bokeh_avocado.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "[![CraigDoesData][logo]][link]\n",
    "\n",
    "[logo]: https://www.craigdoesdata.de/img/logo/logo.png\n",
    "[link]: https://www.craigdoesdata.de/\n",
    "\n",
    "\n",
    "# Using Bokeh to create an interactive visualisation of avocado prices\n",
    "Data visualisation project mapping price data for avocados onto a map of the USA.\n",
    "\n",
    "![Static Image of the Resulting Viz](./img/bokehmap_sm.jpeg)\n",
    "\n",
    "There is an accompanying [article]((https://towardsdatascience.com/creating-an-interactive-map-in-python-using-bokeh-and-pandas-f84414536a06)) on [Towards Data Science](https://towardsdatascience.com/) to walk you through this visualisation [here](https://towardsdatascience.com/creating-an-interactive-map-in-python-using-bokeh-and-pandas-f84414536a06).\n",
    "\n",
    "This is a follow-up to this [article](https://towardsdatascience.com/mapping-avocado-prices-in-python-with-geopandas-geopy-and-matplotlib-c7e0ef08bc26) on [Towards Data Science](https://towardsdatascience.com/mapping-avocado-prices-in-python-with-geopandas-geopy-and-matplotlib-c7e0ef08bc26), the code and data for which are stored in [this repository](https://github.com/thecraigd/Avocado-Prices). \n",
    "\n",
    "My objective here was to produce an interactive version of the [static visualisation](https://github.com/thecraigd/Avocado-Prices/blob/master/img/Avocado_Prices_Display.jpg) I produced previously. I used [Bokeh](https://docs.bokeh.org/en/latest/index.html) to do that, and produced [this visualisation](http://www.craigdoesdata.de/blog/avocadobokeh.html) using the code presented here.\n",
    "\n",
    "#### Project status - Complete\n",
    "\n",
    "## Introduction\n",
    "This project was intended to allow me to experiment with using Bokeh to produce interactive maps which can be embedded in HTML pages. I was able to do that [successfully](http://www.craigdoesdata.de/blog/avocadobokeh.html).\n",
    "\n",
    "### Methods used\n",
    "* Co-ordinate transformation\n",
    "* Data visualisation\n",
    "* Geographical mapping\n",
    "\n",
    "### Technologies used\n",
    "* Jupyter Notebook\n",
    "* pandas\n",
    "* Bokeh\n",
    "* Numpy\n",
    "\n",
    "\n",
    "### Data Sources\n",
    "\n",
    "Original avocado price data sourced from [Kaggle](https://www.kaggle.com/neuromusic/avocado-prices) - stored [here](https://github.com/thecraigd/Avocado-Prices/blob/master/data/avocado.csv).\n",
    "\n",
    "The data used in this Notebook has already been [extensively manipulated](https://towardsdatascience.com/mapping-avocado-prices-in-python-with-geopandas-geopy-and-matplotlib-c7e0ef08bc26) so that it is ready for our visualisation. We are using the final version of the DataFrame from [that project](https://github.com/thecraigd/Avocado-Prices), exported as a [CSV file](https://github.com/thecraigd/Avocado-Prices/blob/master/data/avocado_df.csv) and available in the [original repository](https://github.com/thecraigd/Avocado-Prices/blob/master/data/avocado_df.csv) as well as [this repository](https://github.com/thecraigd/BokehAvocado/blob/master/data/avocado_df.csv).\n",
    "\n",
    "\n",
    "---------------------\n",
    "\n",
    "\n",
    "## Table of Contents\n",
    "\n",
    "#### 1. Import Data and Libraries\n",
    "* 1.1 Import libraries\n",
    "* 1.2 Import CSV file to pandas DataFrame\n",
    "* 1.3 Create Coordinate Transform Function\n",
    "* 1.4 Add Mercator Coordinates to DataFrame\n",
    "\n",
    "#### 2. Create Visualisation with Bokeh\n",
    "* 2.1 Create Visualisation\n",
