diff --git a/data-exploration/.ipynb_checkpoints/Prener Data Exploration-checkpoint.ipynb b/data-exploration/.ipynb_checkpoints/Prener Data Exploration-checkpoint.ipynb
new file mode 100644
index 0000000..af6be96
--- /dev/null
+++ b/data-exploration/.ipynb_checkpoints/Prener Data Exploration-checkpoint.ipynb	
@@ -0,0 +1,800 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Enter password: ········\n"
+     ]
+    }
+   ],
+   "source": [
+    "from arcgis.gis import GIS\n",
+    "\n",
+    "gis = GIS(\"https://www.arcgis.com/home/\", \"gregbrunner_slugis\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = \"prcl_shape.zip\"\n",
+    "stl = gis.content.add({\"title\":\"St. Louis parcel data from STL's Open Data site\", \"tags\":\"St. Louis, parcels\"}, data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "published_stl = stl.publish()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div class=\"item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
+       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
+       "                       <a href='https://SLUSTL.maps.arcgis.com/home/item.html?id=29e09729f4dd4d8a985c014d7cb79e87' target='_blank'>\n",
+       "                        <img src='http://static.arcgis.com/images/desktopapp.png' class=\"itemThumbnail\">\n",
+       "                       </a>\n",
+       "                    </div>\n",
+       "\n",
+       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
+       "                        <a href='https://SLUSTL.maps.arcgis.com/home/item.html?id=29e09729f4dd4d8a985c014d7cb79e87' target='_blank'><b>St. Louis parcel data from STL's Open Data site</b>\n",
+       "                        </a>\n",
+       "                        <br/><img src='https://SLUSTL.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by gregbrunner_slugis\n",
+       "                        <br/>Last Modified: September 20, 2018\n",
+       "                        <br/>0 comments, 0 views\n",
+       "                    </div>\n",
+       "                </div>\n",
+       "                "
+      ],
+      "text/plain": [
+       "<Item title:\"St. Louis parcel data from STL's Open Data site\" type:Feature Layer Collection owner:gregbrunner_slugis>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "published_stl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0e211e68d11b4e969754569b6af3046d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oc…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "stl_map = gis.map('St. Louis, MO')\n",
+    "stl_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stl_map.add_layer(published_stl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Ignore this :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "high_estimate = '../data-2017/parcel/high-estimate/parcel-data-2017-highEstimate.csv'\n",
+    "h_est = gis.content.add({\"title\":\"high_estimate\", \"tags\":\"St. Louis, parcels, vacancy\"}, high_estimate)\n",
+    "\n",
+    "from arcgis.features import analysis\n",
+    "\n",
+    "enriched_parcels = analysis.join_features(target_layer=published_stl, join_layer=h_est, attribute_relationship='HANDLE', gis=gis)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## This didn't work. Let's just join dataframes..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#from arcgis.features import FeatureLayer\n",
+    "\n",
+    "#url = 'https://services1.arcgis.com/g2TonOxuRkIqSOFx/arcgis/rest/services/prcl_shape/FeatureServer/0'\n",
+    "\n",
+    "#slugis = GIS(\"https://www.arcgis.com/home/\", \"gregbrunner_slugis\")\n",
+    "\n",
+    "#parcel_fl = FeatureLayer(url, gis = gis)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from arcgis.features import FeatureLayer\n",
+    "\n",
+    "parcel_fl = FeatureLayer(url = published_stl.url, gis = gis)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parcels_sdf = published_stl.layers[0].query().df\n",
+    "#parcels_sdf = parcel_fl.query().df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "127758"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(parcels_sdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('O')"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parcels_sdf.HANDLE.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parcels_sdf['H'] = parcels_sdf['HANDLE'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float64')"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parcels_sdf.H.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "low_estimate = '../data-2017/parcel/low-estimate/parcel-data-2017-lowEstimate.csv'\n",
+    "high_estimate = '../data-2017/parcel/high-estimate/parcel-data-2017-highEstimate.csv'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "estimate = high_estimate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h_est_df = pd.read_csv(estimate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h_est_df = h_est_df.rename(columns={ 'handle' : \"H\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float64')"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_est_df.H.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "48013"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(h_est_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "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>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              H  vacantBinary  cityStatus\n",
