diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 5e4b1cca..fcf1fb0d 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -22,4 +22,24 @@ repos:
         files: ^space2stats_api/
         exclude: ^space2stats/env/
         additional_dependencies:
-          - types-requests
\ No newline at end of file
+          - types-requests
+  
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.8.7
+    hooks:
+      - id: nbqa-ruff
+        args: ["--fix"]
+        # Match all `.ipynb` files under `notebooks/user-docs/`
+        files: ^notebooks/user-docs/.*\.ipynb$
+      - id: nbqa-isort
+        args: ["--profile=black"]
+        additional_dependencies: [isort==5.6.4]
+        # Match all `.ipynb` files under `notebooks/user-docs/`
+        files: ^notebooks/user-docs/.*\.ipynb$
+      - id: nbqa-black
+        # Match all `.ipynb` files under `notebooks/user-docs/`
+        files: ^notebooks/user-docs/.*\.ipynb$
+      - id: nbqa-pyupgrade
+        args: ["--py37-plus"]
+        # Match all `.ipynb` files under `notebooks/user-docs/`
+        files: ^notebooks/user-docs/.*\.ipynb$
\ No newline at end of file
diff --git a/notebooks/user-docs/s2s_python_lib.ipynb b/notebooks/user-docs/s2s_python_lib.ipynb
new file mode 100644
index 00000000..ced1148d
--- /dev/null
+++ b/notebooks/user-docs/s2s_python_lib.ipynb
@@ -0,0 +1,895 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Access S2S via Python Library"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "%pip install \"git+https://github.com/worldbank/DECAT_Space2Stats.git#subdirectory=space2stats_api/src\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "from typing import Dict\n",
+    "\n",
+    "import geopandas as gpd\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from dotenv import load_dotenv\n",
+    "from geojson_pydantic import Feature, Polygon\n",
+    "from lonboard import Map, ScatterplotLayer\n",
+    "from shapely.geometry import shape\n",
+    "from space2stats import StatsTable"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "__Expected environment variables to be set__ from dotenv file\n",
+    "\n",
+    "\n",
+    "```.env\n",
+    "PGHOST=\n",
+    "PGPORT=\n",
+    "PGDATABASE=\n",
+    "PGUSER=\n",
+    "PGPASSWORD=\n",
+    "PGTABLENAME=space2stats\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "load_dotenv(\"../../space2stats_api/db.env\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['sum_pop_2020',\n",
+       " 'ogc_fid',\n",
+       " 'sum_pop_f_0_2020',\n",
+       " 'sum_pop_f_10_2020',\n",
+       " 'sum_pop_f_15_2020',\n",
+       " 'sum_pop_f_1_2020',\n",
+       " 'sum_pop_f_20_2020',\n",
+       " 'sum_pop_f_25_2020',\n",
+       " 'sum_pop_f_30_2020',\n",
+       " 'sum_pop_f_35_2020',\n",
+       " 'sum_pop_f_40_2020',\n",
+       " 'sum_pop_f_45_2020',\n",
+       " 'sum_pop_f_50_2020',\n",
+       " 'sum_pop_f_55_2020',\n",
+       " 'sum_pop_f_5_2020',\n",
+       " 'sum_pop_f_60_2020',\n",
+       " 'sum_pop_f_65_2020',\n",
+       " 'sum_pop_f_70_2020',\n",
+       " 'sum_pop_f_75_2020',\n",
+       " 'sum_pop_f_80_2020',\n",
+       " 'sum_pop_m_0_2020',\n",
+       " 'sum_pop_m_10_2020',\n",
+       " 'sum_pop_m_15_2020',\n",
+       " 'sum_pop_m_1_2020',\n",
+       " 'sum_pop_m_20_2020',\n",
+       " 'sum_pop_m_25_2020',\n",
+       " 'sum_pop_m_30_2020',\n",
+       " 'sum_pop_m_35_2020',\n",
+       " 'sum_pop_m_40_2020',\n",
+       " 'sum_pop_m_45_2020',\n",
+       " 'sum_pop_m_50_2020',\n",
+       " 'sum_pop_m_55_2020',\n",
+       " 'sum_pop_m_5_2020',\n",
+       " 'sum_pop_m_60_2020',\n",
+       " 'sum_pop_m_65_2020',\n",
+       " 'sum_pop_m_70_2020',\n",
+       " 'sum_pop_m_75_2020',\n",
+       " 'sum_pop_m_80_2020',\n",
+       " 'sum_pop_m_2020',\n",
+       " 'sum_pop_f_2020']"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "with StatsTable.connect() as stats_table:\n",
+    "    fields = stats_table.fields()\n",
+    "\n",
+    "fields"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "AOIModel = Feature[Polygon, Dict]\n",
+    "\n",
+    "# ~kenya\n",
+    "aoi = {\n",
+    "    \"type\": \"Feature\",\n",
+    "    \"geometry\": {\n",
+    "        \"type\": \"Polygon\",\n",
+    "        \"coordinates\": [\n",
+    "            [\n",
+    "                [33.78593974945852, 5.115816884114494],\n",
+    "                [33.78593974945852, -4.725410543134203],\n",
+    "                [41.94362577283266, -4.725410543134203],\n",
+    "                [41.94362577283266, 5.115816884114494],\n",
+    "                [33.78593974945852, 5.115816884114494],\n",
+    "            ]\n",
+    "        ],\n",
+    "    },\n",
+    "    \"properties\": {\"name\": \"Updated AOI\"},\n",
+    "}\n",
+    "\n",
+    "\n",
+    "feat = AOIModel(**aoi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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>hex_id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "      <th>ogc_fid</th>\n",
+       "      <th>sum_pop_f_0_2020</th>\n",
+       "      <th>sum_pop_f_10_2020</th>\n",
+       "      <th>sum_pop_f_15_2020</th>\n",
+       "      <th>sum_pop_f_1_2020</th>\n",
+       "      <th>sum_pop_f_20_2020</th>\n",
+       "      <th>sum_pop_f_25_2020</th>\n",
+       "      <th>...</th>\n",
+       "      <th>sum_pop_m_50_2020</th>\n",
+       "      <th>sum_pop_m_55_2020</th>\n",
+       "      <th>sum_pop_m_5_2020</th>\n",
+       "      <th>sum_pop_m_60_2020</th>\n",
+       "      <th>sum_pop_m_65_2020</th>\n",
+       "      <th>sum_pop_m_70_2020</th>\n",
+       "      <th>sum_pop_m_75_2020</th>\n",
+       "      <th>sum_pop_m_80_2020</th>\n",
+       "      <th>sum_pop_m_2020</th>\n",
+       "      <th>sum_pop_f_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>866a4a017ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.078694056627...</td>\n",
+       "      <td>676.912804</td>\n",
+       "      <td>6157254</td>\n",
+       "      <td>8.924362</td>\n",
+       "      <td>49.524105</td>\n",
+       "      <td>36.898296</td>\n",
+       "      <td>32.985901</td>\n",
+       "      <td>28.963400</td>\n",
+       "      <td>33.645473</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6.732327</td>\n",
+       "      <td>4.131749</td>\n",
+       "      <td>53.380043</td>\n",
+       "      <td>3.240541</td>\n",
+       "      <td>2.475817</td>\n",
+       "      <td>0.702667</td>\n",
+       "      <td>0.399492</td>\n",
+       "      <td>0.129285</td>\n",
+       "      <td>336.082180</td>\n",
+       "      <td>340.830624</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>866a4a01fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.134817927246...</td>\n",
+       "      <td>347.182722</td>\n",
+       "      <td>6157255</td>\n",
+       "      <td>4.515680</td>\n",
+       "      <td>24.773327</td>\n",
+       "      <td>19.462585</td>\n",
+       "      <td>16.690670</td>\n",
+       "      <td>15.832314</td>\n",
+       "      <td>16.429201</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.445144</td>\n",
+       "      <td>2.752507</td>\n",
+       "      <td>25.548544</td>\n",
+       "      <td>1.827761</td>\n",
+       "      <td>1.524122</td>\n",
+       "      <td>0.585427</td>\n",
+       "      <td>0.381080</td>\n",
+       "      <td>0.209030</td>\n",
+       "      <td>171.759225</td>\n",
+       "      <td>175.423497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>866a4a04fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.339286712001...</td>\n",
+       "      <td>285.943490</td>\n",
+       "      <td>6157260</td>\n",
+       "      <td>3.642580</td>\n",
+       "      <td>19.623219</td>\n",
+       "      <td>16.698730</td>\n",
+       "      <td>13.463530</td>\n",
+       "      <td>14.255625</td>\n",
+       "      <td>12.501910</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.827743</td>\n",
+       "      <td>3.055085</td>\n",
+       "      <td>18.765499</td>\n",
+       "      <td>1.711561</td>\n",
+       "      <td>1.571700</td>\n",
+       "      <td>0.762171</td>\n",
+       "      <td>0.533085</td>\n",
+       "      <td>0.349744</td>\n",
+       "      <td>140.698267</td>\n",
+       "      <td>145.245222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a057ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.237081352434...</td>\n",
+       "      <td>279.463912</td>\n",
+       "      <td>6157261</td>\n",
+       "      <td>3.560037</td>\n",
+       "      <td>19.178549</td>\n",
+       "      <td>16.320332</td>\n",
+       "      <td>13.158442</td>\n",
+       "      <td>13.932587</td>\n",
+       "      <td>12.218613</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.763665</td>\n",
+       "      <td>2.985856</td>\n",
+       "      <td>18.340267</td>\n",
+       "      <td>1.672776</td>\n",
+       "      <td>1.536084</td>\n",
+       "      <td>0.744900</td>\n",
+       "      <td>0.521005</td>\n",
+       "      <td>0.341818</td>\n",
+       "      <td>137.509998</td>\n",
+       "      <td>141.953914</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>866a4a05fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.293182542907...</td>\n",
+       "      <td>235.258474</td>\n",
+       "      <td>6157262</td>\n",
+       "      <td>2.996913</td>\n",
+       "      <td>16.144897</td>\n",
+       "      <td>13.738791</td>\n",
+       "      <td>11.077046</td>\n",
+       "      <td>11.728739</td>\n",
+       "      <td>10.285879</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.326510</td>\n",
+       "      <td>2.513555</td>\n",
+       "      <td>15.439214</td>\n",
+       "      <td>1.408177</td>\n",
+       "      <td>1.293108</td>\n",
+       "      <td>0.627072</td>\n",
+       "      <td>0.438593</td>\n",
+       "      <td>0.287750</td>\n",
+       "      <td>115.758746</td>\n",
+       "      <td>119.499727</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 42 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            hex_id                                           geometry  \\\n",
+       "0  866a4a017ffffff  {\"type\":\"Point\",\"coordinates\":[36.078694056627...   \n",
+       "1  866a4a01fffffff  {\"type\":\"Point\",\"coordinates\":[36.134817927246...   \n",
+       "2  866a4a04fffffff  {\"type\":\"Point\",\"coordinates\":[36.339286712001...   \n",
+       "3  866a4a057ffffff  {\"type\":\"Point\",\"coordinates\":[36.237081352434...   \n",
+       "4  866a4a05fffffff  {\"type\":\"Point\",\"coordinates\":[36.293182542907...   \n",
+       "\n",
+       "   sum_pop_2020  ogc_fid  sum_pop_f_0_2020  sum_pop_f_10_2020  \\\n",
+       "0    676.912804  6157254          8.924362          49.524105   \n",
+       "1    347.182722  6157255          4.515680          24.773327   \n",
+       "2    285.943490  6157260          3.642580          19.623219   \n",
+       "3    279.463912  6157261          3.560037          19.178549   \n",
+       "4    235.258474  6157262          2.996913          16.144897   \n",
+       "\n",
+       "   sum_pop_f_15_2020  sum_pop_f_1_2020  sum_pop_f_20_2020  sum_pop_f_25_2020  \\\n",
+       "0          36.898296         32.985901          28.963400          33.645473   \n",
+       "1          19.462585         16.690670          15.832314          16.429201   \n",
+       "2          16.698730         13.463530          14.255625          12.501910   \n",
+       "3          16.320332         13.158442          13.932587          12.218613   \n",
+       "4          13.738791         11.077046          11.728739          10.285879   \n",
+       "\n",
+       "   ...  sum_pop_m_50_2020  sum_pop_m_55_2020  sum_pop_m_5_2020  \\\n",
+       "0  ...           6.732327           4.131749         53.380043   \n",
+       "1  ...           3.445144           2.752507         25.548544   \n",
+       "2  ...           2.827743           3.055085         18.765499   \n",
+       "3  ...           2.763665           2.985856         18.340267   \n",
+       "4  ...           2.326510           2.513555         15.439214   \n",
+       "\n",
+       "   sum_pop_m_60_2020  sum_pop_m_65_2020  sum_pop_m_70_2020  sum_pop_m_75_2020  \\\n",
+       "0           3.240541           2.475817           0.702667           0.399492   \n",
+       "1           1.827761           1.524122           0.585427           0.381080   \n",
+       "2           1.711561           1.571700           0.762171           0.533085   \n",
+       "3           1.672776           1.536084           0.744900           0.521005   \n",
+       "4           1.408177           1.293108           0.627072           0.438593   \n",
+       "\n",
+       "   sum_pop_m_80_2020  sum_pop_m_2020  sum_pop_f_2020  \n",
+       "0           0.129285      336.082180      340.830624  \n",
+       "1           0.209030      171.759225      175.423497  \n",
+       "2           0.349744      140.698267      145.245222  \n",
+       "3           0.341818      137.509998      141.953914  \n",
+       "4           0.287750      115.758746      119.499727  \n",
+       "\n",
+       "[5 rows x 42 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "with StatsTable.connect() as stats_table:\n",
+    "    data = stats_table.summaries(\n",
+    "        aoi=feat, spatial_join_method=\"centroid\", fields=fields, geometry=\"point\"\n",
+    "    )\n",
+    "    df = pd.DataFrame(data)\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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>hex_id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "      <th>ogc_fid</th>\n",
+       "      <th>sum_pop_f_0_2020</th>\n",
+       "      <th>sum_pop_f_10_2020</th>\n",
+       "      <th>sum_pop_f_15_2020</th>\n",
+       "      <th>sum_pop_f_1_2020</th>\n",
+       "      <th>sum_pop_f_20_2020</th>\n",
+       "      <th>sum_pop_f_25_2020</th>\n",
+       "      <th>...</th>\n",
+       "      <th>sum_pop_m_50_2020</th>\n",
+       "      <th>sum_pop_m_55_2020</th>\n",
+       "      <th>sum_pop_m_5_2020</th>\n",
+       "      <th>sum_pop_m_60_2020</th>\n",
+       "      <th>sum_pop_m_65_2020</th>\n",
+       "      <th>sum_pop_m_70_2020</th>\n",
+       "      <th>sum_pop_m_75_2020</th>\n",
+       "      <th>sum_pop_m_80_2020</th>\n",
+       "      <th>sum_pop_m_2020</th>\n",
+       "      <th>sum_pop_f_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>866a4a017ffffff</td>\n",
+       "      <td>POINT (36.07869 5.11252)</td>\n",
+       "      <td>676.912804</td>\n",
+       "      <td>6157254</td>\n",
+       "      <td>8.924362</td>\n",
+       "      <td>49.524105</td>\n",
+       "      <td>36.898296</td>\n",
+       "      <td>32.985901</td>\n",
+       "      <td>28.963400</td>\n",
+       "      <td>33.645473</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6.732327</td>\n",
+       "      <td>4.131749</td>\n",
+       "      <td>53.380043</td>\n",
+       "      <td>3.240541</td>\n",
+       "      <td>2.475817</td>\n",
+       "      <td>0.702667</td>\n",
+       "      <td>0.399492</td>\n",
+       "      <td>0.129285</td>\n",
+       "      <td>336.082180</td>\n",
+       "      <td>340.830624</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>866a4a01fffffff</td>\n",
+       "      <td>POINT (36.13482 5.09047)</td>\n",
+       "      <td>347.182722</td>\n",
+       "      <td>6157255</td>\n",
+       "      <td>4.515680</td>\n",
+       "      <td>24.773327</td>\n",
+       "      <td>19.462585</td>\n",
+       "      <td>16.690670</td>\n",
+       "      <td>15.832314</td>\n",
+       "      <td>16.429201</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.445144</td>\n",
+       "      <td>2.752507</td>\n",
+       "      <td>25.548544</td>\n",
+       "      <td>1.827761</td>\n",
+       "      <td>1.524122</td>\n",
+       "      <td>0.585427</td>\n",
+       "      <td>0.381080</td>\n",
+       "      <td>0.209030</td>\n",
+       "      <td>171.759225</td>\n",
+       "      <td>175.423497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>866a4a04fffffff</td>\n",
+       "      <td>POINT (36.33929 5.11542)</td>\n",
+       "      <td>285.943490</td>\n",
+       "      <td>6157260</td>\n",
+       "      <td>3.642580</td>\n",
+       "      <td>19.623219</td>\n",
+       "      <td>16.698730</td>\n",
+       "      <td>13.463530</td>\n",
+       "      <td>14.255625</td>\n",
+       "      <td>12.501910</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.827743</td>\n",
+       "      <td>3.055085</td>\n",
+       "      <td>18.765499</td>\n",
+       "      <td>1.711561</td>\n",
+       "      <td>1.571700</td>\n",
+       "      <td>0.762171</td>\n",
+       "      <td>0.533085</td>\n",
+       "      <td>0.349744</td>\n",
+       "      <td>140.698267</td>\n",
+       "      <td>145.245222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a057ffffff</td>\n",
+       "      <td>POINT (36.23708 5.10296)</td>\n",
+       "      <td>279.463912</td>\n",
+       "      <td>6157261</td>\n",
+       "      <td>3.560037</td>\n",
+       "      <td>19.178549</td>\n",
+       "      <td>16.320332</td>\n",
+       "      <td>13.158442</td>\n",
+       "      <td>13.932587</td>\n",
+       "      <td>12.218613</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.763665</td>\n",
+       "      <td>2.985856</td>\n",
+       "      <td>18.340267</td>\n",
+       "      <td>1.672776</td>\n",
+       "      <td>1.536084</td>\n",
+       "      <td>0.744900</td>\n",
+       "      <td>0.521005</td>\n",
+       "      <td>0.341818</td>\n",
+       "      <td>137.509998</td>\n",
+       "      <td>141.953914</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>866a4a05fffffff</td>\n",
+       "      <td>POINT (36.29318 5.0809)</td>\n",
+       "      <td>235.258474</td>\n",
+       "      <td>6157262</td>\n",
+       "      <td>2.996913</td>\n",
+       "      <td>16.144897</td>\n",
+       "      <td>13.738791</td>\n",
+       "      <td>11.077046</td>\n",
+       "      <td>11.728739</td>\n",
+       "      <td>10.285879</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.326510</td>\n",
+       "      <td>2.513555</td>\n",
+       "      <td>15.439214</td>\n",
+       "      <td>1.408177</td>\n",
+       "      <td>1.293108</td>\n",
+       "      <td>0.627072</td>\n",
+       "      <td>0.438593</td>\n",
+       "      <td>0.287750</td>\n",
+       "      <td>115.758746</td>\n",
+       "      <td>119.499727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25801</th>\n",
+       "      <td>86969ed97ffffff</td>\n",
+       "      <td>POINT (34.80875 -3.47225)</td>\n",
+       "      <td>196.448391</td>\n",
+       "      <td>8710025</td>\n",
+       "      <td>4.108127</td>\n",
+       "      <td>14.176966</td>\n",
+       "      <td>11.835453</td>\n",
+       "      <td>15.015658</td>\n",
+       "      <td>8.398741</td>\n",
+       "      <td>6.313566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.962373</td>\n",
+       "      <td>1.294143</td>\n",
+       "      <td>16.514441</td>\n",
+       "      <td>1.084920</td>\n",
+       "      <td>0.696495</td>\n",
+       "      <td>0.607390</td>\n",
+       "      <td>0.353109</td>\n",
+       "      <td>0.295762</td>\n",
+       "      <td>96.252689</td>\n",
+       "      <td>100.195702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25802</th>\n",
+       "      <td>86969ed9fffffff</td>\n",
+       "      <td>POINT (34.75041 -3.44944)</td>\n",
+       "      <td>296.740893</td>\n",
+       "      <td>8710026</td>\n",
+       "      <td>6.205442</td>\n",
+       "      <td>21.414711</td>\n",
+       "      <td>17.877789</td>\n",
+       "      <td>22.681580</td>\n",
+       "      <td>12.686538</td>\n",
+       "      <td>9.536821</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.964221</td>\n",
+       "      <td>1.954840</td>\n",
+       "      <td>24.945534</td>\n",
+       "      <td>1.638802</td>\n",
+       "      <td>1.052075</td>\n",
+       "      <td>0.917481</td>\n",
+       "      <td>0.533381</td>\n",
+       "      <td>0.446756</td>\n",
+       "      <td>145.392433</td>\n",
+       "      <td>151.348460</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25803</th>\n",
+       "      <td>86969eda7ffffff</td>\n",
+       "      <td>POINT (34.77046 -3.5715)</td>\n",
+       "      <td>154.818453</td>\n",
+       "      <td>8710027</td>\n",
+       "      <td>3.237562</td>\n",
+       "      <td>11.172684</td>\n",
+       "      <td>9.327369</td>\n",
+       "      <td>11.833648</td>\n",
+       "      <td>6.618940</td>\n",
+       "      <td>4.975640</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.546521</td>\n",
+       "      <td>1.019898</td>\n",
+       "      <td>13.014819</td>\n",
+       "      <td>0.855011</td>\n",
+       "      <td>0.548899</td>\n",
+       "      <td>0.478677</td>\n",
+       "      <td>0.278281</td>\n",
+       "      <td>0.233086</td>\n",
+       "      <td>75.855508</td>\n",
+       "      <td>78.962945</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25804</th>\n",
+       "      <td>86969edafffffff</td>\n",
+       "      <td>POINT (34.7121 -3.54868)</td>\n",
+       "      <td>157.875350</td>\n",
+       "      <td>8710028</td>\n",
+       "      <td>3.301488</td>\n",
+       "      <td>11.393290</td>\n",
+       "      <td>9.511538</td>\n",
+       "      <td>12.067303</td>\n",
+       "      <td>6.749631</td>\n",
+       "      <td>5.073884</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.577057</td>\n",
+       "      <td>1.040035</td>\n",
+       "      <td>13.271797</td>\n",
+       "      <td>0.871894</td>\n",
+       "      <td>0.559737</td>\n",
+       "      <td>0.488128</td>\n",
+       "      <td>0.283775</td>\n",
+       "      <td>0.237688</td>\n",
+       "      <td>77.353279</td>\n",
+       "      <td>80.522071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25805</th>\n",
+       "      <td>86969edb7ffffff</td>\n",
+       "      <td>POINT (34.81878 -3.53328)</td>\n",
+       "      <td>236.127331</td>\n",
+       "      <td>8710029</td>\n",
+       "      <td>4.937892</td>\n",
+       "      <td>17.040451</td>\n",
+       "      <td>14.225995</td>\n",
+       "      <td>18.048544</td>\n",
+       "      <td>10.095131</td>\n",
+       "      <td>7.588790</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.358737</td>\n",
+       "      <td>1.555536</td>\n",
+       "      <td>19.850052</td>\n",
+       "      <td>1.304053</td>\n",
+       "      <td>0.837174</td>\n",
+       "      <td>0.730072</td>\n",
+       "      <td>0.424430</td>\n",
+       "      <td>0.355500</td>\n",
+       "      <td>115.693951</td>\n",
+       "      <td>120.433380</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>25806 rows × 42 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                hex_id                   geometry  sum_pop_2020  ogc_fid  \\\n",
+       "0      866a4a017ffffff   POINT (36.07869 5.11252)    676.912804  6157254   \n",
+       "1      866a4a01fffffff   POINT (36.13482 5.09047)    347.182722  6157255   \n",
+       "2      866a4a04fffffff   POINT (36.33929 5.11542)    285.943490  6157260   \n",
+       "3      866a4a057ffffff   POINT (36.23708 5.10296)    279.463912  6157261   \n",
+       "4      866a4a05fffffff    POINT (36.29318 5.0809)    235.258474  6157262   \n",
+       "...                ...                        ...           ...      ...   \n",
+       "25801  86969ed97ffffff  POINT (34.80875 -3.47225)    196.448391  8710025   \n",
+       "25802  86969ed9fffffff  POINT (34.75041 -3.44944)    296.740893  8710026   \n",
+       "25803  86969eda7ffffff   POINT (34.77046 -3.5715)    154.818453  8710027   \n",
+       "25804  86969edafffffff   POINT (34.7121 -3.54868)    157.875350  8710028   \n",
+       "25805  86969edb7ffffff  POINT (34.81878 -3.53328)    236.127331  8710029   \n",
+       "\n",
+       "       sum_pop_f_0_2020  sum_pop_f_10_2020  sum_pop_f_15_2020  \\\n",
+       "0              8.924362          49.524105          36.898296   \n",
+       "1              4.515680          24.773327          19.462585   \n",
+       "2              3.642580          19.623219          16.698730   \n",
+       "3              3.560037          19.178549          16.320332   \n",
+       "4              2.996913          16.144897          13.738791   \n",
+       "...                 ...                ...                ...   \n",
+       "25801          4.108127          14.176966          11.835453   \n",
+       "25802          6.205442          21.414711          17.877789   \n",
+       "25803          3.237562          11.172684           9.327369   \n",
+       "25804          3.301488          11.393290           9.511538   \n",
+       "25805          4.937892          17.040451          14.225995   \n",
+       "\n",
+       "       sum_pop_f_1_2020  sum_pop_f_20_2020  sum_pop_f_25_2020  ...  \\\n",
+       "0             32.985901          28.963400          33.645473  ...   \n",
+       "1             16.690670          15.832314          16.429201  ...   \n",
+       "2             13.463530          14.255625          12.501910  ...   \n",
+       "3             13.158442          13.932587          12.218613  ...   \n",
+       "4             11.077046          11.728739          10.285879  ...   \n",
+       "...                 ...                ...                ...  ...   \n",
+       "25801         15.015658           8.398741           6.313566  ...   \n",
+       "25802         22.681580          12.686538           9.536821  ...   \n",
+       "25803         11.833648           6.618940           4.975640  ...   \n",
+       "25804         12.067303           6.749631           5.073884  ...   \n",
+       "25805         18.048544          10.095131           7.588790  ...   \n",
+       "\n",
+       "       sum_pop_m_50_2020  sum_pop_m_55_2020  sum_pop_m_5_2020  \\\n",
+       "0               6.732327           4.131749         53.380043   \n",
+       "1               3.445144           2.752507         25.548544   \n",
+       "2               2.827743           3.055085         18.765499   \n",
+       "3               2.763665           2.985856         18.340267   \n",
+       "4               2.326510           2.513555         15.439214   \n",
+       "...                  ...                ...               ...   \n",