    "\n",
    "#### 3. Conclusion\n",
    "* 3.1 Conclusion\n",
    "\n",
    "--------------------\n",
    "\n",
    "##### 1.1 - Import Libraries\n",
    "\n",
    "As noted in the [article accompanying this notebook](https://towardsdatascience.com/creating-an-interactive-map-in-python-using-bokeh-and-pandas-f84414536a06), Bokeh is a little unusual among python libraries, as it is not imported in one package (like pandas or NumPy, for example), but instead the relevant functions or sub-packages are imported individually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from bokeh.io import output_notebook, show, output_file\n",
    "from bokeh.plotting import figure, ColumnDataSource\n",
    "from bokeh.tile_providers import get_provider, Vendors\n",
    "from bokeh.palettes import PRGn, RdYlGn\n",
    "from bokeh.transform import linear_cmap,factor_cmap\n",
    "from bokeh.layouts import row, column\n",
    "from bokeh.models import GeoJSONDataSource, LinearColorMapper, ColorBar, NumeralTickFormatter\n",
    "\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.2 - Import CSV file to pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>region</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Albany</td>\n",
       "      <td>1.561036</td>\n",
       "      <td>47537.86973</td>\n",
       "      <td>42.651550</td>\n",
       "      <td>-73.755211</td>\n",
       "      <td>POINT (-73.75521087646484 42.65155029296875)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Atlanta</td>\n",
       "      <td>1.337959</td>\n",
       "      <td>262145.32200</td>\n",
       "      <td>33.748310</td>\n",
       "      <td>-84.391113</td>\n",
       "      <td>POINT (-84.39111328125 33.74831008911133)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BaltimoreWashington</td>\n",
       "      <td>1.534231</td>\n",
       "      <td>398561.89150</td>\n",
       "      <td>39.183739</td>\n",
       "      <td>-76.674210</td>\n",
       "      <td>POINT (-76.67420959472656 39.18373870849609)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Boise</td>\n",
       "      <td>1.348136</td>\n",
       "      <td>42642.56731</td>\n",
       "      <td>43.607639</td>\n",
       "      <td>-116.193398</td>\n",
       "      <td>POINT (-116.1933975219727 43.60763931274414)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Boston</td>\n",
       "      <td>1.530888</td>\n",
       "      <td>287792.85450</td>\n",
       "      <td>42.358662</td>\n",
       "      <td>-71.056740</td>\n",
       "      <td>POINT (-71.05673980712891 42.35866165161133)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                region  AveragePrice  Total Volume   latitude   longitude  \\\n",
       "0               Albany      1.561036   47537.86973  42.651550  -73.755211   \n",
       "1              Atlanta      1.337959  262145.32200  33.748310  -84.391113   \n",
       "2  BaltimoreWashington      1.534231  398561.89150  39.183739  -76.674210   \n",
       "3                Boise      1.348136   42642.56731  43.607639 -116.193398   \n",
       "4               Boston      1.530888  287792.85450  42.358662  -71.056740   \n",
       "\n",
       "                                       geometry  \n",
       "0  POINT (-73.75521087646484 42.65155029296875)  \n",
       "1     POINT (-84.39111328125 33.74831008911133)  \n",
       "2  POINT (-76.67420959472656 39.18373870849609)  \n",
       "3  POINT (-116.1933975219727 43.60763931274414)  \n",
       "4  POINT (-71.05673980712891 42.35866165161133)  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv('./data/avocado_df.csv', index_col=0)\n",
