diff --git a/0_Cleaning_and_merge.ipynb b/0_Cleaning_and_merge.ipynb
index a3018ba..a8dfc0f 100644
--- a/0_Cleaning_and_merge.ipynb
+++ b/0_Cleaning_and_merge.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 1,
    "id": "15103481-8d74-404c-aa09-7601fe7730da",
    "metadata": {},
    "outputs": [],
@@ -119,10 +119,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "dd6a3518-b752-4a1e-b77b-9e03e853c3ed",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2240/4081512283.py:10: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  df = pd.read_csv(file_in)\n"
+     ]
+    }
+   ],
    "source": [
     "# loop to create dataframes from liste\n",
     "files_path = liste_database\n",
@@ -149,7 +158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "d237be96-8c86-4a91-b7a1-487e87a16c3d",
    "metadata": {},
    "outputs": [],
@@ -190,11 +199,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "7e7b90ce-da54-4f00-bc34-64c543b0858f",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "def preprocessing_customerplus(customerplus = None):\n",
+    "\n",
+    "    customerplus_copy = customerplus.copy()\n",
+    "    \n",
+    "    # Passage en format date\n",
+    "    cleaning_date(customerplus_copy, 'first_buying_date')\n",
+    "    cleaning_date(customerplus_copy, 'last_visiting_date')\n",
+    "    \n",
+    "    # Selection des variables\n",
+    "    customerplus_copy.drop(['lastname', 'firstname', 'email', 'civility', 'note', 'created_at', 'updated_at', 'deleted_at', 'extra', 'reference', 'extra_field', 'identifier', 'need_reload', 'preferred_category', 'preferred_supplier', 'preferred_formula', 'zipcode', 'last_visiting_date'], axis = 1, inplace=True)\n",
+    "    customerplus_copy.rename(columns = {'id' : 'customer_id'}, inplace = True)\n",
+    "\n",
+    "    return customerplus_copy\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "03329e32-00a5-42c8-9470-75f7b6216ccd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1_customerplus_clean = preprocessing_customerplus(df1_customersplus)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -206,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "b95464b1-26bc-4aac-84b4-45da83b92251",
    "metadata": {},
    "outputs": [],
@@ -222,8 +255,8 @@
     "    suppliers.rename(columns = {'name' : 'supplier_name'}, inplace = True)\n",
     "\n",
     "    # Base des types de billets\n",
-    "    # type_ofs = type_ofs[['id', 'name', 'children']]\n",
-    "    # type_ofs.rename(columns = {'name' : 'type_of_ticket_name'}, inplace = True)\n",
+    "    type_ofs = type_ofs[['id', 'name', 'children']]\n",
+    "    type_ofs.rename(columns = {'name' : 'type_of_ticket_name'}, inplace = True)\n",
     "\n",
     "    # Base des achats\n",
     "    # Nettoyage de la date d'achat\n",
@@ -236,9 +269,9 @@
     "    ticket_information = pd.merge(tickets, suppliers, left_on = 'supplier_id', right_on = 'id', how = 'inner')\n",
     "    ticket_information.drop(['supplier_id', 'id'], axis = 1, inplace=True)\n",
     "    \n",
-    "    # # Fusion avec type de tickets\n",
-    "    # ticket_information = pd.merge(ticket_information, type_ofs, left_on = 'type_of', right_on = 'id', how = 'inner')\n",
-    "    # ticket_information.drop(['type_of', 'id'], axis = 1, inplace=True)\n",
+    "    # Fusion avec type de tickets\n",
+    "    ticket_information = pd.merge(ticket_information, type_ofs, left_on = 'type_of', right_on = 'id', how = 'inner')\n",
+    "    ticket_information.drop(['type_of', 'id'], axis = 1, inplace=True)\n",
     "    \n",
     "    # Fusion avec achats\n",
     "    ticket_information = pd.merge(ticket_information, purchases, left_on = 'purchase_id', right_on = 'id', how = 'inner')\n",
@@ -249,22 +282,501 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "3e1d2ba7-ff4f-48eb-93a8-2bb648c70396",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2240/1591303091.py:5: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  tickets.rename(columns = {'id' : 'ticket_id'}, inplace = True)\n",
+      "/tmp/ipykernel_2240/1591303091.py:9: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  suppliers.rename(columns = {'name' : 'supplier_name'}, inplace = True)\n",
+      "/tmp/ipykernel_2240/1591303091.py:13: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  type_ofs.rename(columns = {'name' : 'type_of_ticket_name'}, inplace = True)\n"
+     ]
+    }
+   ],
    "source": [
     "df1_ticket_information = preprocessing_tickets_area(tickets = df1_tickets, purchases = df1_purchases, suppliers = df1_suppliers, type_ofs = df1_type_ofs)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "4b18edfc-6450-4c6a-9e7b-ee5a5808c8c9",
    "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>ticket_id</th>\n",
+       "      <th>product_id</th>\n",
+       "      <th>is_from_subscription</th>\n",
+       "      <th>supplier_name</th>\n",
+       "      <th>type_of_ticket_name</th>\n",
+       "      <th>children</th>\n",
+       "      <th>purchase_date</th>\n",
+       "      <th>customer_id</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>13070859</td>\n",
+       "      <td>225251</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vente en ligne</td>\n",
+       "      <td>Atelier</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2018-12-28 14:47:50+00:00</td>\n",
+       "      <td>48187</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13070860</td>\n",
+       "      <td>224914</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vente en ligne</td>\n",
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+       "      <td>pricing_formula</td>\n",
