diff --git a/data_1-Copy1.ipynb b/data_1-Copy1.ipynb
new file mode 100644
index 0000000..5ecebd5
--- /dev/null
+++ b/data_1-Copy1.ipynb
@@ -0,0 +1,1724 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e637deae-9168-4fb2-b95f-4e42d8d72d9e",
+   "metadata": {},
+   "source": [
+    "# DATA COLLECTION "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f8508d94-74a7-4bb0-8b81-c2e06850c25f",
+   "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>Agreement - Code</th>\n",
+       "      <th>Company - Id</th>\n",
+       "      <th>Company - Ultimate Parent Id</th>\n",
+       "      <th>Registrar Account - ID</th>\n",
+       "      <th>Registrar Account - Region</th>\n",
+       "      <th>RegistrarAccount - Country</th>\n",
+       "      <th>Product - Asset Type</th>\n",
+       "      <th>Product - Strategy</th>\n",
+       "      <th>Product - Legal Status</th>\n",
+       "      <th>Product - Is Dedie ?</th>\n",
+       "      <th>Product - Fund</th>\n",
+       "      <th>Product - Shareclass Type</th>\n",
+       "      <th>Product - Shareclass Currency</th>\n",
+       "      <th>Product - Isin</th>\n",
+       "      <th>Centralisation Date</th>\n",
+       "      <th>Quantity - AUM</th>\n",
+       "      <th>Value - AUM CCY</th>\n",
+       "      <th>Value - AUM €</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-03-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.464867e+04</td>\n",
+       "      <td>2.464867e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-11-30</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.241306e+04</td>\n",
+       "      <td>2.241306e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-12-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.205124e+04</td>\n",
+       "      <td>2.205124e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2016-03-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.162612e+04</td>\n",
+       "      <td>2.162612e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2016-11-30</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.248945e+04</td>\n",
+       "      <td>2.248945e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880292</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-02-29</td>\n",
+       "      <td>26801.000</td>\n",
+       "      <td>2.740670e+06</td>\n",
+       "      <td>2.740670e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880293</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-06-30</td>\n",
+       "      <td>3099.000</td>\n",
+       "      <td>3.122862e+05</td>\n",
+       "      <td>3.122862e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880294</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-10-31</td>\n",
+       "      <td>3099.000</td>\n",
+       "      <td>3.184222e+05</td>\n",
+       "      <td>3.184222e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880295</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2021-07-31</td>\n",
+       "      <td>2835.000</td>\n",
+       "      <td>2.976183e+05</td>\n",
+       "      <td>2.976183e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880296</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>FW &amp; FW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1792391911</td>\n",
+       "      <td>2020-07-31</td>\n",
+       "      <td>2916.394</td>\n",
+       "      <td>2.874106e+05</td>\n",
+       "      <td>2.874106e+05</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4880297 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Agreement - Code    Company - Id Company - Ultimate Parent Id  \\\n",
+       "0                    003             166                          166   \n",
+       "1                    003             166                          166   \n",
+       "2                    003             166                          166   \n",
+       "3                    003             166                          166   \n",
+       "4                    003             166                          166   \n",
+       "...                  ...             ...                          ...   \n",
+       "4880292   Private Client  Private Client               Private Client   \n",
+       "4880293   Private Client  Private Client               Private Client   \n",
+       "4880294   Private Client  Private Client               Private Client   \n",
+       "4880295   Private Client  Private Client               Private Client   \n",
+       "4880296   Private Client  Private Client               Private Client   \n",
+       "\n",
+       "        Registrar Account - ID Registrar Account - Region  \\\n",
+       "0                    200000647                     France   \n",
+       "1                    200000647                     France   \n",
+       "2                    200000647                     France   \n",
+       "3                    200000647                     France   \n",
+       "4                    200000647                     France   \n",
+       "...                        ...                        ...   \n",
+       "4880292         Private Client                Switzerland   \n",
+       "4880293         Private Client                Switzerland   \n",
+       "4880294         Private Client                Switzerland   \n",
+       "4880295         Private Client                Switzerland   \n",
+       "4880296         Private Client                Switzerland   \n",
+       "\n",
+       "        RegistrarAccount - Country Product - Asset Type Product - Strategy  \\\n",
+       "0                           France          Diversified         Patrimoine   \n",
+       "1                           France          Diversified         Patrimoine   \n",
+       "2                           France          Diversified         Patrimoine   \n",
+       "3                           France          Diversified         Patrimoine   \n",
+       "4                           France          Diversified         Patrimoine   \n",
+       "...                            ...                  ...                ...   \n",
+       "4880292                Switzerland         Fixed Income           Sécurité   \n",
+       "4880293                Switzerland         Fixed Income           Sécurité   \n",
+       "4880294                Switzerland         Fixed Income           Sécurité   \n",
+       "4880295                Switzerland         Fixed Income           Sécurité   \n",
+       "4880296                Switzerland         Fixed Income           Sécurité   \n",
+       "\n",
+       "        Product - Legal Status Product - Is Dedie ?  \\\n",
+       "0                          FCP                   NO   \n",
+       "1                          FCP                   NO   \n",
+       "2                          FCP                   NO   \n",
+       "3                          FCP                   NO   \n",
+       "4                          FCP                   NO   \n",
+       "...                        ...                  ...   \n",
+       "4880292                  SICAV                   NO   \n",
+       "4880293                  SICAV                   NO   \n",
+       "4880294                  SICAV                   NO   \n",
+       "4880295                  SICAV                   NO   \n",
+       "4880296                  SICAV                   NO   \n",
+       "\n",
+       "                       Product - Fund Product - Shareclass Type  \\\n",
+       "0                Carmignac Patrimoine                         A   \n",
+       "1                Carmignac Patrimoine                         A   \n",
+       "2                Carmignac Patrimoine                         A   \n",
+       "3                Carmignac Patrimoine                         A   \n",
+       "4                Carmignac Patrimoine                         A   \n",
+       "...                               ...                       ...   \n",
+       "4880292  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880293  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880294  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880295  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880296  Carmignac Portfolio Sécurité                 FW & FW-R   \n",
+       "\n",
+       "        Product - Shareclass Currency Product - Isin Centralisation Date  \\\n",
+       "0                                 EUR   FR0010135103          2015-03-31   \n",
+       "1                                 EUR   FR0010135103          2015-11-30   \n",
+       "2                                 EUR   FR0010135103          2015-12-31   \n",
+       "3                                 EUR   FR0010135103          2016-03-31   \n",
+       "4                                 EUR   FR0010135103          2016-11-30   \n",
+       "...                               ...            ...                 ...   \n",
+       "4880292                           EUR   LU1299306321          2020-02-29   \n",
+       "4880293                           EUR   LU1299306321          2020-06-30   \n",
+       "4880294                           EUR   LU1299306321          2020-10-31   \n",
+       "4880295                           EUR   LU1299306321          2021-07-31   \n",
+       "4880296                           EUR   LU1792391911          2020-07-31   \n",
+       "\n",
+       "         Quantity - AUM  Value - AUM CCY  Value - AUM €  \n",
+       "0                35.368     2.464867e+04   2.464867e+04  \n",
+       "1                35.368     2.241306e+04   2.241306e+04  \n",
+       "2                35.368     2.205124e+04   2.205124e+04  \n",
+       "3                35.368     2.162612e+04   2.162612e+04  \n",
+       "4                35.368     2.248945e+04   2.248945e+04  \n",
+       "...                 ...              ...            ...  \n",
+       "4880292       26801.000     2.740670e+06   2.740670e+06  \n",
+       "4880293        3099.000     3.122862e+05   3.122862e+05  \n",
+       "4880294        3099.000     3.184222e+05   3.184222e+05  \n",
+       "4880295        2835.000     2.976183e+05   2.976183e+05  \n",
+       "4880296        2916.394     2.874106e+05   2.874106e+05  \n",
+       "\n",
+       "[4880297 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd \n",
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/AUM ENSAE V2 -20251105.csv\"\n",
+    "df_aum2 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_aum2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "4644da13-5aea-4ca0-9fcf-947324766292",
+   "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>Agreement - Code</th>\n",
+       "      <th>Company - Id</th>\n",
+       "      <th>Company - Ultimate Parent Id</th>\n",
+       "      <th>Registrar Account - ID</th>\n",
+       "      <th>Registrar Account - Region</th>\n",
+       "      <th>RegistrarAccount - Country</th>\n",
+       "      <th>Product - Asset Type</th>\n",
+       "      <th>Product - Strategy</th>\n",
+       "      <th>Product - Legal Status</th>\n",
+       "      <th>Product - Is Dedie ?</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Centralisation Date</th>\n",
+       "      <th>Quantity - Subscription</th>\n",
+       "      <th>Quantity - Redemption</th>\n",
+       "      <th>Quantity - NetFlows</th>\n",
+       "      <th>Value Ccy - Subscription</th>\n",
+       "      <th>Value Ccy - Redemption</th>\n",
+       "      <th>Value Ccy - NetFlows</th>\n",
+       "      <th>Value € - Subscription</th>\n",
+       "      <th>Value € - Redemption</th>\n",
+       "      <th>Value € - NetFlows</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200127202</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2020-11-05</td>\n",
+       "      <td>1636.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1636.000</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-03-09</td>\n",
+       "      <td>144.690</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>144.690</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>99985.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2016-10-26</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-8.321</td>\n",
+       "      <td>-8.321</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>-9384.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2018-10-18</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-22.083</td>\n",
+       "      <td>-22.083</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>-25227.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2019-04-08</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-465.992</td>\n",
+       "      <td>-465.992</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>-563775.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574456</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-06-12</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-20.000</td>\n",
+       "      <td>-20.000</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>-34294.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574457</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-09-18</td>\n",
+       "      <td>328.726</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>328.726</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>564028.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574458</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-09-25</td>\n",
+       "      <td>4.443</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4.443</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7603.66</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574459</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-11-09</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-440.000</td>\n",
+       "      <td>-440.000</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>-754696.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574460</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2016-01-11</td>\n",
+       "      <td>3595.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3595.000</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>358385.55</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2574461 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Agreement - Code    Company - Id Company - Ultimate Parent Id  \\\n",
+       "0                    003             166                          166   \n",
+       "1                    003             166                          166   \n",
+       "2                    003             166                          166   \n",
+       "3                    003             166                          166   \n",
+       "4                    003             166                          166   \n",
+       "...                  ...             ...                          ...   \n",
+       "2574456   Private Client  Private Client               Private Client   \n",
+       "2574457   Private Client  Private Client               Private Client   \n",
+       "2574458   Private Client  Private Client               Private Client   \n",
+       "2574459   Private Client  Private Client               Private Client   \n",
+       "2574460   Private Client  Private Client               Private Client   \n",
+       "\n",
+       "        Registrar Account - ID Registrar Account - Region  \\\n",
+       "0                    200127202                     France   \n",
+       "1                       406533                     France   \n",
+       "2                       406533                     France   \n",
+       "3                       406533                     France   \n",
+       "4                       406533                     France   \n",
+       "...                        ...                        ...   \n",
+       "2574456         Private Client                 Luxembourg   \n",
+       "2574457         Private Client                 Luxembourg   \n",
+       "2574458         Private Client                 Luxembourg   \n",
+       "2574459         Private Client                 Luxembourg   \n",
+       "2574460         Private Client                 Luxembourg   \n",
+       "\n",
+       "        RegistrarAccount - Country Product - Asset Type Product - Strategy  \\\n",
+       "0                           France               Equity     Investissement   \n",
+       "1                           France          Diversified         Patrimoine   \n",
+       "2                           France               Equity     Investissement   \n",
+       "3                           France               Equity     Investissement   \n",
+       "4                           France               Equity     Investissement   \n",
+       "...                            ...                  ...                ...   \n",
+       "2574456                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574457                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574458                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574459                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574460                 Luxembourg         Fixed Income           Sécurité   \n",
+       "\n",
+       "        Product - Legal Status Product - Is Dedie ?  ... Centralisation Date  \\\n",
+       "0                        SICAV                   NO  ...          2020-11-05   \n",
+       "1                          FCP                   NO  ...          2015-03-09   \n",
+       "2                          FCP                   NO  ...          2016-10-26   \n",
+       "3                          FCP                   NO  ...          2018-10-18   \n",
