{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Header 1\n",
    "\n",
    " * Bullet 1\n",
    " * Bullet 2\n",
    " * **Bold-Bullet**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets\n",
    "import traitlets\n",
    "import pandas as pd\n",
    "import bqplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "buildings = pd.read_csv(\"/home/shared/sp18-is590dv/data/IL_Building_Inventory.csv\",\n",
    "                        na_values = {\n",
    "                            'Year Acquired': 0,\n",
    "                            'Year Constructed': 0\n",
    "                        })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_sc = bqplot.LinearScale()\n",
    "y_sc = bqplot.LinearScale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_ax = bqplot.Axis(scale = x_sc, label = 'Year Constructed')\n",
    "y_ax = bqplot.Axis(scale = y_sc, label = 'Year Acquired',\n",
    "                   orientation = 'vertical')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scatter = bqplot.Scatter(x = buildings['Year Constructed'],\n",
    "                         y = buildings['Year Acquired'],\n",
    "                        scales = {\n",
    "                            'x': x_sc,\n",
    "                            'y': y_sc\n",
    "                        }, sizes = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = bqplot.Figure(marks = [scatter],\n",
    "                    axes = [x_ax, y_ax],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53aa89a6dd8d4445815532f060926c80",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Figure</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Figure(axes=[Axis(label='Year Constructed', scale=LinearScale()), Axis(label='Year Acquired', orientation='vertical', scale=LinearScale())], fig_margin={'top': 60, 'bottom': 60, 'left': 60, 'right': 60}, layout=Layout(min_width='125px'), marks=[Scatter(colors=['steelblue'], interactions={'hover': 'tooltip'}, scales={'x': LinearScale(), 'y': LinearScale()}, scales_metadata={'x': {'orientation': 'horizontal', 'dimension': 'x'}, 'y': {'orientation': 'vertical', 'dimension': 'y'}, 'color': {'dimension': 'color'}, 'size': {'dimension': 'size'}, 'opacity': {'dimension': 'opacity'}, 'rotation': {'dimension': 'rotation'}, 'skew': {'dimension': 'skew'}}, tooltip_style={'opacity': 0.9}, x=array([1975., 2004., 2004., ..., 1987., 1971., 2017.]), y=array([1975., 2004., 2004., ...,   nan, 1971.,   nan]))], scale_x=LinearScale(allow_padding=False, max=1.0, min=0.0), scale_y=LinearScale(allow_padding=False, max=1.0, min=0.0))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "pz = bqplot.PanZoom(scales = {'x': [x_sc], 'y': [y_sc]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.interaction = pz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(None, None)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_sc.min, x_sc.max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "tooltip = bqplot.Tooltip(fields = [\"x\"])\n",
    "\n",
    "scatter = bqplot.Scatter(x = buildings['Year Constructed'],\n",
    "                         y = buildings['Year Acquired'],\n",
    "                        scales = {\n",
    "                            'x': x_sc,\n",
    "                            'y': y_sc\n",
    "                        }, sizes = 0.5,\n",
    "                        tooltip = tooltip,\n",
    "\n",
    "                         interactions = {'click': ''})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_selector = bqplot.interacts.LassoSelector(\n",
    "                    marks = [scatter]\n",
    ")\n",
    "fig = bqplot.Figure(marks = [scatter],\n",
    "                    axes = [x_ax, y_ax],\n",
    "                    interaction = lasso_selector\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16d1952daab348ae8a6979c43e5b96c9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Figure</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Figure(axes=[Axis(label='Year Constructed', scale=LinearScale()), Axis(label='Year Acquired', orientation='vertical', scale=LinearScale())], fig_margin={'top': 60, 'bottom': 60, 'left': 60, 'right': 60}, interaction=LassoSelector(marks=[Scatter(colors=['steelblue'], interactions={'click': ''}, scales={'x': LinearScale(), 'y': LinearScale()}, scales_metadata={'x': {'orientation': 'horizontal', 'dimension': 'x'}, 'y': {'orientation': 