    "\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.3 - Create Coordinate Transform Function\n",
    "\n",
    "For this particular visualisation, we will need to convert our latitudes and longitudes into Mercator coordinates. To do this we will use a function ('borrowed' from my friend [Nadine Amersi-Belton](https://github.com/nadinezab/kc-house-prices-prediction)) to perform this transformation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Define function to switch from lat/long to mercator coordinates\n",
    "def x_coord(x, y):\n",
    "    \n",
    "    lat = x\n",
    "    lon = y\n",
    "    \n",
    "    r_major = 6378137.000\n",
    "    x = r_major * np.radians(lon)\n",
    "    scale = x/lon\n",
    "    y = 180.0/np.pi * np.log(np.tan(np.pi/4.0 + \n",
    "        lat * (np.pi/180.0)/2.0)) * scale\n",
    "    return (x, y)\n",
    "\n",
    "# Define coord as tuple (lat,long)\n",
    "df['coordinates'] = list(zip(df['latitude'], df['longitude']))\n",
    "\n",
    "\n",
    "# Obtain list of mercator coordinates\n",
    "mercators = [x_coord(x, y) for x, y in df['coordinates'] ]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.4 - Add Mercator Coordinates to DataFrame\n",
    "\n",
    "Now we will add those coordinates to our DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>region</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>mercator</th>\n",
       "      <th>mercator_x</th>\n",
       "      <th>mercator_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Albany</td>\n",
       "      <td>1.561036</td>\n",
       "      <td>47537.86973</td>\n",
       "      <td>42.651550</td>\n",
       "      <td>-73.755211</td>\n",
       "      <td>(42.65155029, -73.75521088)</td>\n",
       "      <td>(-8210392.518512112, 5259083.750058974)</td>\n",
       "      <td>-8.210393e+06</td>\n",
       "      <td>5.259084e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Atlanta</td>\n",
       "      <td>1.337959</td>\n",
       "      <td>262145.32200</td>\n",
       "      <td>33.748310</td>\n",
       "      <td>-84.391113</td>\n",
       "      <td>(33.74831009, -84.39111328)</td>\n",
       "      <td>(-9394375.757807067, 3995056.081948725)</td>\n",
       "      <td>-9.394376e+06</td>\n",
       "      <td>3.995056e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BaltimoreWashington</td>\n",
       "      <td>1.534231</td>\n",
       "      <td>398561.89150</td>\n",
       "      <td>39.183739</td>\n",
       "      <td>-76.674210</td>\n",
       "      <td>(39.18373871, -76.67420959)</td>\n",
       "      <td>(-8535333.968535533, 4748024.844048325)</td>\n",
       "      <td>-8.535334e+06</td>\n",
       "      <td>4.748025e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Boise</td>\n",
       "      <td>1.348136</td>\n",
       "      <td>42642.56731</td>\n",
       "      <td>43.607639</td>\n",
       "      <td>-116.193398</td>\n",
       "      <td>(43.60763931, -116.1933975)</td>\n",
       "      <td>(-12934589.843240427, 5404922.878631644)</td>\n",
       "      <td>-1.293459e+07</td>\n",
       "      <td>5.404923e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Boston</td>\n",
       "      <td>1.530888</td>\n",
       "      <td>287792.85450</td>\n",
       "      <td>42.358662</td>\n",
       "      <td>-71.056740</td>\n",
       "      <td>(42.35866165, -71.05673981)</td>\n",
       "      <td>(-7910000.093079331, 5214857.553783183)</td>\n",
       "      <td>-7.910000e+06</td>\n",
       "      <td>5.214858e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                region  AveragePrice  Total Volume   latitude   longitude  \\\n",