+       "4                          FCP                   NO  ...          2019-04-08   \n",
+       "...                        ...                  ...  ...                 ...   \n",
+       "2574456                    FCP                   NO  ...          2015-06-12   \n",
+       "2574457                    FCP                   NO  ...          2015-09-18   \n",
+       "2574458                    FCP                   NO  ...          2015-09-25   \n",
+       "2574459                    FCP                   NO  ...          2015-11-09   \n",
+       "2574460                  SICAV                   NO  ...          2016-01-11   \n",
+       "\n",
+       "        Quantity - Subscription Quantity - Redemption Quantity - NetFlows  \\\n",
+       "0                      1636.000                 0.000            1636.000   \n",
+       "1                       144.690                 0.000             144.690   \n",
+       "2                         0.000                -8.321              -8.321   \n",
+       "3                         0.000               -22.083             -22.083   \n",
+       "4                         0.000              -465.992            -465.992   \n",
+       "...                         ...                   ...                 ...   \n",
+       "2574456                   0.000               -20.000             -20.000   \n",
+       "2574457                 328.726                 0.000             328.726   \n",
+       "2574458                   4.443                 0.000               4.443   \n",
+       "2574459                   0.000              -440.000            -440.000   \n",
+       "2574460                3595.000                 0.000            3595.000   \n",
+       "\n",
+       "        Value Ccy - Subscription  Value Ccy - Redemption  \\\n",
+       "0                      280983.00                    0.00   \n",
+       "1                       99985.13                    0.00   \n",
+       "2                           0.00                -9384.76   \n",
+       "3                           0.00               -25227.40   \n",
+       "4                           0.00              -563775.76   \n",
+       "...                          ...                     ...   \n",
+       "2574456                     0.00               -34294.40   \n",
+       "2574457                564028.07                    0.00   \n",
+       "2574458                  7603.66                    0.00   \n",
+       "2574459                     0.00              -754696.80   \n",
+       "2574460                358385.55                    0.00   \n",
+       "\n",
+       "         Value Ccy - NetFlows  Value € - Subscription  Value € - Redemption  \\\n",
+       "0                   280983.00               280983.00                  0.00   \n",
+       "1                    99985.13                99985.13                  0.00   \n",
+       "2                    -9384.76                    0.00              -9384.76   \n",
+       "3                   -25227.40                    0.00             -25227.40   \n",
+       "4                  -563775.76                    0.00            -563775.76   \n",
+       "...                       ...                     ...                   ...   \n",
+       "2574456             -34294.40                    0.00             -34294.40   \n",
+       "2574457             564028.07               564028.07                  0.00   \n",
+       "2574458               7603.66                 7603.66                  0.00   \n",
+       "2574459            -754696.80                    0.00            -754696.80   \n",
+       "2574460             358385.55               358385.55                  0.00   \n",
+       "\n",
+       "         Value € - NetFlows  \n",
+       "0                 280983.00  \n",
+       "1                  99985.13  \n",
+       "2                  -9384.76  \n",
+       "3                 -25227.40  \n",
+       "4                -563775.76  \n",
+       "...                     ...  \n",
+       "2574456           -34294.40  \n",
+       "2574457           564028.07  \n",
+       "2574458             7603.66  \n",
+       "2574459          -754696.80  \n",
+       "2574460           358385.55  \n",
+       "\n",
+       "[2574461 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/Flows ENSAE V2 -20251105.csv\"\n",
+    "df_flows2 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_flows2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59d31eaf-c06c-4ebe-9f8c-cb9158a50976",
+   "metadata": {},
+   "source": [
+    "## DATA ANALYSIS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5773b911-6b84-448d-962f-8228eeac0250",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4880297, 18)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_aum2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6f571810-c373-4d30-8ca5-c3a074b95b08",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Agreement - Code', 'Company - Id', 'Company - Ultimate Parent Id',\n",
+       "       'Registrar Account - ID', 'Registrar Account - Region',\n",
+       "       'RegistrarAccount - Country', 'Product - Asset Type',\n",
+       "       'Product - Strategy', 'Product - Legal Status', 'Product - Is Dedie ?',\n",
+       "       'Product - Fund', 'Product - Shareclass Type',\n",
+       "       'Product - Shareclass Currency', 'Product - Isin',\n",
+       "       'Centralisation Date', 'Quantity - AUM', 'Value - AUM CCY',\n",
+       "       'Value - AUM €'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_aum2.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "af25fd07-a613-4adc-b88b-93a8d300379c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2574461, 24)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_flows2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c6d0fe83-2957-430b-89cf-cd30833b7cab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Agreement - Code', 'Company - Id', 'Company - Ultimate Parent Id',\n",
+       "       'Registrar Account - ID', 'Registrar Account - Region',\n",
+       "       'RegistrarAccount - Country', 'Product - Asset Type',\n",
+       "       'Product - Strategy', 'Product - Legal Status', 'Product - Is Dedie ?',\n",
+       "       'Product - Fund', 'Product - Shareclass Type',\n",
+       "       'Product - Shareclass Currency', 'Product - Isin',\n",
+       "       'Centralisation Date', 'Quantity - Subscription',\n",
+       "       'Quantity - Redemption', 'Quantity - NetFlows',\n",
+       "       'Value Ccy - Subscription', 'Value Ccy - Redemption',\n",
+       "       'Value Ccy - NetFlows', 'Value € - Subscription',\n",
+       "       'Value € - Redemption', 'Value € - NetFlows'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_flows2.columns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ce2ad22-08e6-4e63-96b2-c2301172516e",
+   "metadata": {},
+   "source": [
+    "# ETUDE ET ANALYSE DES ANOMALIES"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c883dfc2-b9b9-4d3e-80d3-0140cd222492",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_aum2['Centralisation Date'] = pd.to_datetime(df_aum2['Centralisation Date'])\n",
+    "df_flows2['Centralisation Date'] = pd.to_datetime(df_flows2['Centralisation Date'])\n",
+    "\n",
+    "\n",
+    "key_cols = ['Registrar Account - ID', 'Product - Isin']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "64ca9883-372b-4a5e-8fc1-10e5d835c411",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Doublons AUM: 250232\n",
+      "Doublons Flows: 4849\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Vérifier doublons exacts\n",
+    "doublons_aum = df_aum2[df_aum2.duplicated(subset=key_cols + ['Centralisation Date'], keep=False)]\n",
+    "doublons_flows = df_flows2[df_flows2.duplicated(subset=key_cols + ['Centralisation Date'], keep=False)]\n",
+    "\n",
+    "print(\"Doublons AUM:\", doublons_aum.shape[0])\n",
+    "print(\"Doublons Flows:\", doublons_flows.shape[0])\n",
+    "\n",
+    "#same date, code isin du produit, et account ==> revoir les autres caracteristiques "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f47b276d-cce6-433c-87c5-860810d71d34",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Cols:  ['Company - Id', 'Company - Ultimate Parent Id', 'Registrar Account - ID', 'Registrar Account - Region', 'Product - Isin']\n",
+      "Doublons AUM: 26452\n",
+      "Doublons Flows: 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "cols= ['Company - Id', 'Company - Ultimate Parent Id',\n",
+    "       'Registrar Account - ID', 'Registrar Account - Region','Product - Isin']\n",
+    "\n",
+    "doublons_aum2 = df_aum2[df_aum2.duplicated(subset=cols + ['Centralisation Date'], keep=False)]\n",
+    "doublons_flows2 = df_flows2[df_flows2.duplicated(subset=cols + ['Centralisation Date'], keep=False)]\n",
+    "\n",
+    "print(\" Cols: \", cols)\n",
+    "print(\"Doublons AUM:\", doublons_aum2.shape[0])\n",
+    "print(\"Doublons Flows:\", doublons_flows2.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d2f355e6-30c5-420e-a3db-9095dd5e0147",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Comptes avec same flux et same product ISIN mais IDs différents ---> candidats pseudo-client\n",
+    "# #plusieurs comptes diff réalisent EXACTEMENT le même flux sur le même produit le même jour.\n",
+    "# #date?\n",
+    "\n",
+    "# pseudo_client_candidates = df_flows2.groupby(['Product - Isin','Centralisation Date', 'Quantity - NetFlows', 'Value € - NetFlows'])['Registrar Account - ID'].nunique()\n",
+    "# pseudo_client_candidates = pseudo_client_candidates[pseudo_client_candidates > 1]\n",
+    "# print(\"Comptes potentiels à fusionner:\")\n",
+    "# print(pseudo_client_candidates)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8df98c34-b1f7-4fb9-bbc7-c9bbe762022a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = df_flows2.copy()\n",
+    "df[\"Date\"] = pd.to_datetime(df[\"Centralisation Date\"])\n",
+    "\n",
+    "# Groupby par ISIN et Date\n",
+    "grouped = df.groupby([\"Product - Isin\", \"Date\"])\n",
+    "\n",
+    "transfers = []\n",
+    "\n",
+    "for (isin, date), group in grouped:\n",
+    "    # Sépare flux positifs et négatifs\n",
+    "    entrants = group[group[\"Value € - NetFlows\"] > 0][[\"Registrar Account - ID\", \"Value € - NetFlows\"]]\n",
+    "    sortants = group[group[\"Value € - NetFlows\"] < 0][[\"Registrar Account - ID\", \"Value € - NetFlows\"]]\n",
+    "\n",
+    "    # On cherche des paires +M / -M\n",
+    "    for _, row_sortie in sortants.iterrows():\n",
+    "        montant_sortie = row_sortie[\"Value € - NetFlows\"]\n",
+    "        compte_sortant = row_sortie[\"Registrar Account - ID\"]\n",
+    "\n",
+    "        # Chercher un +M qui matche exactement le -M\n",
+    "        match = entrants[entrants[\"Value € - NetFlows\"] == -montant_sortie]\n",
+    "\n",
+    "        if len(match) > 0:\n",
+    "            for _, row_entree in match.iterrows():\n",
+    "                transfers.append({\n",
+    "                    \"ISIN\": isin,\n",
+    "                    \"Date\": date,\n",
+    "                    \"Compte sortant\": compte_sortant,\n",
+    "                    \"Montant sortie\": montant_sortie,\n",
+    "                    \"Compte entrant\": row_entree[\"Registrar Account - ID\"],\n",
+    "                    \"Montant entrée\": row_entree[\"Value € - NetFlows\"]\n",
+    "                })\n",
+    "\n",
+    "\n",
+    "transf_compte = pd.DataFrame(transfers)\n",
+    "transf_compte"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c898b0c5-0a8e-4640-bc52-9490ee80e53d",
+   "metadata": {},
+   "source": [
+    "# MERGE AND ANALYSIS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "ce33dbf8-1c59-416a-adc4-6eb7c1ea9d8e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Merged dataset:\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "df_aum2 = df_aum2.rename(columns={\n",
+    "    \"Registrar Account - ID\": \"Account_ID\",\n",
+    "    \"Product - Isin\": \"ISIN\",\n",
+    "    \"Centralisation Date\": \"Date\",\n",
+    "    \"Value - AUM €\": \"AUM_EUR\"\n",
+    "})\n",
+    "\n",
+    "df_flows2 = df_flows2.rename(columns={\n",
+    "    \"Registrar Account - ID\": \"Account_ID\",\n",
+    "    \"Product - Isin\": \"ISIN\",\n",
+    "    \"Centralisation Date\": \"Date\",\n",
+    "    \"Value € - NetFlows\": \"Flow_EUR\"\n",
+    "})\n",
+    "\n",
+    "\n",
+    "df_aum2[\"Date\"] = pd.to_datetime(df_aum2[\"Date\"])\n",
+    "df_flows2[\"Date\"] = pd.to_datetime(df_flows2[\"Date\"])\n",
+    "\n",
+    "df_aum2[\"Account_ID\"] = df_aum2[\"Account_ID\"].astype(str)\n",
+    "df_flows2[\"Account_ID\"] = df_flows2[\"Account_ID\"].astype(str)\n",
+    "\n",
+    "df_aum2[\"ISIN\"] = df_aum2[\"ISIN\"].str.upper()\n",
+    "df_flows2[\"ISIN\"] = df_flows2[\"ISIN\"].str.upper()\n",
+    "\n",
+    "\n",
+    "df_merged = pd.merge(\n",
+    "    df_aum2[[\"Account_ID\", \"ISIN\", \"Date\", \"AUM_EUR\"]],\n",
+    "    df_flows2[[\"Account_ID\", \"ISIN\", \"Date\", \"Flow_EUR\"]],\n",
+    "    on=[\"Account_ID\", \"ISIN\", \"Date\"],\n",
+    "    how=\"outer\"\n",
+    ").sort_values([\"Account_ID\", \"ISIN\", \"Date\"])\n",
+    "\n",
+    "print(\"Merged dataset:\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7e5d642e-5c16-4c78-8d83-075094902670",
+   "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>Account_ID</th>\n",
+       "      <th>ISIN</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>AUM_EUR</th>\n",
+       "      <th>Flow_EUR</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>100000014</td>\n",
+       "      <td>LU0553415323</td>\n",
+       "      <td>2015-01-31</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>100000014</td>\n",
+       "      <td>LU0553415323</td>\n",
+       "      <td>2015-02-28</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>100000014</td>\n",
+       "      <td>LU0553415323</td>\n",
+       "      <td>2015-03-31</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>100000014</td>\n",
+       "      <td>LU0553415323</td>\n",
+       "      <td>2015-04-30</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>100000014</td>\n",
+       "      <td>LU0553415323</td>\n",
+       "      <td>2015-05-31</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7369446</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>LU2809794220</td>\n",
+       "      <td>2025-10-30</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-1623.71</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7369447</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>LU2809794220</td>\n",
+       "      <td>2025-10-31</td>\n",
+       "      <td>4.438147e+06</td>\n",
+       "      <td>4946.23</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7369448</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>LU2809794576</td>\n",
+       "      <td>2025-09-23</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>71660.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7369449</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>LU2809794576</td>\n",
+       "      <td>2025-09-30</td>\n",
+       "      <td>7.094499e+04</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7369450</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>LU2809794576</td>\n",
+       "      <td>2025-10-31</td>\n",
+       "      <td>7.871629e+04</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7369451 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Account_ID          ISIN       Date       AUM_EUR  Flow_EUR\n",
+       "0             100000014  LU0553415323 2015-01-31  0.000000e+00       NaN\n",
+       "1             100000014  LU0553415323 2015-02-28  0.000000e+00       NaN\n",
+       "2             100000014  LU0553415323 2015-03-31  0.000000e+00       NaN\n",
+       "3             100000014  LU0553415323 2015-04-30  0.000000e+00       NaN\n",
+       "4             100000014  LU0553415323 2015-05-31  0.000000e+00       NaN\n",
+       "...                 ...           ...        ...           ...       ...\n",
+       "7369446  Private Client  LU2809794220 2025-10-30           NaN  -1623.71\n",
+       "7369447  Private Client  LU2809794220 2025-10-31  4.438147e+06   4946.23\n",
+       "7369448  Private Client  LU2809794576 2025-09-23           NaN  71660.14\n",
+       "7369449  Private Client  LU2809794576 2025-09-30  7.094499e+04       NaN\n",
+       "7369450  Private Client  LU2809794576 2025-10-31  7.871629e+04       NaN\n",
+       "\n",
+       "[7369451 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e484a3df-260e-4532-850b-3917592fcfdf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date   2025-11-28\n",
+       "dtype: datetime64[ns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_merged[['Date']].max() #2015-01-02 jusuqua 2025-11-28"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "ea14866a-1ce6-4b19-9225-d725304af8ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 2. HISTOGRAMME DES AUM (SANS ISIN)\n",
+    "\n",
+    "# We keep the mean AUM per Account \n",
+    "aum_by_account = (\n",
+    "    df_merged.groupby(\"Account_ID\")[\"AUM_EUR\"]\n",
+    "    .mean()\n",
+    "    .dropna()\n",
+    ")\n",
+    "\n",
+    "# plt.figure(figsize=(10,6))\n",
+    "# plt.hist(aum_by_account, bins=50)\n",
+    "# plt.xlabel(\"Mean AUM value (€)\")\n",
+    "# plt.ylabel(\"Number of client accounts\")\n",
+    "# plt.title(\"Distribution of client average AUM (one value per Account_ID)\")\n",
+    "# plt.grid(True)\n",
+    "# plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(10,6))\n",