+       "      <td>2018-12-28 14:47:50+00:00</td>\n",
+       "      <td>48187</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13070861</td>\n",
+       "      <td>224914</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vente en ligne</td>\n",
+       "      <td>Atelier</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2018-12-28 14:47:50+00:00</td>\n",
+       "      <td>48187</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13070862</td>\n",
+       "      <td>224914</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vente en ligne</td>\n",
+       "      <td>Atelier</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2018-12-28 14:47:50+00:00</td>\n",
+       "      <td>48187</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13070863</td>\n",
+       "      <td>224914</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vente en ligne</td>\n",
+       "      <td>Atelier</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2018-12-28 14:47:50+00:00</td>\n",
+       "      <td>48187</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1826667</th>\n",
+       "      <td>18643847</td>\n",
+       "      <td>350454</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vad</td>\n",
+       "      <td>Billet en nombre</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2022-08-02 08:59:17+00:00</td>\n",
+       "      <td>41</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1826668</th>\n",
+       "      <td>19853111</td>\n",
+       "      <td>383564</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vad</td>\n",
+       "      <td>Billet en nombre</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2022-11-04 14:25:42+00:00</td>\n",
+       "      <td>62763</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1826669</th>\n",
+       "      <td>19860514</td>\n",
+       "      <td>383751</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vad</td>\n",
+       "      <td>Billet en nombre</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2022-11-18 10:47:26+00:00</td>\n",
+       "      <td>1195566</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1826670</th>\n",
+       "      <td>19860515</td>\n",
+       "      <td>383751</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vad</td>\n",
+       "      <td>Billet en nombre</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2022-11-18 10:47:26+00:00</td>\n",
+       "      <td>1195566</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1826671</th>\n",
+       "      <td>19860516</td>\n",
+       "      <td>383751</td>\n",
+       "      <td>False</td>\n",
+       "      <td>vad</td>\n",
+       "      <td>Billet en nombre</td>\n",
+       "      <td>pricing_formula</td>\n",
+       "      <td>2022-11-18 10:47:26+00:00</td>\n",
+       "      <td>1195566</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1826672 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         ticket_id  product_id  is_from_subscription   supplier_name  \\\n",
+       "0         13070859      225251                 False  vente en ligne   \n",
+       "1         13070860      224914                 False  vente en ligne   \n",
+       "2         13070861      224914                 False  vente en ligne   \n",
+       "3         13070862      224914                 False  vente en ligne   \n",
+       "4         13070863      224914                 False  vente en ligne   \n",
+       "...            ...         ...                   ...             ...   \n",
+       "1826667   18643847      350454                 False             vad   \n",
+       "1826668   19853111      383564                 False             vad   \n",
+       "1826669   19860514      383751                 False             vad   \n",
+       "1826670   19860515      383751                 False             vad   \n",
+       "1826671   19860516      383751                 False             vad   \n",
+       "\n",
+       "        type_of_ticket_name         children             purchase_date  \\\n",
+       "0                   Atelier  pricing_formula 2018-12-28 14:47:50+00:00   \n",
+       "1                   Atelier  pricing_formula 2018-12-28 14:47:50+00:00   \n",
+       "2                   Atelier  pricing_formula 2018-12-28 14:47:50+00:00   \n",
+       "3                   Atelier  pricing_formula 2018-12-28 14:47:50+00:00   \n",
+       "4                   Atelier  pricing_formula 2018-12-28 14:47:50+00:00   \n",
+       "...                     ...              ...                       ...   \n",
+       "1826667    Billet en nombre  pricing_formula 2022-08-02 08:59:17+00:00   \n",
+       "1826668    Billet en nombre  pricing_formula 2022-11-04 14:25:42+00:00   \n",
+       "1826669    Billet en nombre  pricing_formula 2022-11-18 10:47:26+00:00   \n",
+       "1826670    Billet en nombre  pricing_formula 2022-11-18 10:47:26+00:00   \n",
+       "1826671    Billet en nombre  pricing_formula 2022-11-18 10:47:26+00:00   \n",
+       "\n",
+       "         customer_id  \n",
+       "0              48187  \n",
+       "1              48187  \n",
+       "2              48187  \n",
+       "3              48187  \n",
+       "4              48187  \n",
+       "...              ...  \n",
+       "1826667           41  \n",
+       "1826668        62763  \n",
+       "1826669      1195566  \n",
+       "1826670      1195566  \n",
+       "1826671      1195566  \n",
+       "\n",
+       "[1826672 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1_ticket_information"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37499eae-1a7f-4dce-83b0-ff942ccf7a9d",