'vertical', 'dimension': 'y'}, 'color': {'dimension': 'color'}, 'size': {'dimension': 'size'}, 'opacity': {'dimension': 'opacity'}, 'rotation': {'dimension': 'rotation'}, 'skew': {'dimension': 'skew'}}, tooltip=Tooltip(fields=['x']), tooltip_style={'opacity': 0.9}, x=array([1975., 2004., 2004., ..., 1987., 1971., 2017.]), y=array([1975., 2004., 2004., ...,   nan, 1971.,   nan]))]), layout=Layout(min_width='125px'), marks=[Scatter(colors=['steelblue'], interactions={'click': ''}, scales={'x': LinearScale(), 'y': LinearScale()}, scales_metadata={'x': {'orientation': 'horizontal', 'dimension': 'x'}, 'y': {'orientation': 'vertical', 'dimension': 'y'}, 'color': {'dimension': 'color'}, 'size': {'dimension': 'size'}, 'opacity': {'dimension': 'opacity'}, 'rotation': {'dimension': 'rotation'}, 'skew': {'dimension': 'skew'}}, tooltip=Tooltip(fields=['x']), tooltip_style={'opacity': 0.9}, x=array([1975., 2004., 2004., ..., 1987., 1971., 2017.]), y=array([1975., 2004., 2004., ...,   nan, 1971.,   nan]))], scale_x=LinearScale(allow_padding=False, max=1.0, min=0.0), scale_y=LinearScale(allow_padding=False, max=1.0, min=0.0))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "TypeError",
     "evalue": "'NoneType' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/ipywidgets/widgets/widget.py\u001b[0m in \u001b[0;36m_handle_msg\u001b[0;34m(self, msg)\u001b[0m\n\u001b[1;32m    665\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;34m'buffer_paths'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    666\u001b[0m                     \u001b[0m_put_buffers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'buffer_paths'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'buffers'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 667\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_state\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    668\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    669\u001b[0m         \u001b[0;31m# Handle a state request.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/ipywidgets/widgets/widget.py\u001b[0m in \u001b[0;36mset_state\u001b[0;34m(self, sync_data)\u001b[0m\n\u001b[1;32m    535\u001b[0m                     from_json = self.trait_metadata(name, 'from_json',\n\u001b[1;32m    536\u001b[0m                                                     self._trait_from_json)\n\u001b[0;32m--> 537\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_trait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfrom_json\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msync_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    538\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    539\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/contextlib.py\u001b[0m in \u001b[0;36m__exit__\u001b[0;34m(self, type, value, traceback)\u001b[0m\n\u001b[1;32m     86\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 88\u001b[0;31m                 \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     89\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/traitlets/traitlets.py\u001b[0m in \u001b[0;36mhold_trait_notifications\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1129\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mchanges\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1130\u001b[0m                     \u001b[0;32mfor\u001b[0m \u001b[0mchange\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mchanges\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1131\u001b[0;31m                         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnotify_change\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchange\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1133\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_notify_trait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mold_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/ipywidgets/widgets/widget.py\u001b[0m in \u001b[0;36mnotify_change\u001b[0;34m(self, change)\u001b[0m\n\u001b[1;32m    596\u001b[0m                 \u001b[0;31m# Send new state to front-end\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    597\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_state\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 598\u001b[0;31m         \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mWidget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnotify_change\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchange\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    599\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    600\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__repr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/traitlets/traitlets.py\u001b[0m in \u001b[0;36mnotify_change\u001b[0;34m(self, change)\u001b[0m\n\u001b[1;32m   1174\u001b[0m                 \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1175\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1176\u001b[0;31m             \u001b[0mc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchange\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1177\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1178\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_add_notifiers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-18-625ad9e2f010>\u001b[0m in \u001b[0;36mupdate_histogram\u001b[0;34m(event)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mupdate_histogram\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0mindices\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mlasso\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mevent\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'new'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m         \u001b[0mindices\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlasso\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'indices'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mindices\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindices\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object is not iterable"
     ]
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b122ecdf82c54ab888b9d48f132f6bff",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Figure</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Figure(axes=[Axis(scale=LinearScale()), Axis(orientation='vertical', scale=LinearScale())], fig_margin={'top': 60, 'bottom': 60, 'left': 60, 'right': 60}, layout=Layout(min_width='125px'), marks=[Hist(colors=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'], interactions={'hover': 'tooltip'}, opacities=[0.1], sample=array([  144,   144,   144, ...,   130, 49552,   288]), scales={'sample': LinearScale(), 'count': LinearScale()}, scales_metadata={'sample': {'orientation': 'horizontal', 'dimension': 'x'}, 'count': {'orientation': 'vertical', 'dimension': 'y'}}, tooltip_style={'opacity': 0.9}), Hist(colors=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'], interactions={'hover': 'tooltip'}, sample=array([  144,   144,   144, ...,   130, 49552,   288]), scales={'sample': LinearScale(), 'count': LinearScale()}, scales_metadata={'sample': {'orientation': 'horizontal', 'dimension': 'x'}, 'count': {'orientation': 'vertical', 'dimension': 'y'}}, tooltip_style={'opacity': 0.9})], scale_x=LinearScale(allow_padding=False, max=1.0, min=0.0), scale_y=LinearScale(allow_padding=False, max=1.0, min=0.0))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_sc2 = bqplot.LinearScale()\n",
    "y_sc2 = bqplot.LinearScale()\n",
    "x_ax2 = bqplot.Axis(scale = x_sc2)\n",
    "y_ax2 = bqplot.Axis(scale = y_sc2, orientation='vertical')\n",
    "\n",
    "hist = bqplot.Hist(sample=buildings[\"Square Footage\"],\n",
    "                   scales = {'sample': x_sc2,\n",
    "                             'count': y_sc2},\n",
    "                   select_bars = True,\n",
    "                   opacities = [0.1],\n",
    "                  )\n",
    "\n",
    "hist2 = bqplot.Hist(sample = buildings[\"Square Footage\"],\n",
    "                   scales = {'sample': x_sc2,\n",
    "                            'count': y_sc2})\n",
    "\n",
    "fig2 = bqplot.Figure(marks = [hist, hist2], axes = [x_ax2, y_ax2])\n",
    "fig2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "selector = bqplot.interacts.LassoSelector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist.selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_histogram(event):\n",
    "    indices = []\n",
    "    for lasso in event['new']:\n",
    "        indices.append(lasso['indices'])\n",
    "    indices = np.concatenate(indices)\n",
    "    ind = np.unique(indices)\n",
    "    hist2.sample = buildings[\"Square Footage\"].iloc[ind]\n",
    "\n",
    "scatter.unobserve(\"selected\")    \n",