+       "0  1.000100e+10          True       False\n",
+       "1  1.000100e+10          True       False\n",
+       "2  1.000100e+10          True       False\n",
+       "3  1.001400e+10          True       False\n",
+       "4  1.001400e+10          True       False"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_est_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from arcgis.features import SpatialDataFrame as spd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_data = spd.merge(parcels_sdf, h_est_df, how = 'left', left_on='H', right_on='H')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "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>FID</th>\n",
+       "      <th>HANDLE</th>\n",
+       "      <th>Shape__Area</th>\n",
+       "      <th>Shape__Length</th>\n",
+       "      <th>SHAPE</th>\n",
+       "      <th>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>10329000045</td>\n",
+       "      <td>1830.843750</td>\n",
+       "      <td>179.595654</td>\n",
+       "      <td>{'rings': [[[-10039885.1163153, 4671794.922912...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>10001000005</td>\n",
+       "      <td>1020.195312</td>\n",
+       "      <td>130.846919</td>\n",
+       "      <td>{'rings': [[[-10039556.032893, 4667225.8128700...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>10329000075</td>\n",
+       "      <td>1830.839844</td>\n",
+       "      <td>179.595194</td>\n",
+       "      <td>{'rings': [[[-10039873.7565212, 4671765.761943...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>10001000010</td>\n",
+       "      <td>2003.324219</td>\n",
+       "      <td>273.216695</td>\n",
+       "      <td>{'rings': [[[-10039533.5723971, 4667298.017724...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>10329000105</td>\n",
+       "      <td>1830.824219</td>\n",
+       "      <td>179.594684</td>\n",
+       "      <td>{'rings': [[[-10039862.3967913, 4671736.601044...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   FID       HANDLE  Shape__Area  Shape__Length  \\\n",
+       "0    1  10329000045  1830.843750     179.595654   \n",
+       "1    2  10001000005  1020.195312     130.846919   \n",
+       "2    3  10329000075  1830.839844     179.595194   \n",
+       "3    4  10001000010  2003.324219     273.216695   \n",
+       "4    5  10329000105  1830.824219     179.594684   \n",
+       "\n",
+       "                                               SHAPE             H  \\\n",
+       "0  {'rings': [[[-10039885.1163153, 4671794.922912...  1.032900e+10   \n",
+       "1  {'rings': [[[-10039556.032893, 4667225.8128700...  1.000100e+10   \n",
+       "2  {'rings': [[[-10039873.7565212, 4671765.761943...  1.032900e+10   \n",
+       "3  {'rings': [[[-10039533.5723971, 4667298.017724...  1.000100e+10   \n",
+       "4  {'rings': [[[-10039862.3967913, 4671736.601044...  1.032900e+10   \n",
+       "\n",
+       "  vacantBinary cityStatus  \n",
+       "0          NaN        NaN  \n",
+       "1         True      False  \n",
+       "2          NaN        NaN  \n",
+       "3         True      False  \n",
+       "4          NaN        NaN  "
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "31473"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(merged_data[merged_data['vacantBinary']==True])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "empty_parcels = merged_data[merged_data['vacantBinary']==True].copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "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>FID</th>\n",
+       "      <th>HANDLE</th>\n",
+       "      <th>Shape__Area</th>\n",
+       "      <th>Shape__Length</th>\n",
+       "      <th>SHAPE</th>\n",
+       "      <th>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2</td>\n",
+       "      <td>10001000005</td>\n",
+       "      <td>1020.195312</td>\n",
+       "      <td>130.846919</td>\n",
+       "      <td>{'rings': [[[-10039556.032893, 4667225.8128700...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4</td>\n",
+       "      <td>10001000010</td>\n",
+       "      <td>2003.324219</td>\n",
+       "      <td>273.216695</td>\n",
+       "      <td>{'rings': [[[-10039533.5723971, 4667298.017724...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>10330000030</td>\n",
+       "      <td>244.117188</td>\n",
+       "      <td>78.191878</td>\n",
+       "      <td>{'rings': [[[-10039983.5732021, 4671883.351409...</td>\n",
+       "      <td>1.033000e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>10001000032</td>\n",
+       "      <td>323.976562</td>\n",
+       "      <td>88.823036</td>\n",
+       "      <td>{'rings': [[[-10039503.905549, 4667209.6188938...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>14</td>\n",
+       "      <td>10014000005</td>\n",
+       "      <td>1417.808594</td>\n",