+       "25801           1.962373           1.294143         16.514441   \n",
+       "25802           2.964221           1.954840         24.945534   \n",
+       "25803           1.546521           1.019898         13.014819   \n",
+       "25804           1.577057           1.040035         13.271797   \n",
+       "25805           2.358737           1.555536         19.850052   \n",
+       "\n",
+       "       sum_pop_m_60_2020  sum_pop_m_65_2020  sum_pop_m_70_2020  \\\n",
+       "0               3.240541           2.475817           0.702667   \n",
+       "1               1.827761           1.524122           0.585427   \n",
+       "2               1.711561           1.571700           0.762171   \n",
+       "3               1.672776           1.536084           0.744900   \n",
+       "4               1.408177           1.293108           0.627072   \n",
+       "...                  ...                ...                ...   \n",
+       "25801           1.084920           0.696495           0.607390   \n",
+       "25802           1.638802           1.052075           0.917481   \n",
+       "25803           0.855011           0.548899           0.478677   \n",
+       "25804           0.871894           0.559737           0.488128   \n",
+       "25805           1.304053           0.837174           0.730072   \n",
+       "\n",
+       "       sum_pop_m_75_2020  sum_pop_m_80_2020  sum_pop_m_2020  sum_pop_f_2020  \n",
+       "0               0.399492           0.129285      336.082180      340.830624  \n",
+       "1               0.381080           0.209030      171.759225      175.423497  \n",
+       "2               0.533085           0.349744      140.698267      145.245222  \n",
+       "3               0.521005           0.341818      137.509998      141.953914  \n",
+       "4               0.438593           0.287750      115.758746      119.499727  \n",
+       "...                  ...                ...             ...             ...  \n",
+       "25801           0.353109           0.295762       96.252689      100.195702  \n",
+       "25802           0.533381           0.446756      145.392433      151.348460  \n",
+       "25803           0.278281           0.233086       75.855508       78.962945  \n",
+       "25804           0.283775           0.237688       77.353279       80.522071  \n",
+       "25805           0.424430           0.355500      115.693951      120.433380  \n",
+       "\n",
+       "[25806 rows x 42 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"geometry\"] = df[\"geometry\"].apply(lambda geom: shape(json.loads(geom)))\n",
+    "gdf = gpd.GeoDataFrame(df, geometry=\"geometry\", crs=\"EPSG:4326\")\n",
+    "gdf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "496338079450487fbcf9db5fbd702c87",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(custom_attribution='', layers=(ScatterplotLayer(get_fill_color=arro3.core.ChunkedArray<FixedSizeList(Field…"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Define custom breaks and corresponding RGBA colors\n",
+    "breaks = [0, 1, 1000, 10000, 50000, 100000, 200000, gdf[\"sum_pop_2020\"].max()]\n",
+    "colors = np.array(\n",
+    "    [\n",
+    "        [211, 211, 211, 255],  # Light gray for 0\n",
+    "        [255, 255, 0, 255],  # Yellow for 1-1000\n",
+    "        [255, 165, 0, 255],  # Orange for 1000-10000\n",
+    "        [255, 0, 0, 255],  # Red for 10000-50000\n",
+    "        [128, 0, 128, 255],  # Purple for 50000-100000\n",
+    "        [0, 0, 255, 255],  # Blue for 100000-200000\n",
+    "        [0, 0, 139, 255],  # Dark blue for 200000+\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "# Function to assign colors based on custom bins\n",
+    "\n",
+    "\n",
+    "def assign_color(value, breaks, colors):\n",
+    "    for i in range(len(breaks) - 1):\n",
+    "        if breaks[i] <= value < breaks[i + 1]:\n",
+    "            return colors[i]\n",
+    "    return colors[-1]  # In case value exceeds all breaks\n",
+    "\n",
+    "\n",
+    "# Map sum_pop_2020 values to colors using the custom function\n",
+    "gdf[\"color\"] = gdf[\"sum_pop_2020\"].apply(lambda x: assign_color(x, breaks, colors))\n",
+    "colors = np.uint8(gdf[\"color\"].tolist())\n",
+    "\n",
+    "# Create the scatterplot layer with the assigned colors\n",
+    "layer = ScatterplotLayer.from_geopandas(gdf, get_radius=2000, get_fill_color=colors)\n",
+    "\n",
+    "m = Map(layer)\n",
+    "m"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "space2stats-PM9A6h4E-py3.12",
+   "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": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/user-docs/space2stats_api_adm_example.ipynb b/notebooks/user-docs/space2stats_api_adm_example.ipynb
new file mode 100644
index 00000000..64e3d8ab
--- /dev/null
+++ b/notebooks/user-docs/space2stats_api_adm_example.ipynb
@@ -0,0 +1,570 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "from typing import Dict\n",
+    "\n",
+    "import geopandas as gpd\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import requests\n",
+    "from lonboard import Map, PolygonLayer, ScatterplotLayer\n",
+    "from shapely import from_geojson"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "BASE_URL = \"http://127.0.0.1:8000\"\n",
+    "FIELDS_ENDPOINT = f\"{BASE_URL}/fields\"\n",
+    "SUMMARY_ENDPOINT = f\"{BASE_URL}/summary\"\n",
+    "AGGREGATION_ENDPOINT = f\"{BASE_URL}/aggregate\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fetch_admin_boundaries(iso3: str, adm: str) -> gpd.GeoDataFrame:\n",
+    "    \"\"\"Fetch administrative boundaries from GeoBoundaries API.\"\"\"\n",
+    "    url = f\"https://www.geoboundaries.org/api/current/gbOpen/{iso3}/{adm}/\"\n",
+    "    res = requests.get(url).json()\n",
+    "    return gpd.read_file(res[\"gjDownloadURL\"])\n",
+    "\n",
+    "\n",
+    "def fetch_summary_data(feature: Dict) -> pd.DataFrame:\n",
+    "    \"\"\"Fetch summary data for each administrative feature.\"\"\"\n",
+    "    request_payload = {\n",
+    "        \"aoi\": feature,\n",
+    "        \"spatial_join_method\": \"touches\",\n",
+    "        \"fields\": [\"sum_pop_2020\"],\n",
+    "        \"geometry\": \"point\",\n",
+    "    }\n",
+    "    response = requests.post(SUMMARY_ENDPOINT, json=request_payload)\n",
+    "    if response.status_code != 200:\n",
+    "        raise Exception(f\"Failed to get summary: {response.text}\")\n",
+    "\n",
+    "    summary_data = response.json()\n",
+    "    if not summary_data:\n",
+    "        print(f\"Failed to get summary for {feature['id']}\")\n",
+    "        return pd.DataFrame()  # Return an empty DataFrame if no data\n",
+    "\n",
+    "    df = pd.DataFrame(summary_data)\n",
+    "    df[\"adm_id\"] = int(feature[\"id\"])\n",
+    "    df[\"adm_name\"] = feature[\"properties\"][\"shapeName\"]\n",
+    "    df[\"geometry\"] = df[\"geometry\"].apply(lambda geom: from_geojson(geom))\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Turkana 0\n",
+      "Marsabit 1\n",
+      "Mandera 2\n",
+      "Wajir 3\n",
+      "West Pokot 4\n",
+      "Samburu 5\n",
+      "Isiolo 6\n",
+      "Baringo 7\n",
+      "Elgeyo-Marakwet 8\n",
+      "Trans Nzoia 9\n",
+      "Bungoma 10\n",
+      "Garissa 11\n",
+      "Uasin Gishu 12\n",
+      "Kakamega 13\n",
+      "Laikipia 14\n",
+      "Busia 15\n",
+      "Meru 16\n",
+      "Nandi 17\n",
+      "Siaya 18\n",
+      "Nakuru 19\n",
+      "Vihiga 20\n",
+      "Nyandarua 21\n",
+      "Tharaka 22\n",
+      "Kericho 23\n",
+      "Kisumu 24\n",
+      "Nyeri 25\n",
+      "Tana River 26\n",
+      "Kitui 27\n",
+      "Kirinyaga 28\n",
+      "Embu 29\n",
+      "Homa Bay 30\n",
+      "Bomet 31\n",
+      "Nyamira 32\n",
+      "Narok 33\n",
+      "Kisii 34\n",
+      "Murang'a 35\n",
+      "Migori 36\n",
+      "Kiambu 37\n",
+      "Machakos 38\n",
+      "Kajiado 39\n",
+      "Nairobi 40\n",
+      "Makueni 41\n",
+      "Lamu 42\n",
+      "Kilifi 43\n",
+      "Taita Taveta 44\n",
+      "Kwale 45\n",
+      "Mombasa 46\n"
+     ]
+    },
+    {
+     "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>hex_id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "      <th>adm_id</th>\n",
+       "      <th>adm_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>866a4a407ffffff</td>\n",
+       "      <td>POINT (35.80117 4.9048)</td>\n",
+       "      <td>554.655021</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Turkana</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>866a4a417ffffff</td>\n",
+       "      <td>POINT (35.75483 4.8701)</td>\n",
+       "      <td>207.977046</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Turkana</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>866a4a41fffffff</td>\n",
+       "      <td>POINT (35.81106 4.84803)</td>\n",
+       "      <td>637.218817</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Turkana</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a427ffffff</td>\n",
+       "      <td>POINT (35.79128 4.96154)</td>\n",
+       "      <td>948.876730</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Turkana</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>866a4a437ffffff</td>\n",
+       "      <td>POINT (35.74495 4.92687)</td>\n",
+       "      <td>112.805780</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Turkana</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            hex_id                  geometry  sum_pop_2020  adm_id adm_name\n",
+       "0  866a4a407ffffff   POINT (35.80117 4.9048)    554.655021       0  Turkana\n",
+       "1  866a4a417ffffff   POINT (35.75483 4.8701)    207.977046       0  Turkana\n",
+       "2  866a4a41fffffff  POINT (35.81106 4.84803)    637.218817       0  Turkana\n",
+       "3  866a4a427ffffff  POINT (35.79128 4.96154)    948.876730       0  Turkana\n",
+       "4  866a4a437ffffff  POINT (35.74495 4.92687)    112.805780       0  Turkana"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ISO3 = \"KEN\"\n",
+    "ADM = \"ADM1\"\n",
+    "adm_boundaries = fetch_admin_boundaries(ISO3, ADM)\n",
+    "geojson_str = adm_boundaries.to_json()\n",
+    "adm_geojson = json.loads(geojson_str)\n",
+    "adm_features = adm_geojson[\"features\"]\n",
+    "\n",
+    "gdfs = []\n",
+    "for i, feature in enumerate(adm_features):\n",
+    "    df = fetch_summary_data(feature)\n",
+    "    if not df.empty:\n",
+    "        gdfs.append(gpd.GeoDataFrame(df, geometry=\"geometry\", crs=\"EPSG:4326\"))\n",
+    "        print(feature[\"properties\"][\"shapeName\"], i)\n",
+    "\n",
+    "# Concatenate all GeoDataFrames into a single GeoDataFrame\n",
+    "gdf = pd.concat(gdfs, ignore_index=True)\n",
+    "\n",
+    "# Display the GeoDataFrame structure\n",
+    "gdf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define custom breaks and corresponding RGBA colors for visualization\n",
+    "breaks = [\n",
+    "    gdf[\"sum_pop_2020\"].min(),\n",
+    "    1,\n",
+    "    1000,\n",
+    "    10000,\n",
+    "    50000,\n",
+    "    100000,\n",
+    "    200000,\n",
+    "    gdf[\"sum_pop_2020\"].max(),\n",
+    "]\n",
+    "colors = np.array(\n",
+    "    [\n",
+    "        [211, 211, 211, 255],  # Light gray for 0\n",
+    "        [255, 255, 0, 255],  # Yellow for 1-1000\n",
+    "        [255, 165, 0, 255],  # Orange for 1000-10000\n",
+    "        [255, 0, 0, 255],  # Red for 10000-50000\n",
+    "        [128, 0, 128, 255],  # Purple for 50000-100000\n",
+    "        [0, 0, 255, 255],  # Blue for 100000-200000\n",
+    "        [0, 0, 139, 255],  # Dark blue for 200000+\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "def assign_color(value: float) -> list:\n",
+    "    \"\"\"Assign colors based on population value.\"\"\"\n",
+    "    for i in range(len(breaks) - 1):\n",
+    "        if breaks[i] <= value < breaks[i + 1]:\n",
+    "            return colors[i].tolist()  # Convert to list\n",
+    "    return colors[-1].tolist()  # In case value exceeds all breaks"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fcab8e1932cd43d49f23111a0f39c97b",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[ScatterplotLayer(get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x11bd4d7e0>\n",
+       "[\n",
+       "  [\n",
+       "    2…"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Map sum_pop_2020 values to colors using the custom function\n",
+    "gdf[\"color\"] = gdf[\"sum_pop_2020\"].apply(assign_color)\n",
+    "\n",
+    "# Flatten the color list into a 2D array for ScatterplotLayer\n",
+    "color_list = np.array(gdf[\"color\"].tolist(), dtype=np.uint8)\n",
+    "\n",
+    "# Create the scatterplot layer with the assigned colors\n",
+    "layer = ScatterplotLayer.from_geopandas(gdf, get_radius=2000, get_fill_color=color_list)\n",
+    "\n",
+    "# Create the map with the scatterplot layer\n",
+    "m = Map(layer)\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fetch_aggregated_population(row):\n",
+    "    request_payload = {\n",
+    "        \"aoi\": {\n",
+    "            \"type\": \"Feature\",\n",
+    "            \"geometry\": row.geometry.__geo_interface__,\n",
+    "            \"properties\": {},\n",
+    "        },\n",
+    "        \"spatial_join_method\": \"touches\",\n",
+    "        \"fields\": [\"sum_pop_2020\"],\n",
+    "        \"aggregation_type\": \"sum\",\n",
+    "    }\n",
+    "\n",
+    "    response = requests.post(AGGREGATION_ENDPOINT, json=request_payload)\n",
+    "\n",
+    "    if response.status_code == 200:\n",
+    "        result = response.json()\n",
+    "        return result.get(\"sum_pop_2020\", 0)\n",
+    "    else:\n",
+    "        print(response.content)\n",
+    "        return 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "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>geometry</th>\n",
+       "      <th>shapeName</th>\n",
+       "      <th>shapeISO</th>\n",
+       "      <th>shapeID</th>\n",
+       "      <th>shapeGroup</th>\n",
+       "      <th>shapeType</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>POLYGON ((36.05061 4.45622, 35.94395 4.54803, ...</td>\n",
+       "      <td>Turkana</td>\n",
+       "      <td>KE-43</td>\n",
+       "      <td>32016919B72266624462344</td>\n",
+       "      <td>KEN</td>\n",
+       "      <td>ADM1</td>\n",
+       "      <td>1.374176e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>POLYGON ((36.60089 2.40574, 36.60138 2.4053, 3...</td>\n",
+       "      <td>Marsabit</td>\n",
+       "      <td>KE-25</td>\n",
+       "      <td>32016919B63496705134089</td>\n",
+       "      <td>KEN</td>\n",
+       "      <td>ADM1</td>\n",
+       "      <td>4.460342e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>POLYGON ((40.99195 2.17919, 40.99245 2.25188, ...</td>\n",
+       "      <td>Mandera</td>\n",
+       "      <td>KE-24</td>\n",
+       "      <td>32016919B2031803566233</td>\n",
+       "      <td>KEN</td>\n",
+       "      <td>ADM1</td>\n",
+       "      <td>2.815273e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>POLYGON ((38.96255 2.09739, 38.96272 2.09718, ...</td>\n",
+       "      <td>Wajir</td>\n",
+       "      <td>KE-46</td>\n",
+       "      <td>32016919B89873713911655</td>\n",
+       "      <td>KEN</td>\n",
+       "      <td>ADM1</td>\n",
+       "      <td>1.930365e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>POLYGON ((34.94278 2.45547, 34.93892 2.45551, ...</td>\n",
+       "      <td>West Pokot</td>\n",
+       "      <td>KE-47</td>\n",
+       "      <td>32016919B96045830258165</td>\n",
+       "      <td>KEN</td>\n",
+       "      <td>ADM1</td>\n",
+       "      <td>9.429576e+05</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                            geometry   shapeName shapeISO  \\\n",
+       "0  POLYGON ((36.05061 4.45622, 35.94395 4.54803, ...     Turkana    KE-43   \n",
+       "1  POLYGON ((36.60089 2.40574, 36.60138 2.4053, 3...    Marsabit    KE-25   \n",
+       "2  POLYGON ((40.99195 2.17919, 40.99245 2.25188, ...     Mandera    KE-24   \n",
+       "3  POLYGON ((38.96255 2.09739, 38.96272 2.09718, ...       Wajir    KE-46   \n",
+       "4  POLYGON ((34.94278 2.45547, 34.93892 2.45551, ...  West Pokot    KE-47   \n",
+       "\n",
+       "                   shapeID shapeGroup shapeType  sum_pop_2020  \n",
+       "0  32016919B72266624462344        KEN      ADM1  1.374176e+06  \n",
+       "1  32016919B63496705134089        KEN      ADM1  4.460342e+05  \n",
+       "2   32016919B2031803566233        KEN      ADM1  2.815273e+06  \n",
+       "3  32016919B89873713911655        KEN      ADM1  1.930365e+06  \n",
+       "4  32016919B96045830258165        KEN      ADM1  9.429576e+05  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "adm_gdf = gpd.GeoDataFrame.from_features(adm_features)\n",
+    "adm_gdf[\"sum_pop_2020\"] = adm_gdf.apply(fetch_aggregated_population, axis=1)\n",
+    "adm_gdf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "breaks = [\n",
+    "    adm_gdf[\"sum_pop_2020\"].min(),\n",
+    "    10_000,\n",
+    "    100_000,\n",
+    "    1_000_000,\n",
+    "    5_000_000,\n",
+    "    10_000_000,\n",
+    "    20_000_000,\n",
+    "    gdf[\"sum_pop_2020\"].max(),\n",
+    "]\n",
+    "colors = np.array(\n",
+    "    [\n",
+    "        [211, 211, 211, 125],  # Light gray with transparency for 0 - 10,000\n",
+    "        [255, 255, 0, 125],  # Yellow with transparency for 10,000 - 100,000\n",
+    "        [255, 165, 0, 125],  # Orange with transparency for 100,000 - 1,000,000\n",
+    "        [255, 0, 0, 125],  # Red with transparency for 1,000,000 - 5,000,000\n",
+    "        [128, 0, 128, 125],  # Purple with transparency for 5,000,000 - 10,000,000\n",
+    "        [0, 0, 255, 125],  # Blue with transparency for 10,000,000 - 20,000,000\n",
+    "        [0, 0, 139, 125],  # Dark blue with transparency for 20,000,000 - max\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "def assign_color(value: float) -> list:\n",
+    "    \"\"\"Assign colors based on population value, including transparency.\"\"\"\n",
+    "    for i in range(len(breaks) - 1):\n",
+    "        if breaks[i] <= value < breaks[i + 1]:\n",
+    "            return colors[i].tolist()  # Convert to list\n",
+    "    return colors[-1].tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/envs/spacestats/lib/python3.11/site-packages/lonboard/_geoarrow/ops/reproject.py:23: UserWarning: No CRS exists on data. If no data is shown on the map, double check that your CRS is WGS84.\n",
+      "  warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "94fb588e3bdc4ba99ccd323f7aec0889",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[PolygonLayer(get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x11bc82aa0>\n",
+       "[\n",
+       "  [\n",
+       "    255,\n",
+       "…"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Assign colors to each row in gdf based on sum_pop_2020\n",
+    "adm_gdf[\"color\"] = adm_gdf[\"sum_pop_2020\"].apply(assign_color)\n",
+    "\n",
+    "# Convert the list of colors into a 2D numpy array of uint8\n",
+    "color_array = np.array(adm_gdf[\"color\"].tolist(), dtype=np.uint8)\n",
+    "\n",
+    "# Create the polygon layer using PolygonLayer, referencing the color_array\n",
+    "layer = PolygonLayer.from_geopandas(\n",
+    "    adm_gdf,\n",
+    "    get_fill_color=color_array,  # Pass the 2D numpy array for the colors\n",
+    "    get_line_color=[0, 0, 0, 255],  # Optional: Black outline\n",
+    "    line_width_min_pixels=1,\n",
+    ")\n",
+    "\n",
+    "# Create the map with the polygon layer\n",
+    "m = Map(layer)\n",
+    "m"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "spacestats",
+   "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": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/user-docs/space2stats_api_demo.ipynb b/notebooks/user-docs/space2stats_api_demo.ipynb
index bd8e6295..e81c875b 100644
--- a/notebooks/user-docs/space2stats_api_demo.ipynb
+++ b/notebooks/user-docs/space2stats_api_demo.ipynb
@@ -11,35 +11,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
     "from typing import Dict\n",
     "\n",
+    "import geopandas as gpd\n",
     "import numpy as np\n",
-    "import requests\n",
     "import pandas as pd\n",
-    "import geopandas as gpd\n",
-    "from shapely.geometry import shape\n",
+    "import requests\n",
+    "from geojson_pydantic import Feature, Polygon\n",
     "from lonboard import Map, ScatterplotLayer\n",
-    "from geojson_pydantic import Feature, Polygon"
+    "from shapely import from_geojson"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
-    "BASE_URL = \"https://space2stats.ds.io\"\n",
+    "BASE_URL = \"http://localhost:8000\"\n",
     "FIELDS_ENDPOINT = f\"{BASE_URL}/fields\"\n",
     "SUMMARY_ENDPOINT = f\"{BASE_URL}/summary\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -78,32 +78,29 @@
     "                [33.78593974945852, -4.725410543134203],\n",
     "                [41.94362577283266, -4.725410543134203],\n",
     "                [41.94362577283266, 5.115816884114494],\n",
-    "                [33.78593974945852, 5.115816884114494]\n",
+    "                [33.78593974945852, 5.115816884114494],\n",
     "            ]\n",
-    "        ]\n",
+    "        ],\n",
     "    },\n",
-    "    \"properties\": {\n",
-    "        \"name\": \"Updated AOI\"\n",
-    "    }\n",
+    "    \"properties\": {\"name\": \"Updated AOI\"},\n",
     "}\n",
-    "          \n",
-    "  \n",
+    "\n",
     "\n",
     "feat = AOIModel(**aoi)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Define the Request Payload\n",
     "request_payload = {\n",
     "    \"aoi\": aoi,\n",
-    "    \"spatial_join_method\": \"centroid\",\n",
-    "    \"fields\": [\"sum_pop_2020\"], \n",
-    "    \"geometry\": \"point\"\n",
+    "    \"spatial_join_method\": \"touches\",\n",
+    "    \"fields\": [\"sum_pop_2020\"],\n",
+    "    \"geometry\": \"point\",\n",
     "}\n",
     "\n",
     "# Get Summary Data\n",
@@ -117,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -149,33 +146,175 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>866a4a00fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.180976490229...</td>\n",
+       "      <td>476.538185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>866a4a017ffffff</td>\n",
-       "      <td>POINT (36.40245 -0.10117)</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.078694056627...</td>\n",
        "      <td>676.912804</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <th>2</th>\n",
        "      <td>866a4a01fffffff</td>\n",
-       "      <td>POINT (36.29170 -0.39057)</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.134817927246...</td>\n",
        "      <td>347.182722</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a047ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.283201202805...</td>\n",
+       "      <td>380.988678</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
        "      <td>866a4a04fffffff</td>\n",
-       "      <td>POINT (39.40696 -2.61300)</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.339286712001...</td>\n",
        "      <td>285.943490</td>\n",
        "    </tr>\n",
        "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26184</th>\n",
+       "      <td>86969ed97ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.808746693532...</td>\n",
+       "      <td>196.448391</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26185</th>\n",
+       "      <td>86969ed9fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.750412026186...</td>\n",
+       "      <td>296.740893</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26186</th>\n",
+       "      <td>86969eda7ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.770464787099...</td>\n",
+       "      <td>154.818453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26187</th>\n",
+       "      <td>86969edafffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.712102323801...</td>\n",
+       "      <td>157.875350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26188</th>\n",
+       "      <td>86969edb7ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.818784182799...</td>\n",
+       "      <td>236.127331</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>26189 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                hex_id                                           geometry  \\\n",
+       "0      866a4a00fffffff  {\"type\":\"Point\",\"coordinates\":[36.180976490229...   \n",
+       "1      866a4a017ffffff  {\"type\":\"Point\",\"coordinates\":[36.078694056627...   \n",
+       "2      866a4a01fffffff  {\"type\":\"Point\",\"coordinates\":[36.134817927246...   \n",
+       "3      866a4a047ffffff  {\"type\":\"Point\",\"coordinates\":[36.283201202805...   \n",
+       "4      866a4a04fffffff  {\"type\":\"Point\",\"coordinates\":[36.339286712001...   \n",
+       "...                ...                                                ...   \n",
+       "26184  86969ed97ffffff  {\"type\":\"Point\",\"coordinates\":[34.808746693532...   \n",
+       "26185  86969ed9fffffff  {\"type\":\"Point\",\"coordinates\":[34.750412026186...   \n",
+       "26186  86969eda7ffffff  {\"type\":\"Point\",\"coordinates\":[34.770464787099...   \n",
+       "26187  86969edafffffff  {\"type\":\"Point\",\"coordinates\":[34.712102323801...   \n",
+       "26188  86969edb7ffffff  {\"type\":\"Point\",\"coordinates\":[34.818784182799...   \n",
+       "\n",
+       "       sum_pop_2020  \n",
+       "0        476.538185  \n",
+       "1        676.912804  \n",
+       "2        347.182722  \n",
+       "3        380.988678  \n",
+       "4        285.943490  \n",
+       "...             ...  \n",
+       "26184    196.448391  \n",
+       "26185    296.740893  \n",
+       "26186    154.818453  \n",
+       "26187    157.875350  \n",
+       "26188    236.127331  \n",
+       "\n",
+       "[26189 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>hex_id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>866a4a00fffffff</td>\n",
+       "      <td>POINT (36.18098 5.12501)</td>\n",
+       "      <td>476.538185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>866a4a017ffffff</td>\n",
+       "      <td>POINT (36.07869 5.11252)</td>\n",
+       "      <td>676.912804</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>866a4a01fffffff</td>\n",
