diff --git a/0_Cleaning_and_merge.ipynb b/0_Cleaning_and_merge.ipynb
index 68efb55..be348ed 100644
--- a/0_Cleaning_and_merge.ipynb
+++ b/0_Cleaning_and_merge.ipynb
@@ -1759,6 +1759,772 @@
     "# Construction des variables explicatives"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b09c2964-bef9-489e-ad71-84959054531b",
+   "metadata": {},
+   "source": [
+    "## Alexis' work"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "id": "4ab1c0d2-0097-4669-b984-b6822c976740",
+   "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>event_type_id</th>\n",
+       "      <th>avg_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2</td>\n",
+       "      <td>6.150659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4</td>\n",
+       "      <td>7.762474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>4.452618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>6</td>\n",
+       "      <td>6.439463</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   event_type_id  avg_amount\n",
+       "0              2    6.150659\n",
+       "1              4    7.762474\n",
+       "2              5    4.452618\n",
+       "3              6    6.439463"
+      ]
+     },
+     "execution_count": 142,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "avg_amount =  (df1_products_purchased_reduced.groupby([\"event_type_id\"])\n",
+    "              .agg({\"amount\" : \"mean\"}).reset_index()\n",
+    "              .rename(columns = {'amount' : 'avg_amount'}))\n",
+    "\n",
+    "avg_amount"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "a9c62b39-389e-4dac-89a6-ac8a59fea58a",
+   "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>event_type_id</th>\n",
+       "      <th>nb_tickets</th>\n",
+       "      <th>avg_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>384226</td>\n",
+       "      <td>6.150659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>453242</td>\n",
+       "      <td>7.762474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>201750</td>\n",
+       "      <td>4.452618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>217356</td>\n",
+       "      <td>6.439463</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>143</td>\n",
+       "      <td>6.150659</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id  event_type_id  nb_tickets  avg_amount\n",
+       "0            1              2      384226    6.150659\n",
+       "1            1              4      453242    7.762474\n",
+       "2            1              5      201750    4.452618\n",
+       "3            1              6      217356    6.439463\n",
+       "4            2              2         143    6.150659"
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nb_tickets = (df1_products_purchased_reduced.groupby([\"customer_id\", \"event_type_id\"])\n",
+    "              .agg({\"ticket_id\" : \"count\"}).reset_index()\n",
+    "              .rename(columns = {'ticket_id' : 'nb_tickets'})\n",
+    "             .merge(avg_amount, how='left', on='event_type_id'))\n",
+    "nb_tickets.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "8710611c-7eb8-45ca-bdcc-009f4081f9e2",
+   "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>birthdate</th>\n",
+       "      <th>street_id</th>\n",
+       "      <th>is_partner</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>is_email_true</th>\n",
+       "      <th>opt_in</th>\n",
+       "      <th>structure_id</th>\n",
+       "      <th>profession</th>\n",
+       "      <th>language</th>\n",
+       "      <th>mcp_contact_id</th>\n",
+       "      <th>last_buying_date</th>\n",
+       "      <th>max_price</th>\n",
+       "      <th>ticket_sum</th>\n",
+       "      <th>average_price</th>\n",
+       "      <th>fidelity</th>\n",
+       "      <th>average_purchase_delay</th>\n",
+       "      <th>average_price_basket</th>\n",
+       "      <th>average_ticket_basket</th>\n",
+       "      <th>total_price</th>\n",
+       "      <th>purchase_count</th>\n",
+       "      <th>first_buying_date</th>\n",
+       "      <th>country</th>\n",
+       "      <th>age</th>\n",
+       "      <th>tenant_id</th>\n",
+       "      <th>nb_campaigns</th>\n",
+       "      <th>nb_campaigns_opened</th>\n",
+       "      <th>time_to_open</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>12751</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12825</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11261</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13071</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>653061</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0 days 19:53:02.500000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id birthdate  street_id  is_partner  gender  is_email_true  \\\n",
+       "0        12751       NaN          2       False       1           True   \n",
+       "1        12825       NaN          2       False       2           True   \n",
+       "2        11261       NaN          2       False       1           True   \n",
+       "3        13071       NaN          2       False       2           True   \n",
+       "4       653061       NaN         10       False       2           True   \n",
+       "\n",
+       "   opt_in  structure_id profession language  mcp_contact_id last_buying_date  \\\n",
+       "0    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "1    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "2    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "3    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "4   False           NaN        NaN      NaN             NaN              NaN   \n",
+       "\n",
+       "   max_price  ticket_sum  average_price  fidelity  average_purchase_delay  \\\n",
+       "0        NaN           0            0.0         0                     NaN   \n",
+       "1        NaN           0            0.0         0                     NaN   \n",
+       "2        NaN           0            0.0         0                     NaN   \n",
+       "3        NaN           0            0.0         0                     NaN   \n",
+       "4        NaN           0            0.0         0                     NaN   \n",
+       "\n",
+       "   average_price_basket  average_ticket_basket  total_price  purchase_count  \\\n",
+       "0                   NaN                    NaN          NaN               0   \n",
+       "1                   NaN                    NaN          NaN               0   \n",
+       "2                   NaN                    NaN          NaN               0   \n",
+       "3                   NaN                    NaN          NaN               0   \n",
+       "4                   NaN                    NaN          NaN               0   \n",
+       "\n",
+       "  first_buying_date country  age  tenant_id  nb_campaigns  \\\n",
