generated from dhairya/scenario_template
System save at 23/05/2025 19:01 by user_client2024
This commit is contained in:
user_client2024
parent
a73e5758e1
commit
0ecf48e442
@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
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"metadata": {
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"tags": []
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@ -94,181 +94,104 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 6,
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"id": "b6c85de2-6a47-4109-8885-c138c289ec25",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# import pandas as pd\n",
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"\n",
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"# query = \"\"\"\n",
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"# SELECT \n",
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"# t.transaction_id,\n",
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"# t.transaction_date,\n",
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"# t.transaction_amount,\n",
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"# t.transaction_desc,\n",
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"# t.benef_account_number,\n",
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"\n",
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"# -- Account data\n",
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"# a.account_number,\n",
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"# a.customer_number AS acc_customer_number,\n",
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"# a.account_type,\n",
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"# a.branch_code,\n",
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"\n",
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"# -- Party data\n",
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"# p.customer_number AS party_customer_number,\n",
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"# p.customer_name,\n",
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"# p.date_of_birth,\n",
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"# p.nationality,\n",
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"# p.business_segment,\n",
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"# CASE\n",
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"# WHEN p.risk_classification = 1 THEN 'Low Risk'\n",
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"# WHEN p.risk_classification = 2 THEN 'Medium Risk'\n",
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"# WHEN p.risk_classification = 3 THEN 'High Risk'\n",
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"# ELSE 'Unknown Risk'\n",
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"# END AS risk_level,\n",
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"\n",
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"# -- Alert data\n",
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"# COALESCE(al.sar_flag, 'N') AS sar_flag\n",
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"\n",
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"# FROM {trans_data} t\n",
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"\n",
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"# -- Join with account data on beneficiary account\n",
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"# LEFT JOIN {acc_data} a\n",
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"# ON t.benef_account_number = a.account_number\n",
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"\n",
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"# -- Join with party/customer data using account's customer number\n",
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"# LEFT JOIN {cust_data} p\n",
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"# ON a.customer_number = p.customer_number\n",
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"\n",
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"# -- Join with alert data using party's customer number\n",
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"# LEFT JOIN {alert_data} al\n",
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"# ON p.customer_number = al.customer_number\n",
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"\n",
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"# WHERE a.account_number IS NOT NULL\n",
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"# limit 100\n",
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"# \"\"\"\n",
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"\n",
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"# from tms_data_interface import SQLQueryInterface\n",
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"\n",
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"# class Scenario:\n",
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"# seq = SQLQueryInterface(schema=\"transactionschema\")\n",
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"\n",
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"# def logic(self, **kwargs):\n",
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"# row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
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"# cust_data=\"customer_data_v1\",\n",
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"# acc_data=\"account_data_v1\",\n",
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"# alert_data=\"alert_data_v1\")\n",
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"# )\n",
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"# cols = [\n",
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"# \"transaction_id\",\n",
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"# \"transaction_date\",\n",
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"# \"transaction_amount\",\n",
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"# \"transaction_desc\",\n",
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"# \"benef_account_number\",\n",
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"# \"account_number\",\n",
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"# \"acc_customer_number\",\n",
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"# \"account_type\",\n",
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"# \"branch_code\",\n",
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"# \"party_customer_number\",\n",
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"# \"customer_name\",\n",
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"# \"date_of_birth\",\n",
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"# \"nationality\",\n",