+    "plt.hist(aum_by_account, bins=100)\n",
+    "\n",
+    "# ZOOM sur les petits AUM (0 à 0.5M €)\n",
+    "plt.xlim(0, 0.5e7)\n",
+    "\n",
+    "plt.xlabel(\"Mean AUM value (€)\")\n",
+    "plt.ylabel(\"Number of client accounts\")\n",
+    "plt.title(\"Distribution of client average AUM \")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "8d0dec63-9b9a-47ea-90bd-ffe059bb232a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 2. HISTOGRAMME DES AUM (SANS ISIN) POUR 2022+\n",
+    "df_filtered = df_merged[df_merged[\"Date\"].dt.year >= 2022]\n",
+    "\n",
+    "aum_by_account = (\n",
+    "    df_filtered\n",
+    "    .groupby(\"Account_ID\")[\"AUM_EUR\"]\n",
+    "    .mean()\n",
+    "    .dropna()\n",
+    ")\n",
+    "\n",
+    "plt.figure(figsize=(10,6))\n",
+    "plt.hist(aum_by_account, bins=100)\n",
+    "\n",
+    "# ZOOM sur les petits AUM (0 à 5M €)\n",
+    "plt.xlim(0, 0.5e7)\n",
+    "\n",
+    "plt.xlabel(\"Mean AUM value (€)\")\n",
+    "plt.ylabel(\"Number of client accounts\")\n",
+    "plt.title(\"Distribution of client average AUM per account (2022–2025)\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c79ae705-833e-420f-ab3e-51ccb2ae52c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # 1) Créer une colonne Année-Mois\n",
+    "\n",
+    "# df_filtered = df_merged[df_merged[\"Date\"].dt.year >= 2022]\n",
+    "# df_filtered[\"YearMonth\"] = df_merged[\"Date\"].dt.to_period(\"M\")\n",
+    "\n",
+    "# # 2) AUM moyen par compte ET par mois\n",
+    "# aum_monthly = (\n",
+    "#     df_merged.groupby([\"Account_ID\", \"YearMonth\"])[\"AUM_EUR\"]\n",
+    "#     .mean()\n",
+    "#     .reset_index()\n",
+    "# )\n",
+    "\n",
+    "# # 3) Pour chaque compte : moyenne des AUM mensuels sur toute la période\n",
+    "# aum_avg_over_time = (\n",
+    "#     aum_monthly.groupby(\"Account_ID\")[\"AUM_EUR\"]\n",
+    "#     .mean()\n",
+    "#     .dropna()\n",
+    "# )\n",
+    "\n",
+    "# # 4) Histogramme des AUM mensuels moyens par compte (sur toute l’historique)\n",
+    "# plt.figure(figsize=(10,6))\n",
+    "# plt.hist(aum_avg_over_time, bins=100)\n",
+    "\n",
+    "# # Option : zoom sur les petits AUM (ex. 0 à 5M €)\n",
+    "# plt.xlim(0, 0.5e7)\n",
+    "\n",
+    "# plt.xlabel(\"Average monthly AUM per account (€)\")\n",
+    "# plt.ylabel(\"Number of client accounts\")\n",
+    "# plt.title(\"Distribution of average monthly AUM per account (full history)\")\n",
+    "# plt.grid(True)\n",
+    "# plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f13c213e-7f72-494a-bcf0-b4cd9feee55d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Monthly flow summary:\n",
+      "           n_positive_flows  n_negative_flows\n",
+      "YearMonth                                    \n",
+      "2015-01               10688             11779\n",
+      "2015-02               12905             10822\n",
+      "2015-03               15497             13207\n",
+      "2015-04               13838             11641\n",
+      "2015-05               11143              9065\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "###############################################################################\n",
+    "# 4. ANALYSE MENSUELLE DES FLOWS (ENTRANTS / SORTANTS)\n",
+    "\n",
+    "df_merged[\"YearMonth\"] = df_merged[\"Date\"].dt.to_period(\"M\")\n",
+    "\n",
+    "flows_monthly = df_merged.groupby(\"YearMonth\").agg(\n",
+    "    n_positive_flows=(\"Flow_EUR\", lambda x: (x > 0).sum()),\n",
+    "    n_negative_flows=(\"Flow_EUR\", lambda x: (x < 0).sum()),\n",
+    ")\n",
+    "\n",
+    "print(\"Monthly flow summary:\")\n",
+    "print(flows_monthly.head())\n",
+    "\n",
+    "# ---- Plot bar chart ----\n",
+    "flows_monthly.index = flows_monthly.index.astype(str)\n",
+    "\n",
+    "plt.figure(figsize=(14,6))\n",
+    "plt.bar(flows_monthly.index, flows_monthly[\"n_positive_flows\"], label=\"Positive flows (inflows)\", alpha=0.7)\n",
+    "plt.bar(flows_monthly.index, flows_monthly[\"n_negative_flows\"], label=\"Negative flows (outflows)\", alpha=0.7)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.xlabel(\"Year-Month\")\n",
+    "plt.ylabel(\"Number of accounts with flows\")\n",
+    "plt.title(\"Monthly number of accounts with inflows vs outflows\")\n",
+    "plt.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "4af0e205-a304-4b10-be1d-de69904aa0da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_merged[\"YearMonth\"] = df_merged[\"Date\"].dt.to_period(\"M\")\n",
+    "\n",
+    "monthly_flow_amounts = df_merged.groupby(\"YearMonth\").agg(\n",
+    "    avg_positive_flow=(\"Flow_EUR\", lambda x: x[x > 0].mean()),\n",
+    "    avg_negative_flow=(\"Flow_EUR\", lambda x: x[x < 0].mean())\n",
+    ")\n",
+    "\n",
+    "monthly_flow_amounts.index = monthly_flow_amounts.index.astype(str)\n",
+    "\n",
+    "plt.figure(figsize=(14,6))\n",
+    "plt.plot(monthly_flow_amounts.index, monthly_flow_amounts[\"avg_positive_flow\"], label=\"Average inflow (positive)\", marker=\"o\")\n",
+    "plt.plot(monthly_flow_amounts.index, monthly_flow_amounts[\"avg_negative_flow\"], label=\"Average outflow (negative)\", marker=\"o\")\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.xlabel(\"Year-Month\")\n",
+    "plt.ylabel(\"Average flow (€)\")\n",
+    "plt.title(\"Monthly average inflows and outflows\")\n",
+    "plt.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "2d548152-196f-456a-b21e-4d05e39d03c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = df_merged.copy()\n",
+    "df[\"YearMonth\"] = df[\"Date\"].dt.to_period(\"M\")\n",
+    "\n",
+    "# 1) Flow mensuel total par client\n",
+    "monthly_client_flow = (\n",
+    "    df.groupby([\"Account_ID\", \"YearMonth\"])[\"Flow_EUR\"]\n",
+    "    .sum()\n",
+    "    .reset_index()\n",
+    ")\n",
+    "\n",
+    "# 2) Calcul des seuils de quantiles (tu peux ajuster)\n",
+    "q1 = monthly_client_flow[\"Flow_EUR\"].quantile(0.33)\n",
+    "q2 = monthly_client_flow[\"Flow_EUR\"].quantile(0.66)\n",
+    "\n",
+    "# 3) Catégorisation des clients\n",
+    "def categorize(flow):\n",
+    "    if flow <= q1:\n",
+    "        return \"Petits flows\"\n",
+    "    elif flow <= q2:\n",
+    "        return \"Flows moyens\"\n",
+    "    else:\n",
+    "        return \"Grands flows\"\n",
+    "\n",
+    "monthly_client_flow[\"Flow_category\"] = monthly_client_flow[\"Flow_EUR\"].apply(categorize)\n",
+    "\n",
+    "# 4) Nombre de clients dans chaque catégorie par mois\n",
+    "category_counts = (\n",
+    "    monthly_client_flow.groupby([\"YearMonth\", \"Flow_category\"])\n",
+    "    .size()\n",
+    "    .unstack(fill_value=0)\n",
+    ")\n",
+    "\n",
+    "category_counts.index = category_counts.index.astype(str)\n",
+    "\n",
+    "# 5) Plot\n",
+    "category_counts.plot(kind=\"bar\", stacked=True, figsize=(14,6))\n",
+    "plt.title(\"Répartition des clients par niveau de flux mensuel\")\n",
+    "plt.xlabel(\"Mois\")\n",
+    "plt.ylabel(\"Nombre de clients\")\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "2c5a83e0-1faf-4745-88b3-c0fb363317fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Répartition des comptes par catégorie :\n",
+      "Grands flows : YearMonth\n",
+      "2015-01    432\n",
+      "2015-02    499\n",
+      "2015-03    536\n",
+      "2015-04    530\n",
+      "2015-05    472\n",
+      "          ... \n",
+      "2025-07    412\n",
+      "2025-08    388\n",
+      "2025-09    407\n",
+      "2025-10    418\n",
+      "2025-11    231\n",
+      "Name: Grands flows, Length: 131, dtype: int64 comptes\n",
+      "Petits flows : YearMonth\n",
+      "2015-01    7429\n",
+      "2015-02    7380\n",
+      "2015-03    7390\n",
+      "2015-04    7416\n",
+      "2015-05    7493\n",
+      "           ... \n",
+      "2025-07    3474\n",
+      "2025-08    3507\n",
+      "2025-09    3509\n",
+      "2025-10    3529\n",
+      "2025-11     174\n",
+      "Name: Petits flows, Length: 131, dtype: int64 comptes\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Répartition des comptes par catégorie :\")\n",
+    "for cat, count in category_counts.items():\n",
+    "    print(f\"{cat} : {count} comptes\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "943b359e-b1c0-435e-943b-94167f8c566f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Moyenne du nombre de comptes par catégorie (sur toute la période) :\n",
+      "Grands flows : 334 comptes en moyenne par mois\n",
+      "Petits flows : 6736 comptes en moyenne par mois\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Nombre de comptes dans chaque catégorie par mois\n",
+    "category_counts_by_month = (\n",
+    "    monthly_client_flow.groupby([\"YearMonth\", \"Flow_category\"])\n",
+    "    .size()\n",
+    "    .unstack(fill_value=0)\n",
+    ")\n",
+    "\n",
+    "# Moyenne sur tous les mois\n",
+    "category_counts_mean = category_counts_by_month.mean()\n",
+    "\n",
+    "print(\"Moyenne du nombre de comptes par catégorie (sur toute la période) :\")\n",
+    "for cat, mean_val in category_counts_mean.items():\n",
+    "    print(f\"{cat} : {mean_val:.0f} comptes en moyenne par mois\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6bb455c-91f9-4169-a179-273e98ef3ebd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/data_1.ipynb b/data_1.ipynb
new file mode 100644
index 0000000..ccf2fae
--- /dev/null
+++ b/data_1.ipynb
@@ -0,0 +1,3658 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e637deae-9168-4fb2-b95f-4e42d8d72d9e",
+   "metadata": {},
+   "source": [
+    "# DATA COLLECTION "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9f99615b-5a9d-434a-baa0-dca55edf7699",
+   "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>003</th>\n",
+       "      <th>166</th>\n",
+       "      <th>166.1</th>\n",
+       "      <th>200000647</th>\n",
+       "      <th>France</th>\n",
+       "      <th>France.1</th>\n",
+       "      <th>Diversified</th>\n",
+       "      <th>Patrimoine</th>\n",
+       "      <th>FCP</th>\n",
+       "      <th>1989-11-07</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Carmignac Patrimoine</th>\n",
+       "      <th>A</th>\n",
+       "      <th>EUR</th>\n",
+       "      <th>FR0010135103</th>\n",
+       "      <th>1989-11-07.1</th>\n",
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>003</td>\n",
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+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
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+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>1989-11-07</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
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+       "      <td>1989-11-07</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2016-09-30</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>22501.1216</td>\n",
+       "      <td>22501.1216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>1989-11-07</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>1989-11-07</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2018-01-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>23602.1274</td>\n",
+       "      <td>23602.1274</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>1989-11-07</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>1989-11-07</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-11-30</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>1989-01-26</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Investissement</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010148981</td>\n",
+       "      <td>1989-01-26</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2015-02-28</td>\n",
+       "      <td>193.970</td>\n",
+       "      <td>241339.4137</td>\n",
+       "      <td>241339.4137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
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+       "      <td>Investissement</td>\n",
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+       "      <td>1989-01-26</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Investissement</td>\n",
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+       "      <td>FR0010148981</td>\n",
+       "      <td>1989-01-26</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2017-02-28</td>\n",
+       "      <td>193.970</td>\n",
+       "      <td>230036.7818</td>\n",
+       "      <td>230036.7818</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4842120</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>2013-11-25</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2015-11-19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2021-03-31</td>\n",
+       "      <td>2835.000</td>\n",
+       "      <td>296115.7500</td>\n",
+       "      <td>296115.7500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4842121</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>2013-11-25</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2015-11-19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2021-06-30</td>\n",
+       "      <td>2835.000</td>\n",
+       "      <td>296711.1000</td>\n",
+       "      <td>296711.1000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4842122</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>2013-11-25</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2015-11-19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2021-08-31</td>\n",
+       "      <td>2835.000</td>\n",
+       "      <td>297079.6500</td>\n",
+       "      <td>297079.6500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4842123</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>2013-11-25</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>FW &amp; FW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1792391911</td>\n",
+       "      <td>2018-03-16</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2021-01-31</td>\n",
+       "      <td>3524.100</td>\n",
+       "      <td>356427.4740</td>\n",
+       "      <td>356427.4740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4842124</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>2013-11-25</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>FW &amp; FW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1792391911</td>\n",
+       "      <td>2018-03-16</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2021-04-30</td>\n",
+       "      <td>4415.840</td>\n",
+       "      <td>448693.5024</td>\n",
+       "      <td>448693.5024</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4842125 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    003             166           166.1       200000647  \\\n",
+       "0                   003             166             166       200000647   \n",
+       "1                   003             166             166       200000647   \n",
+       "2                   003             166             166       200000647   \n",
+       "3                   003             166             166       200000647   \n",
+       "4                   003             166             166       200000647   \n",
+       "...                 ...             ...             ...             ...   \n",
+       "4842120  Private Client  Private Client  Private Client  Private Client   \n",
+       "4842121  Private Client  Private Client  Private Client  Private Client   \n",
+       "4842122  Private Client  Private Client  Private Client  Private Client   \n",
+       "4842123  Private Client  Private Client  Private Client  Private Client   \n",
+       "4842124  Private Client  Private Client  Private Client  Private Client   \n",
+       "\n",
+       "              France     France.1   Diversified      Patrimoine    FCP  \\\n",
+       "0             France       France   Diversified      Patrimoine    FCP   \n",
+       "1             France       France   Diversified      Patrimoine    FCP   \n",
+       "2             France       France   Diversified      Patrimoine    FCP   \n",
+       "3             France       France        Equity  Investissement    FCP   \n",
+       "4             France       France        Equity  Investissement    FCP   \n",
+       "...              ...          ...           ...             ...    ...   \n",
+       "4842120  Switzerland  Switzerland  Fixed Income        Sécurité  SICAV   \n",
+       "4842121  Switzerland  Switzerland  Fixed Income        Sécurité  SICAV   \n",
+       "4842122  Switzerland  Switzerland  Fixed Income        Sécurité  SICAV   \n",
+       "4842123  Switzerland  Switzerland  Fixed Income        Sécurité  SICAV   \n",
+       "4842124  Switzerland  Switzerland  Fixed Income        Sécurité  SICAV   \n",
+       "\n",
+       "         1989-11-07  ...          Carmignac Patrimoine          A  EUR  \\\n",
+       "0        1989-11-07  ...          Carmignac Patrimoine          A  EUR   \n",
+       "1        1989-11-07  ...          Carmignac Patrimoine          A  EUR   \n",
+       "2        1989-11-07  ...          Carmignac Patrimoine          A  EUR   \n",
+       "3        1989-01-26  ...      Carmignac Investissement          A  EUR   \n",
+       "4        1989-01-26  ...      Carmignac Investissement          A  EUR   \n",
+       "...             ...  ...                           ...        ...  ...   \n",
+       "4842120  2013-11-25  ...  Carmignac Portfolio Sécurité  AW & AW-R  EUR   \n",
+       "4842121  2013-11-25  ...  Carmignac Portfolio Sécurité  AW & AW-R  EUR   \n",
+       "4842122  2013-11-25  ...  Carmignac Portfolio Sécurité  AW & AW-R  EUR   \n",
+       "4842123  2013-11-25  ...  Carmignac Portfolio Sécurité  FW & FW-R  EUR   \n",
