diff --git a/SQLCreate.ipynb b/SQLCreate-SQLMagic.ipynb
similarity index 100%
rename from SQLCreate.ipynb
rename to SQLCreate-SQLMagic.ipynb
diff --git a/SpatialSQL.ipynb b/SpatialSQL.ipynb
index 80dd170..e462d5e 100644
--- a/SpatialSQL.ipynb
+++ b/SpatialSQL.ipynb
@@ -1,93 +1,225 @@
 {
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "18414ef7-739d-47b9-b3ef-ffe8ff29cfa8",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Importing libraries\n",
     "import sqlite3\n",
     "import pandas"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "39742f38-5f10-4088-8423-27798c3235ac",
    "metadata": {},
    "source": [
     "D'abord on établit une connexion à la base de données :"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "40eb692d-b7f0-4c1f-96f5-8e99e54d2921",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Etablir la connexion à la base de données\n",
     "con = sqlite3.connect(\"india.sqlite\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "7a8829ae-6f4a-45a7-b8d5-3f84751cbca0",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Charger l'extension spatialite\n",
     "con.enable_load_extension(True)\n",
     "con.load_extension(\"mod_spatialite\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "2799208d-39ee-48af-bc2c-c3ceca3c3f06",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ID</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3593.0</td>\n",
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+       "    <tr>\n",
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+       "      <td>3594.0</td>\n",
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+       "      <td>3694.0</td>\n",
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+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>3734.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <td>3735.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>3747.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
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+       "    </tr>\n",
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+       "    </tr>\n",
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+       "  </tbody>\n",
+       "</table>\n",
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+      "text/plain": [
+       "        ID\n",
+       "0   3593.0\n",
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+       "7   3694.0\n",
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+       "10  3747.0\n",
+       "11  3757.0\n",
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+       "13  3760.0\n",
+       "14  3762.0\n",
+       "15  3763.0\n",
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+     "output_type": "display_data"
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+   ],
    "source": [
     "# Donner la requête à executer\n",
     "query = 'SELECT DISTINCT Cultivated_Fields.ID FROM Cultivated_Fields, Roads WHERE Distance(Cultivated_Fields.Geometry, Roads.Geometry) <10 and Roads.Type=\"double\"'\n",
     "\n",
     "# Executer la requête et récupérer la table résultat\n",
     "resulttable = pandas.read_sql_query(query, con)\n",
     "\n",
     "# Afficher la table résultat\n",
     "display(resulttable)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "0450c8de-85d0-4e19-96e9-7bd942e8b410",
    "metadata": {},
    "outputs": [],
    "source": []
   }
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