+   "metadata": {},
+   "source": [
+    "### KPI tickets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "043303fe-e90f-4689-a2a9-5d690555a045",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "df1_ticket_information"
+    "def tickets_kpi_function(tickets_information = None):\n",
+    "    tickets_information_copy = tickets_information.copy()\n",
+    "    tickets_information_copy['purchase_date_max'] = tickets_information_copy['purchase_date']\n",
+    "    tickets_kpi = (tickets_information_copy[['product_id', 'customer_id', 'ticket_id','supplier_name', 'purchase_date', 'purchase_date_max']]\n",
+    "                   .groupby(['product_id', 'customer_id'])\n",
+    "                   .agg({'ticket_id': 'count', \n",
+    "                         'supplier_name': 'nunique',\n",
+    "                         'purchase_date_max' : 'max',\n",
+    "                         'purchase_date' : 'min'})\n",
+    "                   .reset_index()\n",
+    "                  )\n",
+    "    \n",
+    "    tickets_kpi.rename(columns = {'ticket_id' : 'nb_tickets', \n",
+    "                                  'supplier_name' : 'nb_suppliers', \n",
+    "                                  'purchase_date' : 'purchase_date_min'}, inplace = True)\n",
+    "    \n",
+    "    tickets_kpi['time_between_purchase'] = tickets_kpi['purchase_date_max'] - tickets_kpi['purchase_date_min']\n",
+    "    \n",
+    "    return tickets_kpi\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "5882234a-1ed5-4269-87a6-0d75613476e3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1_tickets_kpi = tickets_kpi_function(tickets_information = df1_ticket_information)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "a7a452a6-cd5e-4c8b-b250-8a7d26e48fad",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>product_id</th>\n",
+       "      <th>customer_id</th>\n",
+       "      <th>nb_tickets</th>\n",
+       "      <th>nb_suppliers</th>\n",
+       "      <th>purchase_date_max</th>\n",
+       "      <th>purchase_date_min</th>\n",
+       "      <th>time_between_purchase</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>107310</td>\n",
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+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-06-05 14:37:13+00:00</td>\n",
+       "      <td>2019-06-05 14:18:38+00:00</td>\n",
+       "      <td>0 days 00:18:35</td>\n",
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+       "      <th>1</th>\n",
+       "      <td>110089</td>\n",
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+       "      <td>2017-02-17 13:32:51+00:00</td>\n",
+       "      <td>2017-02-17 13:32:51+00:00</td>\n",
+       "      <td>0 days 00:00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>110089</td>\n",
+       "      <td>54356</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-03-02 14:36:16+00:00</td>\n",
+       "      <td>2017-03-02 14:36:16+00:00</td>\n",
+       "      <td>0 days 00:00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>110089</td>\n",
+       "      <td>54357</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-03-06 15:16:41+00:00</td>\n",
+       "      <td>2017-03-06 15:16:41+00:00</td>\n",
+       "      <td>0 days 00:00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>110089</td>\n",
+       "      <td>54358</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-03-13 16:07:27+00:00</td>\n",
+       "      <td>2017-03-13 16:07:27+00:00</td>\n",
+       "      <td>0 days 00:00:00</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128360</th>\n",
+       "      <td>406026</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2023-11-08 12:53:31+00:00</td>\n",
+       "      <td>2023-11-08 09:30:28+00:00</td>\n",
+       "      <td>0 days 03:23:03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128361</th>\n",
+       "      <td>406027</td>\n",
+       "      <td>1</td>\n",
+       "      <td>31</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2023-11-08 15:59:11+00:00</td>\n",
+       "      <td>2023-11-08 09:15:36+00:00</td>\n",
+       "      <td>0 days 06:43:35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128362</th>\n",
+       "      <td>406028</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2023-11-08 14:56:08+00:00</td>\n",
+       "      <td>2023-11-08 11:18:37+00:00</td>\n",
+       "      <td>0 days 03:37:31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128363</th>\n",
+       "      <td>406029</td>\n",
+       "      <td>1256130</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2023-11-08 10:35:43+00:00</td>\n",
+       "      <td>2023-11-08 10:35:43+00:00</td>\n",
+       "      <td>0 days 00:00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128364</th>\n",
+       "      <td>406029</td>\n",
+       "      <td>1256133</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2023-11-08 16:51:19+00:00</td>\n",
+       "      <td>2023-11-08 16:51:19+00:00</td>\n",
+       "      <td>0 days 00:00:00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>128365 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        product_id  customer_id  nb_tickets  nb_suppliers  \\\n",
+       "0           107310         2805           4             2   \n",
+       "1           110089        54355           1             1   \n",
+       "2           110089        54356           1             1   \n",
+       "3           110089        54357           1             1   \n",
+       "4           110089        54358           1             1   \n",