+       "4842124  2013-11-25  ...  Carmignac Portfolio Sécurité  FW & FW-R  EUR   \n",
+       "\n",
+       "         FR0010135103 1989-11-07.1 NULL.1  2015-02-28 35.368000000  \\\n",
+       "0        FR0010135103   1989-11-07    NaN  2016-09-30       35.368   \n",
+       "1        FR0010135103   1989-11-07    NaN  2018-01-31       35.368   \n",
+       "2        FR0010135103   1989-11-07    NaN  2019-11-30        0.000   \n",
+       "3        FR0010148981   1989-01-26    NaN  2015-02-28      193.970   \n",
+       "4        FR0010148981   1989-01-26    NaN  2017-02-28      193.970   \n",
+       "...               ...          ...    ...         ...          ...   \n",
+       "4842120  LU1299306321   2015-11-19    NaN  2021-03-31     2835.000   \n",
+       "4842121  LU1299306321   2015-11-19    NaN  2021-06-30     2835.000   \n",
+       "4842122  LU1299306321   2015-11-19    NaN  2021-08-31     2835.000   \n",
+       "4842123  LU1792391911   2018-03-16    NaN  2021-01-31     3524.100   \n",
+       "4842124  LU1792391911   2018-03-16    NaN  2021-04-30     4415.840   \n",
+       "\n",
+       "          23920.7931  23920.7931.1  \n",
+       "0         22501.1216    22501.1216  \n",
+       "1         23602.1274    23602.1274  \n",
+       "2             0.0000        0.0000  \n",
+       "3        241339.4137   241339.4137  \n",
+       "4        230036.7818   230036.7818  \n",
+       "...              ...           ...  \n",
+       "4842120  296115.7500   296115.7500  \n",
+       "4842121  296711.1000   296711.1000  \n",
+       "4842122  297079.6500   297079.6500  \n",
+       "4842123  356427.4740   356427.4740  \n",
+       "4842124  448693.5024   448693.5024  \n",
+       "\n",
+       "[4842125 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/AUM ENSAE V1 -20251027.csv\"\n",
+    "df_aum1 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_aum1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "036d6acb-cc41-4dd6-9456-3aaf6fedbda4",
+   "metadata": {},
+   "outputs": [
+    {
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+       "      <th>3</th>\n",
+       "      <td>006</td>\n",
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+       "      <td>968</td>\n",
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+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>008</td>\n",
+       "      <td>927</td>\n",
+       "      <td>927</td>\n",
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+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Multi Expertise</td>\n",
+       "      <td>FCP</td>\n",
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+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
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+       "    <tr>\n",
+       "      <th>2566308</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
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+       "      <td>68640.40</td>\n",
+       "      <td>-37752.22</td>\n",
+       "      <td>30888.18</td>\n",
+       "      <td>68640.40</td>\n",
+       "      <td>-37752.22</td>\n",
+       "      <td>30888.18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2566309</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>1989-01-26</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-12-17</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>26.00000</td>\n",
+       "      <td>44621.20</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>44621.20</td>\n",
+       "      <td>44621.20</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>44621.20</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2566310 rows × 27 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    003             166           166.1          406533  \\\n",
+       "0                   003             166             166          406533   \n",
+       "1                   003             166             166          406533   \n",
+       "2                   003             166             166          406533   \n",
+       "3                   006             968             968          412182   \n",
+       "4                   008             927             927          411986   \n",
+       "...                 ...             ...             ...             ...   \n",
+       "2566305  Private Client  Private Client  Private Client  Private Client   \n",
+       "2566306  Private Client  Private Client  Private Client  Private Client   \n",
+       "2566307  Private Client  Private Client  Private Client  Private Client   \n",
+       "2566308  Private Client  Private Client  Private Client  Private Client   \n",
+       "2566309  Private Client  Private Client  Private Client  Private Client   \n",
+       "\n",
+       "             France    France.1        Equity   Investissement    FCP  \\\n",
+       "0            France      France        Equity   Investissement    FCP   \n",
+       "1            France      France        Equity   Investissement    FCP   \n",
+       "2            France      France        Equity   Investissement    FCP   \n",
+       "3            France      France        Equity   Investissement    FCP   \n",
+       "4            France      France   Diversified  Multi Expertise    FCP   \n",
+       "...             ...         ...           ...              ...    ...   \n",
+       "2566305  Luxembourg  Luxembourg  Fixed Income      Global Bond  SICAV   \n",
+       "2566306  Luxembourg  Luxembourg  Fixed Income      Global Bond  SICAV   \n",
+       "2566307  Luxembourg  Luxembourg  Fixed Income         Sécurité    FCP   \n",
+       "2566308  Luxembourg  Luxembourg  Fixed Income         Sécurité    FCP   \n",
+       "2566309  Luxembourg  Luxembourg  Fixed Income         Sécurité    FCP   \n",
+       "\n",
+       "         1989-01-26  ...  2016-04-04 0.000000000 -25.580000000  \\\n",
+       "0        1989-01-26  ...  2016-07-12         0.0      -8.87500   \n",
+       "1        1989-01-26  ...  2016-11-22         0.0    -177.06500   \n",
+       "2        1989-01-26  ...  2017-12-12         0.0     -72.63700   \n",
+       "3        1989-01-26  ...  2018-09-18         0.0    -265.02125   \n",
+       "4        2002-01-02  ...  2022-07-06         0.0      -0.29700   \n",
+       "...             ...  ...         ...         ...           ...   \n",
+       "2566305  2007-12-14  ...  2015-04-07         0.0      -1.00000   \n",
+       "2566306  2007-12-14  ...  2015-04-10         0.0     -31.00000   \n",
+       "2566307  1989-01-26  ...  2015-10-12        97.0       0.00000   \n",
+       "2566308  1989-01-26  ...  2015-11-10        40.0     -22.00000   \n",
+       "2566309  1989-01-26  ...  2015-12-17        26.0       0.00000   \n",
+       "\n",
+       "        -25.580000000.1     0.0000 -27030.1300 -27030.1300.1   0.0000.1  \\\n",
+       "0              -8.87500       0.00   -10134.72     -10134.72       0.00   \n",
+       "1            -177.06500       0.00  -200504.86    -200504.86       0.00   \n",
+       "2             -72.63700       0.00   -86605.10     -86605.10       0.00   \n",
+       "3            -265.02125       0.00  -315155.32    -315155.32       0.00   \n",
+       "4              -0.29700       0.00    -1090.03      -1090.03       0.00   \n",
+       "...                 ...        ...         ...           ...        ...   \n",
+       "2566305        -1.00000       0.00    -1382.36      -1382.36       0.00   \n",
+       "2566306       -31.00000       0.00   -43323.43     -43323.43       0.00   \n",
+       "2566307        97.00000  166077.58        0.00     166077.58  166077.58   \n",
+       "2566308        18.00000   68640.40   -37752.22      30888.18   68640.40   \n",
+       "2566309        26.00000   44621.20        0.00      44621.20   44621.20   \n",
+       "\n",
+       "         -27030.1300.2  -27030.1300.3  \n",
+       "0            -10134.72      -10134.72  \n",
+       "1           -200504.86     -200504.86  \n",
+       "2            -86605.10      -86605.10  \n",
+       "3           -315155.32     -315155.32  \n",
+       "4             -1090.03       -1090.03  \n",
+       "...                ...            ...  \n",
+       "2566305       -1382.36       -1382.36  \n",
+       "2566306      -43323.43      -43323.43  \n",
+       "2566307           0.00      166077.58  \n",
+       "2566308      -37752.22       30888.18  \n",
+       "2566309           0.00       44621.20  \n",
+       "\n",
+       "[2566310 rows x 27 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/Flows ENSAE V1 -20251027.csv\"\n",
+    "df_flows1 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_flows1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f8508d94-74a7-4bb0-8b81-c2e06850c25f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-03-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.464867e+04</td>\n",
+       "      <td>2.464867e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-11-30</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.241306e+04</td>\n",
+       "      <td>2.241306e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-12-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.205124e+04</td>\n",
+       "      <td>2.205124e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2016-03-31</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.162612e+04</td>\n",
+       "      <td>2.162612e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200000647</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Patrimoine</td>\n",
+       "      <td>A</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2016-11-30</td>\n",
+       "      <td>35.368</td>\n",
+       "      <td>2.248945e+04</td>\n",
+       "      <td>2.248945e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880292</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-02-29</td>\n",
+       "      <td>26801.000</td>\n",
+       "      <td>2.740670e+06</td>\n",
+       "      <td>2.740670e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880293</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-06-30</td>\n",
+       "      <td>3099.000</td>\n",
+       "      <td>3.122862e+05</td>\n",
+       "      <td>3.122862e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880294</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2020-10-31</td>\n",
+       "      <td>3099.000</td>\n",
+       "      <td>3.184222e+05</td>\n",
+       "      <td>3.184222e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880295</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>AW &amp; AW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1299306321</td>\n",
+       "      <td>2021-07-31</td>\n",
+       "      <td>2835.000</td>\n",
+       "      <td>2.976183e+05</td>\n",
+       "      <td>2.976183e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4880296</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>Carmignac Portfolio Sécurité</td>\n",
+       "      <td>FW &amp; FW-R</td>\n",
+       "      <td>EUR</td>\n",
+       "      <td>LU1792391911</td>\n",
+       "      <td>2020-07-31</td>\n",
+       "      <td>2916.394</td>\n",
+       "      <td>2.874106e+05</td>\n",
+       "      <td>2.874106e+05</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4880297 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Agreement - Code    Company - Id Company - Ultimate Parent Id  \\\n",
+       "0                    003             166                          166   \n",
+       "1                    003             166                          166   \n",
+       "2                    003             166                          166   \n",
+       "3                    003             166                          166   \n",
+       "4                    003             166                          166   \n",
+       "...                  ...             ...                          ...   \n",
+       "4880292   Private Client  Private Client               Private Client   \n",
+       "4880293   Private Client  Private Client               Private Client   \n",
+       "4880294   Private Client  Private Client               Private Client   \n",
+       "4880295   Private Client  Private Client               Private Client   \n",
+       "4880296   Private Client  Private Client               Private Client   \n",
+       "\n",
+       "        Registrar Account - ID Registrar Account - Region  \\\n",
+       "0                    200000647                     France   \n",
+       "1                    200000647                     France   \n",
+       "2                    200000647                     France   \n",
+       "3                    200000647                     France   \n",
+       "4                    200000647                     France   \n",
+       "...                        ...                        ...   \n",
+       "4880292         Private Client                Switzerland   \n",
+       "4880293         Private Client                Switzerland   \n",
+       "4880294         Private Client                Switzerland   \n",
+       "4880295         Private Client                Switzerland   \n",
+       "4880296         Private Client                Switzerland   \n",
+       "\n",
+       "        RegistrarAccount - Country Product - Asset Type Product - Strategy  \\\n",
+       "0                           France          Diversified         Patrimoine   \n",
+       "1                           France          Diversified         Patrimoine   \n",
+       "2                           France          Diversified         Patrimoine   \n",
+       "3                           France          Diversified         Patrimoine   \n",
+       "4                           France          Diversified         Patrimoine   \n",
+       "...                            ...                  ...                ...   \n",
+       "4880292                Switzerland         Fixed Income           Sécurité   \n",
+       "4880293                Switzerland         Fixed Income           Sécurité   \n",
+       "4880294                Switzerland         Fixed Income           Sécurité   \n",
+       "4880295                Switzerland         Fixed Income           Sécurité   \n",
+       "4880296                Switzerland         Fixed Income           Sécurité   \n",
+       "\n",
+       "        Product - Legal Status Product - Is Dedie ?  \\\n",
+       "0                          FCP                   NO   \n",
+       "1                          FCP                   NO   \n",
+       "2                          FCP                   NO   \n",
+       "3                          FCP                   NO   \n",
+       "4                          FCP                   NO   \n",
+       "...                        ...                  ...   \n",
+       "4880292                  SICAV                   NO   \n",
+       "4880293                  SICAV                   NO   \n",
+       "4880294                  SICAV                   NO   \n",
+       "4880295                  SICAV                   NO   \n",
+       "4880296                  SICAV                   NO   \n",
+       "\n",
+       "                       Product - Fund Product - Shareclass Type  \\\n",
+       "0                Carmignac Patrimoine                         A   \n",
+       "1                Carmignac Patrimoine                         A   \n",
+       "2                Carmignac Patrimoine                         A   \n",
+       "3                Carmignac Patrimoine                         A   \n",
+       "4                Carmignac Patrimoine                         A   \n",
+       "...                               ...                       ...   \n",
+       "4880292  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880293  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880294  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880295  Carmignac Portfolio Sécurité                 AW & AW-R   \n",
+       "4880296  Carmignac Portfolio Sécurité                 FW & FW-R   \n",
+       "\n",
+       "        Product - Shareclass Currency Product - Isin Centralisation Date  \\\n",
+       "0                                 EUR   FR0010135103          2015-03-31   \n",
+       "1                                 EUR   FR0010135103          2015-11-30   \n",
+       "2                                 EUR   FR0010135103          2015-12-31   \n",
+       "3                                 EUR   FR0010135103          2016-03-31   \n",
+       "4                                 EUR   FR0010135103          2016-11-30   \n",
+       "...                               ...            ...                 ...   \n",
+       "4880292                           EUR   LU1299306321          2020-02-29   \n",
+       "4880293                           EUR   LU1299306321          2020-06-30   \n",
+       "4880294                           EUR   LU1299306321          2020-10-31   \n",
+       "4880295                           EUR   LU1299306321          2021-07-31   \n",
+       "4880296                           EUR   LU1792391911          2020-07-31   \n",
+       "\n",
+       "         Quantity - AUM  Value - AUM CCY  Value - AUM €  \n",
+       "0                35.368     2.464867e+04   2.464867e+04  \n",
+       "1                35.368     2.241306e+04   2.241306e+04  \n",
+       "2                35.368     2.205124e+04   2.205124e+04  \n",
+       "3                35.368     2.162612e+04   2.162612e+04  \n",
+       "4                35.368     2.248945e+04   2.248945e+04  \n",
+       "...                 ...              ...            ...  \n",