+       "      <td>176.194846</td>\n",
+       "      <td>{'rings': [[[-10039171.9315976, 4668734.117673...</td>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   FID       HANDLE  Shape__Area  Shape__Length  \\\n",
+       "0    2  10001000005  1020.195312     130.846919   \n",
+       "1    4  10001000010  2003.324219     273.216695   \n",
+       "2    7  10330000030   244.117188      78.191878   \n",
+       "3    8  10001000032   323.976562      88.823036   \n",
+       "4   14  10014000005  1417.808594     176.194846   \n",
+       "\n",
+       "                                               SHAPE             H  \\\n",
+       "0  {'rings': [[[-10039556.032893, 4667225.8128700...  1.000100e+10   \n",
+       "1  {'rings': [[[-10039533.5723971, 4667298.017724...  1.000100e+10   \n",
+       "2  {'rings': [[[-10039983.5732021, 4671883.351409...  1.033000e+10   \n",
+       "3  {'rings': [[[-10039503.905549, 4667209.6188938...  1.000100e+10   \n",
+       "4  {'rings': [[[-10039171.9315976, 4668734.117673...  1.001400e+10   \n",
+       "\n",
+       "  vacantBinary cityStatus  \n",
+       "0         True      False  \n",
+       "1         True      False  \n",
+       "2         True      False  \n",
+       "3         True      False  \n",
+       "4         True      False  "
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "empty_parcels.reset_index(inplace=True, drop=True)\n",
+    "empty_parcels.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'C:\\\\Users\\\\greg6750\\\\Documents\\\\IPython Notebooks\\\\vacancy-data\\\\data-exploration\\\\vacancy.gdb\\\\high_estimate_all'"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_data.to_featureclass(out_location=r'C:\\Users\\greg6750\\Documents\\IPython Notebooks\\vacancy-data\\data-exploration\\vacancy.gdb', \n",
+    "                              out_name=\"high_estimate_all\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#merged_data[merged_data['vacantBinary']==True].to_featureclass(out_location=r'C:\\Users\\greg6750\\Documents\\IPython Notebooks\\vacancy-data\\data-exploration\\vacancy.gdb', \n",
+    "#                              out_name=\"vacant_low_estimate\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fs = gis.content.import_data(merged_data, title='STL Vacancy - High Estimate')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Extra"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#sdf = sdf[sdf.SHAPE.notna()].copy()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/data-exploration/Prener Data Exploration.ipynb b/data-exploration/Prener Data Exploration.ipynb
new file mode 100644
index 0000000..af6be96
--- /dev/null
+++ b/data-exploration/Prener Data Exploration.ipynb	
@@ -0,0 +1,800 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Enter password: ········\n"
+     ]
+    }
+   ],
+   "source": [
+    "from arcgis.gis import GIS\n",
+    "\n",
+    "gis = GIS(\"https://www.arcgis.com/home/\", \"gregbrunner_slugis\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = \"prcl_shape.zip\"\n",
+    "stl = gis.content.add({\"title\":\"St. Louis parcel data from STL's Open Data site\", \"tags\":\"St. Louis, parcels\"}, data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "published_stl = stl.publish()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div class=\"item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
+       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
+       "                       <a href='https://SLUSTL.maps.arcgis.com/home/item.html?id=29e09729f4dd4d8a985c014d7cb79e87' target='_blank'>\n",
+       "                        <img src='http://static.arcgis.com/images/desktopapp.png' class=\"itemThumbnail\">\n",
+       "                       </a>\n",
+       "                    </div>\n",
+       "\n",
+       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
+       "                        <a href='https://SLUSTL.maps.arcgis.com/home/item.html?id=29e09729f4dd4d8a985c014d7cb79e87' target='_blank'><b>St. Louis parcel data from STL's Open Data site</b>\n",
+       "                        </a>\n",
+       "                        <br/><img src='https://SLUSTL.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by gregbrunner_slugis\n",
+       "                        <br/>Last Modified: September 20, 2018\n",
+       "                        <br/>0 comments, 0 views\n",
+       "                    </div>\n",
+       "                </div>\n",
+       "                "
+      ],
+      "text/plain": [
+       "<Item title:\"St. Louis parcel data from STL's Open Data site\" type:Feature Layer Collection owner:gregbrunner_slugis>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "published_stl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0e211e68d11b4e969754569b6af3046d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oc…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "stl_map = gis.map('St. Louis, MO')\n",
+    "stl_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stl_map.add_layer(published_stl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Ignore this :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "high_estimate = '../data-2017/parcel/high-estimate/parcel-data-2017-highEstimate.csv'\n",