+       "      <td>POINT (36.13482 5.09047)</td>\n",
+       "      <td>347.182722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>866a4a057ffffff</td>\n",
-       "      <td>POINT (35.34318 -1.13463)</td>\n",
-       "      <td>279.463912</td>\n",
+       "      <td>866a4a047ffffff</td>\n",
+       "      <td>POINT (36.2832 5.13748)</td>\n",
+       "      <td>380.988678</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>866a4a05fffffff</td>\n",
-       "      <td>POINT (34.80333 2.72332)</td>\n",
-       "      <td>235.258474</td>\n",
+       "      <td>866a4a04fffffff</td>\n",
+       "      <td>POINT (36.33929 5.11542)</td>\n",
+       "      <td>285.943490</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -184,115 +323,129 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25801</th>\n",
+       "      <th>26184</th>\n",
        "      <td>86969ed97ffffff</td>\n",
-       "      <td>POINT (35.56103 -0.82817)</td>\n",
+       "      <td>POINT (34.80875 -3.47225)</td>\n",
        "      <td>196.448391</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25802</th>\n",
+       "      <th>26185</th>\n",
        "      <td>86969ed9fffffff</td>\n",
-       "      <td>POINT (41.42538 3.56386)</td>\n",
+       "      <td>POINT (34.75041 -3.44944)</td>\n",
        "      <td>296.740893</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25803</th>\n",
+       "      <th>26186</th>\n",
        "      <td>86969eda7ffffff</td>\n",
-       "      <td>POINT (37.98080 -3.00927)</td>\n",
+       "      <td>POINT (34.77046 -3.5715)</td>\n",
        "      <td>154.818453</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25804</th>\n",
+       "      <th>26187</th>\n",
        "      <td>86969edafffffff</td>\n",
-       "      <td>POINT (39.24303 4.54271)</td>\n",
+       "      <td>POINT (34.7121 -3.54868)</td>\n",
        "      <td>157.875350</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25805</th>\n",
+       "      <th>26188</th>\n",
        "      <td>86969edb7ffffff</td>\n",
-       "      <td>POINT (40.62723 -1.21057)</td>\n",
+       "      <td>POINT (34.81878 -3.53328)</td>\n",
        "      <td>236.127331</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>25806 rows × 3 columns</p>\n",
+       "<p>26189 rows × 3 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "                hex_id                   geometry  sum_pop_2020\n",
-       "0      866a4a017ffffff  POINT (36.40245 -0.10117)    676.912804\n",
-       "1      866a4a01fffffff  POINT (36.29170 -0.39057)    347.182722\n",
-       "2      866a4a04fffffff  POINT (39.40696 -2.61300)    285.943490\n",
-       "3      866a4a057ffffff  POINT (35.34318 -1.13463)    279.463912\n",
-       "4      866a4a05fffffff   POINT (34.80333 2.72332)    235.258474\n",
+       "0      866a4a00fffffff   POINT (36.18098 5.12501)    476.538185\n",
+       "1      866a4a017ffffff   POINT (36.07869 5.11252)    676.912804\n",
+       "2      866a4a01fffffff   POINT (36.13482 5.09047)    347.182722\n",
+       "3      866a4a047ffffff    POINT (36.2832 5.13748)    380.988678\n",
+       "4      866a4a04fffffff   POINT (36.33929 5.11542)    285.943490\n",
        "...                ...                        ...           ...\n",
-       "25801  86969ed97ffffff  POINT (35.56103 -0.82817)    196.448391\n",
-       "25802  86969ed9fffffff   POINT (41.42538 3.56386)    296.740893\n",
-       "25803  86969eda7ffffff  POINT (37.98080 -3.00927)    154.818453\n",
-       "25804  86969edafffffff   POINT (39.24303 4.54271)    157.875350\n",
-       "25805  86969edb7ffffff  POINT (40.62723 -1.21057)    236.127331\n",
+       "26184  86969ed97ffffff  POINT (34.80875 -3.47225)    196.448391\n",
+       "26185  86969ed9fffffff  POINT (34.75041 -3.44944)    296.740893\n",
+       "26186  86969eda7ffffff   POINT (34.77046 -3.5715)    154.818453\n",
+       "26187  86969edafffffff   POINT (34.7121 -3.54868)    157.875350\n",
+       "26188  86969edb7ffffff  POINT (34.81878 -3.53328)    236.127331\n",
        "\n",
-       "[25806 rows x 3 columns]"
+       "[26189 rows x 3 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df['geometry'] = df['geometry'].apply(lambda geom: shape(geom))\n",
-    "gdf = gpd.GeoDataFrame(df, geometry='geometry', crs='EPSG:4326')\n",
+    "df[\"geometry\"] = df[\"geometry\"].apply(lambda geom: from_geojson(geom))\n",
+    "gdf = gpd.GeoDataFrame(df, geometry=\"geometry\", crs=\"EPSG:4326\")\n",
     "gdf"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fc98ebd574fd4a989e4040baf6218300",
+       "model_id": "897d8bcee7ee4431893b3ba08ee67363",
        "version_major": 2,
-       "version_minor": 0
+       "version_minor": 1
       },
       "text/plain": [
-       "Map(layers=[ScatterplotLayer(get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x1681dd180>\n",
+       "Map(layers=[ScatterplotLayer(get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x1411fada0>\n",
        "[\n",
        "  [\n",
        "    2…"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Define custom breaks and corresponding RGBA colors\n",
-    "breaks = [0, 1, 1000, 10000, 50000, 100000, 200000, gdf[\"sum_pop_2020\"].max()]\n",
-    "colors = np.array([\n",
-    "    [211, 211, 211, 255],  # Light gray for 0\n",
-    "    [255, 255, 0, 255],    # Yellow for 1-1000\n",
-    "    [255, 165, 0, 255],    # Orange for 1000-10000\n",
-    "    [255, 0, 0, 255],      # Red for 10000-50000\n",
-    "    [128, 0, 128, 255],    # Purple for 50000-100000\n",
-    "    [0, 0, 255, 255],      # Blue for 100000-200000\n",
-    "    [0, 0, 139, 255],      # Dark blue for 200000+\n",
-    "])\n",
+    "breaks = [\n",
+    "    gdf[\"sum_pop_2020\"].min(),\n",
+    "    1,\n",
+    "    1000,\n",
+    "    10000,\n",
+    "    50000,\n",
+    "    100000,\n",
+    "    200000,\n",
+    "    gdf[\"sum_pop_2020\"].max(),\n",
+    "]\n",
+    "colors = np.array(\n",
+    "    [\n",
+    "        [211, 211, 211, 255],  # Light gray for 0\n",
+    "        [255, 255, 0, 255],  # Yellow for 1-1000\n",
+    "        [255, 165, 0, 255],  # Orange for 1000-10000\n",
+    "        [255, 0, 0, 255],  # Red for 10000-50000\n",
+    "        [128, 0, 128, 255],  # Purple for 50000-100000\n",
+    "        [0, 0, 255, 255],  # Blue for 100000-200000\n",
+    "        [0, 0, 139, 255],  # Dark blue for 200000+\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "# Function to assign colors based on custom bins\n",
+    "\n",
+    "\n",
     "def assign_color(value, breaks, colors):\n",
     "    for i in range(len(breaks) - 1):\n",
     "        if breaks[i] <= value < breaks[i + 1]:\n",
     "            return colors[i]\n",
     "    return colors[-1]  # In case value exceeds all breaks\n",
     "\n",
+    "\n",
     "# Map sum_pop_2020 values to colors using the custom function\n",
-    "gdf['color'] = gdf[\"sum_pop_2020\"].apply(lambda x: assign_color(x, breaks, colors))\n",
-    "colors = np.uint8(gdf['color'].tolist())\n",
+    "gdf[\"color\"] = gdf[\"sum_pop_2020\"].apply(lambda x: assign_color(x, breaks, colors))\n",
+    "colors = np.uint8(gdf[\"color\"].tolist())\n",
     "\n",
     "# Create the scatterplot layer with the assigned colors\n",
     "layer = ScatterplotLayer.from_geopandas(gdf, get_radius=2000, get_fill_color=colors)\n",
@@ -304,7 +457,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "spacestats",
    "language": "python",
    "name": "python3"
   },
@@ -318,7 +471,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/user-docs/space2stats_py_package_demo.ipynb b/notebooks/user-docs/space2stats_py_package_demo.ipynb
index 0e9abfd8..dce9e9c8 100644
--- a/notebooks/user-docs/space2stats_py_package_demo.ipynb
+++ b/notebooks/user-docs/space2stats_py_package_demo.ipynb
@@ -9,30 +9,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%capture\n",
-    "%pip install \"git+https://github.com/worldbank/DECAT_Space2Stats.git#subdirectory=space2stats_api/src\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
     "from typing import Dict\n",
     "\n",
+    "import geopandas as gpd\n",
     "import numpy as np\n",
-    "from dotenv import load_dotenv\n",
     "import pandas as pd\n",
-    "import geopandas as gpd\n",
-    "from shapely.geometry import shape\n",
-    "from lonboard import Map, ScatterplotLayer\n",
+    "from dotenv import load_dotenv\n",
     "from geojson_pydantic import Feature, Polygon\n",
-    "\n",
+    "from lonboard import Map, ScatterplotLayer\n",
+    "from shapely import from_geojson\n",
     "from space2stats import StatsTable"
    ]
   },
@@ -55,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -64,7 +53,7 @@
        "True"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -75,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -123,7 +112,7 @@
        " 'sum_pop_f_2020']"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -137,7 +126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -154,23 +143,120 @@
     "                [33.78593974945852, -4.725410543134203],\n",
     "                [41.94362577283266, -4.725410543134203],\n",
     "                [41.94362577283266, 5.115816884114494],\n",
-    "                [33.78593974945852, 5.115816884114494]\n",
+    "                [33.78593974945852, 5.115816884114494],\n",
     "            ]\n",
-    "        ]\n",
+    "        ],\n",
     "    },\n",
-    "    \"properties\": {\n",
-    "        \"name\": \"Updated AOI\"\n",
-    "    }\n",
+    "    \"properties\": {\"name\": \"Updated AOI\"},\n",
     "}\n",
-    "          \n",
-    "  \n",
+    "\n",
     "\n",
     "feat = AOIModel(**aoi)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 5,
+   "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>hex_id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>sum_pop_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>866a4a00fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.180976490229...</td>\n",
+       "      <td>476.538185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>866a4a017ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.078694056627...</td>\n",
+       "      <td>676.912804</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>866a4a01fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.134817927246...</td>\n",
+       "      <td>347.182722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a047ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.283201202805...</td>\n",
+       "      <td>380.988678</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>866a4a04fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.339286712001...</td>\n",
+       "      <td>285.943490</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            hex_id                                           geometry  \\\n",
+       "0  866a4a00fffffff  {\"type\":\"Point\",\"coordinates\":[36.180976490229...   \n",
+       "1  866a4a017ffffff  {\"type\":\"Point\",\"coordinates\":[36.078694056627...   \n",
+       "2  866a4a01fffffff  {\"type\":\"Point\",\"coordinates\":[36.134817927246...   \n",
+       "3  866a4a047ffffff  {\"type\":\"Point\",\"coordinates\":[36.283201202805...   \n",
+       "4  866a4a04fffffff  {\"type\":\"Point\",\"coordinates\":[36.339286712001...   \n",
+       "\n",
+       "   sum_pop_2020  \n",
+       "0    476.538185  \n",
+       "1    676.912804  \n",
+       "2    347.182722  \n",
+       "3    380.988678  \n",
+       "4    285.943490  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "with StatsTable.connect() as stats_table:\n",
+    "    data = stats_table.summaries(\n",
+    "        aoi=feat,\n",
+    "        spatial_join_method=\"touches\",\n",
+    "        fields=[\"sum_pop_2020\"],\n",
+    "        geometry=\"point\",\n",
+    "    )\n",
+    "    df = pd.DataFrame(data)\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -220,8 +306,32 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>866a4a00fffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.180976490229...</td>\n",
+       "      <td>476.538185</td>\n",
+       "      <td>6157253</td>\n",
+       "      <td>6.070529</td>\n",
+       "      <td>32.703007</td>\n",
+       "      <td>27.829216</td>\n",
+       "      <td>22.437599</td>\n",
+       "      <td>23.757664</td>\n",
+       "      <td>20.835018</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.712565</td>\n",
+       "      <td>5.091442</td>\n",
+       "      <td>31.273582</td>\n",
+       "      <td>2.852396</td>\n",
+       "      <td>2.619311</td>\n",
+       "      <td>1.270194</td>\n",
+       "      <td>0.888411</td>\n",
+       "      <td>0.582864</td>\n",
+       "      <td>234.480238</td>\n",
+       "      <td>242.057947</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>866a4a017ffffff</td>\n",
-       "      <td>{'type': 'Point', 'coordinates': (38.494790325...</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.078694056627...</td>\n",
        "      <td>676.912804</td>\n",
        "      <td>6157254</td>\n",
        "      <td>8.924362</td>\n",
@@ -243,9 +353,9 @@
        "      <td>340.830624</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <th>2</th>\n",
        "      <td>866a4a01fffffff</td>\n",
-       "      <td>{'type': 'Point', 'coordinates': (40.094390450...</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.134817927246...</td>\n",
        "      <td>347.182722</td>\n",
        "      <td>6157255</td>\n",
        "      <td>4.515680</td>\n",
@@ -267,9 +377,33 @@
        "      <td>175.423497</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a047ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.283201202805...</td>\n",
+       "      <td>380.988678</td>\n",
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+       "      <td>4.853342</td>\n",
+       "      <td>26.145809</td>\n",
+       "      <td>22.249249</td>\n",
+       "      <td>17.938692</td>\n",
+       "      <td>18.994072</td>\n",
+       "      <td>16.657440</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.767660</td>\n",
+       "      <td>4.070570</td>\n",
+       "      <td>25.002991</td>\n",
+       "      <td>2.280469</td>\n",
+       "      <td>2.094120</td>\n",
+       "      <td>1.015510</td>\n",
+       "      <td>0.710278</td>\n",
+       "      <td>0.465995</td>\n",
+       "      <td>187.465175</td>\n",
+       "      <td>193.523504</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
        "      <td>866a4a04fffffff</td>\n",
-       "      <td>{'type': 'Point', 'coordinates': (34.462341228...</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[36.339286712001...</td>\n",
        "      <td>285.943490</td>\n",
        "      <td>6157260</td>\n",
        "      <td>3.642580</td>\n",
@@ -291,120 +425,267 @@
        "      <td>145.245222</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>866a4a057ffffff</td>\n",
-       "      <td>{'type': 'Point', 'coordinates': (41.436122880...</td>\n",
-       "      <td>279.463912</td>\n",
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-       "      <td>13.158442</td>\n",
-       "      <td>13.932587</td>\n",
-       "      <td>12.218613</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2.763665</td>\n",
-       "      <td>2.985856</td>\n",
-       "      <td>18.340267</td>\n",
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-       "      <td>0.341818</td>\n",
-       "      <td>137.509998</td>\n",
-       "      <td>141.953914</td>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
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-       "      <td>{'type': 'Point', 'coordinates': (41.251660148...</td>\n",
-       "      <td>235.258474</td>\n",
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-       "      <td>11.077046</td>\n",
-       "      <td>11.728739</td>\n",
-       "      <td>10.285879</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2.326510</td>\n",
-       "      <td>2.513555</td>\n",
-       "      <td>15.439214</td>\n",
-       "      <td>1.408177</td>\n",
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-       "      <td>0.438593</td>\n",
-       "      <td>0.287750</td>\n",
-       "      <td>115.758746</td>\n",
-       "      <td>119.499727</td>\n",
+       "      <th>26184</th>\n",
+       "      <td>86969ed97ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.808746693532...</td>\n",
+       "      <td>196.448391</td>\n",
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+       "      <td>15.015658</td>\n",
+       "      <td>8.398741</td>\n",
+       "      <td>6.313566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.962373</td>\n",
+       "      <td>1.294143</td>\n",
+       "      <td>16.514441</td>\n",
+       "      <td>1.084920</td>\n",
+       "      <td>0.696495</td>\n",
+       "      <td>0.607390</td>\n",
+       "      <td>0.353109</td>\n",
+       "      <td>0.295762</td>\n",
+       "      <td>96.252689</td>\n",
+       "      <td>100.195702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26185</th>\n",
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+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.750412026186...</td>\n",
+       "      <td>296.740893</td>\n",
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+       "      <td>6.205442</td>\n",
+       "      <td>21.414711</td>\n",
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+       "      <td>22.681580</td>\n",
+       "      <td>12.686538</td>\n",
+       "      <td>9.536821</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.964221</td>\n",
+       "      <td>1.954840</td>\n",
+       "      <td>24.945534</td>\n",
+       "      <td>1.638802</td>\n",
+       "      <td>1.052075</td>\n",
+       "      <td>0.917481</td>\n",
+       "      <td>0.533381</td>\n",
+       "      <td>0.446756</td>\n",
+       "      <td>145.392433</td>\n",
+       "      <td>151.348460</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26186</th>\n",
+       "      <td>86969eda7ffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.770464787099...</td>\n",
+       "      <td>154.818453</td>\n",
+       "      <td>8710027</td>\n",
+       "      <td>3.237562</td>\n",
+       "      <td>11.172684</td>\n",
+       "      <td>9.327369</td>\n",
+       "      <td>11.833648</td>\n",
+       "      <td>6.618940</td>\n",
+       "      <td>4.975640</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.546521</td>\n",
+       "      <td>1.019898</td>\n",
+       "      <td>13.014819</td>\n",
+       "      <td>0.855011</td>\n",
+       "      <td>0.548899</td>\n",
+       "      <td>0.478677</td>\n",
+       "      <td>0.278281</td>\n",
+       "      <td>0.233086</td>\n",
+       "      <td>75.855508</td>\n",
+       "      <td>78.962945</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26187</th>\n",
+       "      <td>86969edafffffff</td>\n",
+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.712102323801...</td>\n",
+       "      <td>157.875350</td>\n",
+       "      <td>8710028</td>\n",
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+       "      <td>11.393290</td>\n",
+       "      <td>9.511538</td>\n",
+       "      <td>12.067303</td>\n",
+       "      <td>6.749631</td>\n",
+       "      <td>5.073884</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.577057</td>\n",
+       "      <td>1.040035</td>\n",
+       "      <td>13.271797</td>\n",
+       "      <td>0.871894</td>\n",
+       "      <td>0.559737</td>\n",
+       "      <td>0.488128</td>\n",
+       "      <td>0.283775</td>\n",
+       "      <td>0.237688</td>\n",
+       "      <td>77.353279</td>\n",
+       "      <td>80.522071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26188</th>\n",
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+       "      <td>{\"type\":\"Point\",\"coordinates\":[34.818784182799...</td>\n",
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+       "      <td>17.040451</td>\n",
+       "      <td>14.225995</td>\n",
+       "      <td>18.048544</td>\n",
+       "      <td>10.095131</td>\n",
+       "      <td>7.588790</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.358737</td>\n",
+       "      <td>1.555536</td>\n",
+       "      <td>19.850052</td>\n",
+       "      <td>1.304053</td>\n",
+       "      <td>0.837174</td>\n",
+       "      <td>0.730072</td>\n",
+       "      <td>0.424430</td>\n",
+       "      <td>0.355500</td>\n",
+       "      <td>115.693951</td>\n",
+       "      <td>120.433380</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 42 columns</p>\n",
+       "<p>26189 rows × 42 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "            hex_id                                           geometry  \\\n",
-       "0  866a4a017ffffff  {'type': 'Point', 'coordinates': (38.494790325...   \n",
-       "1  866a4a01fffffff  {'type': 'Point', 'coordinates': (40.094390450...   \n",
-       "2  866a4a04fffffff  {'type': 'Point', 'coordinates': (34.462341228...   \n",
-       "3  866a4a057ffffff  {'type': 'Point', 'coordinates': (41.436122880...   \n",
-       "4  866a4a05fffffff  {'type': 'Point', 'coordinates': (41.251660148...   \n",
+       "                hex_id                                           geometry  \\\n",
+       "0      866a4a00fffffff  {\"type\":\"Point\",\"coordinates\":[36.180976490229...   \n",
+       "1      866a4a017ffffff  {\"type\":\"Point\",\"coordinates\":[36.078694056627...   \n",
+       "2      866a4a01fffffff  {\"type\":\"Point\",\"coordinates\":[36.134817927246...   \n",
+       "3      866a4a047ffffff  {\"type\":\"Point\",\"coordinates\":[36.283201202805...   \n",
+       "4      866a4a04fffffff  {\"type\":\"Point\",\"coordinates\":[36.339286712001...   \n",
+       "...                ...                                                ...   \n",
+       "26184  86969ed97ffffff  {\"type\":\"Point\",\"coordinates\":[34.808746693532...   \n",
+       "26185  86969ed9fffffff  {\"type\":\"Point\",\"coordinates\":[34.750412026186...   \n",
+       "26186  86969eda7ffffff  {\"type\":\"Point\",\"coordinates\":[34.770464787099...   \n",
+       "26187  86969edafffffff  {\"type\":\"Point\",\"coordinates\":[34.712102323801...   \n",
+       "26188  86969edb7ffffff  {\"type\":\"Point\",\"coordinates\":[34.818784182799...   \n",
+       "\n",
+       "       sum_pop_2020  ogc_fid  sum_pop_f_0_2020  sum_pop_f_10_2020  \\\n",
+       "0        476.538185  6157253          6.070529          32.703007   \n",
+       "1        676.912804  6157254          8.924362          49.524105   \n",
+       "2        347.182722  6157255          4.515680          24.773327   \n",
+       "3        380.988678  6157259          4.853342          26.145809   \n",
+       "4        285.943490  6157260          3.642580          19.623219   \n",
+       "...             ...      ...               ...                ...   \n",
+       "26184    196.448391  8710025          4.108127          14.176966   \n",
+       "26185    296.740893  8710026          6.205442          21.414711   \n",
+       "26186    154.818453  8710027          3.237562          11.172684   \n",
+       "26187    157.875350  8710028          3.301488          11.393290   \n",
+       "26188    236.127331  8710029          4.937892          17.040451   \n",
        "\n",
-       "   sum_pop_2020  ogc_fid  sum_pop_f_0_2020  sum_pop_f_10_2020  \\\n",
-       "0    676.912804  6157254          8.924362          49.524105   \n",
-       "1    347.182722  6157255          4.515680          24.773327   \n",
-       "2    285.943490  6157260          3.642580          19.623219   \n",
-       "3    279.463912  6157261          3.560037          19.178549   \n",
-       "4    235.258474  6157262          2.996913          16.144897   \n",
+       "       sum_pop_f_15_2020  sum_pop_f_1_2020  sum_pop_f_20_2020  \\\n",
+       "0              27.829216         22.437599          23.757664   \n",
+       "1              36.898296         32.985901          28.963400   \n",
+       "2              19.462585         16.690670          15.832314   \n",
+       "3              22.249249         17.938692          18.994072   \n",
+       "4              16.698730         13.463530          14.255625   \n",
+       "...                  ...               ...                ...   \n",
+       "26184          11.835453         15.015658           8.398741   \n",
+       "26185          17.877789         22.681580          12.686538   \n",
+       "26186           9.327369         11.833648           6.618940   \n",
+       "26187           9.511538         12.067303           6.749631   \n",
+       "26188          14.225995         18.048544          10.095131   \n",
        "\n",
-       "   sum_pop_f_15_2020  sum_pop_f_1_2020  sum_pop_f_20_2020  sum_pop_f_25_2020  \\\n",
-       "0          36.898296         32.985901          28.963400          33.645473   \n",
-       "1          19.462585         16.690670          15.832314          16.429201   \n",
-       "2          16.698730         13.463530          14.255625          12.501910   \n",
-       "3          16.320332         13.158442          13.932587          12.218613   \n",
-       "4          13.738791         11.077046          11.728739          10.285879   \n",
+       "       sum_pop_f_25_2020  ...  sum_pop_m_50_2020  sum_pop_m_55_2020  \\\n",
+       "0              20.835018  ...           4.712565           5.091442   \n",
+       "1              33.645473  ...           6.732327           4.131749   \n",
+       "2              16.429201  ...           3.445144           2.752507   \n",
+       "3              16.657440  ...           3.767660           4.070570   \n",
+       "4              12.501910  ...           2.827743           3.055085   \n",
+       "...                  ...  ...                ...                ...   \n",
+       "26184           6.313566  ...           1.962373           1.294143   \n",
+       "26185           9.536821  ...           2.964221           1.954840   \n",
+       "26186           4.975640  ...           1.546521           1.019898   \n",
+       "26187           5.073884  ...           1.577057           1.040035   \n",
+       "26188           7.588790  ...           2.358737           1.555536   \n",
        "\n",
-       "   ...  sum_pop_m_50_2020  sum_pop_m_55_2020  sum_pop_m_5_2020  \\\n",
