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System save at 07/11/2024 15:25 by user_client2024

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user_client2024 2024-11-07 09:55:58 +00:00
parent 2b6b23b4a6
commit 0d638798e8
3 changed files with 519 additions and 33 deletions
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188
.ipynb_checkpoints/main-checkpoint.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "77134554-e1dc-4e5b-aaa2-bb432789aa01",
"metadata": {},
"outputs": [],
"source": [
"from tms_data_interface import SQLQueryInterface\n",
"seq = SQLQueryInterface(schema=\"transactionschema\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9a13f2ec-d02f-4151-9d9a-17edd4f29063",
"metadata": {},
"outputs": [],
"source": [
"seq.execute_raw(\"show tables\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "32c443d5-c51f-425c-be6f-bcd8c9908ef4",
"metadata": {},
"outputs": [],
"source": [
"query = \"\"\"\n",
" select final.CUSTOMER_NUMBER_main as Focal_id,\n",
" final.Credit_transaction_amount,\n",
" final.Total_no_of_credit_transactions,\n",
" final.Debit_transaction_amount,\n",
" final.Total_no_of_debit_transactions,\n",
" final.Wash_Ratio,\n",
" final.SEGMENT,\n",
" final.RISK,\n",
" final.SAR_FLAG\n",
" from \n",
" (\n",
" (\n",
" select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n",
" subquery.Credit_transaction_amount,\n",
" subquery.Total_no_of_credit_transactions,\n",
" case\n",
" when subquery.Debit_transaction_amount is NULL then 0\n",
" else Debit_transaction_amount\n",
" end as Debit_transaction_amount,\n",
" case\n",
" when subquery.Total_no_of_debit_transactions is NULL then 0\n",
" else Total_no_of_debit_transactions\n",
" end as Total_no_of_debit_transactions,\n",
" case\n",
" when subquery.Debit_transaction_amount = 0\n",
" or subquery.Debit_transaction_amount is NULL then 0\n",
" else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount\n",
" end as Wash_Ratio\n",
" from \n",
" (\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_1, \n",
" sum(transaction_amount) as Credit_transaction_amount, \n",
" count(*) as Total_no_of_credit_transactions\n",
" from \n",
" (\n",
" select * \n",
" from {trans_data} as trans_table left join {acc_data} as acc_table\n",
" on trans_table.benef_account_number = acc_table.account_number\n",
" )\n",
" where account_number not in ('None')\n",
" group by 1\n",
" ) credit left join\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_2, \n",
" sum(transaction_amount) as Debit_transaction_amount, \n",
" count(*) as Total_no_of_debit_transactions\n",
" from \n",
" (\n",
" select * \n",
" from {trans_data} as trans_table left join {acc_data} as acc_table\n",
" on trans_table.orig_account_number = acc_table.account_number\n",
" )\n",
" where account_number not in ('None')\n",
" group by 1\n",
" ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n",
" ) subquery\n",
" ) main left join \n",
" (\n",
" select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
" subquery.SEGMENT,\n",
" subquery.RISK,\n",
" case\n",
" when subquery.SAR_FLAG is NULL then 'N'\n",
" else subquery.SAR_FLAG\n",
" end as SAR_FLAG \n",
" from\n",
" (\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_3, \n",
" business_segment as SEGMENT,\n",
" case\n",
" when RISK_CLASSIFICATION = 1 then 'Low Risk'\n",
" when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n",
" when RISK_CLASSIFICATION = 3 then 'High Risk'\n",
" else 'Unknown Risk'\n",
" end AS RISK\n",
" from {cust_data}\n",
" ) cd left join\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_4, \n",
" sar_flag as SAR_FLAG\n",
" from {alert_data}\n",
" ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
" ) subquery\n",
" ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
" ) final\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c34dc466-7bb5-471e-b0c5-0bfcd81b761c",
"metadata": {},
"outputs": [],
"source": [
"from tms_data_interface import SQLQueryInterface\n",
"\n",
"class Scenario:\n",
" seq = SQLQueryInterface(schema=\"transactionschema\")\n",
"\n",
" def logic(self, **kwargs):\n",
" row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
" cust_data=\"customer_data_v1\",\n",
" acc_data=\"account_data_v1\",\n",
" alert_data=\"alert_data_v1\")\n",