+       "0               NaT      fr  NaN       1311           NaN   \n",
+       "1               NaT      fr  NaN       1311           NaN   \n",
+       "2               NaT      fr  NaN       1311           NaN   \n",
+       "3               NaT      fr  NaN       1311           NaN   \n",
+       "4               NaT     NaN  NaN       1311          80.0   \n",
+       "\n",
+       "   nb_campaigns_opened           time_to_open  \n",
+       "0                  NaN                    NaT  \n",
+       "1                  NaN                    NaT  \n",
+       "2                  NaN                    NaT  \n",
+       "3                  NaN                    NaT  \n",
+       "4                  2.0 0 days 19:53:02.500000  "
+      ]
+     },
+     "execution_count": 144,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Fusion avec KPI campaigns liés au customer\n",
+    "df1_customer = pd.merge(df1_customerplus_clean, df1_campaigns_kpi, on = 'customer_id', how = 'left')\n",
+    "df1_customer.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "a89fad43-ee68-4081-9384-3e9f08ec6a59",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "shape :  (156289, 31)\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>customer_id</th>\n",
+       "      <th>birthdate</th>\n",
+       "      <th>street_id</th>\n",
+       "      <th>is_partner</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>is_email_true</th>\n",
+       "      <th>opt_in</th>\n",
+       "      <th>structure_id</th>\n",
+       "      <th>profession</th>\n",
+       "      <th>language</th>\n",
+       "      <th>mcp_contact_id</th>\n",
+       "      <th>last_buying_date</th>\n",
+       "      <th>max_price</th>\n",
+       "      <th>ticket_sum</th>\n",
+       "      <th>average_price</th>\n",
+       "      <th>fidelity</th>\n",
+       "      <th>average_purchase_delay</th>\n",
+       "      <th>average_price_basket</th>\n",
+       "      <th>average_ticket_basket</th>\n",
+       "      <th>total_price</th>\n",
+       "      <th>purchase_count</th>\n",
+       "      <th>first_buying_date</th>\n",
+       "      <th>country</th>\n",
+       "      <th>age</th>\n",
+       "      <th>tenant_id</th>\n",
+       "      <th>nb_campaigns</th>\n",
+       "      <th>nb_campaigns_opened</th>\n",
+       "      <th>time_to_open</th>\n",
+       "      <th>event_type_id</th>\n",
+       "      <th>nb_tickets</th>\n",
+       "      <th>avg_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>12751</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12825</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11261</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13071</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>fr</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>653061</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0 days 19:53:02.500000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id birthdate  street_id  is_partner  gender  is_email_true  \\\n",
+       "0        12751       NaN          2       False       1           True   \n",
+       "1        12825       NaN          2       False       2           True   \n",
+       "2        11261       NaN          2       False       1           True   \n",
+       "3        13071       NaN          2       False       2           True   \n",
+       "4       653061       NaN         10       False       2           True   \n",
+       "\n",
+       "   opt_in  structure_id profession language  mcp_contact_id last_buying_date  \\\n",
+       "0    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "1    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "2    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "3    True           NaN        NaN      NaN             NaN              NaN   \n",
+       "4   False           NaN        NaN      NaN             NaN              NaN   \n",
+       "\n",
+       "   max_price  ticket_sum  average_price  fidelity  average_purchase_delay  \\\n",
+       "0        NaN           0            0.0         0                     NaN   \n",
+       "1        NaN           0            0.0         0                     NaN   \n",
+       "2        NaN           0            0.0         0                     NaN   \n",
+       "3        NaN           0            0.0         0                     NaN   \n",
+       "4        NaN           0            0.0         0                     NaN   \n",
+       "\n",
+       "   average_price_basket  average_ticket_basket  total_price  purchase_count  \\\n",
+       "0                   NaN                    NaN          NaN               0   \n",
+       "1                   NaN                    NaN          NaN               0   \n",
+       "2                   NaN                    NaN          NaN               0   \n",
+       "3                   NaN                    NaN          NaN               0   \n",
+       "4                   NaN                    NaN          NaN               0   \n",
+       "\n",
+       "  first_buying_date country  age  tenant_id  nb_campaigns  \\\n",
+       "0               NaT      fr  NaN       1311           NaN   \n",
+       "1               NaT      fr  NaN       1311           NaN   \n",
+       "2               NaT      fr  NaN       1311           NaN   \n",
+       "3               NaT      fr  NaN       1311           NaN   \n",
+       "4               NaT     NaN  NaN       1311          80.0   \n",
+       "\n",
+       "   nb_campaigns_opened           time_to_open  event_type_id  nb_tickets  \\\n",
+       "0                  NaN                    NaT            NaN         NaN   \n",
+       "1                  NaN                    NaT            NaN         NaN   \n",
+       "2                  NaN                    NaT            NaN         NaN   \n",
+       "3                  NaN                    NaT            NaN         NaN   \n",
+       "4                  2.0 0 days 19:53:02.500000            NaN         NaN   \n",
+       "\n",
+       "   avg_amount  \n",
+       "0         NaN  \n",
+       "1         NaN  \n",
+       "2         NaN  \n",
+       "3         NaN  \n",
+       "4         NaN  "
+      ]
+     },
+     "execution_count": 146,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1_customer_product = pd.merge(df1_customer, nb_tickets, on = 'customer_id', how = 'left')\n",
+    "print(\"shape : \", df1_customer_product.shape)\n",
+    "df1_customer_product.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "id": "a19fec00-4ece-400c-937c-ce5cd8daccfd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1_customer_product.to_csv(\"customer_product.csv\", index = False)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "314f1b7f-ae48-4c6f-8469-9ce879043243",