-       "0  ...           6.732327           4.131749         53.380043   \n",
-       "1  ...           3.445144           2.752507         25.548544   \n",
-       "2  ...           2.827743           3.055085         18.765499   \n",
-       "3  ...           2.763665           2.985856         18.340267   \n",
-       "4  ...           2.326510           2.513555         15.439214   \n",
+       "       sum_pop_m_5_2020  sum_pop_m_60_2020  sum_pop_m_65_2020  \\\n",
+       "0             31.273582           2.852396           2.619311   \n",
+       "1             53.380043           3.240541           2.475817   \n",
+       "2             25.548544           1.827761           1.524122   \n",
+       "3             25.002991           2.280469           2.094120   \n",
+       "4             18.765499           1.711561           1.571700   \n",
+       "...                 ...                ...                ...   \n",
+       "26184         16.514441           1.084920           0.696495   \n",
+       "26185         24.945534           1.638802           1.052075   \n",
+       "26186         13.014819           0.855011           0.548899   \n",
+       "26187         13.271797           0.871894           0.559737   \n",
+       "26188         19.850052           1.304053           0.837174   \n",
        "\n",
-       "   sum_pop_m_60_2020  sum_pop_m_65_2020  sum_pop_m_70_2020  sum_pop_m_75_2020  \\\n",
-       "0           3.240541           2.475817           0.702667           0.399492   \n",
-       "1           1.827761           1.524122           0.585427           0.381080   \n",
-       "2           1.711561           1.571700           0.762171           0.533085   \n",
-       "3           1.672776           1.536084           0.744900           0.521005   \n",
-       "4           1.408177           1.293108           0.627072           0.438593   \n",
+       "       sum_pop_m_70_2020  sum_pop_m_75_2020  sum_pop_m_80_2020  \\\n",
+       "0               1.270194           0.888411           0.582864   \n",
+       "1               0.702667           0.399492           0.129285   \n",
+       "2               0.585427           0.381080           0.209030   \n",
+       "3               1.015510           0.710278           0.465995   \n",
+       "4               0.762171           0.533085           0.349744   \n",
+       "...                  ...                ...                ...   \n",
+       "26184           0.607390           0.353109           0.295762   \n",
+       "26185           0.917481           0.533381           0.446756   \n",
+       "26186           0.478677           0.278281           0.233086   \n",
+       "26187           0.488128           0.283775           0.237688   \n",
+       "26188           0.730072           0.424430           0.355500   \n",
        "\n",
-       "   sum_pop_m_80_2020  sum_pop_m_2020  sum_pop_f_2020  \n",
-       "0           0.129285      336.082180      340.830624  \n",
-       "1           0.209030      171.759225      175.423497  \n",
-       "2           0.349744      140.698267      145.245222  \n",
-       "3           0.341818      137.509998      141.953914  \n",
-       "4           0.287750      115.758746      119.499727  \n",
+       "       sum_pop_m_2020  sum_pop_f_2020  \n",
+       "0          234.480238      242.057947  \n",
+       "1          336.082180      340.830624  \n",
+       "2          171.759225      175.423497  \n",
+       "3          187.465175      193.523504  \n",
+       "4          140.698267      145.245222  \n",
+       "...               ...             ...  \n",
+       "26184       96.252689      100.195702  \n",
+       "26185      145.392433      151.348460  \n",
+       "26186       75.855508       78.962945  \n",
+       "26187       77.353279       80.522071  \n",
+       "26188      115.693951      120.433380  \n",
        "\n",
-       "[5 rows x 42 columns]"
+       "[26189 rows x 42 columns]"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "with StatsTable.connect() as stats_table:\n",
-    "    data = stats_table.summaries(aoi=feat, spatial_join_method=\"centroid\", fields=fields, geometry=\"point\")\n",
+    "    data = stats_table.summaries(\n",
+    "        aoi=feat, spatial_join_method=\"touches\", fields=fields, geometry=\"point\"\n",
+    "    )\n",
     "    df = pd.DataFrame(data)\n",
     "\n",
-    "df.head()"
+    "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -454,8 +735,32 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>866a4a00fffffff</td>\n",
+       "      <td>POINT (36.18098 5.12501)</td>\n",
+       "      <td>476.538185</td>\n",
+       "      <td>6157253</td>\n",
+       "      <td>6.070529</td>\n",
+       "      <td>32.703007</td>\n",
+       "      <td>27.829216</td>\n",
+       "      <td>22.437599</td>\n",
+       "      <td>23.757664</td>\n",
+       "      <td>20.835018</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.712565</td>\n",
+       "      <td>5.091442</td>\n",
+       "      <td>31.273582</td>\n",
+       "      <td>2.852396</td>\n",
+       "      <td>2.619311</td>\n",
+       "      <td>1.270194</td>\n",
+       "      <td>0.888411</td>\n",
+       "      <td>0.582864</td>\n",
+       "      <td>234.480238</td>\n",
+       "      <td>242.057947</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>866a4a017ffffff</td>\n",
-       "      <td>POINT (38.49479 -0.20685)</td>\n",
+       "      <td>POINT (36.07869 5.11252)</td>\n",
        "      <td>676.912804</td>\n",
        "      <td>6157254</td>\n",
        "      <td>8.924362</td>\n",
@@ -477,9 +782,9 @@
        "      <td>340.830624</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <th>2</th>\n",
        "      <td>866a4a01fffffff</td>\n",
-       "      <td>POINT (40.09439 0.52663)</td>\n",
+       "      <td>POINT (36.13482 5.09047)</td>\n",
        "      <td>347.182722</td>\n",
        "      <td>6157255</td>\n",
        "      <td>4.515680</td>\n",
@@ -501,9 +806,33 @@
        "      <td>175.423497</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <td>866a4a047ffffff</td>\n",
+       "      <td>POINT (36.2832 5.13748)</td>\n",
+       "      <td>380.988678</td>\n",
+       "      <td>6157259</td>\n",
+       "      <td>4.853342</td>\n",
+       "      <td>26.145809</td>\n",
+       "      <td>22.249249</td>\n",
+       "      <td>17.938692</td>\n",
+       "      <td>18.994072</td>\n",
+       "      <td>16.657440</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.767660</td>\n",
+       "      <td>4.070570</td>\n",
+       "      <td>25.002991</td>\n",
+       "      <td>2.280469</td>\n",
+       "      <td>2.094120</td>\n",
+       "      <td>1.015510</td>\n",
+       "      <td>0.710278</td>\n",
+       "      <td>0.465995</td>\n",
+       "      <td>187.465175</td>\n",
+       "      <td>193.523504</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
        "      <td>866a4a04fffffff</td>\n",
-       "      <td>POINT (34.46234 5.05804)</td>\n",
+       "      <td>POINT (36.33929 5.11542)</td>\n",
        "      <td>285.943490</td>\n",
        "      <td>6157260</td>\n",
        "      <td>3.642580</td>\n",
@@ -525,54 +854,6 @@
        "      <td>145.245222</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>866a4a057ffffff</td>\n",
-       "      <td>POINT (41.43612 -4.68139)</td>\n",
-       "      <td>279.463912</td>\n",
-       "      <td>6157261</td>\n",
-       "      <td>3.560037</td>\n",
-       "      <td>19.178549</td>\n",
-       "      <td>16.320332</td>\n",
-       "      <td>13.158442</td>\n",
-       "      <td>13.932587</td>\n",
-       "      <td>12.218613</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2.763665</td>\n",
-       "      <td>2.985856</td>\n",
-       "      <td>18.340267</td>\n",
-       "      <td>1.672776</td>\n",
-       "      <td>1.536084</td>\n",
-       "      <td>0.744900</td>\n",
-       "      <td>0.521005</td>\n",
-       "      <td>0.341818</td>\n",
-       "      <td>137.509998</td>\n",
-       "      <td>141.953914</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>866a4a05fffffff</td>\n",
-       "      <td>POINT (41.25166 -0.09407)</td>\n",
-       "      <td>235.258474</td>\n",
-       "      <td>6157262</td>\n",
-       "      <td>2.996913</td>\n",
-       "      <td>16.144897</td>\n",
-       "      <td>13.738791</td>\n",
-       "      <td>11.077046</td>\n",
-       "      <td>11.728739</td>\n",
-       "      <td>10.285879</td>\n",
-       "      <td>...</td>\n",
-       "      <td>2.326510</td>\n",
-       "      <td>2.513555</td>\n",
-       "      <td>15.439214</td>\n",
-       "      <td>1.408177</td>\n",
-       "      <td>1.293108</td>\n",
-       "      <td>0.627072</td>\n",
-       "      <td>0.438593</td>\n",
-       "      <td>0.287750</td>\n",
-       "      <td>115.758746</td>\n",
-       "      <td>119.499727</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
@@ -597,9 +878,9 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25801</th>\n",
+       "      <th>26184</th>\n",
        "      <td>86969ed97ffffff</td>\n",
-       "      <td>POINT (36.22291 0.63262)</td>\n",
+       "      <td>POINT (34.80875 -3.47225)</td>\n",
        "      <td>196.448391</td>\n",
        "      <td>8710025</td>\n",
        "      <td>4.108127</td>\n",
@@ -621,9 +902,9 @@
        "      <td>100.195702</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25802</th>\n",
+       "      <th>26185</th>\n",
        "      <td>86969ed9fffffff</td>\n",
-       "      <td>POINT (36.93237 -1.31051)</td>\n",
+       "      <td>POINT (34.75041 -3.44944)</td>\n",
        "      <td>296.740893</td>\n",
        "      <td>8710026</td>\n",
        "      <td>6.205442</td>\n",
@@ -645,9 +926,9 @@
        "      <td>151.348460</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25803</th>\n",
+       "      <th>26186</th>\n",
        "      <td>86969eda7ffffff</td>\n",
-       "      <td>POINT (37.92797 0.89329)</td>\n",
+       "      <td>POINT (34.77046 -3.5715)</td>\n",
        "      <td>154.818453</td>\n",
        "      <td>8710027</td>\n",
        "      <td>3.237562</td>\n",
@@ -669,9 +950,9 @@
        "      <td>78.962945</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25804</th>\n",
+       "      <th>26187</th>\n",
        "      <td>86969edafffffff</td>\n",
-       "      <td>POINT (39.02185 -1.07532)</td>\n",
+       "      <td>POINT (34.7121 -3.54868)</td>\n",
        "      <td>157.875350</td>\n",
        "      <td>8710028</td>\n",
        "      <td>3.301488</td>\n",
@@ -693,9 +974,9 @@
        "      <td>80.522071</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25805</th>\n",
+       "      <th>26188</th>\n",
        "      <td>86969edb7ffffff</td>\n",
-       "      <td>POINT (36.5281 3.44777)</td>\n",
+       "      <td>POINT (34.81878 -3.53328)</td>\n",
        "      <td>236.127331</td>\n",
        "      <td>8710029</td>\n",
        "      <td>4.937892</td>\n",
@@ -718,149 +999,160 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>25806 rows × 42 columns</p>\n",
+       "<p>26189 rows × 42 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "                hex_id                   geometry  sum_pop_2020  ogc_fid  \\\n",
-       "0      866a4a017ffffff  POINT (38.49479 -0.20685)    676.912804  6157254   \n",
-       "1      866a4a01fffffff   POINT (40.09439 0.52663)    347.182722  6157255   \n",
-       "2      866a4a04fffffff   POINT (34.46234 5.05804)    285.943490  6157260   \n",
-       "3      866a4a057ffffff  POINT (41.43612 -4.68139)    279.463912  6157261   \n",
-       "4      866a4a05fffffff  POINT (41.25166 -0.09407)    235.258474  6157262   \n",
+       "0      866a4a00fffffff   POINT (36.18098 5.12501)    476.538185  6157253   \n",
+       "1      866a4a017ffffff   POINT (36.07869 5.11252)    676.912804  6157254   \n",
+       "2      866a4a01fffffff   POINT (36.13482 5.09047)    347.182722  6157255   \n",
+       "3      866a4a047ffffff    POINT (36.2832 5.13748)    380.988678  6157259   \n",
+       "4      866a4a04fffffff   POINT (36.33929 5.11542)    285.943490  6157260   \n",
        "...                ...                        ...           ...      ...   \n",
-       "25801  86969ed97ffffff   POINT (36.22291 0.63262)    196.448391  8710025   \n",
-       "25802  86969ed9fffffff  POINT (36.93237 -1.31051)    296.740893  8710026   \n",
-       "25803  86969eda7ffffff   POINT (37.92797 0.89329)    154.818453  8710027   \n",
-       "25804  86969edafffffff  POINT (39.02185 -1.07532)    157.875350  8710028   \n",
-       "25805  86969edb7ffffff    POINT (36.5281 3.44777)    236.127331  8710029   \n",
+       "26184  86969ed97ffffff  POINT (34.80875 -3.47225)    196.448391  8710025   \n",
+       "26185  86969ed9fffffff  POINT (34.75041 -3.44944)    296.740893  8710026   \n",
+       "26186  86969eda7ffffff   POINT (34.77046 -3.5715)    154.818453  8710027   \n",
+       "26187  86969edafffffff   POINT (34.7121 -3.54868)    157.875350  8710028   \n",
+       "26188  86969edb7ffffff  POINT (34.81878 -3.53328)    236.127331  8710029   \n",
        "\n",
        "       sum_pop_f_0_2020  sum_pop_f_10_2020  sum_pop_f_15_2020  \\\n",
-       "0              8.924362          49.524105          36.898296   \n",
-       "1              4.515680          24.773327          19.462585   \n",
-       "2              3.642580          19.623219          16.698730   \n",
-       "3              3.560037          19.178549          16.320332   \n",
-       "4              2.996913          16.144897          13.738791   \n",
+       "0              6.070529          32.703007          27.829216   \n",
+       "1              8.924362          49.524105          36.898296   \n",
+       "2              4.515680          24.773327          19.462585   \n",
+       "3              4.853342          26.145809          22.249249   \n",
+       "4              3.642580          19.623219          16.698730   \n",
        "...                 ...                ...                ...   \n",
-       "25801          4.108127          14.176966          11.835453   \n",
-       "25802          6.205442          21.414711          17.877789   \n",
-       "25803          3.237562          11.172684           9.327369   \n",
-       "25804          3.301488          11.393290           9.511538   \n",
-       "25805          4.937892          17.040451          14.225995   \n",
+       "26184          4.108127          14.176966          11.835453   \n",
+       "26185          6.205442          21.414711          17.877789   \n",
+       "26186          3.237562          11.172684           9.327369   \n",
+       "26187          3.301488          11.393290           9.511538   \n",
+       "26188          4.937892          17.040451          14.225995   \n",
        "\n",
        "       sum_pop_f_1_2020  sum_pop_f_20_2020  sum_pop_f_25_2020  ...  \\\n",
-       "0             32.985901          28.963400          33.645473  ...   \n",
-       "1             16.690670          15.832314          16.429201  ...   \n",
-       "2             13.463530          14.255625          12.501910  ...   \n",
-       "3             13.158442          13.932587          12.218613  ...   \n",
-       "4             11.077046          11.728739          10.285879  ...   \n",
+       "0             22.437599          23.757664          20.835018  ...   \n",
+       "1             32.985901          28.963400          33.645473  ...   \n",
+       "2             16.690670          15.832314          16.429201  ...   \n",
+       "3             17.938692          18.994072          16.657440  ...   \n",
+       "4             13.463530          14.255625          12.501910  ...   \n",
        "...                 ...                ...                ...  ...   \n",
-       "25801         15.015658           8.398741           6.313566  ...   \n",
-       "25802         22.681580          12.686538           9.536821  ...   \n",
-       "25803         11.833648           6.618940           4.975640  ...   \n",
-       "25804         12.067303           6.749631           5.073884  ...   \n",
-       "25805         18.048544          10.095131           7.588790  ...   \n",
+       "26184         15.015658           8.398741           6.313566  ...   \n",
+       "26185         22.681580          12.686538           9.536821  ...   \n",
+       "26186         11.833648           6.618940           4.975640  ...   \n",
+       "26187         12.067303           6.749631           5.073884  ...   \n",
+       "26188         18.048544          10.095131           7.588790  ...   \n",
        "\n",
        "       sum_pop_m_50_2020  sum_pop_m_55_2020  sum_pop_m_5_2020  \\\n",
-       "0               6.732327           4.131749         53.380043   \n",
-       "1               3.445144           2.752507         25.548544   \n",
-       "2               2.827743           3.055085         18.765499   \n",
-       "3               2.763665           2.985856         18.340267   \n",
-       "4               2.326510           2.513555         15.439214   \n",
+       "0               4.712565           5.091442         31.273582   \n",
+       "1               6.732327           4.131749         53.380043   \n",
+       "2               3.445144           2.752507         25.548544   \n",
+       "3               3.767660           4.070570         25.002991   \n",
+       "4               2.827743           3.055085         18.765499   \n",
        "...                  ...                ...               ...   \n",
-       "25801           1.962373           1.294143         16.514441   \n",
-       "25802           2.964221           1.954840         24.945534   \n",
-       "25803           1.546521           1.019898         13.014819   \n",
-       "25804           1.577057           1.040035         13.271797   \n",
-       "25805           2.358737           1.555536         19.850052   \n",
+       "26184           1.962373           1.294143         16.514441   \n",
+       "26185           2.964221           1.954840         24.945534   \n",
+       "26186           1.546521           1.019898         13.014819   \n",
+       "26187           1.577057           1.040035         13.271797   \n",
+       "26188           2.358737           1.555536         19.850052   \n",
        "\n",
        "       sum_pop_m_60_2020  sum_pop_m_65_2020  sum_pop_m_70_2020  \\\n",
-       "0               3.240541           2.475817           0.702667   \n",
-       "1               1.827761           1.524122           0.585427   \n",
-       "2               1.711561           1.571700           0.762171   \n",
-       "3               1.672776           1.536084           0.744900   \n",
-       "4               1.408177           1.293108           0.627072   \n",
+       "0               2.852396           2.619311           1.270194   \n",
+       "1               3.240541           2.475817           0.702667   \n",
+       "2               1.827761           1.524122           0.585427   \n",
+       "3               2.280469           2.094120           1.015510   \n",
+       "4               1.711561           1.571700           0.762171   \n",
        "...                  ...                ...                ...   \n",
-       "25801           1.084920           0.696495           0.607390   \n",
-       "25802           1.638802           1.052075           0.917481   \n",
-       "25803           0.855011           0.548899           0.478677   \n",
-       "25804           0.871894           0.559737           0.488128   \n",
-       "25805           1.304053           0.837174           0.730072   \n",
+       "26184           1.084920           0.696495           0.607390   \n",
+       "26185           1.638802           1.052075           0.917481   \n",
+       "26186           0.855011           0.548899           0.478677   \n",
+       "26187           0.871894           0.559737           0.488128   \n",
+       "26188           1.304053           0.837174           0.730072   \n",
        "\n",
        "       sum_pop_m_75_2020  sum_pop_m_80_2020  sum_pop_m_2020  sum_pop_f_2020  \n",
-       "0               0.399492           0.129285      336.082180      340.830624  \n",
-       "1               0.381080           0.209030      171.759225      175.423497  \n",
-       "2               0.533085           0.349744      140.698267      145.245222  \n",
-       "3               0.521005           0.341818      137.509998      141.953914  \n",
-       "4               0.438593           0.287750      115.758746      119.499727  \n",
+       "0               0.888411           0.582864      234.480238      242.057947  \n",
+       "1               0.399492           0.129285      336.082180      340.830624  \n",
+       "2               0.381080           0.209030      171.759225      175.423497  \n",
+       "3               0.710278           0.465995      187.465175      193.523504  \n",
+       "4               0.533085           0.349744      140.698267      145.245222  \n",
        "...                  ...                ...             ...             ...  \n",
-       "25801           0.353109           0.295762       96.252689      100.195702  \n",
-       "25802           0.533381           0.446756      145.392433      151.348460  \n",
-       "25803           0.278281           0.233086       75.855508       78.962945  \n",
-       "25804           0.283775           0.237688       77.353279       80.522071  \n",
-       "25805           0.424430           0.355500      115.693951      120.433380  \n",
+       "26184           0.353109           0.295762       96.252689      100.195702  \n",
+       "26185           0.533381           0.446756      145.392433      151.348460  \n",
+       "26186           0.278281           0.233086       75.855508       78.962945  \n",
+       "26187           0.283775           0.237688       77.353279       80.522071  \n",
+       "26188           0.424430           0.355500      115.693951      120.433380  \n",
        "\n",
-       "[25806 rows x 42 columns]"
+       "[26189 rows x 42 columns]"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df['geometry'] = df['geometry'].apply(lambda geom: shape(geom))\n",
-    "gdf = gpd.GeoDataFrame(df, geometry='geometry', crs='EPSG:4326')\n",
+    "df[\"geometry\"] = df[\"geometry\"].apply(lambda geom: from_geojson(geom))\n",
+    "gdf = gpd.GeoDataFrame(df, geometry=\"geometry\", crs=\"EPSG:4326\")\n",
     "gdf"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e472e297d8dc4c5582193eab628f4d44",
+       "model_id": "6868905940b74debbc4b3f7cd62770a5",
        "version_major": 2,
        "version_minor": 1
       },
       "text/plain": [
-       "Map(layers=[ScatterplotLayer(get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x150f0dcc0>\n",
-       "[\n",
-       "  [\n",
-       "    2…"
+       "Map(custom_attribution='', layers=(ScatterplotLayer(get_fill_color=arro3.core.ChunkedArray<FixedSizeList(Field…"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Define custom breaks and corresponding RGBA colors\n",
-    "breaks = [0, 1, 1000, 10000, 50000, 100000, 200000, gdf[\"sum_pop_2020\"].max()]\n",
-    "colors = np.array([\n",
-    "    [211, 211, 211, 255],  # Light gray for 0\n",
-    "    [255, 255, 0, 255],    # Yellow for 1-1000\n",
-    "    [255, 165, 0, 255],    # Orange for 1000-10000\n",
-    "    [255, 0, 0, 255],      # Red for 10000-50000\n",
-    "    [128, 0, 128, 255],    # Purple for 50000-100000\n",
-    "    [0, 0, 255, 255],      # Blue for 100000-200000\n",
-    "    [0, 0, 139, 255],      # Dark blue for 200000+\n",
-    "])\n",
+    "breaks = [\n",
+    "    gdf[\"sum_pop_2020\"].min(),\n",
+    "    1,\n",
+    "    1000,\n",
+    "    10000,\n",
+    "    50000,\n",
+    "    100000,\n",
+    "    200000,\n",
+    "    gdf[\"sum_pop_2020\"].max(),\n",
+    "]\n",
+    "colors = np.array(\n",
+    "    [\n",
+    "        [211, 211, 211, 255],  # Light gray for 0\n",
+    "        [255, 255, 0, 255],  # Yellow for 1-1000\n",
+    "        [255, 165, 0, 255],  # Orange for 1000-10000\n",
+    "        [255, 0, 0, 255],  # Red for 10000-50000\n",
+    "        [128, 0, 128, 255],  # Purple for 50000-100000\n",
+    "        [0, 0, 255, 255],  # Blue for 100000-200000\n",
+    "        [0, 0, 139, 255],  # Dark blue for 200000+\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "# Function to assign colors based on custom bins\n",
+    "\n",
+    "\n",
     "def assign_color(value, breaks, colors):\n",
     "    for i in range(len(breaks) - 1):\n",
     "        if breaks[i] <= value < breaks[i + 1]:\n",
     "            return colors[i]\n",
     "    return colors[-1]  # In case value exceeds all breaks\n",
     "\n",
+    "\n",
     "# Map sum_pop_2020 values to colors using the custom function\n",
-    "gdf['color'] = gdf[\"sum_pop_2020\"].apply(lambda x: assign_color(x, breaks, colors))\n",
-    "colors = np.uint8(gdf['color'].tolist())\n",
+    "gdf[\"color\"] = gdf[\"sum_pop_2020\"].apply(lambda x: assign_color(x, breaks, colors))\n",
+    "colors = np.uint8(gdf[\"color\"].tolist())\n",
     "\n",
     "# Create the scatterplot layer with the assigned colors\n",
     "layer = ScatterplotLayer.from_geopandas(gdf, get_radius=2000, get_fill_color=colors)\n",
@@ -872,7 +1164,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "space2stats-PM9A6h4E-py3.12",
    "language": "python",
    "name": "python3"
   },
@@ -886,7 +1178,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
diff --git a/space2stats_api/cdk/aws_stack.py b/space2stats_api/cdk/aws_stack.py
index 66aaf2f2..0a2dd5b1 100644
--- a/space2stats_api/cdk/aws_stack.py
+++ b/space2stats_api/cdk/aws_stack.py
@@ -31,7 +31,7 @@ def __init__(
             self,
             "Space2StatsFunction",
             entry="../src",
-            runtime=_lambda.Runtime.PYTHON_3_11,
+            runtime=_lambda.Runtime.PYTHON_3_10,
             index="space2stats/api/handler.py",
             timeout=Duration.seconds(120),
             handler="handler",
diff --git a/space2stats_api/src/poetry.lock b/space2stats_api/src/poetry.lock
index bace5bb8..5214ac9a 100644
--- a/space2stats_api/src/poetry.lock
+++ b/space2stats_api/src/poetry.lock
@@ -2,40 +2,37 @@
 