    "scatter.observe(update_histogram, \"selected\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "scatter = bqplot.Scatter(x = buildings['Year Constructed'],\n",
    "                         y = buildings['Year Acquired'],\n",
    "                        scales = {\n",
    "                            'x': x_sc,\n",
    "                            'y': y_sc\n",
    "                        })\n",
    "brush = bqplot.interacts.BrushSelector(marks = [scatter],\n",
    "                                       x_scale = x_sc,\n",
    "                                       y_scale = y_sc,\n",
    "                                       color = 'red')\n",
    "fig = bqplot.Figure(marks = [scatter],\n",
    "                    axes = [x_ax, y_ax],\n",
    "                    interaction = brush\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "62ec10ecbcfe4d6bb0f6ec140bc93fa1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Figure</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Figure(axes=[Axis(label='Year Constructed', scale=LinearScale(), side='bottom'), Axis(label='Year Acquired', orientation='vertical', scale=LinearScale(), side='left')], fig_margin={'top': 60, 'bottom': 60, 'left': 60, 'right': 60}, interaction=BrushSelector(color='red', marks=[Scatter(colors=['steelblue'], interactions={'hover': 'tooltip'}, scales={'x': LinearScale(), 'y': LinearScale()}, scales_metadata={'x': {'orientation': 'horizontal', 'dimension': 'x'}, 'y': {'orientation': 'vertical', 'dimension': 'y'}, 'color': {'dimension': 'color'}, 'size': {'dimension': 'size'}, 'opacity': {'dimension': 'opacity'}, 'rotation': {'dimension': 'rotation'}, 'skew': {'dimension': 'skew'}}, tooltip_style={'opacity': 0.9}, x=array([1975., 2004., 2004., ..., 1987., 1971., 2017.]), y=array([1975., 2004., 2004., ...,   nan, 1971.,   nan]))], x_scale=LinearScale(), y_scale=LinearScale()), layout=Layout(min_width='125px'), marks=[Scatter(colors=['steelblue'], interactions={'hover': 'tooltip'}, scales={'x': LinearScale(), 'y': LinearScale()}, scales_metadata={'x': {'orientation': 'horizontal', 'dimension': 'x'}, 'y': {'orientation': 'vertical', 'dimension': 'y'}, 'color': {'dimension': 'color'}, 'size': {'dimension': 'size'}, 'opacity': {'dimension': 'opacity'}, 'rotation': {'dimension': 'rotation'}, 'skew': {'dimension': 'skew'}}, tooltip_style={'opacity': 0.9}, x=array([1975., 2004., 2004., ..., 1987., 1971., 2017.]), y=array([1975., 2004., 2004., ...,   nan, 1971.,   nan]))], scale_x=LinearScale(allow_padding=False, max=1.0, min=0.0), scale_y=LinearScale(allow_padding=False, max=1.0, min=0.0))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'_display_callbacks': <traitlets.traitlets.Instance at 0x7ff3189b45c0>,\n",
       " '_model_module': <traitlets.traitlets.Unicode at 0x7ff2bd2ae550>,\n",
       " '_model_module_version': <traitlets.traitlets.Unicode at 0x7ff2bd2bb080>,\n",
       " '_model_name': <traitlets.traitlets.Unicode at 0x7ff2bd2bba58>,\n",
       " '_msg_callbacks': <traitlets.traitlets.Instance at 0x7ff3189b45f8>,\n",
       " '_property_lock': <traitlets.traitlets.Dict at 0x7ff3189d47f0>,\n",
       " '_states_to_send': <traitlets.traitlets.Set at 0x7ff3189d4828>,\n",
       " '_view_count': <traitlets.traitlets.Int at 0x7ff3189d46d8>,\n",
       " '_view_module': <traitlets.traitlets.Unicode at 0x7ff2bd2ae438>,\n",
       " '_view_module_version': <traitlets.traitlets.Unicode at 0x7ff2bd2bb048>,\n",
       " '_view_name': <traitlets.traitlets.Unicode at 0x7ff2bd2bba20>,\n",
       " 'brushing': <traitlets.traitlets.Bool at 0x7ff2bd2bb978>,\n",
       " 'clear': <traitlets.traitlets.Bool at 0x7ff2bd2bb940>,\n",
       " 'color': <ipywidgets.widgets.trait_types.Color at 0x7ff2bd2bb9e8>,\n",
       " 'comm': <traitlets.traitlets.Instance at 0x7ff3189d4710>,\n",
       " 'keys': <traitlets.traitlets.List at 0x7ff3189d4748>,\n",
       " 'log': <traitlets.traitlets.Instance at 0x7ff3189d42e8>,\n",
       " 'marks': <traitlets.traitlets.List at 0x7ff2bd2bb470>,\n",
       " 'selected': <traitlets.traitlets.List at 0x7ff2bd2bb9b0>,\n",
       " 'x_scale': <traitlets.traitlets.Instance at 0x7ff2bd2bb550>,\n",
       " 'y_scale': <traitlets.traitlets.Instance at 0x7ff2bd2bb588>}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brush.traits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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