+    "h_est = gis.content.add({\"title\":\"high_estimate\", \"tags\":\"St. Louis, parcels, vacancy\"}, high_estimate)\n",
+    "\n",
+    "from arcgis.features import analysis\n",
+    "\n",
+    "enriched_parcels = analysis.join_features(target_layer=published_stl, join_layer=h_est, attribute_relationship='HANDLE', gis=gis)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## This didn't work. Let's just join dataframes..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#from arcgis.features import FeatureLayer\n",
+    "\n",
+    "#url = 'https://services1.arcgis.com/g2TonOxuRkIqSOFx/arcgis/rest/services/prcl_shape/FeatureServer/0'\n",
+    "\n",
+    "#slugis = GIS(\"https://www.arcgis.com/home/\", \"gregbrunner_slugis\")\n",
+    "\n",
+    "#parcel_fl = FeatureLayer(url, gis = gis)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from arcgis.features import FeatureLayer\n",
+    "\n",
+    "parcel_fl = FeatureLayer(url = published_stl.url, gis = gis)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parcels_sdf = published_stl.layers[0].query().df\n",
+    "#parcels_sdf = parcel_fl.query().df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "127758"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(parcels_sdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('O')"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parcels_sdf.HANDLE.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parcels_sdf['H'] = parcels_sdf['HANDLE'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float64')"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parcels_sdf.H.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "low_estimate = '../data-2017/parcel/low-estimate/parcel-data-2017-lowEstimate.csv'\n",
+    "high_estimate = '../data-2017/parcel/high-estimate/parcel-data-2017-highEstimate.csv'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "estimate = high_estimate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h_est_df = pd.read_csv(estimate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h_est_df = h_est_df.rename(columns={ 'handle' : \"H\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float64')"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_est_df.H.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "48013"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(h_est_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "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>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              H  vacantBinary  cityStatus\n",
+       "0  1.000100e+10          True       False\n",
+       "1  1.000100e+10          True       False\n",
+       "2  1.000100e+10          True       False\n",
+       "3  1.001400e+10          True       False\n",
+       "4  1.001400e+10          True       False"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_est_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from arcgis.features import SpatialDataFrame as spd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_data = spd.merge(parcels_sdf, h_est_df, how = 'left', left_on='H', right_on='H')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "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>FID</th>\n",
+       "      <th>HANDLE</th>\n",
+       "      <th>Shape__Area</th>\n",
+       "      <th>Shape__Length</th>\n",
+       "      <th>SHAPE</th>\n",
+       "      <th>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>10329000045</td>\n",
+       "      <td>1830.843750</td>\n",
+       "      <td>179.595654</td>\n",
+       "      <td>{'rings': [[[-10039885.1163153, 4671794.922912...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>10001000005</td>\n",
+       "      <td>1020.195312</td>\n",
+       "      <td>130.846919</td>\n",
+       "      <td>{'rings': [[[-10039556.032893, 4667225.8128700...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>10329000075</td>\n",
+       "      <td>1830.839844</td>\n",
+       "      <td>179.595194</td>\n",
+       "      <td>{'rings': [[[-10039873.7565212, 4671765.761943...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>10001000010</td>\n",
+       "      <td>2003.324219</td>\n",
+       "      <td>273.216695</td>\n",
+       "      <td>{'rings': [[[-10039533.5723971, 4667298.017724...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>10329000105</td>\n",
+       "      <td>1830.824219</td>\n",
+       "      <td>179.594684</td>\n",
+       "      <td>{'rings': [[[-10039862.3967913, 4671736.601044...</td>\n",
+       "      <td>1.032900e+10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   FID       HANDLE  Shape__Area  Shape__Length  \\\n",
+       "0    1  10329000045  1830.843750     179.595654   \n",
+       "1    2  10001000005  1020.195312     130.846919   \n",
+       "2    3  10329000075  1830.839844     179.595194   \n",
+       "3    4  10001000010  2003.324219     273.216695   \n",
+       "4    5  10329000105  1830.824219     179.594684   \n",
+       "\n",