 [[package]]
 name = "adbc-driver-manager"
-version = "1.2.0"
+version = "1.3.0"
 description = "A generic entrypoint for ADBC drivers."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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@@ -47,17 +44,17 @@ test = ["duckdb", "pandas", "pyarrow (>=8.0.0)", "pytest"]
 
 [[package]]
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-version = "1.2.0"
+version = "1.3.0"
 description = "A libpq-based ADBC driver for working with PostgreSQL."
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-python-versions = ">=3.8"
+python-versions = ">=3.9"
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@@ -81,13 +78,13 @@ files = [
 
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+version = "4.6.2.post1"
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 python-versions = ">=3.9"
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 trio = ["trio (>=0.26.1)"]
 
+[[package]]
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+version = "0.9.13"
+description = "custom jupyter widgets made easy"
+optional = false
+python-versions = ">=3.7"
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+]
+
+[package.dependencies]
+arro3-core = "*"
+
+[[package]]
+name = "arrow"
+version = "1.3.0"
+description = "Better dates & times for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"},
+    {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"},
+]
+
+[package.dependencies]
+python-dateutil = ">=2.7.0"
+types-python-dateutil = ">=2.8.10"
+
+[package.extras]
+doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
+
 [[package]]
 name = "asgi-s3-response-middleware"
 version = "0.0.4"
@@ -121,19 +453,122 @@ starlette = ">=0.38.4"
 lint = ["pre-commit"]
 testing = ["boto3-stubs[s3] (>=1.35.11)", "coverage", "moto (>=5.0.13)", "pytest"]
 