+       "4880292       26801.000     2.740670e+06   2.740670e+06  \n",
+       "4880293        3099.000     3.122862e+05   3.122862e+05  \n",
+       "4880294        3099.000     3.184222e+05   3.184222e+05  \n",
+       "4880295        2835.000     2.976183e+05   2.976183e+05  \n",
+       "4880296        2916.394     2.874106e+05   2.874106e+05  \n",
+       "\n",
+       "[4880297 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd \n",
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/AUM ENSAE V2 -20251105.csv\"\n",
+    "df_aum2 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_aum2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "4644da13-5aea-4ca0-9fcf-947324766292",
+   "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>Agreement - Code</th>\n",
+       "      <th>Company - Id</th>\n",
+       "      <th>Company - Ultimate Parent Id</th>\n",
+       "      <th>Registrar Account - ID</th>\n",
+       "      <th>Registrar Account - Region</th>\n",
+       "      <th>RegistrarAccount - Country</th>\n",
+       "      <th>Product - Asset Type</th>\n",
+       "      <th>Product - Strategy</th>\n",
+       "      <th>Product - Legal Status</th>\n",
+       "      <th>Product - Is Dedie ?</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Centralisation Date</th>\n",
+       "      <th>Quantity - Subscription</th>\n",
+       "      <th>Quantity - Redemption</th>\n",
+       "      <th>Quantity - NetFlows</th>\n",
+       "      <th>Value Ccy - Subscription</th>\n",
+       "      <th>Value Ccy - Redemption</th>\n",
+       "      <th>Value Ccy - NetFlows</th>\n",
+       "      <th>Value € - Subscription</th>\n",
+       "      <th>Value € - Redemption</th>\n",
+       "      <th>Value € - NetFlows</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>200127202</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2020-11-05</td>\n",
+       "      <td>1636.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1636.000</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>280983.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Diversified</td>\n",
+       "      <td>Patrimoine</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-03-09</td>\n",
+       "      <td>144.690</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>144.690</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>99985.13</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>99985.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2016-10-26</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-8.321</td>\n",
+       "      <td>-8.321</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-9384.76</td>\n",
+       "      <td>-9384.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2018-10-18</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-22.083</td>\n",
+       "      <td>-22.083</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-25227.40</td>\n",
+       "      <td>-25227.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>003</td>\n",
+       "      <td>166</td>\n",
+       "      <td>166</td>\n",
+       "      <td>406533</td>\n",
+       "      <td>France</td>\n",
+       "      <td>France</td>\n",
+       "      <td>Equity</td>\n",
+       "      <td>Investissement</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2019-04-08</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-465.992</td>\n",
+       "      <td>-465.992</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-563775.76</td>\n",
+       "      <td>-563775.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574456</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-06-12</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-20.000</td>\n",
+       "      <td>-20.000</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-34294.40</td>\n",
+       "      <td>-34294.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574457</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-09-18</td>\n",
+       "      <td>328.726</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>328.726</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>564028.07</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>564028.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574458</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-09-25</td>\n",
+       "      <td>4.443</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4.443</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>7603.66</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7603.66</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574459</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>FCP</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2015-11-09</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>-440.000</td>\n",
+       "      <td>-440.000</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-754696.80</td>\n",
+       "      <td>-754696.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2574460</th>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Private Client</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>Fixed Income</td>\n",
+       "      <td>Sécurité</td>\n",
+       "      <td>SICAV</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2016-01-11</td>\n",
+       "      <td>3595.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3595.000</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>358385.55</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>358385.55</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2574461 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Agreement - Code    Company - Id Company - Ultimate Parent Id  \\\n",
+       "0                    003             166                          166   \n",
+       "1                    003             166                          166   \n",
+       "2                    003             166                          166   \n",
+       "3                    003             166                          166   \n",
+       "4                    003             166                          166   \n",
+       "...                  ...             ...                          ...   \n",
+       "2574456   Private Client  Private Client               Private Client   \n",
+       "2574457   Private Client  Private Client               Private Client   \n",
+       "2574458   Private Client  Private Client               Private Client   \n",
+       "2574459   Private Client  Private Client               Private Client   \n",
+       "2574460   Private Client  Private Client               Private Client   \n",
+       "\n",
+       "        Registrar Account - ID Registrar Account - Region  \\\n",
+       "0                    200127202                     France   \n",
+       "1                       406533                     France   \n",
+       "2                       406533                     France   \n",
+       "3                       406533                     France   \n",
+       "4                       406533                     France   \n",
+       "...                        ...                        ...   \n",
+       "2574456         Private Client                 Luxembourg   \n",
+       "2574457         Private Client                 Luxembourg   \n",
+       "2574458         Private Client                 Luxembourg   \n",
+       "2574459         Private Client                 Luxembourg   \n",
+       "2574460         Private Client                 Luxembourg   \n",
+       "\n",
+       "        RegistrarAccount - Country Product - Asset Type Product - Strategy  \\\n",
+       "0                           France               Equity     Investissement   \n",
+       "1                           France          Diversified         Patrimoine   \n",
+       "2                           France               Equity     Investissement   \n",
+       "3                           France               Equity     Investissement   \n",
+       "4                           France               Equity     Investissement   \n",
+       "...                            ...                  ...                ...   \n",
+       "2574456                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574457                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574458                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574459                 Luxembourg         Fixed Income           Sécurité   \n",
+       "2574460                 Luxembourg         Fixed Income           Sécurité   \n",
+       "\n",
+       "        Product - Legal Status Product - Is Dedie ?  ... Centralisation Date  \\\n",
+       "0                        SICAV                   NO  ...          2020-11-05   \n",
+       "1                          FCP                   NO  ...          2015-03-09   \n",
+       "2                          FCP                   NO  ...          2016-10-26   \n",
+       "3                          FCP                   NO  ...          2018-10-18   \n",
+       "4                          FCP                   NO  ...          2019-04-08   \n",
+       "...                        ...                  ...  ...                 ...   \n",
+       "2574456                    FCP                   NO  ...          2015-06-12   \n",
+       "2574457                    FCP                   NO  ...          2015-09-18   \n",
+       "2574458                    FCP                   NO  ...          2015-09-25   \n",
+       "2574459                    FCP                   NO  ...          2015-11-09   \n",
+       "2574460                  SICAV                   NO  ...          2016-01-11   \n",
+       "\n",
+       "        Quantity - Subscription Quantity - Redemption Quantity - NetFlows  \\\n",
+       "0                      1636.000                 0.000            1636.000   \n",
+       "1                       144.690                 0.000             144.690   \n",
+       "2                         0.000                -8.321              -8.321   \n",
+       "3                         0.000               -22.083             -22.083   \n",
+       "4                         0.000              -465.992            -465.992   \n",
+       "...                         ...                   ...                 ...   \n",
+       "2574456                   0.000               -20.000             -20.000   \n",
+       "2574457                 328.726                 0.000             328.726   \n",
+       "2574458                   4.443                 0.000               4.443   \n",
+       "2574459                   0.000              -440.000            -440.000   \n",
+       "2574460                3595.000                 0.000            3595.000   \n",
+       "\n",
+       "        Value Ccy - Subscription  Value Ccy - Redemption  \\\n",
+       "0                      280983.00                    0.00   \n",
+       "1                       99985.13                    0.00   \n",
+       "2                           0.00                -9384.76   \n",
+       "3                           0.00               -25227.40   \n",
+       "4                           0.00              -563775.76   \n",
+       "...                          ...                     ...   \n",
+       "2574456                     0.00               -34294.40   \n",
+       "2574457                564028.07                    0.00   \n",
+       "2574458                  7603.66                    0.00   \n",
+       "2574459                     0.00              -754696.80   \n",
+       "2574460                358385.55                    0.00   \n",
+       "\n",
+       "         Value Ccy - NetFlows  Value € - Subscription  Value € - Redemption  \\\n",
+       "0                   280983.00               280983.00                  0.00   \n",
+       "1                    99985.13                99985.13                  0.00   \n",
+       "2                    -9384.76                    0.00              -9384.76   \n",
+       "3                   -25227.40                    0.00             -25227.40   \n",
+       "4                  -563775.76                    0.00            -563775.76   \n",
+       "...                       ...                     ...                   ...   \n",
+       "2574456             -34294.40                    0.00             -34294.40   \n",
+       "2574457             564028.07               564028.07                  0.00   \n",
+       "2574458               7603.66                 7603.66                  0.00   \n",
+       "2574459            -754696.80                    0.00            -754696.80   \n",
+       "2574460             358385.55               358385.55                  0.00   \n",
+       "\n",
+       "         Value € - NetFlows  \n",
+       "0                 280983.00  \n",
+       "1                  99985.13  \n",
+       "2                  -9384.76  \n",
+       "3                 -25227.40  \n",
+       "4                -563775.76  \n",
+       "...                     ...  \n",
+       "2574456           -34294.40  \n",
+       "2574457           564028.07  \n",
+       "2574458             7603.66  \n",
+       "2574459          -754696.80  \n",
+       "2574460           358385.55  \n",
+       "\n",
+       "[2574461 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chemin_fichier = \"s3://projet-bdc-data/carmignac/Flows ENSAE V2 -20251105.csv\"\n",
+    "df_flows2 = pd.read_csv(chemin_fichier, sep=';', engine='python')\n",
+    "df_flows2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59d31eaf-c06c-4ebe-9f8c-cb9158a50976",
+   "metadata": {},
+   "source": [
+    "## DATA ANALYSIS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5773b911-6b84-448d-962f-8228eeac0250",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4880297, 18)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_aum2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "6f571810-c373-4d30-8ca5-c3a074b95b08",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Agreement - Code', 'Company - Id', 'Company - Ultimate Parent Id',\n",
+       "       'Registrar Account - ID', 'Registrar Account - Region',\n",
+       "       'RegistrarAccount - Country', 'Product - Asset Type',\n",
+       "       'Product - Strategy', 'Product - Legal Status', 'Product - Is Dedie ?',\n",
+       "       'Product - Fund', 'Product - Shareclass Type',\n",
+       "       'Product - Shareclass Currency', 'Product - Isin',\n",
+       "       'Centralisation Date', 'Quantity - AUM', 'Value - AUM CCY',\n",
+       "       'Value - AUM €'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_aum2.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "73c15272-a789-4928-b23e-651dd886efd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "'Agreement - Code': Identifie le contrat commercial ou opérationnel entre Carmignac et l’intermédiaire distributeur (banque, assurance, plateforme)., \n",
+    "\n",
+    "'Company - Id' : Identifiant interne de l’entité distributrice (banque privée, CGP, assurance…).Chaque \"Company\" = un partenaire B2B, \n",
+    "\n",
+    "'Company - Ultimate Parent Id': Identifiant du groupe parent de la société distributrice.\n",
+    "\n",
+    "Ex : une banque privée appartient à un grand groupe bancaire //// OU plusieurs filiales → même Ultimate Parent.\n",
+    "Sert à agréger les flux ou AUM au niveau du groupe, pas seulement d’une filiale.,\n",
+    "\n",
+    "'Registrar Account - ID', \n",
+    "Identifiant du compte investisseur dans les registres.Ce n’est PAS le client final : c’est souvent un compte omnibus, une plateforme, \n",
+    "une banque dépositaire, etc.s\n",
+    "→ IMPORTANT car un même investisseur final peut être caché sous plusieurs comptes.,\n",
+    "\n",
+    "'Registrar Account - Region',\n",
+    "\n",
+    "'RegistrarAccount - Country', \n",
+    "\n",
+    "'Product - Asset Type',       \n",
+    "'Product - Strategy', \n",
+    "'Product - Legal Status': Le cadre réglementaire du fonds, typiquement : UCITS,AIF,SICAV,FCP, \n",
+    "'Product - Is Dedie ?': Indique si la part est dédiée à un distributeur particulier (shareclass ségrégée). Valeurs : Oui/Non,\n",
+    "\n",
+    "'Product - Fund', \n",
+    "'Product - Shareclass Type': Chaque share classe peut avoir : Devise différente (EUR, USD) /// Frais différents //Distribution des dividendes \n",
+    "différente .............,\n",
+    "\n",
+    "'Product - Shareclass Currency', \n",
+    "'Product - Isin': c est un code qui identifie un produit financier, pas un client , #REVOIRR \n",
+    "'Centralisation Date': Cette date n’est pas la date de transaction, mais celle où les positions sont centralisées et publiees pour reporting., ....\n",
+    "'Quantity - AUM', \n",
+    "'Value - AUM CCY', Valeur des AUM dans la devise de la share classe,\n",
+    "'Value - AUM €'\n",
+    "\n",
+    "\n",
+    "AUM = Assets Under Management = Encours sous gestion\n",
+    "Ce sont les montants totaux investis dans un fonds ou un compte.\n",
+    "\n",
+    "Exemple :\n",
+    "- Quantity : Compte A détient 1 000 parts de Carmignac Patrimoine A EUR\n",
+    "- Price ou valeurs de la part = 100 EUR\n",
+    "- AUM Value = 1 000 × 100 = 100 000 EUR\n",
+    "==>  AUM représente la valeur financière totale détenue par le compte pour ce fonds.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b179431d-0d07-4eff-8bb7-976ebbe3f987",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#FLOWS VS AUM\n",
+    "Flows = mouvements entrants (subscriptions) ou sortants (redemptions) pendant une période\n",
+    "AUM = stock à un instant donné\n",
+    "\n",
+    "\n",
