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Project_Carmignac/Migration.ipynb
lmoraine-ensae 56c4bd8a2f modification
2026-01-30 15:02:14 +00:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "a9037fe3-296e-4a21-b1e5-4763090ef36f",
"metadata": {},
"source": [
"# Migration de comptes"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "fe2bc65b-0c8a-4335-83e9-f339c82f33a1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fichiers Flows : ['projet-bdc-data/carmignac/Flows ENSAE V1 -20251027.csv', 'projet-bdc-data/carmignac/Flows ENSAE V2 -20251105.csv']\n",
"Fichiers AUM : ['projet-bdc-data/carmignac/AUM ENSAE V1 -20251027.csv', 'projet-bdc-data/carmignac/AUM ENSAE V2 -20251105.csv']\n"
]
}
],
"source": [
"# Import des données\n",
"\n",
"import os\n",
"import s3fs\n",
"import pandas as pd\n",
"\n",
"s3_ENDPOINT_URL = \"https://\" + os.environ[\"AWS_S3_ENDPOINT\"]\n",
"\n",
"fs = s3fs.S3FileSystem(client_kwargs={'endpoint_url': s3_ENDPOINT_URL})\n",
"\n",
"BUCKET = \"projet-bdc-data\"\n",
"carmignac_path = \"projet-bdc-data/carmignac\"\n",
"\n",
"# Liste des fichiers FLOWS\n",
"all_files = fs.ls(carmignac_path)\n",
"flows_files = [f for f in all_files if \"Flows\" in f and f.endswith(\".csv\")]\n",
"print(\"Fichiers Flows :\", flows_files)\n",
"\n",
"# Lire tous les fichiers dans un dictionnaire\n",
"flows_data = {}\n",
"for file_path in flows_files:\n",
" with fs.open(file_path, 'r') as f:\n",
" df = pd.read_csv(f, sep=';',low_memory=False)\n",
" flows_data[os.path.basename(file_path)] = df\n",
"\n",
"\n",
"# Liste des fichiers AUM\n",
"all_files = fs.ls(carmignac_path)\n",
"aum_files = [f for f in all_files if \"AUM\" in f and f.endswith(\".csv\")]\n",
"print(\"Fichiers AUM :\", aum_files)\n",
"\n",
"# Lire tous les fichiers dans un dictionnaire\n",
"aum_data = {}\n",
"for file_path in aum_files:\n",
" with fs.open(file_path, 'r') as f:\n",
" df = pd.read_csv(f, sep=';',low_memory=False)\n",
" aum_data[os.path.basename(file_path)] = df\n",
"\n",
"df = aum_data['AUM ENSAE V2 -20251105.csv']\n",
"dg = flows_data['Flows ENSAE V2 -20251105.csv']"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "e5739d0e-e4e2-473f-8561-89278a8105a3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" vertical-align: middle;\n",
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"\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>old_account</th>\n",
" <th>new_account</th>\n",
" <th>value</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2019-12-31</td>\n",
" <td>406533</td>\n",
" <td>200127202</td>\n",
" <td>7.184443e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2016-06-30</td>\n",
" <td>402699</td>\n",
" <td>200038850</td>\n",
" <td>2.237343e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-07-31</td>\n",
" <td>402703</td>\n",
" <td>200013353</td>\n",
" <td>8.888675e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2019-12-31</td>\n",
" <td>404813</td>\n",
" <td>200127636</td>\n",
" <td>1.608203e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-03-31</td>\n",
" <td>406311</td>\n",
" <td>200001401</td>\n",
" <td>6.326882e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5516</th>\n",
" <td>2019-12-31</td>\n",
" <td>200093279</td>\n",
" <td>200127383</td>\n",
" <td>1.518258e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5517</th>\n",
" <td>2016-11-30</td>\n",
" <td>200040897</td>\n",
" <td>200054018</td>\n",
" <td>4.775338e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5519</th>\n",
" <td>2016-08-31</td>\n",
" <td>200042389</td>\n",
" <td>200044787</td>\n",
" <td>2.668920e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5521</th>\n",
" <td>2016-11-30</td>\n",
" <td>200048502</td>\n",
" <td>200054019</td>\n",
" <td>3.549803e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5524</th>\n",
" <td>2018-12-31</td>\n",
" <td>200090792</td>\n",
" <td>200117574</td>\n",
" <td>2.123958e+05</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>548 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" date old_account new_account value\n",
"0 2019-12-31 406533 200127202 7.184443e+05\n",
"3 2016-06-30 402699 200038850 2.237343e+05\n",
"4 2015-07-31 402703 200013353 8.888675e+04\n",
"5 2019-12-31 404813 200127636 1.608203e+05\n",
"7 2015-03-31 406311 200001401 6.326882e+04\n",
"... ... ... ... ...\n",
"5516 2019-12-31 200093279 200127383 1.518258e+07\n",
"5517 2016-11-30 200040897 200054018 4.775338e+04\n",
"5519 2016-08-31 200042389 200044787 2.668920e+04\n",
"5521 2016-11-30 200048502 200054019 3.549803e+04\n",