       "0               Albany      1.561036   47537.86973  42.651550  -73.755211   \n",
       "1              Atlanta      1.337959  262145.32200  33.748310  -84.391113   \n",
       "2  BaltimoreWashington      1.534231  398561.89150  39.183739  -76.674210   \n",
       "3                Boise      1.348136   42642.56731  43.607639 -116.193398   \n",
       "4               Boston      1.530888  287792.85450  42.358662  -71.056740   \n",
       "\n",
       "                   coordinates                                  mercator  \\\n",
       "0  (42.65155029, -73.75521088)   (-8210392.518512112, 5259083.750058974)   \n",
       "1  (33.74831009, -84.39111328)   (-9394375.757807067, 3995056.081948725)   \n",
       "2  (39.18373871, -76.67420959)   (-8535333.968535533, 4748024.844048325)   \n",
       "3  (43.60763931, -116.1933975)  (-12934589.843240427, 5404922.878631644)   \n",
       "4  (42.35866165, -71.05673981)   (-7910000.093079331, 5214857.553783183)   \n",
       "\n",
       "     mercator_x    mercator_y  \n",
       "0 -8.210393e+06  5.259084e+06  \n",
       "1 -9.394376e+06  3.995056e+06  \n",
       "2 -8.535334e+06  4.748025e+06  \n",
       "3 -1.293459e+07  5.404923e+06  \n",
       "4 -7.910000e+06  5.214858e+06  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create mercator column in our df\n",
    "df['mercator'] = mercators\n",
    "\n",
    "# Split that column out into two separate cols - mercator_x and mercator_y\n",
    "df[['mercator_x', 'mercator_y']] = df['mercator'].apply(pd.Series)\n",
    "\n",
    "# Drop 'geometry' column \n",
    "df = df.drop(columns=['geometry'])\n",
    "\n",
    "# Examine our modified DataFrame\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Create Visualisation with Bokeh\n",
    "\n",
    "##### 2.1 - Create Visualisation\n",
    "\n",
    "The steps are described with comments below. Full explanations of each step can be found in the [associated article](https://towardsdatascience.com/creating-an-interactive-map-in-python-using-bokeh-and-pandas-f84414536a06).\n",
    "\n",
    "This creates a [.html file](./output/avocado.html) which we can embed in dashboards or on [web pages](https://www.craigdoesdata.de/blog/avocadobokeh.html) as we please. The use of the 'show' function at the end also allows the visualisation to be displayed within our notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1252\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1252\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };var element = document.getElementById(\"1252\");\n",
       "  if (element == null) {\n",
       "    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1252' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n",
       "  var css_urls = [];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1252\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1252\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };var element = document.getElementById(\"1252\");\n  if (element == null) {\n    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1252' but no matching script tag was found. \")\n    return false;\n  }\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n  var css_urls = [];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1252\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"941d2c79-afb6-4882-b598-50b67f97dc0c\" data-root-id=\"1198\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = {\"8914b5ed-2cf2-4926-9dce-5c87abc11cc2\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1209\",\"type\":\"MercatorAxis\"}],\"center\":[{\"id\":\"1217\",\"type\":\"Grid\"},{\"id\":\"1226\",\"type\":\"Grid\"}],\"left\":[{\"id\":\"1218\",\"type\":\"MercatorAxis\"}],\"renderers\":[{\"id\":\"1242\",\"type\":\"TileRenderer\"},{\"id\":\"1247\",\"type\":\"GlyphRenderer\"}],\"right\":[{\"id\":\"1250\",\"type\":\"ColorBar\"}],\"title\":{\"id\":\"1199\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1234\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"1201\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"1205\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1203\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"1207\",\"type\":\"LinearScale\"}},\"id\":\"1198\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"callback\":null,\"data\":{\"AveragePrice\":{\"__ndarray__\":\"g3oUXQD6+D+mCohBR2j1P27zFZA1jPg/fFBpJ/eR9T+r7AL4g374PzybXRD0RPg/XBvUxUBT9j88mZlIUrL5P0Ervg6N6Pg/60/0VuNY8z+dkXMoZAv0P9F0UGuVXvE/fw5Mnk1/8z+SmPs/4mr0PxSuR+F6FPg/fToKT2k2+D+I0H1DJRn9P7MpXDFRxPA/zPXZqB4G9T/3FMF+1iz4P5T2ipc8GPY/rh7UnsJ08z8w2hh4RJb0P+1MQ4IZ2/Y/xqIhl8Nk8z/lINSEbuD0PzvRzJgkpPs/vp+/dWqj9z9P6VHSchn4P84xlYg0Hfo/dCT6KUyX8z+jJVy2QNT1PwiIOo1jFfU/8IOJxcPh+D/rtLwSS6n0P+Zcj2SE9/M/TqghVvHx+T9o1d/54l72P3E7Rg8C3vw/rA7Xb8gU9z+6ROHy2XP2P5RqecckIfc/pdCQKdPj9j9cG9TFQFP4P/VnyEOiivY/bv2b5+0v9D8=\",\"dtype\":\"float64\",\"shape\":[46]},\"Total 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\"__ndarray__\":\"bU0vIfZRX8Gb9D/4GOthwTs+/r6kR2DBWdP7ureraMEDA/UFnCxewQwias10v2DBivK4ONZlacFBteAO9ylhwfD7iOlHm2LBZvAujj3xYcGstHrvoZ9hwU5u4u9RjWTBo5lzRd1KZsGnZOOVF6JhwROVxb+3MGLBWG+9X/NSYMEYO5j+mAhjwZ2FGQ/XP2TBDjDFQbNKYsEZSLkYcVZhwQ+iX951cmjBn5paJUAbacGaPKWm3TViwVNwthRCBWHBqpQEk9hsYsHhiIIsMiBjwU0O3FBZbV/BsiM6YAj5XcEnq50sSUdhwWWRudjp6l/By31vmOfLZ8GJsXDbRfxgwV3MoJAPDGrBnl1pfKSyYMEG7QKX7HBgwYdM3OYv+WDBMxxoeqnLacHZuPzFWeBowTsSMH4l/mnB2O6Piz75acEofxej/yxhwbshJV347WjBiZg4KtEmY8F+5nznAStgwefFbHIXgmHBms2Mt4uHZsE=\",\"dtype\":\"float64\",\"shape\":[46]},\"mercator_y\":{\"__ndarray__\":\"W/cA8NIPVEG7S30K2HpOQUTjBDa+HFJBOIA7uD6eVEEFL3FjouRTQaC10L91MlRBLVLmF9kRUUEHcNYN0P9PQeXQWx8an1NBme9pGQESUkHqj/IWgYpSQejqELKXfk1Bc4Z1MBJrUkHuZLdwquBTQSiR+Hl7PlRBcyBJL9i0UkFGH4JnvXNSQYRO/c7VfkpBxKVv/N9uUkG111xrOg5LQUCiTRT0flBBxJDxUsnKTkErMOYHUptRQaLWNHMAr0ZB0TNDGmd+UEG40m/XP69KQSh0+iXW9VJBzs4SIejlVEGMeoi3hU5JQbFoL2UeiVJBjeK98oQsTkGEYAvnU85SQXDjT+jNwFVB7LHXNwpLUEGZGGY97ThRQcEu0TcXFFFBlMwE+lnIUUH2O3rTbG5NQSk19PRkWVFBCBTLm5ALV0Hd6OWnjaNOQaRZrd85FFdBzg6RWhLPUUE5k7tQ+EpUQRetIgV9vEhBiub4RIYrT0E=\",\"dtype\":\"float64\",\"shape\":[46]},\"region\":[\"Albany\",\"Atlanta\",\"BaltimoreWashington\",\"Boise\",\"Boston\",\"BuffaloRochester\",\"California\",\"Charlotte\",\"Chicago\",\"CincinnatiDayton\",\"Columbus\",\"DallasFtWorth\",\"Denver\",\"Detroit\",\"GrandRapids\",\"HarrisburgScranton\",\"HartfordSpringfield\",\"Houston\",\"Indianapolis\",\"Jacksonville\",\"LasVegas\",\"LosAngeles\",\"Louisville\",\"MiamiFtLauderdale\",\"Nashville\",\"NewOrleansMobile\",\"NewYork\",\"NorthernNewEngland\",\"Orlando\",\"Philadelphia\",\"PhoenixTucson\",\"Pittsburgh\",\"Portland\",\"RaleighGreensboro\",\"RichmondNorfolk\",\"Roanoke\",\"Sacramento\",\"SanDiego\",\"SanFrancisco\",\"Seattle\",\"SouthCarolina\",\"Spokane\",\"StLouis\",\"Syracuse\",\"Tampa\",\"WestTexNewMexico\"]},\"selected\":{\"id\":\"1270\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1269\",\"type\":\"UnionRenderers\"}},\"id\":\"1196\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"Price\",\"@AveragePrice\"],[\"Region\",\"@region\"]]},\"id\":\"1233\",\"type\":\"HoverTool\"},{\"attributes\":{\"source\":{\"id\":\"1196\",\"type\":\"ColumnDataSource\"}},\"id\":\"1248\",\"type\":\"CDSView\"},