diff --git a/Spectacle/Stat_desc.ipynb b/Spectacle/Stat_desc.ipynb
index 2fb2c0d..c8e2dce 100644
--- a/Spectacle/Stat_desc.ipynb
+++ b/Spectacle/Stat_desc.ipynb
@@ -3855,163 +3855,74 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 229,
-   "id": "4c02ae98-9184-41d9-a9ea-ed9eaf719bd3",
+   "execution_count": 22,
+   "id": "d64979ba-fccf-45f2-8a15-40ef1b49c74f",
    "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>customer_id</th>\n",
-       "      <th>nb_tickets</th>\n",
-       "      <th>nb_purchases</th>\n",
-       "      <th>total_amount</th>\n",
-       "      <th>nb_suppliers</th>\n",
-       "      <th>vente_internet_max</th>\n",
-       "      <th>purchase_date_min</th>\n",
-       "      <th>purchase_date_max</th>\n",
-       "      <th>time_between_purchase</th>\n",
-       "      <th>nb_tickets_internet</th>\n",
-       "      <th>number_compagny</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>19482</td>\n",
-       "      <td>88</td>\n",
-       "      <td>29</td>\n",
-       "      <td>872.0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2643.092500</td>\n",
-       "      <td>718.149398</td>\n",
-       "      <td>1924.943102</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>19484</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2</td>\n",
-       "      <td>62.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1745.021736</td>\n",
-       "      <td>1743.045035</td>\n",
-       "      <td>1.976701</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>19485</td>\n",
-       "      <td>131</td>\n",
-       "      <td>21</td>\n",
-       "      <td>1878.0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2649.044745</td>\n",
-       "      <td>85.240845</td>\n",
-       "      <td>2563.803900</td>\n",
-       "      <td>84.0</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>19486</td>\n",
-       "      <td>10</td>\n",
-       "      <td>4</td>\n",
-       "      <td>96.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1944.077604</td>\n",
-       "      <td>1742.794225</td>\n",
-       "      <td>201.283380</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>19487</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1742.877766</td>\n",
-       "      <td>1742.877766</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customer_id  nb_tickets  nb_purchases  total_amount  nb_suppliers  \\\n",
-       "0        19482          88            29         872.0             2   \n",
-       "1        19484           3             2          62.0             1   \n",
-       "2        19485         131            21        1878.0             2   \n",
-       "3        19486          10             4          96.0             1   \n",
-       "4        19487           2             1          33.0             1   \n",
-       "\n",
-       "   vente_internet_max  purchase_date_min  purchase_date_max  \\\n",
-       "0                   1        2643.092500         718.149398   \n",
-       "1                   0        1745.021736        1743.045035   \n",
-       "2                   1        2649.044745          85.240845   \n",
-       "3                   0        1944.077604        1742.794225   \n",
-       "4                   0        1742.877766        1742.877766   \n",
-       "\n",
-       "   time_between_purchase  nb_tickets_internet  number_compagny  \n",
-       "0            1924.943102                  8.0               10  \n",
-       "1               1.976701                  0.0               10  \n",
-       "2            2563.803900                 84.0               10  \n",
-       "3             201.283380                  0.0               10  \n",
-       "4               0.000000                  0.0               10  "
-      ]
-     },
-     "execution_count": 229,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_430/3239820253.py:6: DtypeWarning: Columns (39) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  dataset_train = pd.read_csv(file_in, sep=\",\")\n"
+     ]
     }
    ],
    "source": [
-    "products_purchased_reduced_spectacle.head()"
+    "#base d'entrainement\n",
+    "\n",
+    "#FILE_PATH_S3='projet-bdc2324-team1/Generalization/musique/Train_test/dataset_train14.csv'\n",
+    "\n",
+    "#with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
+    "    #dataset_train = pd.read_csv(file_in, sep=\",\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "635d60cd-2dbc-49da-b0f4-94e16667882f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Creation de la variable dependante fictive: 1 si l'individu a effectué un achat au cours de la periode de train et 0 sinon\n",
+    "\n",
+    "#dataset_train_modif=dataset_train\n",
+    "\n",
+    "#dataset_train_modif[\"y_purchase_fictive\"]=np.random.randint(2, size=dataset_train_modif.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "ea63e5d6-70f9-4685-8b08-673a47108954",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#dataset_train_modif[\"y_purchase_fictive\"].value_counts(normalize=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "98f7645f-ffe6-4d7b-8032-15e65f36af87",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "#dataset_train_modif[\"y_purchase_fictive\"]=dataset_train_modif[\"y_purchase_fictive\"].replace([0,1],[\"Purchase_train\",\"no_purchase_train\"])"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e1a95b8f-6539-48bd-b09d-6f8f63d25fb2",
+   "id": "eb6355e0-3f8c-47d9-a5ee-d349040dcf51",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#nombre de ticket par compagnie\n",
+    "#repartion Chiffre d'affaire selon le numero de la compagnie\n",
     "\n",
-    "company_campaigns_stats = campaigns_information_spectacle.groupby(\"number_compagny\")[[\"nb_campaigns\", \"nb_campaigns_opened\"]].sum().reset_index()\n",
-    "company_campaigns_stats[\"ratio_campaigns_opened\"] = company_campaigns_stats[\"nb_campaigns_opened\"]  / company_campaigns_stats[\"nb_campaigns\"]\n",
-    "company_campaigns_stats"
+    "sns.boxplot(data=chiffre_affaire_categ, y=\"chiffre_affaire\",x=\"categ\",showfliers=False,showmeans=True)\n",
+    "plt.title(\"Boite à moustache du chiffre d'affaire selon les categories de livre\")"
    ]
   },
   {
@@ -4240,7 +4151,15 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0a180f0a-c6de-4e66-9ae8-fdbfdf8837c9",
+   "id": "93a8ae1f-6fbd-4210-a857-728ae472d1c5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "904cbf32-77b6-49dd-a96c-9e7e5a0175c3",
    "metadata": {},
    "outputs": [],
    "source": []