+[[package]]
+name = "asttokens"
+version = "2.4.1"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = "*"
+files = [
+    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
+    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+]
+
+[package.dependencies]
+six = ">=1.12.0"
+
+[package.extras]
+astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
+test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
+
+[[package]]
+name = "async-lru"
+version = "2.0.4"
+description = "Simple LRU cache for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "async-lru-2.0.4.tar.gz", hash = "sha256:b8a59a5df60805ff63220b2a0c5b5393da5521b113cd5465a44eb037d81a5627"},
+    {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
+
+[[package]]
+name = "attrs"
+version = "24.2.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
+    {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
+]
+
+[package.extras]
+benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
+tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
+
+[[package]]
+name = "babel"
+version = "2.16.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+
+[[package]]
+name = "beautifulsoup4"
+version = "4.12.3"
+description = "Screen-scraping library"
+optional = false
+python-versions = ">=3.6.0"
+files = [
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+]
+
+[package.dependencies]
+soupsieve = ">1.2"
+
+[package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
+[[package]]
+name = "bleach"
+version = "6.2.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+optional = false
+python-versions = ">=3.9"
+files = [
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+    {file = "bleach-6.2.0.tar.gz", hash = "sha256:123e894118b8a599fd80d3ec1a6d4cc7ce4e5882b1317a7e1ba69b56e95f991f"},
+]
+
+[package.dependencies]
+webencodings = "*"
+
+[package.extras]
+css = ["tinycss2 (>=1.1.0,<1.5)"]
+
 [[package]]
 name = "boto3"
-version = "1.35.37"
+version = "1.35.66"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.35.37-py3-none-any.whl", hash = "sha256:385ca77bf8ea4ab2d97f6e2435bdb29f77d9301e2f7ac796c2f465753c2adf3c"},
-    {file = "boto3-1.35.37.tar.gz", hash = "sha256:470d981583885859fed2fd1c185eeb01cc03e60272d499bafe41b12625b158c8"},
+    {file = "boto3-1.35.66-py3-none-any.whl", hash = "sha256:09a610f8cf4d3c22d4ca69c1f89079e3a1c82805ce94fa0eb4ecdd4d2ba6c4bc"},
+    {file = "boto3-1.35.66.tar.gz", hash = "sha256:c392b9168b65e9c23483eaccb5b68d1f960232d7f967a1e00a045ba065ce050d"},
 ]
 
 [package.dependencies]
-botocore = ">=1.35.37,<1.36.0"
+botocore = ">=1.35.66,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -142,13 +577,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.37"
+version = "1.35.66"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "botocore-1.35.66-py3-none-any.whl", hash = "sha256:d0683e9c18bb6852f768da268086c3749d925332a664db0dd1459cfa7e96e475"},
+    {file = "botocore-1.35.66.tar.gz", hash = "sha256:51f43220315f384959f02ea3266740db4d421592dd87576c18824e424b349fdb"},
 ]
 
 [package.dependencies]
@@ -399,75 +834,92 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "comm"
+version = "0.2.2"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "comm-0.2.2.tar.gz", hash = "sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e"},
+]
+
+[package.dependencies]
+traitlets = ">=4"
+
+[package.extras]
+test = ["pytest"]
+
 [[package]]
 name = "coverage"
-version = "7.6.2"
+version = "7.6.7"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.9"
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 [package.dependencies]
@@ -580,38 +1032,38 @@ dev = ["black (==22.3.0)", "hypothesis", "numpy", "pytest (>=5.30)", "pytest-ben
 
 [[package]]
 name = "cryptography"
-version = "43.0.1"
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 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -624,9 +1076,66 @@ nox = ["nox"]
 pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "cryptography-vectors (==43.0.1)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test = ["certifi", "cryptography-vectors (==43.0.3)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
 test-randomorder = ["pytest-randomly"]
 
+[[package]]
+name = "debugpy"
+version = "1.8.8"
+description = "An implementation of the Debug Adapter Protocol for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[[package]]
+name = "decorator"
+version = "5.1.1"
+description = "Decorators for Humans"
+optional = false
+python-versions = ">=3.5"
+files = [
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+]
+
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+description = "XML bomb protection for Python stdlib modules"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
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+]
+
 [[package]]
 name = "distlib"
 version = "0.3.9"
@@ -652,26 +1161,54 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "executing"
+version = "2.1.0"
+description = "Get the currently executing AST node of a frame, and other information"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.extras]
+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
+
 [[package]]
 name = "fastapi"
-version = "0.115.0"
+version = "0.115.5"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "fastapi-0.115.5-py3-none-any.whl", hash = "sha256:596b95adbe1474da47049e802f9a65ab2ffa9c2b07e7efee70eb8a66c9f2f796"},
+    {file = "fastapi-0.115.5.tar.gz", hash = "sha256:0e7a4d0dc0d01c68df21887cce0945e72d3c48b9f4f79dfe7a7d53aa08fbb289"},
 ]
 
 [package.dependencies]
 pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
-starlette = ">=0.37.2,<0.39.0"
+starlette = ">=0.40.0,<0.42.0"
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=2.11.2)", "python-multipart (>=0.0.7)", "uvicorn[standard] (>=0.12.0)"]
 
+[[package]]
+name = "fastjsonschema"
+version = "2.20.0"
+description = "Fastest Python implementation of JSON schema"
+optional = false
+python-versions = "*"
+files = [
+    {file = "fastjsonschema-2.20.0-py3-none-any.whl", hash = "sha256:5875f0b0fa7a0043a91e93a9b8f793bcbbba9691e7fd83dca95c28ba26d21f0a"},
+    {file = "fastjsonschema-2.20.0.tar.gz", hash = "sha256:3d48fc5300ee96f5d116f10fe6f28d938e6008f59a6a025c2649475b87f76a23"},
+]
+
+[package.extras]
+devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
+
 [[package]]
 name = "filelock"
 version = "3.16.1"
@@ -688,15 +1225,26 @@ docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.
 testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.2)", "pytest (>=8.3.3)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.4)"]
 typing = ["typing-extensions (>=4.12.2)"]
 
+[[package]]
+name = "fqdn"
+version = "1.5.1"
+description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers"
+optional = false
+python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
+files = [
+    {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"},
+    {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
+]
+
 [[package]]
 name = "geojson-pydantic"
-version = "1.1.1"
+version = "1.1.2"
 description = "Pydantic data models for the GeoJSON spec."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "geojson_pydantic-1.1.1-py3-none-any.whl", hash = "sha256:3d8adeee9ee0e1bb658c262fcb2e0da44090e44c0123ea95f989e484bdf123d9"},
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+    {file = "geojson_pydantic-1.1.2-py3-none-any.whl", hash = "sha256:2488736307c1717469419110b31413277fc1095eb2137592d5417e6100268d0f"},
+    {file = "geojson_pydantic-1.1.2.tar.gz", hash = "sha256:be3b686e059dad95caff1ea411f020333b2c6182d87fcc4f69d1cbde2cca2c09"},
 ]
 
 [package.dependencies]
@@ -707,6 +1255,29 @@ dev = ["bump-my-version", "pre-commit"]
 docs = ["mkdocs", "mkdocs-material", "pygments"]
 test = ["pytest", "pytest-cov", "shapely"]
 
+[[package]]
+name = "geopandas"
+version = "1.0.1"
+description = "Geographic pandas extensions"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "geopandas-1.0.1-py3-none-any.whl", hash = "sha256:01e147d9420cc374d26f51fc23716ac307f32b49406e4bd8462c07e82ed1d3d6"},
+    {file = "geopandas-1.0.1.tar.gz", hash = "sha256:b8bf70a5534588205b7a56646e2082fb1de9a03599651b3d80c99ea4c2ca08ab"},
+]
+
+[package.dependencies]
+numpy = ">=1.22"
+packaging = "*"
+pandas = ">=1.4.0"
+pyogrio = ">=0.7.2"
+pyproj = ">=3.3.0"
+shapely = ">=2.0.0"
+
+[package.extras]
+all = ["GeoAlchemy2", "SQLAlchemy (>=1.3)", "folium", "geopy", "mapclassify", "matplotlib (>=3.5.0)", "psycopg-binary (>=3.1.0)", "pyarrow (>=8.0.0)", "xyzservices"]
+dev = ["black", "codecov", "pre-commit", "pytest (>=3.1.0)", "pytest-cov", "pytest-xdist"]
+
 [[package]]
 name = "h11"
 version = "0.14.0"
@@ -719,68 +1290,37 @@ files = [
 ]
 
 [[package]]
-name = "h3"
-version = "3.7.7"
-description = "Hierarchical hexagonal geospatial indexing system"
+name = "h3ronpy"
+version = "0.21.1"
+description = "Data science toolkit for the H3 geospatial grid"
 optional = false
 python-versions = "*"
 files = [
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-]
-
-[package.extras]
-all = ["flake8", "numpy", "pylint", "pytest", "pytest-cov"]
-numpy = ["numpy"]
-test = ["flake8", "pylint", "pytest", "pytest-cov"]
+    {file = "h3ronpy-0.21.1-cp39-abi3-linux_x86_64.whl", hash = "sha256:071536141bc3039fe589a1b2d965ce6292d5ff93873fa35c0b7818bcd602aedc"},
+]
+
+[package.dependencies]
+arro3-core = ">=0.4"
+numpy = "*"
+
+[package.extras]
+pandas = ["geopandas (>=1)"]
+polars = ["polars (>=1)"]
+test = ["h3 (<4)", "pyarrow (>=15)", "pytest (>=6)", "pytest-benchmark", "rasterio (>=1.4)", "shapely (>=1.7)"]
+
+[package.source]
+type = "url"
+url = "https://temp-wheels-cdk.s3.us-east-1.amazonaws.com/h3ronpy-0.21.1-cp39-abi3-linux_x86_64.whl"
 
 [[package]]
 name = "httpcore"
-version = "1.0.6"
+version = "1.0.7"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"},
-    {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"},
+    {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"},
+    {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
 ]
 
 [package.dependencies]
@@ -820,13 +1360,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "identify"
-version = "2.6.1"
+version = "2.6.2"
 description = "File identification library for Python"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "identify-2.6.1-py2.py3-none-any.whl", hash = "sha256:53863bcac7caf8d2ed85bd20312ea5dcfc22226800f6d6881f232d861db5a8f0"},
-    {file = "identify-2.6.1.tar.gz", hash = "sha256:91478c5fb7c3aac5ff7bf9b4344f803843dc586832d5f110d672b19aa1984c98"},
+    {file = "identify-2.6.2-py2.py3-none-any.whl", hash = "sha256:c097384259f49e372f4ea00a19719d95ae27dd5ff0fd77ad630aa891306b82f3"},
+    {file = "identify-2.6.2.tar.gz", hash = "sha256:fab5c716c24d7a789775228823797296a2994b075fb6080ac83a102772a98cbd"},
 ]
 
 [package.extras]
@@ -876,6 +1416,131 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "ipykernel"
+version = "6.29.5"
+description = "IPython Kernel for Jupyter"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "ipykernel-6.29.5-py3-none-any.whl", hash = "sha256:afdb66ba5aa354b09b91379bac28ae4afebbb30e8b39510c9690afb7a10421b5"},
+    {file = "ipykernel-6.29.5.tar.gz", hash = "sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = "*"
+packaging = "*"
+psutil = "*"
+pyzmq = ">=24"
+tornado = ">=6.1"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "ipython"
+version = "8.29.0"
+description = "IPython: Productive Interactive Computing"
+optional = false
+python-versions = ">=3.10"
+files = [
+    {file = "ipython-8.29.0-py3-none-any.whl", hash = "sha256:0188a1bd83267192123ccea7f4a8ed0a78910535dbaa3f37671dca76ebd429c8"},
+    {file = "ipython-8.29.0.tar.gz", hash = "sha256:40b60e15b22591450eef73e40a027cf77bd652e757523eebc5bd7c7c498290eb"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+decorator = "*"
+exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+jedi = ">=0.16"
+matplotlib-inline = "*"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""}
+prompt-toolkit = ">=3.0.41,<3.1.0"
+pygments = ">=2.4.0"
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+[[package]]
+name = "matplotlib-inline"
+version = "0.1.7"
+description = "Inline Matplotlib backend for Jupyter"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+traitlets = "*"
+
 [[package]]
 name = "mdurl"
 version = "0.1.2"
@@ -1025,32 +2059,43 @@ files = [
 
 [[package]]
 name = "mirakuru"
-version = "2.5.2"
+version = "2.5.3"
 description = "Process executor (not only) for tests."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
 psutil = {version = ">=4.0.0", markers = "sys_platform != \"cygwin\""}
 
+[[package]]
+name = "mistune"
+version = "3.0.2"
+description = "A sane and fast Markdown parser with useful plugins and renderers"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
 [[package]]
 name = "moto"
-version = "5.0.16"
+version = "5.0.21"
 description = ""
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "moto-5.0.16-py2.py3-none-any.whl", hash = "sha256:4ce1f34830307f7b3d553d77a7ef26066ab3b70006203d4226b048c9d11a3be4"},
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+    {file = "moto-5.0.21.tar.gz", hash = "sha256:52f63291daeff9444ef5eb14fbf69b24264567b79f184ae6aee4945d09845f06"},
 ]
 
 [package.dependencies]
 boto3 = ">=1.9.201"
-botocore = ">=1.14.0"
+botocore = ">=1.14.0,<1.35.45 || >1.35.45,<1.35.46 || >1.35.46"
 cryptography = ">=3.3.1"
 Jinja2 = ">=2.10.1"
 python-dateutil = ">=2.1,<3.0.0"
@@ -1060,7 +2105,7 @@ werkzeug = ">=0.5,<2.2.0 || >2.2.0,<2.2.1 || >2.2.1"
 xmltodict = "*"
 