"5524 2018-12-31 200090792 200117574 2.123958e+05\n",
"\n",
"[548 rows x 4 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 548 connexions trouvées\n",
"from detection_rupture import detect_ruptures, check_isin_continuity\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"\n",
"ruptures_df = detect_ruptures(df, 0.05)\n",
"ruptures_df"
]
},
{
"cell_type": "markdown",
"id": "27bb5cd0-8900-408c-8d4f-2a0692b13179",
"metadata": {},
"source": [
"## Ruptures par date"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "752f5ee3-7c4d-4b8d-913d-d8ffcc32fe17",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1000x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Copier pour éviter les effets de bord\n",
"df_plot = ruptures_df.copy()\n",
"df_plot['date'] = pd.to_datetime(df_plot['date'])\n",
"\n",
"# Compter les ruptures par date\n",
"counts = df_plot.groupby('date').size().reset_index(name='rupture_count')\n",
"\n",
"plt.figure(figsize=(10, 5))\n",
"plt.plot(counts['date'], counts['rupture_count'], marker='.')\n",
"plt.xlabel(\"Date\")\n",
"plt.ylabel(\"Number of account migrations\")\n",
"plt.title(\"Number of migrations detected by date\")\n",
"plt.grid(True)\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "9fd1c550-96d5-46c7-8a01-903d4f485502",
"metadata": {},
"source": [
"## Vérification de la continuité par ISIN"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "f55d53a6-39fb-4d12-bfdc-1ad0c9ff5fd5",
"metadata": {},
"outputs": [],
"source": [
"result_ISIN = check_isin_continuity(df, ruptures_df, tol=0.10)\n",
"result_ISIN_false = result_ISIN[result_ISIN['check'] == False]\n",
"results_ISIN_unique = result_ISIN_false.iloc[:, :3].drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "02a134ce-944b-46d4-8921-747baa6e8e2b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"105"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(results_ISIN_unique)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "c5f692e7-0fa6-470e-91c5-a7901b7c3eb7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" 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>old_account</th>\n",
" <th>new_account</th>\n",
" <th>value</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2019-12-31</td>\n",
" <td>406533</td>\n",
" <td>200127202</td>\n",
" <td>7.184443e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2016-06-30</td>\n",
" <td>402699</td>\n",
" <td>200038850</td>\n",
" <td>2.237343e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-07-31</td>\n",
" <td>402703</td>\n",
" <td>200013353</td>\n",
" <td>8.888675e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2019-12-31</td>\n",
" <td>404813</td>\n",
" <td>200127636</td>\n",
" <td>1.608203e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-03-31</td>\n",
" <td>406311</td>\n",
" <td>200001401</td>\n",
" <td>6.326882e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>438</th>\n",
" <td>2019-12-31</td>\n",
" <td>200093279</td>\n",
" <td>200127383</td>\n",
" <td>1.518258e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>439</th>\n",
" <td>2016-11-30</td>\n",
" <td>200040897</td>\n",
" <td>200054018</td>\n",
" <td>4.775338e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>440</th>\n",
" <td>2016-08-31</td>\n",
" <td>200042389</td>\n",
" <td>200044787</td>\n",
" <td>2.668920e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>441</th>\n",
" <td>2016-11-30</td>\n",
" <td>200048502</td>\n",
" <td>200054019</td>\n",
" <td>3.549803e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>442</th>\n",
" <td>2018-12-31</td>\n",
" <td>200090792</td>\n",
" <td>200117574</td>\n",
" <td>2.123958e+05</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>443 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" date old_account new_account value\n",
"0 2019-12-31 406533 200127202 7.184443e+05\n",
"1 2016-06-30 402699 200038850 2.237343e+05\n",
"2 2015-07-31 402703 200013353 8.888675e+04\n",
"3 2019-12-31 404813 200127636 1.608203e+05\n",
"4 2015-03-31 406311 200001401 6.326882e+04\n",
".. ... ... ... ...\n",
"438 2019-12-31 200093279 200127383 1.518258e+07\n",
"439 2016-11-30 200040897 200054018 4.775338e+04\n",
"440 2016-08-31 200042389 200044787 2.668920e+04\n",
"441 2016-11-30 200048502 200054019 3.549803e+04\n",
"442 2018-12-31 200090792 200117574 2.123958e+05\n",
"\n",
"[443 rows x 4 columns]"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Colonnes communes pour comparer\n",
"cols = ['date', 'old_account', 'new_account']\n",
"\n",
"# Merge avec indicateur\n",