" )\n",
" cols = [\"Focal_id\", \"Credit_transaction_amount\",\n",
" \"Total_no_of_credit_transactions\",\n",
" \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n",
" \"Wash_Ratio\", \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
" df = pd.DataFrame(row_list, columns = cols)\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "406349d3-a6d0-4790-9b04-19dc6ce01827",
"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": "3.11.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

221
main.ipynb
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@ -1,33 +1,188 @@
{ {
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0", "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": "from tms_data_interface import SQLQueryInterface\n\nclass Scenario:\n\tseq = SQLQueryInterface()\n\n\tdef logic(self, **kwargs):\n\t\t# Write your code here\n" "source": [
} "import pandas as pd"
], ]
"metadata": { },
"kernelspec": { {
"display_name": "Python 3 (ipykernel)", "cell_type": "code",
"language": "python", "execution_count": null,
"name": "python3" "id": "77134554-e1dc-4e5b-aaa2-bb432789aa01",
}, "metadata": {},
"language_info": { "outputs": [],
"codemirror_mode": { "source": [
"name": "ipython", "from tms_data_interface import SQLQueryInterface\n",
"version": 3 "seq = SQLQueryInterface(schema=\"transactionschema\")"
}, ]
"file_extension": ".py", },
"mimetype": "text/x-python", {
"name": "python", "cell_type": "code",
"nbconvert_exporter": "python", "execution_count": null,
"pygments_lexer": "ipython3", "id": "9a13f2ec-d02f-4151-9d9a-17edd4f29063",
"version": "3.8.13" "metadata": {},
} "outputs": [],
}, "source": [
"nbformat": 4, "seq.execute_raw(\"show tables\")"
"nbformat_minor": 5 ]
} },
{
"cell_type": "code",
"execution_count": null,
"id": "32c443d5-c51f-425c-be6f-bcd8c9908ef4",
"metadata": {},
"outputs": [],
"source": [
"query = \"\"\"\n",
" select final.CUSTOMER_NUMBER_main as Focal_id,\n",
" final.Credit_transaction_amount,\n",
" final.Total_no_of_credit_transactions,\n",
" final.Debit_transaction_amount,\n",
" final.Total_no_of_debit_transactions,\n",
" final.Wash_Ratio,\n",
" final.SEGMENT,\n",
" final.RISK,\n",
" final.SAR_FLAG\n",
" from \n",
" (\n",
" (\n",
" select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n",
" subquery.Credit_transaction_amount,\n",
" subquery.Total_no_of_credit_transactions,\n",
" case\n",
" when subquery.Debit_transaction_amount is NULL then 0\n",
" else Debit_transaction_amount\n",
" end as Debit_transaction_amount,\n",
" case\n",
" when subquery.Total_no_of_debit_transactions is NULL then 0\n",
" else Total_no_of_debit_transactions\n",
" end as Total_no_of_debit_transactions,\n",
" case\n",
" when subquery.Debit_transaction_amount = 0\n",
" or subquery.Debit_transaction_amount is NULL then 0\n",
" else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount\n",
" end as Wash_Ratio\n",
" from \n",
" (\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_1, \n",
" sum(transaction_amount) as Credit_transaction_amount, \n",
" count(*) as Total_no_of_credit_transactions\n",
" from \n",
" (\n",
" select * \n",
" from {trans_data} as trans_table left join {acc_data} as acc_table\n",
" on trans_table.benef_account_number = acc_table.account_number\n",
" )\n",
" where account_number not in ('None')\n",
" group by 1\n",
" ) credit left join\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_2, \n",
" sum(transaction_amount) as Debit_transaction_amount, \n",
" count(*) as Total_no_of_debit_transactions\n",
" from \n",
" (\n",
" select * \n",
" from {trans_data} as trans_table left join {acc_data} as acc_table\n",
" on trans_table.orig_account_number = acc_table.account_number\n",
" )\n",
" where account_number not in ('None')\n",
" group by 1\n",
" ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n",
" ) subquery\n",
" ) main left join \n",
" (\n",
" select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
" subquery.SEGMENT,\n",
" subquery.RISK,\n",
" case\n",
" when subquery.SAR_FLAG is NULL then 'N'\n",
" else subquery.SAR_FLAG\n",
" end as SAR_FLAG \n",
" from\n",
" (\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_3, \n",
" business_segment as SEGMENT,\n",
" case\n",
" when RISK_CLASSIFICATION = 1 then 'Low Risk'\n",