+       "...            ...          ...         ...           ...   \n",
+       "128360      406026            1          11             2   \n",
+       "128361      406027            1          31             2   \n",
+       "128362      406028            1           2             1   \n",
+       "128363      406029      1256130           2             1   \n",
+       "128364      406029      1256133           3             1   \n",
+       "\n",
+       "               purchase_date_max         purchase_date_min  \\\n",
+       "0      2019-06-05 14:37:13+00:00 2019-06-05 14:18:38+00:00   \n",
+       "1      2017-02-17 13:32:51+00:00 2017-02-17 13:32:51+00:00   \n",
+       "2      2017-03-02 14:36:16+00:00 2017-03-02 14:36:16+00:00   \n",
+       "3      2017-03-06 15:16:41+00:00 2017-03-06 15:16:41+00:00   \n",
+       "4      2017-03-13 16:07:27+00:00 2017-03-13 16:07:27+00:00   \n",
+       "...                          ...                       ...   \n",
+       "128360 2023-11-08 12:53:31+00:00 2023-11-08 09:30:28+00:00   \n",
+       "128361 2023-11-08 15:59:11+00:00 2023-11-08 09:15:36+00:00   \n",
+       "128362 2023-11-08 14:56:08+00:00 2023-11-08 11:18:37+00:00   \n",
+       "128363 2023-11-08 10:35:43+00:00 2023-11-08 10:35:43+00:00   \n",
+       "128364 2023-11-08 16:51:19+00:00 2023-11-08 16:51:19+00:00   \n",
+       "\n",
+       "       time_between_purchase  \n",
+       "0            0 days 00:18:35  \n",
+       "1            0 days 00:00:00  \n",
+       "2            0 days 00:00:00  \n",
+       "3            0 days 00:00:00  \n",
+       "4            0 days 00:00:00  \n",
+       "...                      ...  \n",
+       "128360       0 days 03:23:03  \n",
+       "128361       0 days 06:43:35  \n",
+       "128362       0 days 03:37:31  \n",
+       "128363       0 days 00:00:00  \n",
+       "128364       0 days 00:00:00  \n",
+       "\n",
+       "[128365 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1_tickets_kpi"
    ]
   },
   {
@@ -277,7 +789,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "baed146a-9d3a-4397-a812-3d50c9a2f038",
    "metadata": {},
    "outputs": [],
@@ -306,32 +818,413 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "5fbfd88b-b94c-489c-9201-670e96e453e7",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2240/3848597476.py:4: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  targets.rename(columns = {'id' : 'target_id' , 'name' : 'target_name'}, inplace = True)\n"
+     ]
+    }
+   ],
    "source": [
     "df1_target_information = preprocessing_target_area(targets = df1_targets, target_types = df1_target_types, customer_target_mappings = df1_customer_target_mappings)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "b4f05142-2a22-42ef-a60d-f23cc4b5cb09",
    "metadata": {},
-   "outputs": [],
+   "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",
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+       "\n",
+       "    .dataframe thead th {\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>customer_id</th>\n",
+       "    </tr>\n",
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+       "      <th>target_name</th>\n",
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+       "    <tr>\n",
+       "      <th>...</th>\n",
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+       "    </tr>\n",
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+       "      <th>Automation_parrainage_newsletter_handicap_visuel</th>\n",
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+       "      <th>consentement optout mediation specialisee</th>\n",
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+       "      <td>1</td>\n",
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+       "      <td>1</td>\n",
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+       "    <tr>\n",
+       "      <th>Inactifs - fin du scénario</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>283 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                  customer_id\n",
+       "target_name                                                  \n",
+       "consentement optin mediation specialisee               150000\n",
+       "consentement optin jeune public                        149979\n",
+       "consentement optin b2c                                 108909\n",
+       "Arenametrix_bascule tel vers sib                        35216\n",
+       "consentement optout b2c                                 34523\n",
+       "...                                                       ...\n",
+       "Automation_parrainage_newsletter_handicap_visuel            1\n",
+       "consentement optout mediation specialisee                   1\n",
+       "Inscrits NL LSF formulaire                                  1\n",
+       "Market auto - contacts inactifs post-scénario               1\n",
+       "Inactifs - fin du scénario                                  1\n",
+       "\n",
+       "[283 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df1_target_information[['target_name', 'customer_id']].groupby('target_name').count().sort_values(by='customer_id', ascending=False)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "4417ff51-f501-4ab9-a192-4ab75764a8ed",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
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+       "      <th></th>\n",
+       "      <th>customer_id</th>\n",
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+       "      <th>target_name</th>\n",