 [package.extras]
-all = ["PyYAML (>=5.1)", "antlr4-python3-runtime", "aws-xray-sdk (>=0.93,!=0.96)", "cfn-lint (>=0.40.0)", "docker (>=3.0.0)", "graphql-core", "joserfc (>=0.9.0)", "jsondiff (>=1.1.2)", "jsonpath-ng", "multipart", "openapi-spec-validator (>=0.5.0)", "py-partiql-parser (==0.5.6)", "pyparsing (>=3.0.7)", "setuptools"]
+all = ["PyYAML (>=5.1)", "antlr4-python3-runtime", "aws-xray-sdk (>=0.93,!=0.96)", "cfn-lint (>=0.40.0)", "docker (>=3.0.0)", "graphql-core", "joserfc (>=0.9.0)", "jsondiff (>=1.1.2)", "jsonpath-ng", "jsonschema", "multipart", "openapi-spec-validator (>=0.5.0)", "py-partiql-parser (==0.5.6)", "pyparsing (>=3.0.7)", "setuptools"]
 apigateway = ["PyYAML (>=5.1)", "joserfc (>=0.9.0)", "openapi-spec-validator (>=0.5.0)"]
 apigatewayv2 = ["PyYAML (>=5.1)", "openapi-spec-validator (>=0.5.0)"]
 appsync = ["graphql-core"]
@@ -1074,6 +2119,7 @@ events = ["jsonpath-ng"]
 glue = ["pyparsing (>=3.0.7)"]
 iotdata = ["jsondiff (>=1.1.2)"]
 proxy = ["PyYAML (>=5.1)", "antlr4-python3-runtime", "aws-xray-sdk (>=0.93,!=0.96)", "cfn-lint (>=0.40.0)", "docker (>=2.5.1)", "graphql-core", "joserfc (>=0.9.0)", "jsondiff (>=1.1.2)", "jsonpath-ng", "multipart", "openapi-spec-validator (>=0.5.0)", "py-partiql-parser (==0.5.6)", "pyparsing (>=3.0.7)", "setuptools"]
+quicksight = ["jsonschema"]
 resourcegroupstaggingapi = ["PyYAML (>=5.1)", "cfn-lint (>=0.40.0)", "docker (>=3.0.0)", "graphql-core", "joserfc (>=0.9.0)", "jsondiff (>=1.1.2)", "openapi-spec-validator (>=0.5.0)", "py-partiql-parser (==0.5.6)", "pyparsing (>=3.0.7)"]
 s3 = ["PyYAML (>=5.1)", "py-partiql-parser (==0.5.6)"]
 s3crc32c = ["PyYAML (>=5.1)", "crc32c", "py-partiql-parser (==0.5.6)"]
@@ -1082,6 +2128,97 @@ ssm = ["PyYAML (>=5.1)"]
 stepfunctions = ["antlr4-python3-runtime", "jsonpath-ng"]
 xray = ["aws-xray-sdk (>=0.93,!=0.96)", "setuptools"]
 
+[[package]]
+name = "nbclient"
+version = "0.10.0"
+description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
+optional = false
+python-versions = ">=3.8.0"
+files = [
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+    {file = "nbclient-0.10.0.tar.gz", hash = "sha256:4b3f1b7dba531e498449c4db4f53da339c91d449dc11e9af3a43b4eb5c5abb09"},
+]
+
+[package.dependencies]
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+nbformat = ">=5.1"
+traitlets = ">=5.4"
+
+[package.extras]
+dev = ["pre-commit"]
+docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
+test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
+
+[[package]]
+name = "nbconvert"
+version = "7.16.4"
+description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "nbconvert-7.16.4-py3-none-any.whl", hash = "sha256:05873c620fe520b6322bf8a5ad562692343fe3452abda5765c7a34b7d1aa3eb3"},
+    {file = "nbconvert-7.16.4.tar.gz", hash = "sha256:86ca91ba266b0a448dc96fa6c5b9d98affabde2867b363258703536807f9f7f4"},
+]
+
+[package.dependencies]
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+bleach = "!=5.0.0"
+defusedxml = "*"
+jinja2 = ">=3.0"
+jupyter-core = ">=4.7"
+jupyterlab-pygments = "*"
+markupsafe = ">=2.0"
+mistune = ">=2.0.3,<4"
+nbclient = ">=0.5.0"
+nbformat = ">=5.7"
+packaging = "*"
+pandocfilters = ">=1.4.1"
+pygments = ">=2.4.1"
+tinycss2 = "*"
+traitlets = ">=5.1"
+
+[package.extras]
+all = ["flaky", "ipykernel", "ipython", "ipywidgets (>=7.5)", "myst-parser", "nbsphinx (>=0.2.12)", "playwright", "pydata-sphinx-theme", "pyqtwebengine (>=5.15)", "pytest (>=7)", "sphinx (==5.0.2)", "sphinxcontrib-spelling", "tornado (>=6.1)"]
+docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sphinx-theme", "sphinx (==5.0.2)", "sphinxcontrib-spelling"]
+qtpdf = ["pyqtwebengine (>=5.15)"]
+qtpng = ["pyqtwebengine (>=5.15)"]
+serve = ["tornado (>=6.1)"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
+webpdf = ["playwright"]
+
+[[package]]
+name = "nbformat"
+version = "5.10.4"
+description = "The Jupyter Notebook format"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "nbformat-5.10.4.tar.gz", hash = "sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a"},
+]
+
+[package.dependencies]
+fastjsonschema = ">=2.15"
+jsonschema = ">=2.6"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+traitlets = ">=5.1"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["pep440", "pre-commit", "pytest", "testpath"]
+
+[[package]]
+name = "nest-asyncio"
+version = "1.6.0"
+description = "Patch asyncio to allow nested event loops"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"},
+    {file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"},
+]
+
 [[package]]
 name = "nodeenv"
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 [[package]]
 name = "packaging"
-version = "24.1"
+version = "24.2"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
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@@ -1318,6 +2490,46 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.9.2)"]
 
+[[package]]
+name = "pandocfilters"
+version = "1.5.1"
+description = "Utilities for writing pandoc filters in python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
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+]
+
+[[package]]
+name = "parso"
+version = "0.8.4"
+description = "A Python Parser"
+optional = false
+python-versions = ">=3.6"
+files = [
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+[package.extras]
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+testing = ["docopt", "pytest"]
+
+[[package]]
+name = "pexpect"
+version = "4.9.0"
+description = "Pexpect allows easy control of interactive console applications."
+optional = false
+python-versions = "*"
+files = [
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+
+[package.dependencies]
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+
 [[package]]
 name = "platformdirs"
 version = "4.3.6"
@@ -1378,34 +2590,63 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
+[[package]]
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+version = "0.21.0"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.8"
+files = [
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+[package.extras]
+twisted = ["twisted"]
+
+[[package]]
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+version = "3.0.48"
+description = "Library for building powerful interactive command lines in Python"
+optional = false
+python-versions = ">=3.7.0"
+files = [
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+
+[package.dependencies]
+wcwidth = "*"
+
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 name = "psutil"
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+version = "6.1.0"
 description = "Cross-platform lib for process and system monitoring in Python."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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 ]
 
 [package.extras]
-test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
+dev = ["black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "wheel"]
+test = ["pytest", "pytest-xdist", "setuptools"]
 
 [[package]]
 name = "psycopg"
@@ -1507,18 +2748,82 @@ files = [
 
 [[package]]
 name = "psycopg-pool"
-version = "3.2.3"
+version = "3.2.4"
 description = "Connection Pool for Psycopg"
 optional = false
 python-versions = ">=3.8"
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 [[package]]
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 pytest = ">=4.6"
 
 [package.extras]
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 [package.extras]
 cli = ["click (>=5.0)"]
 
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-    {file = "s3transfer-0.10.3-py3-none-any.whl", hash = "sha256:263ed587a5803c6c708d3ce44dc4dfedaab4c1a32e8329bab818933d79ddcf5d"},
-    {file = "s3transfer-0.10.3.tar.gz", hash = "sha256:4f50ed74ab84d474ce614475e0b8d5047ff080810aac5d01ea25231cfc944b0c"},
+    {file = "s3transfer-0.10.4-py3-none-any.whl", hash = "sha256:244a76a24355363a68164241438de1b72f8781664920260c48465896b712a41e"},
+    {file = "s3transfer-0.10.4.tar.gz", hash = "sha256:29edc09801743c21eb5ecbc617a152df41d3c287f67b615f73e5f750583666a7"},
 ]
 
 [package.dependencies]
@@ -2039,25 +3756,41 @@ botocore = ">=1.33.2,<2.0a.0"
 [package.extras]
 crt = ["botocore[crt] (>=1.33.2,<2.0a.0)"]
 
+[[package]]
+name = "send2trash"
+version = "1.8.3"
+description = "Send file to trash natively under Mac OS X, Windows and Linux"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+files = [
+    {file = "Send2Trash-1.8.3-py3-none-any.whl", hash = "sha256:0c31227e0bd08961c7665474a3d1ef7193929fedda4233843689baa056be46c9"},
+    {file = "Send2Trash-1.8.3.tar.gz", hash = "sha256:b18e7a3966d99871aefeb00cfbcfdced55ce4871194810fc71f4aa484b953abf"},
+]
+
+[package.extras]
+nativelib = ["pyobjc-framework-Cocoa", "pywin32"]
+objc = ["pyobjc-framework-Cocoa"]
+win32 = ["pywin32"]
+
 [[package]]
 name = "setuptools"
-version = "75.1.0"
+version = "75.6.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "setuptools-75.1.0-py3-none-any.whl", hash = "sha256:35ab7fd3bcd95e6b7fd704e4a1539513edad446c097797f2985e0e4b960772f2"},
-    {file = "setuptools-75.1.0.tar.gz", hash = "sha256:d59a21b17a275fb872a9c3dae73963160ae079f1049ed956880cd7c09b120538"},
+    {file = "setuptools-75.6.0-py3-none-any.whl", hash = "sha256:ce74b49e8f7110f9bf04883b730f4765b774ef3ef28f722cce7c273d253aaf7d"},
+    {file = "setuptools-75.6.0.tar.gz", hash = "sha256:8199222558df7c86216af4f84c30e9b34a61d8ba19366cc914424cdbd28252f6"},
 ]
 
 [package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.5.2)"]
-core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.collections", "jaraco.functools", "jaraco.text (>=3.7)", "more-itertools", "more-itertools (>=8.8)", "packaging", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.7.0)"]
+core = ["importlib_metadata (>=6)", "jaraco.collections", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
 enabler = ["pytest-enabler (>=2.2)"]
-test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
-type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.11.*)", "pytest-mypy"]
+test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
+type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (>=1.12,<1.14)", "pytest-mypy"]
 
 [[package]]
 name = "shapely"
@@ -2150,15 +3883,45 @@ files = [
     {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
 ]
 
+[[package]]
+name = "soupsieve"
+version = "2.6"
+description = "A modern CSS selector implementation for Beautiful Soup."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9"},
+    {file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
+]
+
+[[package]]
+name = "stack-data"
+version = "0.6.3"
+description = "Extract data from python stack frames and tracebacks for informative displays"
+optional = false
+python-versions = "*"
+files = [
+    {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
+    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
+]
+
+[package.dependencies]
+asttokens = ">=2.1.0"
+executing = ">=1.2.0"
+pure-eval = "*"
+
+[package.extras]
+tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
+
 [[package]]
 name = "starlette"
-version = "0.38.6"
+version = "0.41.3"
 description = "The little ASGI library that shines."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "starlette-0.38.6-py3-none-any.whl", hash = "sha256:4517a1409e2e73ee4951214ba012052b9e16f60e90d73cfb06192c19203bbb05"},
-    {file = "starlette-0.38.6.tar.gz", hash = "sha256:863a1588f5574e70a821dadefb41e4881ea451a47a3cd1b4df359d4ffefe5ead"},
+    {file = "starlette-0.41.3-py3-none-any.whl", hash = "sha256:44cedb2b7c77a9de33a8b74b2b90e9f50d11fcf25d8270ea525ad71a25374ff7"},
+    {file = "starlette-0.41.3.tar.gz", hash = "sha256:0e4ab3d16522a255be6b28260b938eae2482f98ce5cc934cb08dce8dc3ba5835"},
 ]
 
 [package.dependencies]
@@ -2186,26 +3949,85 @@ starlette = "*"
 dev = ["pre-commit"]
 test = ["brotlipy", "httpx", "pytest", "pytest-cov"]
 
+[[package]]
+name = "terminado"
+version = "0.18.1"
+description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "terminado-0.18.1-py3-none-any.whl", hash = "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0"},
+    {file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"},
+]
+
+[package.dependencies]
+ptyprocess = {version = "*", markers = "os_name != \"nt\""}
+pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
+tornado = ">=6.1.0"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
+
+[[package]]
+name = "tinycss2"
+version = "1.4.0"
+description = "A tiny CSS parser"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tinycss2-1.4.0-py3-none-any.whl", hash = "sha256:3a49cf47b7675da0b15d0c6e1df8df4ebd96e9394bb905a5775adb0d884c5289"},
+    {file = "tinycss2-1.4.0.tar.gz", hash = "sha256:10c0972f6fc0fbee87c3edb76549357415e94548c1ae10ebccdea16fb404a9b7"},
+]
+
+[package.dependencies]
+webencodings = ">=0.4"
+
+[package.extras]
+doc = ["sphinx", "sphinx_rtd_theme"]
+test = ["pytest", "ruff"]
+
 [[package]]
 name = "tomli"
-version = "2.0.2"
+version = "2.1.0"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"},
-    {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"},
+    {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"},
+    {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"},
+]
+
+[[package]]
+name = "tornado"
+version = "6.4.1"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"},
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"},
+    {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"},
+    {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"},
+    {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"},
 ]
 
 [[package]]
 name = "tqdm"
-version = "4.66.5"
+version = "4.67.0"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
-    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+    {file = "tqdm-4.67.0-py3-none-any.whl", hash = "sha256:0cd8af9d56911acab92182e88d763100d4788bdf421d251616040cc4d44863be"},
+    {file = "tqdm-4.67.0.tar.gz", hash = "sha256:fe5a6f95e6fe0b9755e9469b77b9c3cf850048224ecaa8293d7d2d31f97d869a"},
 ]
 
 [package.dependencies]
@@ -2213,10 +4035,26 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
 dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+discord = ["requests"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "traitlets"
+version = "5.14.3"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"},
+    {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
+
 [[package]]
 name = "typer"
 version = "0.12.5"
@@ -2234,15 +4072,26 @@ rich = ">=10.11.0"
 shellingham = ">=1.3.0"
 typing-extensions = ">=3.7.4.3"
 
+[[package]]
+name = "types-python-dateutil"
+version = "2.9.0.20241003"
+description = "Typing stubs for python-dateutil"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-python-dateutil-2.9.0.20241003.tar.gz", hash = "sha256:58cb85449b2a56d6684e41aeefb4c4280631246a0da1a719bdbe6f3fb0317446"},
+    {file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"},
+]
+
 [[package]]
 name = "types-requests"
-version = "2.32.0.20240914"
+version = "2.32.0.20241016"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-requests-2.32.0.20240914.tar.gz", hash = "sha256:2850e178db3919d9bf809e434eef65ba49d0e7e33ac92d588f4a5e295fffd405"},
-    {file = "types_requests-2.32.0.20240914-py3-none-any.whl", hash = "sha256:59c2f673eb55f32a99b2894faf6020e1a9f4a402ad0f192bfee0b64469054310"},
+    {file = "types-requests-2.32.0.20241016.tar.gz", hash = "sha256:0d9cad2f27515d0e3e3da7134a1b6f28fb97129d86b867f24d9c726452634d95"},
+    {file = "types_requests-2.32.0.20241016-py3-none-any.whl", hash = "sha256:4195d62d6d3e043a4eaaf08ff8a62184584d2e8684e9d2aa178c7915a7da3747"},
 ]
 
 [package.dependencies]
@@ -2270,6 +4119,20 @@ files = [
     {file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"},
 ]
 
+[[package]]
+name = "uri-template"
+version = "1.3.0"
+description = "RFC 6570 URI Template Processor"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"},
+    {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"},
+]
+
+[package.extras]
+dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
+
 [[package]]
 name = "urllib3"
 version = "2.2.3"
@@ -2289,13 +4152,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.31.1"
+version = "0.32.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.31.1-py3-none-any.whl", hash = "sha256:adc42d9cac80cf3e51af97c1851648066841e7cfb6993a4ca8de29ac1548ed41"},
-    {file = "uvicorn-0.31.1.tar.gz", hash = "sha256:f5167919867b161b7bcaf32646c6a94cdbd4c3aa2eb5c17d36bb9aa5cfd8c493"},
+    {file = "uvicorn-0.32.1-py3-none-any.whl", hash = "sha256:82ad92fd58da0d12af7482ecdb5f2470a04c9c9a53ced65b9bbb4a205377602e"},
+    {file = "uvicorn-0.32.1.tar.gz", hash = "sha256:ee9519c246a72b1c084cea8d3b44ed6026e78a4a309cbedae9c37e4cb9fbb175"},
 ]
 
 [package.dependencies]
@@ -2304,17 +4167,17 @@ h11 = ">=0.8"
 typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+standard = ["colorama (>=0.4)", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.26.6"
+version = "20.27.1"
 description = "Virtual Python Environment builder"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.26.6-py3-none-any.whl", hash = "sha256:7345cc5b25405607a624d8418154577459c3e0277f5466dd79c49d5e492995f2"},
-    {file = "virtualenv-20.26.6.tar.gz", hash = "sha256:280aede09a2a5c317e409a00102e7077c6432c5a38f0ef938e643805a7ad2c48"},
+    {file = "virtualenv-20.27.1-py3-none-any.whl", hash = "sha256:f11f1b8a29525562925f745563bfd48b189450f61fb34c4f9cc79dd5aa32a1f4"},
+    {file = "virtualenv-20.27.1.tar.gz", hash = "sha256:142c6be10212543b32c6c45d3d3893dff89112cc588b7d0879ae5a1ec03a47ba"},
 ]
 
 [package.dependencies]
@@ -2326,15 +4189,64 @@ platformdirs = ">=3.9.1,<5"
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
+[[package]]
+name = "wcwidth"
+version = "0.2.13"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
+]
+
+[[package]]
+name = "webcolors"
+version = "24.11.1"
+description = "A library for working with the color formats defined by HTML and CSS."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "webcolors-24.11.1-py3-none-any.whl", hash = "sha256:515291393b4cdf0eb19c155749a096f779f7d909f7cceea072791cb9095b92e9"},
+    {file = "webcolors-24.11.1.tar.gz", hash = "sha256:ecb3d768f32202af770477b8b65f318fa4f566c22948673a977b00d589dd80f6"},
+]
+
+[[package]]
+name = "webencodings"
+version = "0.5.1"
+description = "Character encoding aliases for legacy web content"
+optional = false
+python-versions = "*"
+files = [
+    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
+    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
+]
+
+[[package]]
+name = "websocket-client"
+version = "1.8.0"
+description = "WebSocket client for Python with low level API options"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"},
+    {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
+optional = ["python-socks", "wsaccel"]
+test = ["websockets"]
+
 [[package]]
 name = "werkzeug"
-version = "3.0.4"
+version = "3.1.3"
 description = "The comprehensive WSGI web application library."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "werkzeug-3.0.4-py3-none-any.whl", hash = "sha256:02c9eb92b7d6c06f31a782811505d2157837cea66aaede3e217c7c27c039476c"},
-    {file = "werkzeug-3.0.4.tar.gz", hash = "sha256:34f2371506b250df4d4f84bfe7b0921e4762525762bbd936614909fe25cd7306"},
+    {file = "werkzeug-3.1.3-py3-none-any.whl", hash = "sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e"},
+    {file = "werkzeug-3.1.3.tar.gz", hash = "sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746"},
 ]
 
 [package.dependencies]
@@ -2343,18 +4255,29 @@ MarkupSafe = ">=2.1.1"
 [package.extras]
 watchdog = ["watchdog (>=2.3)"]
 
+[[package]]
+name = "widgetsnbextension"
+version = "4.0.13"
+description = "Jupyter interactive widgets for Jupyter Notebook"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "widgetsnbextension-4.0.13-py3-none-any.whl", hash = "sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71"},
+    {file = "widgetsnbextension-4.0.13.tar.gz", hash = "sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6"},
+]
+
 [[package]]
 name = "xmltodict"
-version = "0.14.1"
+version = "0.14.2"
 description = "Makes working with XML feel like you are working with JSON"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "xmltodict-0.14.1-py2.py3-none-any.whl", hash = "sha256:3ef4a7b71c08f19047fcbea572e1d7f4207ab269da1565b5d40e9823d3894e63"},
-    {file = "xmltodict-0.14.1.tar.gz", hash = "sha256:338c8431e4fc554517651972d62f06958718f6262b04316917008e8fd677a6b0"},
+    {file = "xmltodict-0.14.2-py2.py3-none-any.whl", hash = "sha256:20cc7d723ed729276e808f26fb6b3599f786cbc37e06c65e192ba77c40f20aac"},
+    {file = "xmltodict-0.14.2.tar.gz", hash = "sha256:201e7c28bb210e374999d1dde6382923ab0ed1a8a5faeece48ab525b7810a553"},
 ]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "932cb39d230fe1c3d1759480971d1c51a8de9a534dc306196521352f11476074"
+content-hash = "1cb3521e71698dcbc60e8a67325b04248eb07ec887f647d86be0170f11da3347"
diff --git a/space2stats_api/src/pyproject.toml b/space2stats_api/src/pyproject.toml
index c7b29a5c..90a6971a 100644
--- a/space2stats_api/src/pyproject.toml
+++ b/space2stats_api/src/pyproject.toml
@@ -9,9 +9,7 @@ readme = "README.md"
 python = ">=3.10,<3.13"
 orjson = "*"
 fastapi = ">=0.112.0"
-pandas = "*" 
 shapely = "*"
-h3 = "*"
 psycopg = { version = "*", extras = ["binary", "pool"] }
 httpx = "*"
 geojson-pydantic = "*"
@@ -21,7 +19,8 @@ starlette-cramjam = ">=0.3,<0.4"
 mangum = "*"
 asgi-s3-response-middleware = "^0.0.4"
 boto3 = "^1.35.11"
-numpy = "^2.1.1"
+numpy = "^1.24.0"
+h3ronpy = { url = "https://temp-wheels-cdk.s3.us-east-1.amazonaws.com/h3ronpy-0.21.1-cp39-abi3-linux_x86_64.whl" }
 