+       "                                               SHAPE             H  \\\n",
+       "0  {'rings': [[[-10039885.1163153, 4671794.922912...  1.032900e+10   \n",
+       "1  {'rings': [[[-10039556.032893, 4667225.8128700...  1.000100e+10   \n",
+       "2  {'rings': [[[-10039873.7565212, 4671765.761943...  1.032900e+10   \n",
+       "3  {'rings': [[[-10039533.5723971, 4667298.017724...  1.000100e+10   \n",
+       "4  {'rings': [[[-10039862.3967913, 4671736.601044...  1.032900e+10   \n",
+       "\n",
+       "  vacantBinary cityStatus  \n",
+       "0          NaN        NaN  \n",
+       "1         True      False  \n",
+       "2          NaN        NaN  \n",
+       "3         True      False  \n",
+       "4          NaN        NaN  "
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "31473"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(merged_data[merged_data['vacantBinary']==True])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "empty_parcels = merged_data[merged_data['vacantBinary']==True].copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "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>FID</th>\n",
+       "      <th>HANDLE</th>\n",
+       "      <th>Shape__Area</th>\n",
+       "      <th>Shape__Length</th>\n",
+       "      <th>SHAPE</th>\n",
+       "      <th>H</th>\n",
+       "      <th>vacantBinary</th>\n",
+       "      <th>cityStatus</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2</td>\n",
+       "      <td>10001000005</td>\n",
+       "      <td>1020.195312</td>\n",
+       "      <td>130.846919</td>\n",
+       "      <td>{'rings': [[[-10039556.032893, 4667225.8128700...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4</td>\n",
+       "      <td>10001000010</td>\n",
+       "      <td>2003.324219</td>\n",
+       "      <td>273.216695</td>\n",
+       "      <td>{'rings': [[[-10039533.5723971, 4667298.017724...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>10330000030</td>\n",
+       "      <td>244.117188</td>\n",
+       "      <td>78.191878</td>\n",
+       "      <td>{'rings': [[[-10039983.5732021, 4671883.351409...</td>\n",
+       "      <td>1.033000e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>10001000032</td>\n",
+       "      <td>323.976562</td>\n",
+       "      <td>88.823036</td>\n",
+       "      <td>{'rings': [[[-10039503.905549, 4667209.6188938...</td>\n",
+       "      <td>1.000100e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>14</td>\n",
+       "      <td>10014000005</td>\n",
+       "      <td>1417.808594</td>\n",
+       "      <td>176.194846</td>\n",
+       "      <td>{'rings': [[[-10039171.9315976, 4668734.117673...</td>\n",
+       "      <td>1.001400e+10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   FID       HANDLE  Shape__Area  Shape__Length  \\\n",
+       "0    2  10001000005  1020.195312     130.846919   \n",
+       "1    4  10001000010  2003.324219     273.216695   \n",
+       "2    7  10330000030   244.117188      78.191878   \n",
+       "3    8  10001000032   323.976562      88.823036   \n",
+       "4   14  10014000005  1417.808594     176.194846   \n",
+       "\n",
+       "                                               SHAPE             H  \\\n",
+       "0  {'rings': [[[-10039556.032893, 4667225.8128700...  1.000100e+10   \n",
+       "1  {'rings': [[[-10039533.5723971, 4667298.017724...  1.000100e+10   \n",
+       "2  {'rings': [[[-10039983.5732021, 4671883.351409...  1.033000e+10   \n",
+       "3  {'rings': [[[-10039503.905549, 4667209.6188938...  1.000100e+10   \n",
+       "4  {'rings': [[[-10039171.9315976, 4668734.117673...  1.001400e+10   \n",
+       "\n",
+       "  vacantBinary cityStatus  \n",
+       "0         True      False  \n",
+       "1         True      False  \n",
+       "2         True      False  \n",
+       "3         True      False  \n",
+       "4         True      False  "
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "empty_parcels.reset_index(inplace=True, drop=True)\n",
+    "empty_parcels.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'C:\\\\Users\\\\greg6750\\\\Documents\\\\IPython Notebooks\\\\vacancy-data\\\\data-exploration\\\\vacancy.gdb\\\\high_estimate_all'"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_data.to_featureclass(out_location=r'C:\\Users\\greg6750\\Documents\\IPython Notebooks\\vacancy-data\\data-exploration\\vacancy.gdb', \n",
+    "                              out_name=\"high_estimate_all\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#merged_data[merged_data['vacantBinary']==True].to_featureclass(out_location=r'C:\\Users\\greg6750\\Documents\\IPython Notebooks\\vacancy-data\\data-exploration\\vacancy.gdb', \n",
+    "#                              out_name=\"vacant_low_estimate\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fs = gis.content.import_data(merged_data, title='STL Vacancy - High Estimate')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Extra"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#sdf = sdf[sdf.SHAPE.notna()].copy()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}