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+       "      <th>COM Inscrits NL générale (historique)</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <th>DDCP MD Procès du Siècle</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DDCP Newsletter centres de loisirs</th>\n",
+       "      <td>1032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DDCP Newsletter enseignants</th>\n",
+       "      <td>4510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DDCP Newsletter jeune public</th>\n",
+       "      <td>3862</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DDCP Newsletter relais champ social</th>\n",
+       "      <td>2270</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DDCP PROMO Participants ateliers (adultes et enfants)</th>\n",
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+       "    </tr>\n",
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+       "    </tr>\n",
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+       "      <td>1293</td>\n",
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+       "    <tr>\n",
+       "      <th>DDCP rentrée culturelle 2023</th>\n",
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+       "    </tr>\n",
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+       "      <td>1043</td>\n",
+       "    </tr>\n",
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+       "      <th>DRE Festival Jean Rouch</th>\n",
+       "      <td>1502</td>\n",
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+       "      <th>DRE MucemLab</th>\n",
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+       "    </tr>\n",
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+       "      <th>DRE chercheurs</th>\n",
+       "      <td>1557</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DRE institutionnels</th>\n",
+       "      <td>2229</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>FORMATION _ acheteurs optin last year</th>\n",
+       "      <td>10485</td>\n",
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+       "      <th>Inscrits NL générale (export_291019 + operation_videomaton)</th>\n",
+       "      <td>14086</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Inscrits NL générale site web</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Inscrits NL jeune public site web</th>\n",
+       "      <td>1249</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Votre première liste</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>consentement optin b2b</th>\n",
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+       "      <th>consentement optin newsletter generale</th>\n",
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+       "    <tr>\n",
+       "      <th>consentement optin scolaires</th>\n",
+       "      <td>4849</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>consentement optout b2b</th>\n",
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+       "      <th>consentement optout scolaires</th>\n",
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+       "    </tr>\n",
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+       "    <tr>\n",
+       "      <th>ddcp_promo_visiteurs occasionnels_musee_8mois</th>\n",
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+       "      <th>festival_jean_rouch</th>\n",
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+       "      <th>structures_etiquette champ social</th>\n",
+       "      <td>1488</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                    customer_id\n",
+       "target_name                                                    \n",
+       "Arenametrix_bascule tel vers sib                          35216\n",
+       "Autres_interet_exposition                                  1021\n",
+       "COM Inscrits NL générale (historique)                     23005\n",
+       "Contacts_prenomsdoubles                                   11643\n",
+       "DDCP MD Procès du Siècle                                   1684\n",
+       "DDCP Newsletter centres de loisirs                         1032\n",
+       "DDCP Newsletter enseignants                                4510\n",
+       "DDCP Newsletter jeune public                               3862\n",
+       "DDCP Newsletter relais champ social                        2270\n",
+       "DDCP PROMO Participants ateliers (adultes et en...         1954\n",
+       "DDCP billets famille                                       3609\n",
+       "DDCP promo MD pass musées dps oct 2018                     1785\n",
+       "DDCP promo Plan B 2019 (concerts)                          1948\n",
+       "DDCP promo spectateurs prog 21-22 (spectacles, ...         1293\n",
+       "DDCP rentrée culturelle 2023                               1757\n",
+       "DDCP_marseille_jazz_2023                                   1043\n",
+       "DRE Festival Jean Rouch                                    1502\n",
+       "DRE MucemLab                                               2302\n",
+       "DRE chercheurs                                             1557\n",
+       "DRE institutionnels                                        2229\n",
+       "FORMATION _ acheteurs optin last year                     10485\n",
+       "Inscrits NL générale (export_291019 + operation...        14086\n",
+       "Inscrits NL générale site web                              3732\n",
+       "Inscrits NL jeune public site web                          1249\n",
+       "Votre première liste                                       3715\n",
+       "consentement optin b2b                                    12735\n",
