, notebook_handle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "source3 = ColumnDataSource(data=ColumnDataSource.from_df(get_data2()))\n",
    "columns = [\n",
    "    TableColumn(field='date'),\n",
    "    TableColumn(field='size')\n",
    "]\n",
    "\n",
    "t = DataTable(source=source3, columns=columns)\n",
    "t_handle = show(t, notebook_handle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def update_data(freq={'Quarter': 'QS', 'Month': 'MS', 'Week': 'W'}):\n",
    "    source.data = ColumnDataSource.from_df(get_data(freq))\n",
    "    source2.data = ColumnDataSource.from_df(get_data2(freq))\n",
    "    r.glyph.width = get_width()\n",
    "    f.y_range.end = max(source.data['volume'])\n",
    "    f.extra_y_ranges['size'].end = max(source2.data['size'])\n",
    "\n",
    "    source3.data = ColumnDataSource.from_df(get_data3(freq))\n",
    "    push_notebook(handle=handle)\n",
    "    push_notebook(handle=t_handle)\n",
    "    \n",
    "i = interact(update_data)"
   ]
  }
 ],
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