 [tool.poetry.group.lambda.dependencies]
 mangum = "*"
@@ -37,6 +36,13 @@ adbc-driver-postgresql = "^1.2.0"
 tqdm = "^4.66.5"
 pystac = "^1.11.0"
 
+[tool.poetry.group.notebook.dependencies]
+pandas = "*"
+jupyter = "*"
+geopandas = "*"
+shapely = "*"
+lonboard = "*"
+
 [tool.poetry.group.test.dependencies]
 pre-commit = "*"
 pytest = "*"
diff --git a/space2stats_api/src/space2stats/api/app.py b/space2stats_api/src/space2stats/api/app.py
index 182d7a1a..1556543a 100644
--- a/space2stats_api/src/space2stats/api/app.py
+++ b/space2stats_api/src/space2stats/api/app.py
@@ -62,8 +62,8 @@ def get_summary(body: SummaryRequest, table: StatsTable = Depends(stats_table)):
                 body.fields,
                 body.geometry,
             )
-        except pg.errors.UndefinedColumn as e:
-            raise HTTPException(status_code=400, detail=e.diag.message_primary) from e
+        except ValueError as e:
+            raise HTTPException(status_code=400, detail=str(e)) from e
 
     @app.post("/aggregate", response_model=Dict[str, float])
     def get_aggregate(body: AggregateRequest, table: StatsTable = Depends(stats_table)):
diff --git a/space2stats_api/src/space2stats/h3_utils.py b/space2stats_api/src/space2stats/h3_utils.py
index de597c48..98a0f63e 100644
--- a/space2stats_api/src/space2stats/h3_utils.py
+++ b/space2stats_api/src/space2stats/h3_utils.py
@@ -1,145 +1,51 @@
-from typing import Any, Dict, Iterable, List, Literal, Optional, Set
+from typing import Any, Dict, List, Literal
 
-import h3
-from shapely.geometry import MultiPolygon, Point, Polygon, mapping, shape
+from arro3.core import Array
+from h3ronpy import ContainmentMode
+from h3ronpy.vector import cells_to_wkb_points, cells_to_wkb_polygons, geometry_to_cells
+from shapely import from_wkb, to_geojson
+from shapely.geometry import shape
 
-# https://h3geo.org/docs/core-library/restable
-MAX_RESOLUTION = 15
-
-
-def _recursive_polyfill(
-    aoi_geojson: Dict[str, Any], resolution: int, original_resolution: int
-) -> Set[str]:
-    # Attempt to get H3 IDs at the current resolution
-    h3_ids = h3.polyfill(aoi_geojson, resolution, geo_json_conformant=True)
-
-    # If valid H3 IDs are found, return them
-    if h3_ids:
-        return {h3.h3_to_parent(h3_id, original_resolution) for h3_id in h3_ids}
-
-    # If we haven't reached the maximum resolution, try the next higher resolution
-    if resolution < MAX_RESOLUTION:
-        return _recursive_polyfill(aoi_geojson, resolution + 1, original_resolution)
-
-    return set()
-
-
-def _find_within(aoi_geojson: Dict[str, Any], h3_ids: Iterable[str]) -> Set[str]:
-    # Convert AOI GeoJSON to Shapely geometry
-    aoi_shape = shape(aoi_geojson)
-
-    # Find H3 IDs that are within the polygon
-    contained_h3_ids = [
-        h3_id
-        for h3_id in h3_ids
-        if aoi_shape.contains(Polygon(h3.h3_to_geo_boundary(h3_id, geo_json=True)))
-    ]
-
-    return set(contained_h3_ids)
-
-
-def _find_touches(aoi_geojson: Dict[str, Any], h3_ids: Iterable[str]) -> Set[str]:
-    aoi_shape = shape(aoi_geojson)
-
-    neighbors = set()
-    for h3_id in h3_ids:
-        parent_id = h3.h3_to_parent(h3_id, h3.h3_get_resolution(h3_id) - 1)
-
-        for n_h3_id in h3.h3_to_children(
-            parent_id, h3.h3_get_resolution(parent_id) + 1
-        ):
-            boundary = Polygon(h3.h3_to_geo_boundary(n_h3_id, geo_json=True))
-            if h3.h3_indexes_are_neighbors(h3_id, n_h3_id) and aoi_shape.intersects(
-                boundary
-            ):
-                neighbors.add(n_h3_id)
-
-    return neighbors.union(h3_ids)
-
-
-def _generate_h3_ids(
-    aoi_geojson: Dict[str, Any],
-    resolution: int,
-    spatial_join_method: Literal["touches", "within", "centroid"],
-) -> Set[str]:
-    if spatial_join_method not in ["touches", "within", "centroid"]:
-        raise ValueError(f"Invalid spatial join method: {spatial_join_method}")
-
-    # Generate H3 hexagons covering the AOI
-    # Polyfill defines containment based on centroid:
-    # https://h3geo.org/docs/3.x/api/regions/#polyfill
-    h3_ids = _recursive_polyfill(aoi_geojson, resolution, resolution)
-
-    if spatial_join_method == "within":
-        h3_ids = _find_within(aoi_geojson, h3_ids)
-
-    if spatial_join_method == "touches":
-        h3_ids = _find_touches(aoi_geojson, h3_ids)
-
-    return h3_ids
+CONTAINMENT_MODE_MAP = {
+    "centroid": ContainmentMode.ContainsCentroid,
+    "touches": ContainmentMode.IntersectsBoundary,
+    "within": ContainmentMode.ContainsBoundary,
+}
 
 
 def generate_h3_ids(
     aoi_geojson: Dict[str, Any],
     resolution: int,
-    spatial_join_method: Literal["touches", "within", "centroid"],
-) -> Set[str]:
+    spatial_join_method: Literal["touches", "within", "centroid"] = "centroid",
+) -> Array:
     """
-    Generate H3 hexagon IDs for a given AOI GeoJSON object, supporting both Polygon and MultiPolygon.
-
-    Parameters:
-        aoi_geojson (Dict[str, Any]): The AOI GeoJSON object.
-        resolution (int): The H3 resolution.
-        spatial_join_method (str): The spatial join method to use.
-
-    Returns:
-        Set[str]: A set of H3 hexagon IDs.
+    Generate H3 IDs using h3ronpy's geometry_to_cells with the correct containment mode.
+    Returns the H3 IDs in uint64 format for geometry creation.
     """
-    if spatial_join_method not in ["touches", "within", "centroid"]:
-        raise ValueError("Invalid spatial join method")
+    geom = shape(aoi_geojson)
+    containment_mode = CONTAINMENT_MODE_MAP.get(spatial_join_method)
 
-    aoi_shape = shape(aoi_geojson)
+    if containment_mode is None:
+        raise ValueError(f"Invalid spatial join method: {spatial_join_method}")
 
-    if isinstance(aoi_shape, MultiPolygon):
-        h3_ids = set()
-        for geom in aoi_shape.geoms:
-            # Convert each geometry to GeoJSON
-            geom_geojson = mapping(geom)
-            h3_ids.update(
-                _generate_h3_ids(geom_geojson, resolution, spatial_join_method)
-            )
-    else:
-        # Single polygon case
-        h3_ids = _generate_h3_ids(aoi_geojson, resolution, spatial_join_method)
+    # Generate H3 IDs as uint64
+    h3_ids_uint64 = geometry_to_cells(
+        geom, resolution, containment_mode=containment_mode
+    )
 
-    return h3_ids
+    return h3_ids_uint64
 
 
 def generate_h3_geometries(
-    h3_ids: List[str], geometry_type: Optional[str]
-) -> List[Dict[str, Any]]:
-    """
-    Generate geometries (polygon or point) for a list of H3 hexagon IDs.
-
-    Parameters:
-        h3_ids (List[str]): A list of H3 hexagon IDs.
-        geometry_type (Optional[str]):
-            The type of geometry to generate ('polygon' or 'point').
-
-    Returns:
-        List[Dict[str, Any]]: A list of geometries in GeoJSON format.
-    """
-    if geometry_type not in ["polygon", "point"]:
-        raise ValueError("Invalid geometry type")
-
-    geometries = []
-    for h3_id in h3_ids:
-        if geometry_type == "polygon":
-            hex_boundary = h3.h3_to_geo_boundary(h3_id, geo_json=True)
-            geometries.append(mapping(Polygon(hex_boundary)))
-        elif geometry_type == "point":
-            # h3_to_geo does not have geo_json parameter to invert order of coords
-            x, y = h3.h3_to_geo(h3_id)
-            geometries.append(mapping(Point(y, x)))
+    h3_ids_uint64: List[int], geometry_type: Literal["polygon", "point"] = "polygon"
+) -> List[Dict]:
+    if geometry_type == "polygon":
+        wkb_geometries = cells_to_wkb_polygons(h3_ids_uint64)
+    elif geometry_type == "point":
+        wkb_geometries = cells_to_wkb_points(h3_ids_uint64)
+    else:
+        raise ValueError(
+            f"Invalid geometry type. Use 'polygon' or 'point', not {geometry_type}"
+        )
 
-    return geometries
+    return to_geojson(from_wkb(wkb_geometries))
diff --git a/space2stats_api/src/space2stats/lib.py b/space2stats_api/src/space2stats/lib.py
index 6b8e4eb7..68e424d3 100644
--- a/space2stats_api/src/space2stats/lib.py
+++ b/space2stats_api/src/space2stats/lib.py
@@ -3,6 +3,7 @@
 
 import psycopg as pg
 from geojson_pydantic import Feature
+from h3ronpy.arrow import cells_to_string
 from psycopg import Connection
 
 from .h3_utils import generate_h3_geometries, generate_h3_ids
@@ -36,7 +37,7 @@ def __exit__(self, exc_type, exc_value, traceback) -> None:
         if self.conn:
             self.conn.close()
 
-    def _get_summaries(self, fields: List[str], h3_ids: List[str]):
+    def _get_summaries(self, fields: List[str], h3_ids: List[int]):
         colnames = ["hex_id"] + fields
         cols = [pg.sql.Identifier(c) for c in colnames]
         sql_query = pg.sql.SQL(
@@ -47,13 +48,16 @@ def _get_summaries(self, fields: List[str], h3_ids: List[str]):
             """
         ).format(pg.sql.SQL(", ").join(cols), pg.sql.Identifier(self.table_name))
 
-        # Convert h3_ids to a list to ensure compatibility with psycopg
-        h3_ids = list(h3_ids)
+        # Convert h3_ids to integers to ensure compatibility with psycopg
+        h3_ids = [
+            scalar.as_py() if hasattr(scalar, "as_py") else scalar for scalar in h3_ids
+        ]
+
         with self.conn.cursor() as cur:
             cur.execute(
                 sql_query,
                 [
-                    h3_ids,
+                    cells_to_string(h3_ids).to_pylist(),
                 ],
             )
             rows = cur.fetchall()
@@ -72,6 +76,10 @@ def summaries(
         if not isinstance(aoi, Feature):
             aoi = AoiModel.model_validate(aoi)
 
+        invalid_fields = [field for field in fields if field not in self.fields()]
+        if invalid_fields:
+            raise ValueError(f"Invalid fields: {invalid_fields}")
+
         # Get H3 ids from geometry
         resolution = 6
         h3_ids = generate_h3_ids(
@@ -84,19 +92,17 @@ def summaries(
             return []
 
         # Get Summaries from H3 ids
-        rows, colnames = self._get_summaries(fields=fields, h3_ids=list(h3_ids))
+        rows, colnames = self._get_summaries(fields=fields, h3_ids=h3_ids)
         if not rows:
             return []
 
         # Format Summaries
         summaries: List[Dict] = []
-        geometries = (
-            generate_h3_geometries(list(h3_ids), geometry) if geometry else None
-        )
+        geometries = generate_h3_geometries(h3_ids, geometry) if geometry else None
 
         for idx, row in enumerate(rows):
             summary = {"hex_id": row[0]}
-            if geometry and geometries:
+            if geometry and geometries is not None:
                 summary["geometry"] = geometries[idx]
 
             summary.update(
@@ -137,6 +143,10 @@ def aggregate(
         if not isinstance(aoi, Feature):
             aoi = AoiModel.model_validate(aoi)
 
+        invalid_fields = [field for field in fields if field not in self.fields()]
+        if invalid_fields:
+            raise ValueError(f"Invalid fields: {invalid_fields}")
+
         # Get H3 ids from geometry
         resolution = 6
         h3_ids = list(
@@ -147,6 +157,11 @@ def aggregate(
             )
         )
 
+        # Convert H3 scalar objects to integers
+        h3_ids = [
+            scalar.as_py() if hasattr(scalar, "as_py") else scalar for scalar in h3_ids
+        ]
+
         if not h3_ids:
             return {}
 
@@ -163,12 +178,10 @@ def aggregate(
             pg.sql.Identifier(self.table_name),
         )
 
-        # Convert h3_ids to a list to ensure compatibility with psycopg
-        h3_ids = list(h3_ids)
         with self.conn.cursor() as cur:
             cur.execute(
                 sql_query,
-                [h3_ids],
+                [cells_to_string(h3_ids).to_pylist()],
             )
             row = cur.fetchone()  # Get a single row of results
             colnames = [desc[0] for desc in cur.description]
diff --git a/space2stats_api/src/tests/test_api.py b/space2stats_api/src/tests/test_api.py
index b1e6d68a..f57abf31 100644
--- a/space2stats_api/src/tests/test_api.py
+++ b/space2stats_api/src/tests/test_api.py
@@ -1,4 +1,5 @@
 import pytest
+from shapely import from_geojson
 
 aoi = {
     "type": "Feature",
@@ -53,7 +54,7 @@ def test_bad_fields_validated(client):
 
     response = client.post("/summary", json=request_payload)
     assert response.status_code == 400
-    assert response.json() == {"error": 'column "a_non_existent_field" does not exist'}
+    assert response.json() == {"error": "Invalid fields: ['a_non_existent_field']"}
 
 
 @pytest.mark.parametrize("aggregation_type", ["sum", "avg", "count", "max", "min"])
@@ -114,7 +115,8 @@ def test_get_summary_with_geometry_multipolygon(client):
     for summary in response_json:
         assert "hex_id" in summary
         assert "geometry" in summary
-        assert summary["geometry"]["type"] == "Polygon"
+        geometry = from_geojson(summary["geometry"])
+        assert geometry.geom_type == "Polygon"
         assert len(summary) == len(request_payload["fields"]) + 2
 
 
@@ -135,7 +137,8 @@ def test_get_summary_with_geometry_polygon(client):
     for summary in response_json:
         assert "hex_id" in summary
         assert "geometry" in summary
-        assert summary["geometry"]["type"] == "Polygon"
+        geometry = from_geojson(summary["geometry"])
+        assert geometry.geom_type == "Polygon"
         assert len(summary) == len(request_payload["fields"]) + 2
 
 
@@ -148,6 +151,7 @@ def test_get_summary_with_geometry_point(client):
     }
 
     response = client.post("/summary", json=request_payload)
+    print(response.json())
     assert response.status_code == 200
     response_json = response.json()
     assert len(response_json) > 0, "Test query failed to return any summaries"
@@ -156,7 +160,8 @@ def test_get_summary_with_geometry_point(client):
     for summary in response_json:
         assert "hex_id" in summary
         assert "geometry" in summary
-        assert summary["geometry"]["type"] == "Point"
+        geometry = from_geojson(summary["geometry"])
+        assert geometry.geom_type == "Point"
         assert len(summary) == len(request_payload["fields"]) + 2
 
 
diff --git a/space2stats_api/src/tests/test_h3_utils.py b/space2stats_api/src/tests/test_h3_utils.py
index 86031780..163d5d0b 100644
--- a/space2stats_api/src/tests/test_h3_utils.py
+++ b/space2stats_api/src/tests/test_h3_utils.py
@@ -1,4 +1,6 @@
 import pytest
+from h3ronpy.arrow import cells_parse
+from shapely import from_geojson
 from shapely.geometry import MultiPolygon, Polygon, mapping
 from space2stats.h3_utils import generate_h3_geometries, generate_h3_ids
 
@@ -49,11 +51,15 @@ def test_generate_h3_ids_centroid_multipolygon():
 def test_generate_h3_geometries_polygon_multipolygon():
     h3_ids = generate_h3_ids(aoi_geojson_multi, resolution, "touches")
     geometries = generate_h3_geometries(h3_ids, "polygon")
+    print(geometries)
     assert len(geometries) == len(
         h3_ids
     ), "Expected the same number of geometries as H3 IDs"
     for geom in geometries:
-        assert geom["type"] == "Polygon", "Expected Polygon geometry for MultiPolygon"
+        geojson = from_geojson(geom)
+        assert (
+            geojson.geom_type == "Polygon"
+        ), "Expected Polygon geometry for MultiPolygon"
 
 
 def test_generate_h3_geometries_point_multipolygon():
@@ -62,8 +68,14 @@ def test_generate_h3_geometries_point_multipolygon():
     assert len(geometries) == len(
         h3_ids
     ), "Expected the same number of geometries as H3 IDs"
-    for geom in geometries:
-        assert geom["type"] == "Point", "Expected Point geometry for MultiPolygon"
+    print(geometries)
+    for g in geometries:
+        geojson = from_geojson(g)
+        print(dir(geojson))
+        assert geojson.geom_type == "Point"
+        assert len(geojson.coords) == 1
+        assert len(geojson.coords[0]) == 2
+        assert geojson.coords[0][0] != geojson.coords[0][1]
 
 
 def test_generate_h3_sliver_polygon_touches():
@@ -83,7 +95,7 @@ def test_generate_h3_sliver_polygon_touches():
         "touches",
     )
 
-    for h in ["867a74817ffffff", "867a74807ffffff"]:
+    for h in cells_parse(["867a74817ffffff", "867a74807ffffff"]):
         assert h in data, f"Missing {h} in generated hexagons"
     assert len(data) == 2
 
@@ -123,9 +135,7 @@ def test_generate_h3_sliver_polygon_centroid():
         6,
         "centroid",
     )
-    h = "867a74817ffffff"
-    assert "867a74817ffffff" in data, f"{h} not in generated hexagons"
-    assert len(data) == 1
+    assert len(data) == 0
 
 
 if __name__ == "__main__":
diff --git a/space2stats_api/src/tests/test_module.py b/space2stats_api/src/tests/test_module.py
index 4e2be5ee..1e61ac1f 100644
--- a/space2stats_api/src/tests/test_module.py
+++ b/space2stats_api/src/tests/test_module.py
@@ -1,4 +1,3 @@
-import psycopg as pg
 import pytest
 from geojson_pydantic import Feature
 from space2stats.lib import Settings, StatsTable
@@ -151,7 +150,7 @@ def test_aggregate_invalid_field(mock_env, database, aoi_example):
     )
 
     with StatsTable.connect(settings) as stats_table:
-        with pytest.raises(pg.errors.UndefinedColumn):
+        with pytest.raises(ValueError):
             stats_table.aggregate(
                 aoi=aoi_example,
                 spatial_join_method="centroid",