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"# \"business_segment\",\n",
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"# \"risk_level\",\n",
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"# \"sar_flag\"\n",
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"# ]\n",
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"# df = pd.DataFrame(row_list, columns = cols)\n",
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"# return df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "1f20337b-8116-47e5-8743-1ba41e2df819",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Focal_id</th>\n",
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" <th>Cash_deposit_total</th>\n",
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" <th>Cash_deposit_count</th>\n",
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" <th>Segment</th>\n",
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" <th>Risk</th>\n",
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" <th>SAR_FLAG</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>PN469304</td>\n",
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" <td>8049952.0</td>\n",
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" <td>141</td>\n",
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" <td>Mass Market</td>\n",
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" <td>High Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>PN605743</td>\n",
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" <td>9766101.0</td>\n",
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" <td>175</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>PN399215</td>\n",
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" <td>8469943.0</td>\n",
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" <td>164</td>\n",
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" <td>Mass Market</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>PN175020</td>\n",
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" <td>17724959.0</td>\n",
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" <td>313</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>PN345085</td>\n",
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" <td>7518628.0</td>\n",
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" <td>124</td>\n",
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" <td>Others</td>\n",
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" <td>Medium Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9005</th>\n",
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" <td>PN660329</td>\n",
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" <td>8528178.0</td>\n",
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" <td>141</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9006</th>\n",
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" <td>PN336833</td>\n",
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" <td>8475036.0</td>\n",
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" <td>150</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9007</th>\n",
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" <td>PN428534</td>\n",
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" <td>7871170.0</td>\n",
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" <td>129</td>\n",
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" <td>Priority Banking</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9008</th>\n",
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" <td>PN101660</td>\n",
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" <td>8450309.0</td>\n",
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" <td>142</td>\n",
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" <td>Mass Market</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9009</th>\n",
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" <td>PN198641</td>\n",
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" <td>8690226.0</td>\n",
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" <td>166</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>9010 rows × 6 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" Focal_id Cash_deposit_total Cash_deposit_count Segment \\\n",
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"0 PN469304 8049952.0 141 Mass Market \n",
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"1 PN605743 9766101.0 175 Others \n",
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"2 PN399215 8469943.0 164 Mass Market \n",
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"3 PN175020 17724959.0 313 Others \n",
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"4 PN345085 7518628.0 124 Others \n",
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"... ... ... ... ... \n",
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"9005 PN660329 8528178.0 141 Others \n",
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"9006 PN336833 8475036.0 150 Others \n",
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"9007 PN428534 7871170.0 129 Priority Banking \n",
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"9008 PN101660 8450309.0 142 Mass Market \n",
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"9009 PN198641 8690226.0 166 Others \n",
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"\n",
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" Risk SAR_FLAG \n",
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"0 High Risk N \n",
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"1 Low Risk N \n",
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"2 Low Risk N \n",
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"3 Low Risk N \n",
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"4 Medium Risk N \n",
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"... ... ... \n",
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"9005 Low Risk N \n",
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"9006 Low Risk N \n",
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"9007 Low Risk N \n",
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"9008 Low Risk N \n",
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"9009 Low Risk N \n",
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"\n",
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"[9010 rows x 6 columns]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"# sen = Scenario()\n",
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"# sen.logic()"
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267
main.ipynb
267
main.ipynb
@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
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"metadata": {