+       "consentement optin b2c                                   108909\n",
+       "consentement optin dre                                     4527\n",
+       "consentement optin jeune public                          149979\n",
+       "consentement optin mediation specialisee                 150000\n",
+       "consentement optin newsletter generale                    22095\n",
+       "consentement optin scolaires                               4849\n",
+       "consentement optout b2b                                   14219\n",
+       "consentement optout b2c                                   34523\n",
+       "consentement optout dre                                   14328\n",
+       "consentement optout newsletter generale                   18855\n",
+       "consentement optout scolaires                             15744\n",
+       "ddcp_md_scene_ouverte_au_talent                            1577\n",
+       "ddcp_promo_MD_billet_musée_oct_2019_agarder2               5482\n",
+       "ddcp_promo_md_musée_dps 011019                             6010\n",
+       "ddcp_promo_visiteurs occasionnels_musee_8mois              6640\n",
+       "ddcp_visiteurs dps 010622                                 12355\n",
+       "festival_jean_rouch                                        1502\n",
+       "rappel po barvalo                                          1248\n",
+       "structures_etiquette champ social                          1488"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df1_target_information_reduced = df1_target_information[['target_name', 'customer_id']].groupby('target_name').count()\n",
     "df1_target_information_reduced[df1_target_information_reduced['customer_id'] >= 1000]"
@@ -347,7 +1240,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "d883cc7b-ac43-4485-b86f-eaf595fbad85",
    "metadata": {},
    "outputs": [],
@@ -372,32 +1265,278 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "c8552dd6-52c5-4431-b43d-3cd6c578fd9f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2240/1967867975.py:15: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  df[column_name] = pd.to_datetime(df[column_name], utc = True, format = 'ISO8601')\n",
+      "/tmp/ipykernel_2240/1967867975.py:15: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  df[column_name] = pd.to_datetime(df[column_name], utc = True, format = 'ISO8601')\n",
+      "/tmp/ipykernel_2240/1967867975.py:15: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  df[column_name] = pd.to_datetime(df[column_name], utc = True, format = 'ISO8601')\n"
+     ]
+    }
+   ],
    "source": [
     "df1_campaigns_information = preprocessing_campaigns_area(campaign_stats = df1_campaign_stats, campaigns = df1_campaigns)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "c24457e7-3cad-451a-a65b-7373b656bd6e",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>customer_id</th>\n",
+       "      <th>opened_at</th>\n",
+       "      <th>sent_at</th>\n",
+       "      <th>delivered_at</th>\n",
+       "      <th>campaign_name</th>\n",
+       "      <th>campaign_service_id</th>\n",
+       "      <th>campaign_sent_at</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>19793</td>\n",
+       "      <td>112597</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>2021-03-28 16:01:09+00:00</td>\n",
+       "      <td>2021-03-28 16:24:18+00:00</td>\n",
+       "      <td>Le Mucem chez vous, gardons le lien #22</td>\n",
+       "      <td>404</td>\n",
+       "      <td>2021-03-27 23:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>14211</td>\n",
+       "      <td>113666</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>2021-03-28 16:01:09+00:00</td>\n",
+       "      <td>2021-03-28 16:21:02+00:00</td>\n",
+       "      <td>Le Mucem chez vous, gardons le lien #22</td>\n",
+       "      <td>404</td>\n",
+       "      <td>2021-03-27 23:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13150</td>\n",
+       "      <td>280561</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>2021-03-28 16:00:59+00:00</td>\n",
+       "      <td>2021-03-28 16:08:45+00:00</td>\n",
+       "      <td>Le Mucem chez vous, gardons le lien #22</td>\n",
+       "      <td>404</td>\n",
+       "      <td>2021-03-27 23:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7073</td>\n",
+       "      <td>101007</td>\n",
+       "      <td>2021-03-28 18:11:06+00:00</td>\n",
+       "      <td>2021-03-28 16:00:59+00:00</td>\n",
+       "      <td>2021-03-28 16:09:47+00:00</td>\n",
+       "      <td>Le Mucem chez vous, gardons le lien #22</td>\n",
+       "      <td>404</td>\n",
+       "      <td>2021-03-27 23:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5175</td>\n",
+       "      <td>103972</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>2021-03-28 16:01:06+00:00</td>\n",
+       "      <td>2021-03-28 16:05:03+00:00</td>\n",
+       "      <td>Le Mucem chez vous, gardons le lien #22</td>\n",
+       "      <td>404</td>\n",
+       "      <td>2021-03-27 23:00:00+00:00</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6214803</th>\n",
+       "      <td>8302994</td>\n",
+       "      <td>266155</td>\n",
+       "      <td>2023-10-23 09:43:25+00:00</td>\n",
+       "      <td>2023-10-23 09:32:33+00:00</td>\n",
+       "      <td>2023-10-23 09:32:34+00:00</td>\n",
+       "      <td>dre_nov_2023</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>2023-10-23 09:31:17+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6214804</th>\n",
+       "      <td>8303307</td>\n",
+       "      <td>21355</td>\n",