+    "\n",
+    "REMARQUE: CLIENT IDENTIFICATION : le client final n’est pas directement identifiable, car intermediaire.\n",
+    "\n",
+    "1- Registrar Account ID → identifie le compte dans le registre → peut représenter un ou plusieurs clients finaux.\n",
+    "2- Company - Id Ultimate Parent → identifie le distributeur, pas le client final.\n",
+    "\n",
+    "En pratique pour le clustering client : Il faudra utiliser Registrar Account - ID + Company - Id comme proxy client.\n",
+    "Mais attention : même investisseur peut avoir plusieurs comptes / plusieurs banques."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "af25fd07-a613-4adc-b88b-93a8d300379c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2574461, 24)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_flows2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c6d0fe83-2957-430b-89cf-cd30833b7cab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Agreement - Code', 'Company - Id', 'Company - Ultimate Parent Id',\n",
+       "       'Registrar Account - ID', 'Registrar Account - Region',\n",
+       "       'RegistrarAccount - Country', 'Product - Asset Type',\n",
+       "       'Product - Strategy', 'Product - Legal Status', 'Product - Is Dedie ?',\n",
+       "       'Product - Fund', 'Product - Shareclass Type',\n",
+       "       'Product - Shareclass Currency', 'Product - Isin',\n",
+       "       'Centralisation Date', 'Quantity - Subscription',\n",
+       "       'Quantity - Redemption', 'Quantity - NetFlows',\n",
+       "       'Value Ccy - Subscription', 'Value Ccy - Redemption',\n",
+       "       'Value Ccy - NetFlows', 'Value € - Subscription',\n",
+       "       'Value € - Redemption', 'Value € - NetFlows'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_flows2.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5fac74b0-662f-48d0-a234-7edc3c3e86ad",
+   "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>Colonne</th>\n",
+       "      <th>Nbr Lignes</th>\n",
+       "      <th>Nb valeurs uniques</th>\n",
+       "      <th>Exemples de valeurs</th>\n",
+       "      <th>Nan Values</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Agreement - Code</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>2427</td>\n",
+       "      <td>[003, 005, 006, 008, 009, 011, 016, 020, 021, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Company - Id</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1562</td>\n",
+       "      <td>[166, nan, 968, 927, 42, 15181, 13536, 231, 48...</td>\n",
+       "      <td>113750</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Company - Ultimate Parent Id</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1068</td>\n",
+       "      <td>[166, nan, 968, 927, 42, 877, 13536, 14977, 48...</td>\n",
+       "      <td>113750</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Registrar Account - ID</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>12501</td>\n",
+       "      <td>[200000647, 200000654, 200127202, 404391, 4054...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Registrar Account - Region</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>15</td>\n",
+       "      <td>[France, Switzerland, Luxembourg, Belgium, Int...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>RegistrarAccount - Country</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>39</td>\n",
+       "      <td>[France, Switzerland, Luxembourg, Belgium, Mon...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Product - Asset Type</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[Diversified, Equity, nan, Alternative, Fixed ...</td>\n",
+       "      <td>315831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Product - Strategy</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>53</td>\n",
+       "      <td>[Patrimoine, Investissement, Euro-Investisseme...</td>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Product - Legal Status</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[FCP, SICAV, FCPE, ICAV, OEIC, Others]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Product - Is Dedie ?</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>2</td>\n",
+       "      <td>[NO, YES]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Product - Fund</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>74</td>\n",
+       "      <td>[Carmignac Patrimoine, Carmignac Investissemen...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Product - Shareclass Type</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>12</td>\n",
+       "      <td>[A, F, AW &amp; AW-R, FW &amp; FW-R, Not Applicable, E...</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Product - Shareclass Currency</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[EUR, CHF, USD, GBP, JPY, CAD]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Product - Isin</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>491</td>\n",
+       "      <td>[FR0010135103, FR0010148981, LU0992625839, FR0...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Centralisation Date</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>130</td>\n",
+       "      <td>[2015-03-31, 2015-11-30, 2015-12-31, 2016-03-3...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Quantity - AUM</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>554404</td>\n",
+       "      <td>[35.368, 0.0, 193.97, 170.2, 285.2, 277.8, 189...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Value - AUM CCY</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1689620</td>\n",
+       "      <td>[24648.6666, 22413.0553, 22051.2406, 21626.117...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Value - AUM €</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1697923</td>\n",
+       "      <td>[24648.6666, 22413.0553, 22051.2406, 21626.117...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Colonne  Nbr Lignes  Nb valeurs uniques  \\\n",
+       "0                Agreement - Code     4880297                2427   \n",
+       "1                    Company - Id     4880297                1562   \n",
+       "2    Company - Ultimate Parent Id     4880297                1068   \n",
+       "3          Registrar Account - ID     4880297               12501   \n",
+       "4      Registrar Account - Region     4880297                  15   \n",
+       "5      RegistrarAccount - Country     4880297                  39   \n",
+       "6            Product - Asset Type     4880297                   6   \n",
+       "7              Product - Strategy     4880297                  53   \n",
+       "8          Product - Legal Status     4880297                   6   \n",
+       "9            Product - Is Dedie ?     4880297                   2   \n",
+       "10                 Product - Fund     4880297                  74   \n",
+       "11      Product - Shareclass Type     4880297                  12   \n",
+       "12  Product - Shareclass Currency     4880297                   6   \n",
+       "13                 Product - Isin     4880297                 491   \n",
+       "14            Centralisation Date     4880297                 130   \n",
+       "15                 Quantity - AUM     4880297              554404   \n",
+       "16                Value - AUM CCY     4880297             1689620   \n",
+       "17                  Value - AUM €     4880297             1697923   \n",
+       "\n",
+       "                                  Exemples de valeurs  Nan Values  \n",
+       "0   [003, 005, 006, 008, 009, 011, 016, 020, 021, ...           0  \n",
+       "1   [166, nan, 968, 927, 42, 15181, 13536, 231, 48...      113750  \n",
+       "2   [166, nan, 968, 927, 42, 877, 13536, 14977, 48...      113750  \n",
+       "3   [200000647, 200000654, 200127202, 404391, 4054...           0  \n",
+       "4   [France, Switzerland, Luxembourg, Belgium, Int...           0  \n",
+       "5   [France, Switzerland, Luxembourg, Belgium, Mon...           0  \n",
+       "6   [Diversified, Equity, nan, Alternative, Fixed ...      315831  \n",
+       "7   [Patrimoine, Investissement, Euro-Investisseme...          75  \n",
+       "8              [FCP, SICAV, FCPE, ICAV, OEIC, Others]           0  \n",
+       "9                                           [NO, YES]           0  \n",
+       "10  [Carmignac Patrimoine, Carmignac Investissemen...           0  \n",
+       "11  [A, F, AW & AW-R, FW & FW-R, Not Applicable, E...          35  \n",
+       "12                     [EUR, CHF, USD, GBP, JPY, CAD]           0  \n",
+       "13  [FR0010135103, FR0010148981, LU0992625839, FR0...           0  \n",
+       "14  [2015-03-31, 2015-11-30, 2015-12-31, 2016-03-3...           0  \n",
+       "15  [35.368, 0.0, 193.97, 170.2, 285.2, 277.8, 189...           0  \n",
+       "16  [24648.6666, 22413.0553, 22051.2406, 21626.117...           0  \n",
+       "17  [24648.6666, 22413.0553, 22051.2406, 21626.117...           0  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#dict avec valeurs unique de chaque col \n",
+    "rows = []\n",
+    "\n",
+    "for col in df_aum2.columns:\n",
+    "    uniques = df_aum2[col].unique()\n",
+    "    rows.append({\n",
+    "        \"Colonne\": col,\n",
+    "        \"Nbr Lignes\": df_aum2.shape[0], #4.8millions\n",
+    "        \"Nb valeurs uniques\": len(uniques),\n",
+    "        \"Exemples de valeurs\": uniques,\n",
+    "        \"Nan Values\" : df_aum2[col].isna().sum()\n",
+    "    })\n",
+    "\n",
+    "df_uniques = pd.DataFrame(rows)\n",
+    "df_uniques"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5de53ba3-b3db-4935-acac-435b05b909e2",
+   "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>Colonne</th>\n",
+       "      <th>Nbr Lignes</th>\n",
+       "      <th>Nb valeurs uniques</th>\n",
+       "      <th>Exemples de valeurs</th>\n",
+       "      <th>Nan Values</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Agreement - Code</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1611</td>\n",
+       "      <td>[003, 008, 006, 009, 016, 020, 021, 022, 030, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Company - Id</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>[166, 927, 968, 42, 13536, 231, 481, 91, 1038,...</td>\n",
+       "      <td>1540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Company - Ultimate Parent Id</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>815</td>\n",
+       "      <td>[166, 927, 968, 42, 13536, 14977, 481, 91, 103...</td>\n",
+       "      <td>1540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Registrar Account - ID</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6842</td>\n",
+       "      <td>[200127202, 406533, 411986, 200000647, 412028,...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Registrar Account - Region</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>15</td>\n",
+       "      <td>[France, International, Belgium, Spain, Luxemb...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>RegistrarAccount - Country</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>34</td>\n",
+       "      <td>[France, Monaco, Israel, Belgium, Spain, Luxem...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Product - Asset Type</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[Equity, Diversified, Fixed Income, Alternativ...</td>\n",
+       "      <td>2049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Product - Strategy</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>50</td>\n",
+       "      <td>[Investissement, Patrimoine, Emerging Patrimoi...</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Product - Legal Status</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[SICAV, FCP, FCPE, ICAV, OEIC, Others]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Product - Is Dedie ?</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>2</td>\n",
+       "      <td>[NO, YES]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Product - Fund</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>70</td>\n",
+       "      <td>[Carmignac Portfolio Investissement, Carmignac...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Product - Shareclass Type</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>11</td>\n",
+       "      <td>[F, A, AW &amp; AW-R, FW &amp; FW-R, E, IW, Dedicated,...</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Product - Shareclass Currency</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "      <td>[EUR, USD, CHF, GBP, JPY, CAD]</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Product - Isin</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>474</td>\n",
+       "      <td>[LU0992625839, FR0010135103, FR0010148981, LU0...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Centralisation Date</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>2780</td>\n",
+       "      <td>[2020-11-05, 2015-03-09, 2016-10-26, 2018-10-1...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Quantity - Subscription</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>359661</td>\n",
+       "      <td>[1636.0, 144.69, 0.0, 160.698, 17.285, 115.0, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Quantity - Redemption</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>374378</td>\n",
+       "      <td>[0.0, -8.321, -22.083, -465.992, -0.397, -36.0...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Quantity - NetFlows</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>667586</td>\n",
+       "      <td>[1636.0, 144.69, -8.321, -22.083, -465.992, 16...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Value Ccy - Subscription</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>926633</td>\n",
+       "      <td>[280983.0, 99985.13, 0.0, 21851.77, 19795.99, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Value Ccy - Redemption</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1296468</td>\n",
+       "      <td>[0.0, -9384.76, -25227.4, -563775.76, -1536.53...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>Value Ccy - NetFlows</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1972319</td>\n",
+       "      <td>[280983.0, 99985.13, -9384.76, -25227.4, -5637...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Value € - Subscription</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>955890</td>\n",
+       "      <td>[280983.0, 99985.13, 0.0, 21851.77, 19795.99, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>Value € - Redemption</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1323531</td>\n",
+       "      <td>[0.0, -9384.76, -25227.4, -563775.76, -1536.53...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Value € - NetFlows</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>2018916</td>\n",
+       "      <td>[280983.0, 99985.13, -9384.76, -25227.4, -5637...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Colonne  Nbr Lignes  Nb valeurs uniques  \\\n",
+       "0                Agreement - Code     2574461                1611   \n",
+       "1                    Company - Id     2574461                1231   \n",
+       "2    Company - Ultimate Parent Id     2574461                 815   \n",
+       "3          Registrar Account - ID     2574461                6842   \n",
+       "4      Registrar Account - Region     2574461                  15   \n",
+       "5      RegistrarAccount - Country     2574461                  34   \n",
+       "6            Product - Asset Type     2574461                   6   \n",
+       "7              Product - Strategy     2574461                  50   \n",
+       "8          Product - Legal Status     2574461                   6   \n",
+       "9            Product - Is Dedie ?     2574461                   2   \n",
+       "10                 Product - Fund     2574461                  70   \n",
+       "11      Product - Shareclass Type     2574461                  11   \n",
+       "12  Product - Shareclass Currency     2574461                   6   \n",
+       "13                 Product - Isin     2574461                 474   \n",
+       "14            Centralisation Date     2574461                2780   \n",
+       "15        Quantity - Subscription     2574461              359661   \n",
+       "16          Quantity - Redemption     2574461              374378   \n",
+       "17            Quantity - NetFlows     2574461              667586   \n",
+       "18       Value Ccy - Subscription     2574461              926633   \n",
+       "19         Value Ccy - Redemption     2574461             1296468   \n",
+       "20           Value Ccy - NetFlows     2574461             1972319   \n",
+       "21         Value € - Subscription     2574461              955890   \n",
+       "22           Value € - Redemption     2574461             1323531   \n",
+       "23             Value € - NetFlows     2574461             2018916   \n",
+       "\n",
+       "                                  Exemples de valeurs  Nan Values  \n",
+       "0   [003, 008, 006, 009, 016, 020, 021, 022, 030, ...           0  \n",
+       "1   [166, 927, 968, 42, 13536, 231, 481, 91, 1038,...        1540  \n",
+       "2   [166, 927, 968, 42, 13536, 14977, 481, 91, 103...        1540  \n",
+       "3   [200127202, 406533, 411986, 200000647, 412028,...           0  \n",
+       "4   [France, International, Belgium, Spain, Luxemb...           0  \n",
+       "5   [France, Monaco, Israel, Belgium, Spain, Luxem...           0  \n",
+       "6   [Equity, Diversified, Fixed Income, Alternativ...        2049  \n",
+       "7   [Investissement, Patrimoine, Emerging Patrimoi...           6  \n",
+       "8              [SICAV, FCP, FCPE, ICAV, OEIC, Others]           0  \n",
+       "9                                           [NO, YES]           0  \n",
+       "10  [Carmignac Portfolio Investissement, Carmignac...           0  \n",
+       "11  [F, A, AW & AW-R, FW & FW-R, E, IW, Dedicated,...           2  \n",
+       "12                     [EUR, USD, CHF, GBP, JPY, CAD]           0  \n",
+       "13  [LU0992625839, FR0010135103, FR0010148981, LU0...           0  \n",
+       "14  [2020-11-05, 2015-03-09, 2016-10-26, 2018-10-1...           0  \n",
+       "15  [1636.0, 144.69, 0.0, 160.698, 17.285, 115.0, ...           0  \n",
+       "16  [0.0, -8.321, -22.083, -465.992, -0.397, -36.0...           0  \n",
+       "17  [1636.0, 144.69, -8.321, -22.083, -465.992, 16...           0  \n",
+       "18  [280983.0, 99985.13, 0.0, 21851.77, 19795.99, ...           0  \n",
+       "19  [0.0, -9384.76, -25227.4, -563775.76, -1536.53...           0  \n",
+       "20  [280983.0, 99985.13, -9384.76, -25227.4, -5637...           0  \n",
+       "21  [280983.0, 99985.13, 0.0, 21851.77, 19795.99, ...           0  \n",
+       "22  [0.0, -9384.76, -25227.4, -563775.76, -1536.53...           0  \n",
+       "23  [280983.0, 99985.13, -9384.76, -25227.4, -5637...           0  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#dict avec valeurs unique de chaque col \n",
+    "rowsf = []\n",
+    "\n",
+    "for col in df_flows2.columns:\n",
+    "    uniques = df_flows2[col].unique()\n",
+    "    rowsf.append({\n",
+    "        \"Colonne\": col,\n",
+    "        \"Nbr Lignes\": df_flows2.shape[0], #4.8millions\n",
+    "        \"Nb valeurs uniques\": len(uniques),\n",
+    "        \"Exemples de valeurs\": uniques,\n",
+    "        \"Nan Values\" : df_flows2[col].isna().sum()\n",
+    "    })\n",
+    "\n",
+    "df_unique_flows = pd.DataFrame(rowsf)\n",
+    "df_unique_flows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "520a5211-3735-44d8-9fe5-b2468c950606",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#rev pour df_flows2 et df_aum2 pas meme valeurs uniques "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e07a2b28-13f7-49f6-a55b-7d09a506407b",
+   "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>Colonne</th>\n",
+       "      <th>Nbr Lignes_aum</th>\n",
+       "      <th>Nb valeurs uniques_aum</th>\n",
+       "      <th>Nbr Lignes_flows</th>\n",
+       "      <th>Nb valeurs uniques_flows</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Agreement - Code</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>2427</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1611</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Company - Id</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1562</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>1231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Company - Ultimate Parent Id</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>1068</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Registrar Account - ID</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>12501</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6842</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Registrar Account - Region</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>15</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>RegistrarAccount - Country</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>39</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Product - Asset Type</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Product - Strategy</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>53</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Product - Legal Status</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Product - Is Dedie ?</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Product - Fund</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Product - Shareclass Type</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Product - Shareclass Currency</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Product - Isin</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>491</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Centralisation Date</td>\n",
+       "      <td>4880297</td>\n",
+       "      <td>130</td>\n",
+       "      <td>2574461</td>\n",
+       "      <td>2780</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Colonne  Nbr Lignes_aum  Nb valeurs uniques_aum  \\\n",
+       "0                Agreement - Code         4880297                    2427   \n",
+       "1                    Company - Id         4880297                    1562   \n",
+       "2    Company - Ultimate Parent Id         4880297                    1068   \n",
+       "3          Registrar Account - ID         4880297                   12501   \n",
+       "4      Registrar Account - Region         4880297                      15   \n",
+       "5      RegistrarAccount - Country         4880297                      39   \n",
+       "6            Product - Asset Type         4880297                       6   \n",
+       "7              Product - Strategy         4880297                      53   \n",
+       "8          Product - Legal Status         4880297                       6   \n",
+       "9            Product - Is Dedie ?         4880297                       2   \n",
+       "10                 Product - Fund         4880297                      74   \n",
+       "11      Product - Shareclass Type         4880297                      12   \n",
+       "12  Product - Shareclass Currency         4880297                       6   \n",
+       "13                 Product - Isin         4880297                     491   \n",
+       "14            Centralisation Date         4880297                     130   \n",
+       "\n",
+       "    Nbr Lignes_flows  Nb valeurs uniques_flows  \n",
+       "0            2574461                      1611  \n",
+       "1            2574461                      1231  \n",
+       "2            2574461                       815  \n",
+       "3            2574461                      6842  \n",
+       "4            2574461                        15  \n",
+       "5            2574461                        34  \n",
+       "6            2574461                         6  \n",
+       "7            2574461                        50  \n",
+       "8            2574461                         6  \n",
+       "9            2574461                         2  \n",
+       "10           2574461                        70  \n",
+       "11           2574461                        11  \n",
+       "12           2574461                         6  \n",
+       "13           2574461                       474  \n",
+       "14           2574461                      2780  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1_aum = df_uniques[['Colonne', 'Nbr Lignes', 'Nb valeurs uniques']]\n",
+    "df2_flows = df_unique_flows[['Colonne', 'Nbr Lignes', 'Nb valeurs uniques']]\n",
+    "\n",
+    "df_merged = df1_aum.merge(df2_flows, on='Colonne', suffixes=('_aum', '_flows'))\n",
+    "df_merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a673272a-d109-470e-9da9-02f61ca2550b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#descriptio colonnes de df_flows2\n",
+    "Colonne\tSignification pour df_flows2\n",
+    "\n",
+    "1- Agreement - Code\t:  Code interne de l’accord/fonds (pour identifier les fonds ou stratégies)\n",
+    "\n",
+    "2- Company - Id  :     \tID de l’intermédiaire (banque, conseiller)\n",
+    "3- Company - Ultimate Parent Id\t:   ID de la société mère de l’intermédiaire\n",
+    "\n",
+    "4- Registrar Account - ID\t: Identifiant unique du compte (le client chez le dépositaire) #hyda code client !!!\n",
+    "5- Registrar Account - Region / Country: \tRégion ou pays du compte\n",
+    "\n",
+    "6- Product - Asset Type / Strategy / Legal Status / Is Dedie? : \n",
+    "Type de produit (Equity, Diversified…), stratégie d’investissement, type légal du fonds (SICAV, FCP), dédié ou non\n",
+    "\n",
+    "8-Product - Fund / Shareclass Type / Currency / ISIN\t:\n",
+    "Nom du fonds, type de shareclass, devise, ISIN unique du produit\n",
+    "\n",
+    "9- Centralisation Date : \tDate de reporting du flux\n",
+    "10- Quantity - Subscription / Redemption / NetFlows : \t\n",
+    "Nombre de parts souscrites, rachetées et flux net (Subscription - Redemption)\n",
+    "\n",
+    "11- Value Ccy / Value € - Subscription / Redemption / NetFlows\t: \n",
+    "Valeurs en devise du fonds et en euro pour les souscriptions, rachats et flux net \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2152a444-4a84-426e-ac7a-4806a8d0a35e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Pour faire de la segmentation client et du clustering, il faut que le dataset soit cohérent et \n",
+    "représentatif des clients finaux, pas juste des comptes !! JE DOIS CLEAN ET IDENTIFIER LES MISMATCH \n",
+    "\n",
+    "ANOMALIES :EXEMPLE CI DESSOUS, Y EN A D AUTRES? ??????\n",
+    "1- Un client change de compte / dépositaire :\n",
+    "\n",
+    "-- Compte A → flux sortants (retrait)\n",
+    "-- Compte B → flux entrants (nouveau compte)\n",
+    "Montants identiques et même ISIN / produit → même client peut etre\n",
+    "\n",
+    "2- Un compte disparaît et un autre se crée avec mêmes montants → flux continu"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ce2ad22-08e6-4e63-96b2-c2301172516e",
+   "metadata": {},
+   "source": [
+    "# ETUDE ET ANALYSE DES ANOMALIES"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c883dfc2-b9b9-4d3e-80d3-0140cd222492",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_aum2['Centralisation Date'] = pd.to_datetime(df_aum2['Centralisation Date'])\n",
+    "df_flows2['Centralisation Date'] = pd.to_datetime(df_flows2['Centralisation Date'])\n",
+    "\n",
+    "\n",
+    "key_cols = ['Registrar Account - ID', 'Product - Isin']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "64ca9883-372b-4a5e-8fc1-10e5d835c411",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Doublons AUM: 250232\n",
+      "Doublons Flows: 4849\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Vérifier doublons exacts\n",
+    "doublons_aum = df_aum2[df_aum2.duplicated(subset=key_cols + ['Centralisation Date'], keep=False)]\n",
+    "doublons_flows = df_flows2[df_flows2.duplicated(subset=key_cols + ['Centralisation Date'], keep=False)]\n",
+    "\n",
+    "print(\"Doublons AUM:\", doublons_aum.shape[0])\n",
+    "print(\"Doublons Flows:\", doublons_flows.shape[0])\n",
+    "\n",
+    "#same date, code isin du produit, et account ==> revoir les autres caracteristiques "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f47b276d-cce6-433c-87c5-860810d71d34",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Cols:  ['Company - Id', 'Company - Ultimate Parent Id', 'Registrar Account - ID', 'Registrar Account - Region', 'Product - Isin']\n",
+      "Doublons AUM: 26452\n",
+      "Doublons Flows: 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "cols= ['Company - Id', 'Company - Ultimate Parent Id',\n",
+    "       'Registrar Account - ID', 'Registrar Account - Region','Product - Isin']\n",
+    "\n",
+    "doublons_aum2 = df_aum2[df_aum2.duplicated(subset=cols + ['Centralisation Date'], keep=False)]\n",
+    "doublons_flows2 = df_flows2[df_flows2.duplicated(subset=cols + ['Centralisation Date'], keep=False)]\n",
+    "\n",
+    "print(\" Cols: \", cols)\n",
+    "print(\"Doublons AUM:\", doublons_aum2.shape[0])\n",
+    "print(\"Doublons Flows:\", doublons_flows2.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d2f355e6-30c5-420e-a3db-9095dd5e0147",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Comptes avec same flux et same product ISIN mais IDs différents ---> candidats pseudo-client\n",
+    "# #plusieurs comptes diff réalisent EXACTEMENT le même flux sur le même produit le même jour.\n",
+    "# #date?\n",
+    "\n",
+    "# pseudo_client_candidates = df_flows2.groupby(['Product - Isin','Centralisation Date', 'Quantity - NetFlows', 'Value € - NetFlows'])['Registrar Account - ID'].nunique()\n",
+    "# pseudo_client_candidates = pseudo_client_candidates[pseudo_client_candidates > 1]\n",
+    "# print(\"Comptes potentiels à fusionner:\")\n",
+    "# print(pseudo_client_candidates)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ff0284ad-2c28-4bb4-b6a5-92f52181e433",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Groupby pour détecter les flows identiques le même jour, sur le même ISIN\n",
+    "\n",
+    "# grouped = df_flows2.groupby(\n",
+    "#     ['Product - Isin', 'Centralisation Date', 'Quantity - NetFlows', 'Value € - NetFlows']\n",
+    "# )['Registrar Account - ID'] \\\n",
+    "#     .agg(['nunique', list]) \\\n",
+    "#     .reset_index()\n",
+    "\n",
+    "# #plusieurs comptes différents apparaissent\n",
+    "# pseudo_client_candidates = grouped[grouped['nunique'] > 1]\n",
+    "\n",
+    "# print(\"Comptes potentiels à fusionner :\")\n",
+    "# display(pseudo_client_candidates)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "3ff99523-0a79-465b-b257-ea15d6c42d2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2574461, 24)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_flows2.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "8df98c34-b1f7-4fb9-bbc7-c9bbe762022a",
+   "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>ISIN</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Compte sortant</th>\n",
+       "      <th>Montant sortie</th>\n",
+       "      <th>Compte entrant</th>\n",
+       "      <th>Montant entrée</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>365247</td>\n",
+       "      <td>-3126.05</td>\n",
+       "      <td>200002169</td>\n",
+       "      <td>3126.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>365888</td>\n",
+       "      <td>-3751.26</td>\n",
+       "      <td>365241</td>\n",
+       "      <td>3751.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-01-05</td>\n",
+       "      <td>419848</td>\n",
+       "      <td>-3135.85</td>\n",
+       "      <td>200001747</td>\n",
+       "      <td>3135.85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-01-05</td>\n",
+       "      <td>417952</td>\n",
+       "      <td>-627.17</td>\n",
+       "      <td>200002169</td>\n",
+       "      <td>627.17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FR0010135103</td>\n",
+       "      <td>2015-01-05</td>\n",
+       "      <td>417937</td>\n",
+       "      <td>-5644.53</td>\n",
+       "      <td>406074</td>\n",
+       "      <td>5644.53</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27875</th>\n",
+       "      <td>LU2809794220</td>\n",
+       "      <td>2025-10-16</td>\n",
+       "      <td>200058108</td>\n",
+       "      <td>-1315.00</td>\n",
+       "      <td>200127345</td>\n",
+       "      <td>1315.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27876</th>\n",
+       "      <td>LU2809794220</td>\n",
+       "      <td>2025-10-31</td>\n",
+       "      <td>420350</td>\n",
+       "      <td>-141.03</td>\n",
+       "      <td>200127644</td>\n",
+       "      <td>141.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27877</th>\n",
+       "      <td>LU2809794220</td>\n",
+       "      <td>2025-11-03</td>\n",
+       "      <td>200127356</td>\n",
+       "      <td>-2996.91</td>\n",
+       "      <td>420350</td>\n",
+       "      <td>2996.91</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27878</th>\n",
+       "      <td>LU2809794493</td>\n",
+       "      <td>2024-12-09</td>\n",
+       "      <td>200058108</td>\n",
+       "      <td>-97.27</td>\n",
+       "      <td>420350</td>\n",
+       "      <td>97.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27879</th>\n",
+       "      <td>LU2970252958</td>\n",
+       "      <td>2025-04-09</td>\n",
+       "      <td>200002082</td>\n",
+       "      <td>-2613.34</td>\n",
+       "      <td>200002271</td>\n",
+       "      <td>2613.34</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>27880 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               ISIN       Date Compte sortant  Montant sortie Compte entrant  \\\n",
+       "0      FR0010135103 2015-01-02         365247        -3126.05      200002169   \n",
+       "1      FR0010135103 2015-01-02         365888        -3751.26         365241   \n",
+       "2      FR0010135103 2015-01-05         419848        -3135.85      200001747   \n",
+       "3      FR0010135103 2015-01-05         417952         -627.17      200002169   \n",
+       "4      FR0010135103 2015-01-05         417937        -5644.53         406074   \n",
+       "...             ...        ...            ...             ...            ...   \n",
+       "27875  LU2809794220 2025-10-16      200058108        -1315.00      200127345   \n",
+       "27876  LU2809794220 2025-10-31         420350         -141.03      200127644   \n",
+       "27877  LU2809794220 2025-11-03      200127356        -2996.91         420350   \n",
+       "27878  LU2809794493 2024-12-09      200058108          -97.27         420350   \n",
+       "27879  LU2970252958 2025-04-09      200002082        -2613.34      200002271   \n",
+       "\n",
+       "       Montant entrée  \n",
+       "0             3126.05  \n",
+       "1             3751.26  \n",
+       "2             3135.85  \n",
+       "3              627.17  \n",
+       "4             5644.53  \n",
+       "...               ...  \n",
+       "27875         1315.00  \n",
+       "27876          141.03  \n",