{\"attributes\":{\"dimension\":\"lat\"},\"id\":\"1221\",\"type\":\"MercatorTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"size\":{\"units\":\"screen\",\"value\":30},\"x\":{\"field\":\"mercator_x\"},\"y\":{\"field\":\"mercator_y\"}},\"id\":\"1246\",\"type\":\"Circle\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1219\",\"type\":\"MercatorTicker\"}},\"id\":\"1226\",\"type\":\"Grid\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1227\",\"type\":\"PanTool\"},{\"id\":\"1228\",\"type\":\"WheelZoomTool\"},{\"id\":\"1229\",\"type\":\"BoxZoomTool\"},{\"id\":\"1230\",\"type\":\"SaveTool\"},{\"id\":\"1231\",\"type\":\"ResetTool\"},{\"id\":\"1232\",\"type\":\"HelpTool\"},{\"id\":\"1233\",\"type\":\"HoverTool\"}]},\"id\":\"1234\",\"type\":\"Toolbar\"},{\"attributes\":{\"tile_source\":{\"id\":\"1195\",\"type\":\"WMTSTileSource\"}},\"id\":\"1242\",\"type\":\"TileRenderer\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1268\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"dimension\":\"lon\"},\"id\":\"1212\",\"type\":\"MercatorTickFormatter\"},{\"attributes\":{\"ticker\":{\"id\":\"1210\",\"type\":\"MercatorTicker\"}},\"id\":\"1217\",\"type\":\"Grid\"},{\"attributes\":{\"color_mapper\":{\"id\":\"1197\",\"type\":\"LinearColorMapper\"},\"formatter\":{\"id\":\"1249\",\"type\":\"NumeralTickFormatter\"},\"label_standoff\":13,\"location\":[0,0],\"ticker\":{\"id\":\"1263\",\"type\":\"BasicTicker\"},\"width\":8},\"id\":\"1250\",\"type\":\"ColorBar\"},{\"attributes\":{},\"id\":\"1227\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1263\",\"type\":\"BasicTicker\"},{\"attributes\":{\"attribution\":\"Map tiles by <a href=\\\"https://stamen.com\\\">Stamen Design</a>, under <a href=\\\"https://creativecommons.org/licenses/by/3.0\\\">CC BY 3.0</a>. Data by <a href=\\\"https://openstreetmap.org\\\">OpenStreetMap</a>, under <a href=\\\"https://www.openstreetmap.org/copyright\\\">ODbL</a>.\",\"url\":\"http://tile.stamen.com/toner/{Z}/{X}/{Y}.png\"},\"id\":\"1195\",\"type\":\"WMTSTileSource\"},{\"attributes\":{},\"id\":\"1207\",\"type\":\"LinearScale\"},{\"attributes\":{\"callback\":null},\"id\":\"1201\",\"type\":\"DataRange1d\"},{\"attributes\":{\"callback\":null},\"id\":\"1203\",\"type\":\"DataRange1d\"},{\"attributes\":{\"dimension\":\"lat\"},\"id\":\"1219\",\"type\":\"MercatorTicker\"},{\"attributes\":{},\"id\":\"1228\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1269\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"overlay\":{\"id\":\"1268\",\"type\":\"BoxAnnotation\"}},\"id\":\"1229\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1270\",\"type\":\"Selection\"},{\"attributes\":{\"format\":\"0.0[0000]\"},\"id\":\"1249\",\"type\":\"NumeralTickFormatter\"},{\"attributes\":{},\"id\":\"1230\",\"type\":\"SaveTool\"},{\"attributes\":{\"data_source\":{\"id\":\"1196\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1245\",\"type\":\"Circle\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1246\",\"type\":\"Circle\"},\"selection_glyph\":null,\"view\":{\"id\":\"1248\",\"type\":\"CDSView\"}},\"id\":\"1247\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"text\":\"Avocado Prices by region in the United