+       "      <td>2023-10-23 09:44:02+00:00</td>\n",
+       "      <td>2023-10-23 09:32:49+00:00</td>\n",
+       "      <td>2023-10-23 09:32:49+00:00</td>\n",
+       "      <td>dre_nov_2023</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>2023-10-23 09:31:17+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6214805</th>\n",
+       "      <td>8304346</td>\n",
+       "      <td>21849</td>\n",
+       "      <td>2023-10-23 09:45:52+00:00</td>\n",
+       "      <td>2023-10-23 09:33:28+00:00</td>\n",
+       "      <td>2023-10-23 09:33:29+00:00</td>\n",
+       "      <td>dre_nov_2023</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>2023-10-23 09:31:17+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6214806</th>\n",
+       "      <td>8302037</td>\n",
+       "      <td>667789</td>\n",
+       "      <td>2023-10-23 09:47:32+00:00</td>\n",
+       "      <td>2023-10-23 09:31:53+00:00</td>\n",
+       "      <td>2023-10-23 09:31:54+00:00</td>\n",
+       "      <td>dre_nov_2023</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>2023-10-23 09:31:17+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6214807</th>\n",
+       "      <td>8304939</td>\n",
+       "      <td>294154</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>2023-10-23 09:33:54+00:00</td>\n",
+       "      <td>2023-10-23 09:33:55+00:00</td>\n",
+       "      <td>dre_nov_2023</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>2023-10-23 09:31:17+00:00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6214808 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              id  customer_id                 opened_at  \\\n",
+       "0          19793       112597                       NaT   \n",
+       "1          14211       113666                       NaT   \n",
+       "2          13150       280561                       NaT   \n",
+       "3           7073       101007 2021-03-28 18:11:06+00:00   \n",
+       "4           5175       103972                       NaT   \n",
+       "...          ...          ...                       ...   \n",
+       "6214803  8302994       266155 2023-10-23 09:43:25+00:00   \n",
+       "6214804  8303307        21355 2023-10-23 09:44:02+00:00   \n",
+       "6214805  8304346        21849 2023-10-23 09:45:52+00:00   \n",
+       "6214806  8302037       667789 2023-10-23 09:47:32+00:00   \n",
+       "6214807  8304939       294154                       NaT   \n",
+       "\n",
+       "                          sent_at              delivered_at  \\\n",
+       "0       2021-03-28 16:01:09+00:00 2021-03-28 16:24:18+00:00   \n",
+       "1       2021-03-28 16:01:09+00:00 2021-03-28 16:21:02+00:00   \n",
+       "2       2021-03-28 16:00:59+00:00 2021-03-28 16:08:45+00:00   \n",
+       "3       2021-03-28 16:00:59+00:00 2021-03-28 16:09:47+00:00   \n",
+       "4       2021-03-28 16:01:06+00:00 2021-03-28 16:05:03+00:00   \n",
+       "...                           ...                       ...   \n",
+       "6214803 2023-10-23 09:32:33+00:00 2023-10-23 09:32:34+00:00   \n",
+       "6214804 2023-10-23 09:32:49+00:00 2023-10-23 09:32:49+00:00   \n",
+       "6214805 2023-10-23 09:33:28+00:00 2023-10-23 09:33:29+00:00   \n",
+       "6214806 2023-10-23 09:31:53+00:00 2023-10-23 09:31:54+00:00   \n",
+       "6214807 2023-10-23 09:33:54+00:00 2023-10-23 09:33:55+00:00   \n",
+       "\n",
+       "                                   campaign_name  campaign_service_id  \\\n",
+       "0        Le Mucem chez vous, gardons le lien #22                  404   \n",
+       "1        Le Mucem chez vous, gardons le lien #22                  404   \n",
+       "2        Le Mucem chez vous, gardons le lien #22                  404   \n",
+       "3        Le Mucem chez vous, gardons le lien #22                  404   \n",
+       "4        Le Mucem chez vous, gardons le lien #22                  404   \n",
+       "...                                          ...                  ...   \n",
+       "6214803                             dre_nov_2023                 1318   \n",
+       "6214804                             dre_nov_2023                 1318   \n",
+       "6214805                             dre_nov_2023                 1318   \n",
+       "6214806                             dre_nov_2023                 1318   \n",
+       "6214807                             dre_nov_2023                 1318   \n",
+       "\n",
+       "                 campaign_sent_at  \n",
+       "0       2021-03-27 23:00:00+00:00  \n",
+       "1       2021-03-27 23:00:00+00:00  \n",
+       "2       2021-03-27 23:00:00+00:00  \n",
+       "3       2021-03-27 23:00:00+00:00  \n",
+       "4       2021-03-27 23:00:00+00:00  \n",
+       "...                           ...  \n",
+       "6214803 2023-10-23 09:31:17+00:00  \n",
+       "6214804 2023-10-23 09:31:17+00:00  \n",
+       "6214805 2023-10-23 09:31:17+00:00  \n",
+       "6214806 2023-10-23 09:31:17+00:00  \n",
+       "6214807 2023-10-23 09:31:17+00:00  \n",
+       "\n",
+       "[6214808 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df1_campaigns_information"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "e2c88552-b863-47a2-be23-8d2898fb28bc",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def campaigns_kpi(campaigns_information = None):\n",
+    "def campaigns_kpi_function(campaigns_information = None):\n",
     "    # Nombre de campagnes de mails\n",
     "    nb_campaigns = campaigns_information[['customer_id', 'campaign_name']].groupby('customer_id').count().reset_index()\n",