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"tags": []
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@ -94,181 +94,104 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 6,
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"id": "b6c85de2-6a47-4109-8885-c138c289ec25",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# import pandas as pd\n",
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"\n",
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"# query = \"\"\"\n",
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"# SELECT \n",
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"# t.transaction_id,\n",
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"# t.transaction_date,\n",
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"# t.transaction_amount,\n",
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"# t.transaction_desc,\n",
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"# t.benef_account_number,\n",
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"\n",
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"# -- Account data\n",
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"# a.account_number,\n",
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"# a.customer_number AS acc_customer_number,\n",
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"# a.account_type,\n",
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"# a.branch_code,\n",
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"\n",
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"# -- Party data\n",
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"# p.customer_number AS party_customer_number,\n",
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"# p.customer_name,\n",
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"# p.date_of_birth,\n",
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"# p.nationality,\n",
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"# p.business_segment,\n",
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"# CASE\n",
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"# WHEN p.risk_classification = 1 THEN 'Low Risk'\n",
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"# WHEN p.risk_classification = 2 THEN 'Medium Risk'\n",
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"# WHEN p.risk_classification = 3 THEN 'High Risk'\n",
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"# ELSE 'Unknown Risk'\n",
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"# END AS risk_level,\n",
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"\n",
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"# -- Alert data\n",
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"# COALESCE(al.sar_flag, 'N') AS sar_flag\n",
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"\n",
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"# FROM {trans_data} t\n",
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"\n",
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"# -- Join with account data on beneficiary account\n",
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"# LEFT JOIN {acc_data} a\n",
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"# ON t.benef_account_number = a.account_number\n",
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"\n",
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"# -- Join with party/customer data using account's customer number\n",
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"# LEFT JOIN {cust_data} p\n",
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"# ON a.customer_number = p.customer_number\n",
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"\n",
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"# -- Join with alert data using party's customer number\n",
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"# LEFT JOIN {alert_data} al\n",
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"# ON p.customer_number = al.customer_number\n",
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"\n",
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"# WHERE a.account_number IS NOT NULL\n",
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"# limit 100\n",
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"# \"\"\"\n",
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"\n",
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"# from tms_data_interface import SQLQueryInterface\n",
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"\n",
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"# class Scenario:\n",
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"# seq = SQLQueryInterface(schema=\"transactionschema\")\n",
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"\n",
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"# def logic(self, **kwargs):\n",
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"# row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
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"# cust_data=\"customer_data_v1\",\n",
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"# acc_data=\"account_data_v1\",\n",
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"# alert_data=\"alert_data_v1\")\n",
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"# )\n",
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"# cols = [\n",
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"# \"transaction_id\",\n",
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"# \"transaction_date\",\n",
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"# \"transaction_amount\",\n",
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"# \"transaction_desc\",\n",
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"# \"benef_account_number\",\n",
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"# \"account_number\",\n",
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"# \"acc_customer_number\",\n",
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"# \"account_type\",\n",
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"# \"branch_code\",\n",
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"# \"party_customer_number\",\n",
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"# \"customer_name\",\n",
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"# \"date_of_birth\",\n",
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"# \"nationality\",\n",
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"# \"business_segment\",\n",
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"# \"risk_level\",\n",
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"# \"sar_flag\"\n",
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"# ]\n",