States\"},\"id\":\"1199\",\"type\":\"Title\"},{\"attributes\":{\"high\":1.818639053,\"low\":1.047928994,\"palette\":[\"#00441b\",\"#1b7837\",\"#5aae61\",\"#a6dba0\",\"#d9f0d3\",\"#f7f7f7\",\"#e7d4e8\",\"#c2a5cf\",\"#9970ab\",\"#762a83\",\"#40004b\"]},\"id\":\"1197\",\"type\":\"LinearColorMapper\"},{\"attributes\":{},\"id\":\"1231\",\"type\":\"ResetTool\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.7},\"fill_color\":{\"field\":\"AveragePrice\",\"transform\":{\"id\":\"1197\",\"type\":\"LinearColorMapper\"}},\"line_color\":{\"field\":\"AveragePrice\",\"transform\":{\"id\":\"1197\",\"type\":\"LinearColorMapper\"}},\"size\":{\"units\":\"screen\",\"value\":30},\"x\":{\"field\":\"mercator_x\"},\"y\":{\"field\":\"mercator_y\"}},\"id\":\"1245\",\"type\":\"Circle\"},{\"attributes\":{\"axis_label\":\"Longitude\",\"formatter\":{\"id\":\"1212\",\"type\":\"MercatorTickFormatter\"},\"ticker\":{\"id\":\"1210\",\"type\":\"MercatorTicker\"}},\"id\":\"1209\",\"type\":\"MercatorAxis\"},{\"attributes\":{},\"id\":\"1205\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1232\",\"type\":\"HelpTool\"},{\"attributes\":{\"dimension\":\"lon\"},\"id\":\"1210\",\"type\":\"MercatorTicker\"},{\"attributes\":{\"axis_label\":\"Latitude\",\"formatter\":{\"id\":\"1221\",\"type\":\"MercatorTickFormatter\"},\"ticker\":{\"id\":\"1219\",\"type\":\"MercatorTicker\"}},\"id\":\"1218\",\"type\":\"MercatorAxis\"}],\"root_ids\":[\"1198\"]},\"title\":\"Bokeh Application\",\"version\":\"1.3.4\"}};\n",
       "  var render_items = [{\"docid\":\"8914b5ed-2cf2-4926-9dce-5c87abc11cc2\",\"roots\":{\"1198\":\"941d2c79-afb6-4882-b598-50b67f97dc0c\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1198"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create map with Bokeh\n",
    "\n",
    "# Select tile set to use\n",
    "chosentile = get_provider(Vendors.STAMEN_TONER)\n",
    "\n",
    "# Choose palette\n",
    "palette = PRGn[11]\n",
    "\n",
    "# Tell Bokeh to use df as the source of the data\n",
    "source = ColumnDataSource(data=df)\n",
    "\n",
    "# Define color mapper - which column will define the colour of the data points\n",
    "color_mapper = linear_cmap(field_name = 'AveragePrice', palette = palette, low = df['AveragePrice'].min(), high = df['AveragePrice'].max())\n",
    "\n",
    "# Set tooltips - these appear when we hover over a data point in our map, very nifty and very useful\n",
    "nan_color = '#d9d9d9'\n",
    "tooltips = [(\"Price\",\"@AveragePrice\"), (\"Region\",\"@region\")]\n",
    "\n",
    "\n",
    "# Create figure\n",
    "p = figure(title = 'Avocado Prices by region in the United States', x_axis_type=\"mercator\", y_axis_type=\"mercator\", \n",
    "           x_axis_label = 'Longitude', y_axis_label = 'Latitude', tooltips = tooltips)\n",
    "\n",
    "# Add map tile\n",
    "p.add_tile(chosentile)\n",
    "\n",
    "# Add points using mercator coordinates\n",
    "p.circle(x = 'mercator_x', y = 'mercator_y', color = color_mapper, source=source, size=30, fill_alpha = 0.7)\n",
    "\n",
    "#Defines color bar\n",
    "color_bar = ColorBar(color_mapper=color_mapper['transform'], \n",
    "                     formatter = NumeralTickFormatter(format='0.0[0000]'), \n",
    "                     label_standoff = 13, width=8, location=(0,0))\n",
    "\n",
    "# Set color_bar location\n",
    "p.add_layout(color_bar, 'right')\n",
    "\n",
    "# Display in notebook\n",
    "output_notebook()\n",
    "\n",
    "# Save as HTML\n",
    "output_file('./output/avocado.html', title='Avocado Prices by region in the United States')\n",
    "\n",
    "# Show map\n",
    "show(p)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---------------------\n",
    "\n",
    "### 3. Conclusion\n",
    "##### 3.1 - Conclusion\n",
    "\n",
    "Now we have produced a working interactive map using Bokeh, which we can embed in our choice of online delivery system for our users / stakeholders. They are then free to examine the visualisation as they choose. \n",
    "\n"
   ]
  }
 ],
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