     "    nb_campaigns.rename(columns = {'campaign_name' : 'nb_campaigns'}, inplace = True)\n",
@@ -426,20 +1565,177 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "24537647-bc29-4777-9848-ac4120a4aa60",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2240/3700263836.py:11: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  opened_campaign.dropna(subset=['opened_at'], inplace=True)\n"
+     ]
+    }
+   ],
    "source": [
-    "df1_campaigns_kpi = campaigns_kpi(campaigns_information = df1_campaigns_information) "
+    "df1_campaigns_kpi = campaigns_kpi_function(campaigns_information = df1_campaigns_information) "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "6be2a9a6-056b-4e19-8c26-a18ba3df36b3",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>customer_id</th>\n",
+       "      <th>nb_campaigns</th>\n",
+       "      <th>nb_campaigns_opened</th>\n",
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+       "  </tbody>\n",
+       "</table>\n",
+       "<p>130472 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        customer_id  nb_campaigns  nb_campaigns_opened  \\\n",
+       "0                 2             4                  0.0   \n",
+       "1                 3           222                124.0   \n",
+       "2                 4             7                  7.0   \n",
+       "3                 5             4                  0.0   \n",
+       "4                 6            20                  0.0   \n",
+       "...             ...           ...                  ...   \n",
+       "130467      1256097             1                  1.0   \n",
+       "130468      1256098             1                  0.0   \n",
+       "130469      1256099             1                  0.0   \n",
+       "130470      1256100             1                  0.0   \n",
+       "130471      1256101             1                  0.0   \n",
+       "\n",
+       "                    time_to_open  \n",
+       "0                            NaT  \n",
+       "1      1 days 00:28:30.169354838  \n",
+       "2      1 days 04:31:01.428571428  \n",
+       "3                            NaT  \n",
+       "4                            NaT  \n",
+       "...                          ...  \n",
+       "130467           0 days 02:11:15  \n",
+       "130468                       NaT  \n",
+       "130469                       NaT  \n",
+       "130470                       NaT  \n",
+       "130471                       NaT  \n",
+       "\n",
+       "[130472 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df1_campaigns_kpi"
    ]
@@ -462,7 +1758,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 24,
    "id": "30488a40-1b38-4b9a-9d3b-26a0597c5e6d",
    "metadata": {},
    "outputs": [],
@@ -473,7 +1769,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 25,
    "id": "607eb4b4-eed9-4b50-b823-f75c116dd37c",
    "metadata": {},
    "outputs": [],
@@ -544,7 +1840,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 26,
    "id": "350b09b9-451f-4d47-81fe-f34b892db027",
    "metadata": {},
    "outputs": [],
@@ -632,7 +1928,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 27,
    "id": "0fccc8ef-e575-4857-a401-94a7274394df",
    "metadata": {},
    "outputs": [
@@ -785,7 +2081,7 @@
        "4   indiv entrées tp  "
       ]
      },
-     "execution_count": 32,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -797,7 +2093,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 28,
    "id": "779d8aaf-6668-4f66-8852-847304407ea3",
    "metadata": {},
    "outputs": [
@@ -967,7 +2263,7 @@
        "4          spectacle vivant           mucem  "
       ]
      },
-     "execution_count": 33,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -979,7 +2275,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 29,
    "id": "7714fa32-303b-4ea7-b174-3fd0fcab5af0",
    "metadata": {},
    "outputs": [
@@ -1078,7 +2374,7 @@
        "4        37                    383                269            1"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1098,7 +2394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 30,
    "id": "15a62ed6-35e4-4abc-aeef-a7daeec0a4ba",
    "metadata": {},
    "outputs": [],
@@ -1126,7 +2422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 31,
    "id": "89dc9685-1de9-4ce3-a6c0-8d7f1931a951",
    "metadata": {},
    "outputs": [
@@ -1330,7 +2626,7 @@
        "4          1     8.5          False                non défini           mucem  "
       ]
      },
-     "execution_count": 36,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1340,10 +2636,35 @@
     "products_global.head()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "7c3211a5-a851-43bc-a1f0-b39d51857fb7",
+   "metadata": {},
+   "source": [
+    "# Fusion des bases locales"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "46de1912-4a66-46e5-8b9e-7768b2d2723b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Fusion liée au product\n",
+    "df1_product_purchased = pd.merge(df1_tickets_kpi, products_global, left_on = 'product_id', right_on = 'id_products', how = 'inner')\n",
+    "\n",
+    "# Fusion liée au customer\n",
+    "df1_customer = pd.merge(df1_customerplus_clean, df1_campaigns_kpi, on = 'customer_id', how = 'left')\n",
+    "\n",
+    "# Fusion product et customer\n",
+    "df1_customer_product = pd.merge(df1_customer, df1_product_purchased, on = 'customer_id', how = 'left')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "117d172a-2195-4060-9245-96c6f637ebbd",
+   "id": "1e42a790-b215-4107-a969-85005da06ebd",
    "metadata": {},
    "outputs": [],
    "source": []