+       "27877         2996.91  \n",
+       "27878           97.27  \n",
+       "27879         2613.34  \n",
+       "\n",
+       "[27880 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = df_flows2.copy()\n",
+    "df[\"Date\"] = pd.to_datetime(df[\"Centralisation Date\"])\n",
+    "\n",
+    "# Groupby par ISIN et Date\n",
+    "grouped = df.groupby([\"Product - Isin\", \"Date\"])\n",
+    "\n",
+    "transfers = []\n",
+    "\n",
+    "for (isin, date), group in grouped:\n",
+    "    # Sépare flux positifs et négatifs\n",
+    "    entrants = group[group[\"Value € - NetFlows\"] > 0][[\"Registrar Account - ID\", \"Value € - NetFlows\"]]\n",
+    "    sortants = group[group[\"Value € - NetFlows\"] < 0][[\"Registrar Account - ID\", \"Value € - NetFlows\"]]\n",
+    "\n",
+    "    # On cherche des paires +M / -M\n",
+    "    for _, row_sortie in sortants.iterrows():\n",
+    "        montant_sortie = row_sortie[\"Value € - NetFlows\"]\n",
+    "        compte_sortant = row_sortie[\"Registrar Account - ID\"]\n",
+    "\n",
+    "        # Chercher un +M qui matche exactement le -M\n",
+    "        match = entrants[entrants[\"Value € - NetFlows\"] == -montant_sortie]\n",
+    "\n",
+    "        if len(match) > 0:\n",
+    "            for _, row_entree in match.iterrows():\n",
+    "                transfers.append({\n",
+    "                    \"ISIN\": isin,\n",
+    "                    \"Date\": date,\n",
+    "                    \"Compte sortant\": compte_sortant,\n",
+    "                    \"Montant sortie\": montant_sortie,\n",
+    "                    \"Compte entrant\": row_entree[\"Registrar Account - ID\"],\n",
+    "                    \"Montant entrée\": row_entree[\"Value € - NetFlows\"]\n",
+    "                })\n",
+    "\n",
+    "\n",
+    "transf_compte = pd.DataFrame(transfers)\n",
+    "transf_compte\n",
+    "\n",
+    "#df initiale : 2 574  461 \n",
+    "# 27 880 rows "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "df0c0bbb-4cff-4205-86e0-0393f83a4cc7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre de comptes uniques impliqués dans les transferts : 1346\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Extraire tous les comptes sortants et entrants\n",
+    "all_accounts = pd.concat([\n",
+    "    transf_compte[\"Compte sortant\"],\n",
+    "    transf_compte[\"Compte entrant\"]\n",
+    "])\n",
+    "\n",
+    "# Comptes uniques impliqués dans au moins un transfert\n",
+    "unique_accounts = all_accounts.unique()\n",
+    "\n",
+    "print(f\"Nombre de comptes uniques impliqués dans les transferts : {len(unique_accounts)}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6dacddcb-74f1-441f-adbe-83275c8f9216",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "transf_compte[\"Date\"] = pd.to_datetime(transf_compte[\"Date\"])\n",
+    "\n",
+    "#  Nombre de transferts par jour\n",
+    "transfers_per_day = transf_compte.groupby(\"Date\").size()\n",
+    "\n",
+    "plt.figure(figsize=(14,5))\n",
+    "transfers_per_day.plot(kind=\"line\")\n",
+    "plt.title(\"Nombre de transferts détectés par jour\")\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Nombre de transferts\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "be0708c4-95df-4915-82f9-a6347187bd70",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Jours anormaux (avec beaucoup de transferts) :\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "2015-01-15    26\n",
+       "2015-01-16    29\n",
+       "2015-01-26    33\n",
+       "2015-01-27    26\n",
+       "2015-01-29    32\n",
+       "              ..\n",
+       "2019-04-01    28\n",
+       "2021-01-04    26\n",
+       "2021-01-18    26\n",
+       "2021-02-08    27\n",
+       "2021-04-06    27\n",
+       "Length: 121, dtype: int64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Détection de jours anormaux (ex: > 95e percentile)\n",
+    "threshold = transfers_per_day.quantile(0.95)\n",
+    "anomalous_days = transfers_per_day[transfers_per_day > threshold]\n",
+    "print(\"Jours anormaux (avec beaucoup de transferts) :\")\n",
+    "display(anomalous_days)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "f7da5d09-7c97-4fa2-921d-886928fdf80f",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Jours anormaux (weekday + month) :\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>Date</th>\n",
+       "      <th>n_transfers</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>month</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2021-07-15</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>July</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2021-10-01</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>October</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2021-06-15</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>June</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2021-07-08</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>July</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2021-09-01</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>September</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2021-10-13</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>October</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2024-02-05</td>\n",
+       "      <td>22</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>February</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2021-08-11</td>\n",
+       "      <td>22</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>August</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2023-05-15</td>\n",
+       "      <td>22</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>May</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2025-10-13</td>\n",
+       "      <td>22</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>October</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2021-05-03</td>\n",
+       "      <td>23</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>May</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-08</td>\n",
+       "      <td>24</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>January</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2021-02-04</td>\n",
+       "      <td>25</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>February</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2021-08-05</td>\n",
+       "      <td>25</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>August</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2021-06-03</td>\n",
+       "      <td>25</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>June</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2021-01-25</td>\n",
+       "      <td>25</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>January</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2021-01-18</td>\n",
+       "      <td>26</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>January</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2021-01-04</td>\n",
+       "      <td>26</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>January</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2021-04-06</td>\n",
+       "      <td>27</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>April</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2021-02-08</td>\n",
+       "      <td>27</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>February</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Date  n_transfers    weekday      month\n",
+       "22 2021-07-15           20   Thursday       July\n",
+       "29 2021-10-01           20     Friday    October\n",
+       "19 2021-06-15           20    Tuesday       June\n",
+       "21 2021-07-08           21   Thursday       July\n",
+       "26 2021-09-01           21  Wednesday  September\n",
+       "30 2021-10-13           21  Wednesday    October\n",
+       "42 2024-02-05           22     Monday   February\n",
+       "25 2021-08-11           22  Wednesday     August\n",
+       "39 2023-05-15           22     Monday        May\n",
+       "53 2025-10-13           22     Monday    October\n",
+       "13 2021-05-03           23     Monday        May\n",
+       "1  2021-01-08           24     Friday    January\n",
+       "6  2021-02-04           25   Thursday   February\n",
+       "24 2021-08-05           25   Thursday     August\n",
+       "17 2021-06-03           25   Thursday       June\n",
+       "4  2021-01-25           25     Monday    January\n",
+       "3  2021-01-18           26     Monday    January\n",
+       "0  2021-01-04           26     Monday    January\n",
+       "11 2021-04-06           27    Tuesday      April\n",
+       "7  2021-02-08           27     Monday   February"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "transf_compte[\"Date\"] = pd.to_datetime(transf_compte[\"Date\"])\n",
+    "transf_comptee = transf_compte[transf_compte[\"Date\"].dt.year >= 2021]\n",
+    "# Nombre de transferts par jour\n",
+    "transfers_per_day = transf_comptee.groupby(\"Date\").size().rename(\"n_transfers\")\n",
+    "\n",
+    "# Détection des jours anormaux (au-dessus du 95e percentile)\n",
+    "threshold = transfers_per_day.quantile(0.95)\n",
+    "anomalous_days = transfers_per_day[transfers_per_day > threshold]\n",
+    "\n",
+    "# Ajouter weekday et month\n",
+    "anomalous_table = anomalous_days.reset_index()\n",
+    "anomalous_table[\"weekday\"] = anomalous_table[\"Date\"].dt.day_name()\n",
+    "anomalous_table[\"month\"] = anomalous_table[\"Date\"].dt.month_name()\n",
+    "\n",
+    "pd.set_option('display.max_rows', None)\n",
+    "print(\"Jours anormaux (weekday + month) :\")\n",
+    "display(anomalous_table.sort_values(\"n_transfers\").tail(20))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "1fa564f5-5844-4a1b-bdca-b392b829d734",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre total de comptes impliqués dans au moins un transfert : 1346\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Aperçu :\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>comptes_uniques</th>\n",
+       "      <th>n_comptes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-01-02</th>\n",
+       "      <td>{365261, 200002169, 406197, 365888, 365247, 41...</td>\n",
+       "      <td>16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-05</th>\n",
+       "      <td>{312478, 364999, 364765, 419848, 417937, 41928...</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-06</th>\n",
+       "      <td>{422250, 364999, 417937, 417622, 411426, 41933...</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-07</th>\n",
+       "      <td>{365364, 365377, 364999, 200001895, 200000201,...</td>\n",
+       "      <td>27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-08</th>\n",
+       "      <td>{405798, 364999, 417937, 348493, 365852, 24969...</td>\n",
+       "      <td>21</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                              comptes_uniques  n_comptes\n",
+       "Date                                                                    \n",
+       "2015-01-02  {365261, 200002169, 406197, 365888, 365247, 41...         16\n",
+       "2015-01-05  {312478, 364999, 364765, 419848, 417937, 41928...         31\n",
+       "2015-01-06  {422250, 364999, 417937, 417622, 411426, 41933...         25\n",
+       "2015-01-07  {365364, 365377, 364999, 200001895, 200000201,...         27\n",
+       "2015-01-08  {405798, 364999, 417937, 348493, 365852, 24969...         21"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#- 2) Nombre total de comptes impliqués ---------\n",
+    "\n",
+    "all_accounts = pd.concat([\n",
+    "    transf_compte[\"Compte sortant\"],\n",
+    "    transf_compte[\"Compte entrant\"]\n",
+    "]).unique()\n",
+    "\n",
+    "print(f\"Nombre total de comptes impliqués dans au moins un transfert : {len(all_accounts)}\")\n",
+    "\n",
+    "# --------- Nombre de comptes impliqués par jour ----------\n",
+    "\n",
+    "accounts_per_day = transf_compte.groupby(\"Date\").agg(\n",
+    "    comptes_uniques=(\"Compte sortant\", lambda x: set(x))  # temp\n",
+    ")\n",
+    "\n",
+    "# On ajoute aussi les comptes entrants\n",
+    "accounts_per_day[\"comptes_uniques\"] = accounts_per_day.index.map(\n",
+    "    lambda d: set(transf_compte[transf_compte[\"Date\"] == d][\"Compte sortant\"]) |\n",
+    "              set(transf_compte[transf_compte[\"Date\"] == d][\"Compte entrant\"])\n",
+    ")\n",
+    "\n",
+    "accounts_per_day[\"n_comptes\"] = accounts_per_day[\"comptes_uniques\"].apply(len)\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(14,5))\n",
+    "plt.plot(accounts_per_day.index, accounts_per_day[\"n_comptes\"], marker=\"o\")\n",
+    "plt.title(\"Nombre de comptes impliqués dans des transferts par jour\")\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Nombre de comptes uniques\")\n",
+    "plt.grid(True)\n",
+    "plt.show()\n",
+    "\n",
+    "print(\"Aperçu :\")\n",
+    "accounts_per_day.head()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c898b0c5-0a8e-4640-bc52-9490ee80e53d",
+   "metadata": {},
+   "source": [
+    "# MERGE AND ANALYSIS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce33dbf8-1c59-416a-adc4-6eb7c1ea9d8e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "df_aum2 = df_aum2.rename(columns={\n",
+    "    \"Registrar Account - ID\": \"Account_ID\",\n",
+    "    \"Product - Isin\": \"ISIN\",\n",
+    "    \"Centralisation Date\": \"Date\",\n",
+    "    \"Value - AUM €\": \"AUM_EUR\"\n",
+    "})\n",
+    "\n",
+    "df_flows2 = df_flows2.rename(columns={\n",
+    "    \"Registrar Account - ID\": \"Account_ID\",\n",
+    "    \"Product - Isin\": \"ISIN\",\n",
+    "    \"Centralisation Date\": \"Date\",\n",
+    "    \"Value € - NetFlows\": \"Flow_EUR\"\n",
+    "})\n",
+    "\n",
+    "\n",
+    "df_aum2[\"Date\"] = pd.to_datetime(df_aum2[\"Date\"])\n",
+    "df_flows2[\"Date\"] = pd.to_datetime(df_flows2[\"Date\"])\n",
+    "\n",
+    "df_aum2[\"Account_ID\"] = df_aum2[\"Account_ID\"].astype(str)\n",
+    "df_flows2[\"Account_ID\"] = df_flows2[\"Account_ID\"].astype(str)\n",
+    "\n",
+    "df_aum2[\"ISIN\"] = df_aum2[\"ISIN\"].str.upper()\n",
+    "df_flows2[\"ISIN\"] = df_flows2[\"ISIN\"].str.upper()\n",
+    "\n",
+    "\n",
+    "df_merged = pd.merge(\n",
+    "    df_aum2[[\"Account_ID\", \"ISIN\", \"Date\", \"AUM_EUR\"]],\n",
+    "    df_flows2[[\"Account_ID\", \"ISIN\", \"Date\", \"Flow_EUR\"]],\n",
+    "    on=[\"Account_ID\", \"ISIN\", \"Date\"],\n",
+    "    how=\"outer\"\n",
+    ").sort_values([\"Account_ID\", \"ISIN\", \"Date\"])\n",
+    "\n",
+    "print(\"Merged dataset:\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e5d642e-5c16-4c78-8d83-075094902670",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea14866a-1ce6-4b19-9225-d725304af8ec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 2. HISTOGRAMME DES AUM (SANS ISIN)\n",
+    "\n",
+    "# We keep the mean AUM per Account \n",
+    "aum_by_account = (\n",
+    "    df_merged.groupby(\"Account_ID\")[\"AUM_EUR\"]\n",
+    "    .mean()\n",
+    "    .dropna()\n",
+    ")\n",
+    "\n",
+    "plt.figure(figsize=(10,6))\n",
+    "plt.hist(aum_by_account, bins=50)\n",
+    "plt.xlabel(\"Mean AUM value (€)\")\n",
+    "plt.ylabel(\"Number of client accounts\")\n",
+    "plt.title(\"Distribution of client average AUM (one value per Account_ID)\")\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f13c213e-7f72-494a-bcf0-b4cd9feee55d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# 3. ANALYSE DES FLOWS POUR UN COMPTE DANS UN FONDS\n",
+    "\n",
+    "account_to_plot = \"YOUR_ACCOUNT_ID_HERE\"\n",
+    "isin_to_plot = \"YOUR_ISIN_HERE\"\n",
+    "\n",
+    "client_flows = df_merged[\n",
+    "    (df_merged[\"Account_ID\"] == account_to_plot) &\n",
+    "    (df_merged[\"ISIN\"] == isin_to_plot)\n",
+    "].sort_values(\"Date\")\n",
+    "\n",
+    "plt.figure(figsize=(12,5))\n",
+    "plt.plot(client_flows[\"Date\"], client_flows[\"Flow_EUR\"], marker=\"o\")\n",
+    "plt.axhline(0, color=\"black\", linewidth=1)\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Flow (€)\")\n",
+    "plt.title(f\"Flow movements for Account {account_to_plot}, ISIN {isin_to_plot}\")\n",
+    "plt.grid(True)\n",
+    "plt.show()\n",
+    "\n",
+    "###############################################################################\n",
+    "# 4. ANALYSE MENSUELLE DES FLOWS (ENTRANTS / SORTANTS)\n",
+    "###############################################################################\n",
+    "\n",
+    "df_merged[\"YearMonth\"] = df_merged[\"Date\"].dt.to_period(\"M\")\n",
+    "\n",
+    "flows_monthly = df_merged.groupby(\"YearMonth\").agg(\n",
+    "    n_positive_flows=(\"Flow_EUR\", lambda x: (x > 0).sum()),\n",
+    "    n_negative_flows=(\"Flow_EUR\", lambda x: (x < 0).sum()),\n",
+    ")\n",
+    "\n",
+    "print(\"Monthly flow summary:\")\n",
+    "print(flows_monthly.head())\n",
+    "\n",
+    "# ---- Plot bar chart ----\n",
+    "flows_monthly.index = flows_monthly.index.astype(str)\n",
+    "\n",
+    "plt.figure(figsize=(14,6))\n",
+    "plt.bar(flows_monthly.index, flows_monthly[\"n_positive_flows\"], label=\"Positive flows (inflows)\", alpha=0.7)\n",
+    "plt.bar(flows_monthly.index, flows_monthly[\"n_negative_flows\"], label=\"Negative flows (outflows)\", alpha=0.7)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.xlabel(\"Year-Month\")\n",
+    "plt.ylabel(\"Number of accounts with flows\")\n",
+    "plt.title(\"Monthly number of accounts with inflows vs outflows\")\n",
+    "plt.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}