" when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n",
" when RISK_CLASSIFICATION = 3 then 'High Risk'\n",
" else 'Unknown Risk'\n",
" end AS RISK\n",
" from {cust_data}\n",
" ) cd left join\n",
" (\n",
" select customer_number as CUSTOMER_NUMBER_4, \n",
" sar_flag as SAR_FLAG\n",
" from {alert_data}\n",
" ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
" ) subquery\n",
" ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
" ) final\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c34dc466-7bb5-471e-b0c5-0bfcd81b761c",
"metadata": {},
"outputs": [],
"source": [
"from tms_data_interface import SQLQueryInterface\n",
"\n",
"class Scenario:\n",
" seq = SQLQueryInterface(schema=\"transactionschema\")\n",
"\n",
" def logic(self, **kwargs):\n",
" row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
" cust_data=\"customer_data_v1\",\n",
" acc_data=\"account_data_v1\",\n",
" alert_data=\"alert_data_v1\")\n",
" )\n",
" cols = [\"Focal_id\", \"Credit_transaction_amount\",\n",
" \"Total_no_of_credit_transactions\",\n",
" \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n",
" \"Wash_Ratio\", \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
" df = pd.DataFrame(row_list, columns = cols)\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "406349d3-a6d0-4790-9b04-19dc6ce01827",
"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": "3.11.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import pandas as pd
# In[ ]:
from tms_data_interface import SQLQueryInterface
seq = SQLQueryInterface(schema="transactionschema")
# In[ ]:
seq.execute_raw("show tables")
# In[ ]:
query = """
select final.CUSTOMER_NUMBER_main as Focal_id,
final.Credit_transaction_amount,
final.Total_no_of_credit_transactions,
final.Debit_transaction_amount,
final.Total_no_of_debit_transactions,
final.Wash_Ratio,
final.SEGMENT,
final.RISK,
final.SAR_FLAG
from
(
(
select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,
subquery.Credit_transaction_amount,
subquery.Total_no_of_credit_transactions,
case
when subquery.Debit_transaction_amount is NULL then 0
else Debit_transaction_amount
end as Debit_transaction_amount,
case
when subquery.Total_no_of_debit_transactions is NULL then 0
else Total_no_of_debit_transactions
end as Total_no_of_debit_transactions,
case
when subquery.Debit_transaction_amount = 0
or subquery.Debit_transaction_amount is NULL then 0
else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount
end as Wash_Ratio
from
(
(
select customer_number as CUSTOMER_NUMBER_1,
sum(transaction_amount) as Credit_transaction_amount,
count(*) as Total_no_of_credit_transactions
from
(
select *
from {trans_data} as trans_table left join {acc_data} as acc_table
on trans_table.benef_account_number = acc_table.account_number
)
where account_number not in ('None')
group by 1
) credit left join
(
select customer_number as CUSTOMER_NUMBER_2,
sum(transaction_amount) as Debit_transaction_amount,
count(*) as Total_no_of_debit_transactions
from
(
select *
from {trans_data} as trans_table left join {acc_data} as acc_table
on trans_table.orig_account_number = acc_table.account_number
)
where account_number not in ('None')
group by 1
) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2
) subquery
) main left join
(
select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,
subquery.SEGMENT,
subquery.RISK,
case
when subquery.SAR_FLAG is NULL then 'N'
else subquery.SAR_FLAG
end as SAR_FLAG
from
(
(
select customer_number as CUSTOMER_NUMBER_3,
business_segment as SEGMENT,
case
when RISK_CLASSIFICATION = 1 then 'Low Risk'
when RISK_CLASSIFICATION = 2 then 'Medium Risk'
when RISK_CLASSIFICATION = 3 then 'High Risk'
else 'Unknown Risk'
end AS RISK
from {cust_data}
) cd left join
(
select customer_number as CUSTOMER_NUMBER_4,
sar_flag as SAR_FLAG
from {alert_data}
) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4
) subquery
) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main
) final
"""
# In[ ]:
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 = ["Focal_id", "Credit_transaction_amount",
"Total_no_of_credit_transactions",
"Debit_transaction_amount", "Total_no_of_debit_transactions",
"Wash_Ratio", "Segment", "Risk", "SAR_FLAG"]
df = pd.DataFrame(row_list, columns = cols)
return df
# In[ ]: