Map.ipynb

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   "source": [
    "import geojson\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "\n",
    "df_geo = gpd.read_file(\"data/us.geojson\")\n",
    "df_suicides = pd.read_csv(\"data/Suicides - Monthly.csv\")\n",
    "\n",
    "df_geo[\"Suicides by gun\"] = df_geo['name'].apply(lambda x: df_suicides.loc[df_suicides['State'] == x]['Suicides with guns'].sum())"
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>density</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Suicides by gun</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>94.650</td>\n",
       "      <td>POLYGON ((-87.359 35.001, -85.607 34.985, -85....</td>\n",
       "      <td>435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>1.264</td>\n",
       "      <td>MULTIPOLYGON (((-131.602 55.118, -131.569 55.2...</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>57.050</td>\n",
       "      <td>POLYGON ((-109.043 37.000, -109.048 31.332, -1...</td>\n",
       "      <td>476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>05</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>56.430</td>\n",
       "      <td>POLYGON ((-94.474 36.502, -90.153 36.496, -90....</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06</td>\n",
       "      <td>California</td>\n",
       "      <td>241.700</td>\n",
       "      <td>POLYGON ((-123.233 42.006, -122.379 42.012, -1...</td>\n",
       "      <td>1532</td>\n",
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      "text/plain": [
       "   id        name  density                                           geometry  \\\n",
       "0  01     Alabama   94.650  POLYGON ((-87.359 35.001, -85.607 34.985, -85....   \n",
       "1  02      Alaska    1.264  MULTIPOLYGON (((-131.602 55.118, -131.569 55.2...   \n",
       "2  04     Arizona   57.050  POLYGON ((-109.043 37.000, -109.048 31.332, -1...   \n",
       "3  05    Arkansas   56.430  POLYGON ((-94.474 36.502, -90.153 36.496, -90....   \n",
       "4  06  California  241.700  POLYGON ((-123.233 42.006, -122.379 42.012, -1...   \n",
       "\n",
       "   Suicides by gun  \n",
       "0              435  \n",
       "1               55  \n",
       "2              476  \n",
       "3              234  \n",
       "4             1532  "
      ]
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    "df_geo.head()"
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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(\"4585\");\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(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\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    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\": \"XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\": \"bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\": \"TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH\"};\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\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  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\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(\"4585\")).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));"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "BokehDeprecationWarning: 'WidgetBox' is deprecated and will be removed in Bokeh 3.0, use 'bokeh.models.Column' instead\n"
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44.333886], [-92.233773, 44.443425], [-92.337835, 44.552964], [-92.545959, 44.569394], [-92.808852, 44.750133], [-92.737652, 45.117088], [-92.75956, 45.286874], [-92.644544, 45.440228], [-92.770513, 45.566198], [-92.885529, 45.577151], [-92.869098, 45.719552], [-92.639067, 45.933153], [-92.354266, 46.015307], [-92.29402, 46.075553], [-92.29402, 46.667063], [-92.091373, 46.749217], [-92.014696, 46.705401], [-91.790141, 46.694447], [-91.09457, 46.864232], [-90.837154, 46.95734], [-90.749522, 46.88614], [-90.886446, 46.754694], [-90.55783, 46.584908], [-90.415429, 46.568478]]]}}, {\\\"id\\\": \\\"50\\\", \\\"type\\\": \\\"Feature\\\", \\\"properties\\\": {\\\"Suicides by gun\\\": 63, \\\"density\\\": 5.851, \\\"id\\\": \\\"56\\\", \\\"name\\\": \\\"Wyoming\\\"}, \\\"geometry\\\": {\\\"type\\\": \\\"Polygon\\\", \\\"coordinates\\\": [[[-109.080842, 45.002073], [-105.91517, 45.002073], [-104.058488, 44.996596], [-104.053011, 43.002989], [-104.053011, 41.003906], [-105.728954, 40.998429], [-107.919731, 41.003906], [-109.04798, 40.998429], [-111.047063, 40.998429], [-111.047063, 42.000709], [-111.047063, 44.476286], [-111.05254, 45.002073], [-109.080842, 45.002073]]]}}, {\\\"id\\\": \\\"51\\\", \\\"type\\\": \\\"Feature\\\", \\\"properties\\\": {\\\"Suicides by gun\\\": 0, \\\"density\\\": 1082.0, \\\"id\\\": \\\"72\\\", \\\"name\\\": \\\"Puerto Rico\\\"}, \\\"geometry\\\": {\\\"type\\\": \\\"Polygon\\\", \\\"coordinates\\\": [[[-66.448338, 17.984326], [-66.771478, 18.006234], [-66.924832, 17.929556], [-66.985078, 17.973372], [-67.209633, 17.956941], [-67.154863, 18.19245], [-67.269879, 18.362235], [-67.094617, 18.515589], [-66.957694, 18.488204], [-66.409999, 18.488204], [-65.840398, 18.433435], [-65.632274, 18.367712], [-65.626797, 18.203403], [-65.730859, 18.186973], [-65.834921, 18.017187], [-66.234737, 17.929556], [-66.448338, 17.984326]]]}}]}\",\"selected\":{\"id\":\"4741\"},\"selection_policy\":{\"id\":\"4742\"}},\"id\":\"4543\",\"type\":\"GeoJSONDataSource\"},{\"attributes\":{\"formatter\":{\"id\":\"4739\"},\"major_label_policy\":{\"id\":\"4738\"},\"ticker\":{\"id\":\"4559\"}},\"id\":\"4558\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"4556\",\"type\":\"LinearScale\"},{\"attributes\":{\"formatter\":{\"id\":\"4736\"},\"major_label_policy\":{\"id\":\"4735\"},\"ticker\":{\"id\":\"4563\"}},\"id\":\"4562\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"4571\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"4559\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis\":{\"id\":\"4558\"},\"grid_line_color\":null,\"ticker\":null},\"id\":\"4561\",\"type\":\"Grid\"},{\"attributes\":{\"color_mapper\":{\"id\":\"4544\"},\"height\":20,\"label_standoff\":8,\"location\":[0,0],\"major_label_overrides\":{\"0\":\"0\",\"10\":\"10%\",\"15\":\"15%\",\"20\":\"20%\",\"25\":\"25%\",\"30\":\"30%\",\"35\":\"35%\",\"40\":\">40%\",\"5\":\"5%\"},\"major_label_policy\":{\"id\":\"4740\"},\"orientation\":\"horizontal\",\"width\":500},\"id\":\"4546\",\"type\":\"ColorBar\"},{\"attributes\":{\"source\":{\"id\":\"4543\"}},\"id\":\"4584\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"4742\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"4741\",\"type\":\"Selection\"},{\"attributes\":{\"active_multi\":null,\"tools\":[{\"id\":\"4566\"},{\"id\":\"4567\"},{\"id\":\"4568\"},{\"id\":\"4569\"},{\"id\":\"4570\"},{\"id\":\"4571\"}]},\"id\":\"4573\",\"type\":\"Toolbar\"},{\"attributes\":{\"below\":[{\"id\":\"4558\"},{\"id\":\"4546\"}],\"center\":[{\"id\":\"4561\"},{\"id\":\"4565\"}],\"left\":[{\"id\":\"4562\"}],\"renderers\":[{\"id\":\"4583\"}],\"title\":{\"id\":\"4548\"},\"toolbar\":{\"id\":\"4573\"},\"width\":950,\"x_range\":{\"id\":\"4550\"},\"x_scale\":{\"id\":\"4554\"},\"y_range\":{\"id\":\"4552\"},\"y_scale\":{\"id\":\"4556\"}},\"id\":\"4547\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"data_source\":{\"id\":\"4543\"},\"glyph\":{\"id\":\"4581\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"4582\"},\"view\":{\"id\":\"4584\"}},\"id\":\"4583\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_color\":{\"field\":\"Suicides by gun\",\"transform\":{\"id\":\"4544\"}},\"line_width\":{\"value\":0.25},\"xs\":{\"field\":\"xs\"},\"ys\":{\"field\":\"ys\"}},\"id\":\"4581\",\"type\":\"Patches\"},{\"attributes\":{},\"id\":\"4735\",\"type\":\"AllLabels\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"4572\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"4550\",\"type\":\"DataRange1d\"},{\"attributes\":{\"args\":{\"source\":{\"id\":\"4543\"}},\"code\":\"\\n    source.change.emit();\\n\"},\"id\":\"4545\",\"type\":\"CustomJS\"},{\"attributes\":{\"axis\":{\"id\":\"4562\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"4565\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"4736\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"4567\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"4566\",\"type\":\"PanTool\"},{\"attributes\":{\"overlay\":{\"id\":\"4572\"}},\"id\":\"4568\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"4563\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"4569\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"4738\",\"type\":\"AllLabels\"},{\"attributes\":{},\"id\":\"4570\",\"type\":\"ResetTool\"},{\"attributes\":{\"high\":1532,\"low\":0,\"palette\":[\"#ffffd9\",\"#edf8b1\",\"#c7e9b4\",\"#7fcdbb\",\"#41b6c4\",\"#1d91c0\",\"#225ea8\",\"#0c2c84\"]},\"id\":\"4544\",\"type\":\"LinearColorMapper\"},{\"attributes\":{},\"id\":\"4739\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"text\":\"Suicide by Guns\"},\"id\":\"4548\",\"type\":\"Title\"},{\"attributes\":{\"end\":2021,\"js_property_callbacks\":{\"change:value\":[{\"id\":\"4545\"}]},\"start\":1999,\"title\":\"Cummulative Since Year\",\"value\":2021},\"id\":\"4542\",\"type\":\"Slider\"}],\"root_ids\":[\"4587\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.2\"}};\n",
       "  var render_items = [{\"docid\":\"334480d1-32f5-4ca2-bb26-4723516fc5a2\",\"root_ids\":[\"4587\"],\"roots\":{\"4587\":\"a763ef99-0508-4575-89b8-1b3d79fc91a0\"}}];\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",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "4587"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.io import output_notebook, show, output_file\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.layouts import row\n",
    "from bokeh.models import ColumnDataSource, Slider, CustomJS\n",
    "from bokeh.models import GeoJSONDataSource, LinearColorMapper, ColorBar\n",
    "from bokeh.layouts import column, row, widgetbox\n",
    "from bokeh.models import (CDSView, ColorBar, ColumnDataSource, CustomJS,\n",
    "                          CustomJSFilter, GeoJSONDataSource, HoverTool,\n",
    "                          LinearColorMapper, Slider)\n",
    "\n",
    "from bokeh.palettes import brewer\n",
    "import geojson\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "df_geo = gpd.read_file(\"data/us.geojson\")\n",
    "df_suicides = pd.read_csv(\"data/Suicides - Monthly.csv\")\n",
    "\n",
    "YEAR = 1999\n",
    "df_geo[\"Suicides by gun\"] = df_geo['name'].apply(\n",
    "    lambda x: df_suicides.loc[\n",
    "        (df_suicides['State'] == x)\n",
    "       & (df_suicides['Year'] == YEAR)]['Suicides with guns'].sum()\n",
    ")\n",
    "\n",
    "sitesource = ColumnDataSource(df_geo)\n",
    "slider = Slider(\n",
    "    title='Year',\n",
    "    value=2021,\n",
    "    start=1999,\n",
    "    end=2021,\n",
    "    step=1\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "geosource = GeoJSONDataSource(geojson = df_geo.to_json()) #Define a sequential multi-hue color palette.\n",
    "palette = brewer['YlGnBu'][8] #Reverse color order so that dark blue is highest obesity.\n",
    "palette = palette[::-1]    #Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors.\n",
    "color_mapper = LinearColorMapper(\n",
    "    palette = palette,\n",
    "    low = 0,\n",
    "    high = df_geo['Suicides by gun'].max()\n",
    ")\n",
    "callback = CustomJS(args=dict(source=geosource), code=\"\"\"\n",
    "    source.change.emit();\n",
    "\"\"\")\n",
    "slider.js_on_change('value', callback)\n",
    "\n",
    "tick_labels = {'0': '0', '5': '5%', '10':'10%', '15':'15%', '20':'20%', '25':'25%', '30':'30%','35':'35%', '40': '>40%'} #Create color bar. \n",
    "color_bar = ColorBar(\n",
    "    color_mapper=color_mapper,\n",
    "    label_standoff=8,\n",
    "    width = 500,\n",
    "    height = 20,\n",
    "    border_line_color=None,\n",
    "    location = (0,0),\n",
    "    orientation = 'horizontal',\n",
    "    major_label_overrides = tick_labels)\n",
    "p = figure(\n",
    "    title = 'Suicide by Guns',\n",
    "    plot_height = 600,\n",
    "    plot_width = 950,\n",
    "    toolbar_location = 'right'\n",
    ")\n",
    "p.xgrid.grid_line_color = None\n",
    "p.ygrid.grid_line_color = None\n",
    "p.patches(\n",
    "    'xs',\n",
    "    'ys',\n",
    "    source = geosource,\n",
    "    fill_color = {\n",
    "        'field' :'Suicides by gun',\n",
    "        'transform' : color_mapper\n",
    "    },\n",
    "    line_color = 'black',\n",
    "    line_width = 0.25,\n",
    "    fill_alpha = 1)#Specify figure layout.\n",
    "\n",
    "\n",
    "p.add_layout(color_bar, 'below')   #Display figure inline in Jupyter Notebook.\n",
    "output_notebook()  #Display figure.\n",
    "output_file('Demo.html')\n",
    "layout = column(p, widgetbox(slider))\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "de613169",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from bokeh.io import curdoc\n",
    "from bokeh.layouts import column, row\n",
    "from bokeh.models import ColumnDataSource, Slider, TextInput\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.models import (CDSView, ColorBar, ColumnDataSource, CustomJS,\n",
    "                          CustomJSFilter, GeoJSONDataSource, HoverTool,\n",
    "                          LinearColorMapper, Slider)\n",
    "# Set up data\n",
    "N = 200\n",
    "x = np.linspace(0, 4*np.pi, N)\n",
    "y = np.sin(x)\n",
    "source = ColumnDataSource(data=dict(x=x, y=y))\n",
    "\n",
    "\n",
    "# Set up plot\n",
    "plot = figure(height=400, width=400, title=\"my sine wave\",\n",
    "              tools=\"crosshair,pan,reset,save,wheel_zoom\",\n",
    "              x_range=[0, 4*np.pi], y_range=[-2.5, 2.5])\n",
    "\n",
    "plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)\n",
    "\n",
    "\n",
    "# Set up widgets\n",
    "text = TextInput(title=\"title\", value='my sine wave')\n",
    "offset = Slider(title=\"offset\", value=0.0, start=-5.0, end=5.0, step=0.1)\n",
    "amplitude = Slider(title=\"amplitude\", value=1.0, start=-5.0, end=5.0, step=0.1)\n",
    "phase = Slider(title=\"phase\", value=0.0, start=0.0, end=2*np.pi)\n",
    "freq = Slider(title=\"frequency\", value=1.0, start=0.1, end=5.1, step=0.1)\n",
    "\n",
    "\n",
    "# Set up callbacks\n",
    "def update_title(attrname, old, new):\n",
    "    plot.title.text = text.value\n",
    "\n",
    "text.on_change('value', update_title)\n",
    "\n",
    "def update_data(attrname, old, new):\n",
    "\n",
    "    # Get the current slider values\n",
    "    a = amplitude.value\n",
    "    b = offset.value\n",
    "    w = phase.value\n",
    "    k = freq.value\n",
    "\n",
    "    # Generate the new curve\n",
    "    x = np.linspace(0, 4*np.pi, N)\n",
    "    y = a*np.sin(k*x + w) + b\n",
    "\n",
    "    source.data = dict(x=x, y=y)\n",
    "\n",
    "for w in [offset, amplitude, phase, freq]:\n",
    "    w.on_change('value', update_data)\n",
    "\n",
    "\n",
    "# Set up layouts and add to document\n",
    "inputs = column(text, offset, amplitude, phase, freq)\n",
    "\n",
    "curdoc().add_root(row(inputs, plot, width=800))\n",
    "curdoc().title = \"Sliders\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8501c1d0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Incident ID</th>\n",
       "      <th>Incident Date</th>\n",
       "      <th>State</th>\n",
       "      <th>City Or County</th>\n",
       "      <th>Address</th>\n",
       "      <th># Killed</th>\n",
       "      <th># Injured</th>\n",
       "      <th>Operations</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022821</td>\n",
       "      <td>June 2, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Toledo</td>\n",
       "      <td>1830 W Bancroft St</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022391</td>\n",
       "      <td>June 2, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Springfield</td>\n",
       "      <td>1935 S Yellow Springs St</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021130</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>New York</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Knickerbocker Ave</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021398</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>Missouri</td>\n",
       "      <td>Saint Louis</td>\n",
       "      <td>8800 block of N Broadway</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022129</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Cleveland (Garfield Heights)</td>\n",
       "      <td>13000 block of Alvin Ave</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Incident ID Incident Date     State                City Or County  \\\n",
       "0      2022821  June 2, 2021      Ohio                        Toledo   \n",
       "1      2022391  June 2, 2021      Ohio                   Springfield   \n",
       "2      2021130  May 31, 2021  New York                      Brooklyn   \n",
       "3      2021398  May 31, 2021  Missouri                   Saint Louis   \n",
       "4      2022129  May 31, 2021      Ohio  Cleveland (Garfield Heights)   \n",
       "\n",
       "                    Address  # Killed  # Injured  Operations  \n",
       "0        1830 W Bancroft St         0          4         NaN  \n",
       "1  1935 S Yellow Springs St         0          6         NaN  \n",
       "2         Knickerbocker Ave         0          5         NaN  \n",
       "3  8800 block of N Broadway         0          4         NaN  \n",
       "4  13000 block of Alvin Ave         1          5         NaN  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cou = pd.read_csv(\"data/mass_shootings.csv\")\n",
    "df_cou.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "722be9dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Incident ID</th>\n",
       "      <th>Incident Date</th>\n",
       "      <th>State</th>\n",
       "      <th>City Or County</th>\n",
       "      <th>Address</th>\n",
       "      <th># Killed</th>\n",
       "      <th># Injured</th>\n",
       "      <th>Operations</th>\n",
       "      <th>fips</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022821</td>\n",
       "      <td>June 2, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Toledo</td>\n",
       "      <td>1830 W Bancroft St</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022391</td>\n",
       "      <td>June 2, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Springfield</td>\n",
       "      <td>1935 S Yellow Springs St</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021130</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>New York</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Knickerbocker Ave</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021398</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>Missouri</td>\n",
       "      <td>Saint Louis</td>\n",
       "      <td>8800 block of N Broadway</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022129</td>\n",
       "      <td>May 31, 2021</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>Cleveland (Garfield Heights)</td>\n",
       "      <td>13000 block of Alvin Ave</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Incident ID Incident Date     State                City Or County  \\\n",
       "0      2022821  June 2, 2021      Ohio                        Toledo   \n",
       "1      2022391  June 2, 2021      Ohio                   Springfield   \n",
       "2      2021130  May 31, 2021  New York                      Brooklyn   \n",
       "3      2021398  May 31, 2021  Missouri                   Saint Louis   \n",
       "4      2022129  May 31, 2021      Ohio  Cleveland (Garfield Heights)   \n",
       "\n",
       "                    Address  # Killed  # Injured  Operations   fips  \n",
       "0        1830 W Bancroft St         0          4         NaN   None  \n",
       "1  1935 S Yellow Springs St         0          6         NaN   None  \n",
       "2         Knickerbocker Ave         0          5         NaN  36047  \n",
       "3  8800 block of N Broadway         0          4         NaN  29510  \n",
       "4  13000 block of Alvin Ave         1          5         NaN   None  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import addfips\n",
    "\n",
    "af = addfips.AddFIPS()\n",
    "\n",
    "df_cou = df_cou.apply(\n",
    "        lambda x: (af.add_county_fips(x, county_field=\"City Or County\", state_field=\"State\")), axis=1)\n",
    "df_cou.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdad8a2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cou.loc[df_cou['fips'].str != 'None']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a73acc40",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install pip install addfips"
   ]
  }
 ],
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