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"# df = pd.DataFrame(row_list, columns = cols)\n",
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"# return df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "1f20337b-8116-47e5-8743-1ba41e2df819",
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||||
"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Focal_id</th>\n",
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" <th>Cash_deposit_total</th>\n",
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" <th>Cash_deposit_count</th>\n",
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" <th>Segment</th>\n",
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" <th>Risk</th>\n",
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" <th>SAR_FLAG</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>PN469304</td>\n",
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" <td>8049952.0</td>\n",
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" <td>141</td>\n",
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" <td>Mass Market</td>\n",
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" <td>High Risk</td>\n",
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" <td>N</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
|
||||
" <td>PN605743</td>\n",
|
||||
" <td>9766101.0</td>\n",
|
||||
" <td>175</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>PN399215</td>\n",
|
||||
" <td>8469943.0</td>\n",
|
||||
" <td>164</td>\n",
|
||||
" <td>Mass Market</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>PN175020</td>\n",
|
||||
" <td>17724959.0</td>\n",
|
||||
" <td>313</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>PN345085</td>\n",
|
||||
" <td>7518628.0</td>\n",
|
||||
" <td>124</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Medium Risk</td>\n",
|
||||
" <td>N</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>9005</th>\n",
|
||||
" <td>PN660329</td>\n",
|
||||
" <td>8528178.0</td>\n",
|
||||
" <td>141</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9006</th>\n",
|
||||
" <td>PN336833</td>\n",
|
||||
" <td>8475036.0</td>\n",
|
||||
" <td>150</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9007</th>\n",
|
||||
" <td>PN428534</td>\n",
|
||||
" <td>7871170.0</td>\n",
|
||||
" <td>129</td>\n",
|
||||
" <td>Priority Banking</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9008</th>\n",
|
||||
" <td>PN101660</td>\n",
|
||||
" <td>8450309.0</td>\n",
|
||||
" <td>142</td>\n",
|
||||
" <td>Mass Market</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9009</th>\n",
|
||||
" <td>PN198641</td>\n",
|
||||
" <td>8690226.0</td>\n",
|
||||
" <td>166</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>9010 rows × 6 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Focal_id Cash_deposit_total Cash_deposit_count Segment \\\n",
|
||||
"0 PN469304 8049952.0 141 Mass Market \n",
|
||||
"1 PN605743 9766101.0 175 Others \n",
|
||||
"2 PN399215 8469943.0 164 Mass Market \n",
|
||||
"3 PN175020 17724959.0 313 Others \n",
|
||||
"4 PN345085 7518628.0 124 Others \n",
|
||||
"... ... ... ... ... \n",
|
||||
"9005 PN660329 8528178.0 141 Others \n",
|
||||
"9006 PN336833 8475036.0 150 Others \n",
|
||||
"9007 PN428534 7871170.0 129 Priority Banking \n",
|
||||
"9008 PN101660 8450309.0 142 Mass Market \n",
|
||||
"9009 PN198641 8690226.0 166 Others \n",
|
||||
"\n",
|
||||
" Risk SAR_FLAG \n",
|
||||
"0 High Risk N \n",
|
||||
"1 Low Risk N \n",
|
||||
"2 Low Risk N \n",
|
||||
"3 Low Risk N \n",
|
||||
"4 Medium Risk N \n",
|
||||
"... ... ... \n",
|
||||
"9005 Low Risk N \n",
|
||||
"9006 Low Risk N \n",
|
||||
"9007 Low Risk N \n",
|
||||
"9008 Low Risk N \n",
|
||||
"9009 Low Risk N \n",
|
||||
"\n",
|
||||
"[9010 rows x 6 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# sen = Scenario()\n",
|
||||
"# sen.logic()"
|
||||
|
||||
90
main.py
90
main.py
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# coding: utf-8
|
||||
|
||||
# In[2]:
|
||||
# In[3]:
|
||||
|
||||
|
||||
import pandas as pd
|
||||
@ -87,7 +87,93 @@ class Scenario:
|
||||
return df
|
||||
|
||||
|
||||
# In[3]:
|
||||
# In[6]:
|
||||
|
||||
|
||||
# import pandas as pd
|
||||
|
||||
# query = """
|
||||
# SELECT
|
||||
# t.transaction_id,
|
||||
# t.transaction_date,
|
||||
# t.transaction_amount,
|
||||
# t.transaction_desc,
|
||||
# t.benef_account_number,
|
||||
|
||||
# -- Account data
|
||||
# a.account_number,
|
||||
# a.customer_number AS acc_customer_number,
|
||||
# a.account_type,
|
||||
# a.branch_code,
|
||||
|
||||
# -- Party data
|
||||
# p.customer_number AS party_customer_number,
|
||||
# p.customer_name,
|
||||
# p.date_of_birth,
|
||||
# p.nationality,
|
||||
# p.business_segment,
|
||||
# CASE
|
||||
# WHEN p.risk_classification = 1 THEN 'Low Risk'
|
||||
# WHEN p.risk_classification = 2 THEN 'Medium Risk'
|
||||
# WHEN p.risk_classification = 3 THEN 'High Risk'
|
||||
# ELSE 'Unknown Risk'
|
||||
# END AS risk_level,
|
||||
|
||||
# -- Alert data
|
||||
# COALESCE(al.sar_flag, 'N') AS sar_flag
|
||||
|
||||
# FROM {trans_data} t
|
||||
|
||||
# -- Join with account data on beneficiary account
|
||||
# LEFT JOIN {acc_data} a
|
||||
# ON t.benef_account_number = a.account_number
|
||||
|
||||
# -- Join with party/customer data using account's customer number
|
||||
# LEFT JOIN {cust_data} p
|
||||
# ON a.customer_number = p.customer_number
|
||||
|
||||
# -- Join with alert data using party's customer number
|
||||
# LEFT JOIN {alert_data} al
|
||||
# ON p.customer_number = al.customer_number
|
||||
|
||||
# WHERE a.account_number IS NOT NULL
|
||||
# limit 100
|
||||
# """
|
||||
|
||||
# from tms_data_interface import SQLQueryInterface
|
||||
|
||||
# class Scenario:
|
||||
# seq = SQLQueryInterface(schema="transactionschema")
|
||||
|
||||
# def logic(self, **kwargs):
|
||||
# row_list = self.seq.execute_raw(query.format(trans_data="transaction10m",
|
||||
# cust_data="customer_data_v1",
|
||||
# acc_data="account_data_v1",
|
||||
# alert_data="alert_data_v1")
|
||||
# )
|
||||
# cols = [
|
||||
# "transaction_id",
|
||||
# "transaction_date",
|
||||
# "transaction_amount",
|
||||
# "transaction_desc",
|
||||
# "benef_account_number",
|
||||
# "account_number",
|
||||
# "acc_customer_number",
|
||||
# "account_type",
|
||||
# "branch_code",
|
||||
# "party_customer_number",
|
||||
# "customer_name",
|
||||
# "date_of_birth",
|
||||
# "nationality",
|
||||
# "business_segment",
|
||||
# "risk_level",
|
||||
# "sar_flag"
|
||||
# ]
|
||||
# df = pd.DataFrame(row_list, columns = cols)
|
||||
# return df
|
||||
|
||||
|
||||
# In[5]:
|
||||
|
||||
|
||||
# sen = Scenario()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user