"rupture_filtered = ruptures_df.merge(\n",
" results_ISIN_unique[cols],\n",
" on=cols,\n",
" how='left',\n",
" indicator=True\n",
")\n",
"\n",
"# Ne garder que les lignes qui ne sont pas dans results_ISIN_unique\n",
"rupture_filtered = rupture_filtered[rupture_filtered['_merge'] == 'left_only'].drop(columns=['_merge'])\n",
"\n",
"rupture_filtered.reset_index(drop=True, inplace=True)\n",
"\n",
"rupture_filtered\n",
"\n",
"# 443 connexions retenues"
]
},
{
"cell_type": "markdown",
"id": "207c6df5-1b0a-4c06-9cd0-848c958db371",
"metadata": {},
"source": [
"## Prise en compte des migrations avant le clustering"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "185fd578-bbab-4fe7-be7d-33e259577eb2",
"metadata": {},
"outputs": [
{
"data": {
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" 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",
" <th>account_clustered</th>\n",
" <th>Account_Clustered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>003</td>\n",
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" <td>NO</td>\n",
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" <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",
" <td>200000647</td>\n",
" <td>200000647</td>\n",
" </tr>\n",
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" <th>2</th>\n",
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" <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",
" <td>200000647</td>\n",
" <td>200000647</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",
" <td>200000647</td>\n",
" <td>200000647</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",
" <td>200000647</td>\n",
" <td>200000647</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",
" </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",
" <td>Private Client</td>\n",
" <td>Private Client</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",
" <td>Private Client</td>\n",
" <td>Private Client</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",
" <td>Private Client</td>\n",
" <td>Private Client</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",
" <td>Private Client</td>\n",
" <td>Private Client</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",
" <td>Private Client</td>\n",
" <td>Private Client</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4880297 rows × 20 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 € account_clustered \\\n",
"0 35.368 2.464867e+04 2.464867e+04 200000647 \n",
"1 35.368 2.241306e+04 2.241306e+04 200000647 \n",
"2 35.368 2.205124e+04 2.205124e+04 200000647 \n",
"3 35.368 2.162612e+04 2.162612e+04 200000647 \n",
"4 35.368 2.248945e+04 2.248945e+04 200000647 \n",
"... ... ... ... ... \n",
"4880292 26801.000 2.740670e+06 2.740670e+06 Private Client \n",
"4880293 3099.000 3.122862e+05 3.122862e+05 Private Client \n",
"4880294 3099.000 3.184222e+05 3.184222e+05 Private Client \n",
"4880295 2835.000 2.976183e+05 2.976183e+05 Private Client \n",
"4880296 2916.394 2.874106e+05 2.874106e+05 Private Client \n",
"\n",
" Account_Clustered \n",
"0 200000647 \n",
"1 200000647 \n",
"2 200000647 \n",
"3 200000647 \n",
"4 200000647 \n",
"... ... \n",
"4880292 Private Client \n",
"4880293 Private Client \n",
"4880294 Private Client \n",
"4880295 Private Client \n",
"4880296 Private Client \n",
"\n",
"[4880297 rows x 20 columns]"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ajout d'une colonne Account_Clustered correspondant à l'id du compte, en tenant compte des migrations détectées\n",
"\n",
"# Trier les connexions par date décroissante : plus récentes en premier\n",
"rupture_sorted = rupture_filtered.sort_values('date', ascending=False)\n",
"\n",
"# fusion des connexions\n",
"df['Account_Clustered'] = df['Registrar Account - ID']\n",
"\n",
"# Pour chaque connexion\n",
"for _, row in rupture_sorted.iterrows():\n",
" old = row['old_account']\n",
" new = row['new_account']\n",
" df.loc[df['Account_Clustered'] == new, 'Account_Clustered'] = old\n",
"\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "27f12c31-08e1-4384-9129-4679d6ebe0ca",
"metadata": {},
"outputs": [],
"source": [
"def evolution_compte(df, id1, id = 'Registrar Account - ID'):\n",
" def prepare_df(idt):\n",
" df_id = df[df[id] == idt].copy()\n",
" df_id['Centralisation Date'] = pd.to_datetime(df_id['Centralisation Date'])\n",
" df_agg = (\n",
" df_id\n",
" .groupby('Centralisation Date')['Quantity - AUM']\n",
" .sum()\n",
" .reset_index()\n",
" .sort_values('Centralisation Date')\n",
" )\n",
" return df_agg\n",
"\n",
" df1 = prepare_df(id1)\n",
"\n",
" plt.figure(figsize=(12, 6))\n",
"\n",
" # Courbe du compte\n",
" plt.plot(df1['Centralisation Date'], df1['Quantity - AUM'],\n",
" marker='.', linestyle='-', label=f'Account {id1}')\n",
"\n",
" plt.title(f\"Évolution AUM pour le compte {id1}\")\n",
" plt.xlabel(\"Date\")\n",
" plt.ylabel(\"Quantity - AUM\")\n",
" plt.grid(True)\n",
" plt.legend()\n",
" plt.tight_layout()\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "4b952bc5-e823-4276-8066-65dfa5839047",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"evolution_compte(df, '406169')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "ce811c95-698d-467a-b63a-6e798cd1c02b",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"evolution_compte(df, '406169', id = 'Account_Clustered')"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "d507fb4c-4de5-481f-9cd0-1432298564b8",
"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>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",
" <th>Account_Clustered</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>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",
" <td>406533</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>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",
" <td>406533</td>\n",
" </tr>\n",
" <tr>\n",
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" <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>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",
" <td>406533</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>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",
" <td>406533</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>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",
" <td>406533</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>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",
" <td>Private Client</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>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",
" <td>Private Client</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>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",
" <td>Private Client</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>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",
" <td>Private Client</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>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",
" <td>Private Client</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2574461 rows × 25 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 ? ... \\\n",
"0 SICAV NO ... \n",
"1 FCP NO ... \n",
"2 FCP NO ... \n",
"3 FCP NO ... \n",
"4 FCP NO ... \n",
"... ... ... ... \n",
"2574456 FCP NO ... \n",
"2574457 FCP NO ... \n",
"2574458 FCP NO ... \n",
"2574459 FCP NO ... \n",
"2574460 SICAV NO ... \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 Value Ccy - NetFlows \\\n",
"0 280983.00 0.00 280983.00 \n",
"1 99985.13 0.00 99985.13 \n",
"2 0.00 -9384.76 -9384.76 \n",
"3 0.00 -25227.40 -25227.40 \n",
"4 0.00 -563775.76 -563775.76 \n",
"... ... ... ... \n",
"2574456 0.00 -34294.40 -34294.40 \n",
"2574457 564028.07 0.00 564028.07 \n",
"2574458 7603.66 0.00 7603.66 \n",
"2574459 0.00 -754696.80 -754696.80 \n",
"2574460 358385.55 0.00 358385.55 \n",
"\n",
" Value € - Subscription Value € - Redemption Value € - NetFlows \\\n",
"0 280983.00 0.00 280983.00 \n",
"1 99985.13 0.00 99985.13 \n",
"2 0.00 -9384.76 -9384.76 \n",
"3 0.00 -25227.40 -25227.40 \n",
"4 0.00 -563775.76 -563775.76 \n",
"... ... ... ... \n",
"2574456 0.00 -34294.40 -34294.40 \n",
"2574457 564028.07 0.00 564028.07 \n",
"2574458 7603.66 0.00 7603.66 \n",
"2574459 0.00 -754696.80 -754696.80 \n",
"2574460 358385.55 0.00 358385.55 \n",
"\n",
" Account_Clustered \n",
"0 406533 \n",
"1 406533 \n",
"2 406533 \n",
"3 406533 \n",
"4 406533 \n",
"... ... \n",
"2574456 Private Client \n",
"2574457 Private Client \n",
"2574458 Private Client \n",
"2574459 Private Client \n",
"2574460 Private Client \n",
"\n",
"[2574461 rows x 25 columns]"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Flux\n",
"\n",
"# fusion des connexions\n",
"dg['Account_Clustered'] = dg['Registrar Account - ID']\n",
"\n",
"# Pour chaque connexion\n",
"for _, row in rupture_sorted.iterrows():\n",
" old = row['old_account']\n",
" new = row['new_account']\n",
" dg.loc[dg['Account_Clustered'] == new, 'Account_Clustered'] = old\n",
"\n",
"dg"
]
}
],
"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": "3.13.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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