##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55

Table Schemas:

Database: financial
Total Tables: 8
Total Columns: 55

Table Schemas:

Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text): frequency of the acount
• date (date): the creation date of the account
  Values: in the form YYMMDD

Table: card (4 columns)
-----------------------
• card_id (integer): id number of credit card
• disp_id (integer): disposition id
• type (text): type of credit card
  Values: "junior": junior class of credit card; 
"classic": standard class of credit card; 
"gold": high-leve...
• issued (date): the date when the credit card issued
  Values: in the form YYMMDD

Table: client (4 columns)
-------------------------
• client_id (integer): the unique number
• gender (text)
  Values: F：female 
M：male
• birth_date (date): birth date
• district_id (integer): location of branch

Table: disp (4 columns)
-----------------------
• disp_id (integer): unique number of identifying this row of record
• client_id (integer): id number of client
• account_id (integer): id number of account
• type (text): type of disposition
  Values: "OWNER" : "USER" : "DISPONENT"
commonsense evidence:
the account can only have the right to issue pe...

Table: district (16 columns)
----------------------------
• district_id (integer): location of branch
• A2 (text): district_name
• A3 (text): region
• A4 (text)
• A5 (text): municipality < district < region
• A6 (text): municipality < district < region
• A7 (text): municipality < district < region
• A8 (integer): municipality < district < region
• A9 (integer)
  Values: not useful
• A10 (real): ratio of urban inhabitants
• A11 (integer): average salary
• A12 (real): unemployment rate 1995
• A13 (real): unemployment rate 1996
• A14 (integer): no. of entrepreneurs per 1000 inhabitants
• A15 (integer): no. of committed crimes 1995
• A16 (integer): no. of committed crimes 1996

Table: loan (7 columns)
-----------------------
• loan_id (integer): the id number identifying the loan data
• account_id (integer): the id number identifying the account
• date (date): the date when the loan is approved
• amount (integer): approved amount
  Values: unit：US dollar
• duration (integer): loan duration
  Values: unit：month
• payments (real): monthly payments
  Values: unit：month
• status (text): repayment status
  Values: 'A' stands for contract finished, no problems;
'B' stands for contract finished, loan not paid;
'C' ...

Table: order (6 columns)
------------------------
• order_id (integer): identifying the unique order
• account_id (integer): id number of account
• bank_to (text): bank of the recipient
• account_to (integer): account of the recipient
  Values: each bank has unique two-letter code
• amount (real): debited amount
• k_symbol (text): purpose of the payment
  Values: "POJISTNE" stands for insurance payment
"SIPO" stands for household payment
"LEASING" stands for lea...

Table: trans (10 columns)
-------------------------
• trans_id (integer): transaction id
• account_id (integer)
• date (date): date of transaction
• type (text): +/- transaction
  Values: "PRIJEM" stands for credit
"VYDAJ" stands for withdrawal
• operation (text): mode of transaction
  Values: "VYBER KARTOU": credit card withdrawal
"VKLAD": credit in cash
"PREVOD Z UCTU" :collection from anot...
• amount (integer): amount of money
  Values: Unit：USD
• balance (integer): balance after transaction
  Values: Unit：USD
• k_symbol (text)
  Values: "POJISTNE": stands for insurrance payment
"SLUZBY": stands for payment for statement
"UROK": stands ...
• bank (text)
  Values: each bank has unique two-letter code
• account (integer)

##Evidence:
Account owners refer to disp.type = 'OWNER'. Good loans refer to status = 'A' and bad loans refer to status = 'B'. Account balance is calculated as total income minus total expense.

##Role Access Policy (Column-Level):
Role: DataOperator_1
Accessible Columns: account: date, district_id, frequency; card: ALL COLUMNS; disp: ALL COLUMNS; district: A10, A13, A14, A16, A2, A5, A6, A7, A9, district_id; loan: account_id, date, loan_id, status; order: account_id, account_to, amount, bank_to, k_symbol; trans: ALL COLUMNS

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: For each district, how many classic credit card holders who are account owners are there, and what are their average loan amounts, account balances, loan performance, district salary, and unemployment rate?
Evidence: Account owners refer to disp.type = 'OWNER'. Good loans refer to status = 'A' and bad loans refer to status = 'B'. Account balance is calculated as total income minus total expense.
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: account: account_id; loan: amount)
Gold SQL: WITH loan_stats AS (
    SELECT 
        l.account_id,
        COUNT(l.loan_id) AS loan_count,
        AVG(l.amount) AS avg_loan_amount,
        SUM(CASE WHEN l.status = 'A' THEN 1 ELSE 0 END) AS good_loans,
        SUM(CASE WHEN l.status = 'B' THEN 1 ELSE 0 END) AS bad_loans
    FROM loan l
    GROUP BY l.account_id
),
account_activity AS (
    SELECT 
        a.account_id,
        COUNT(t.trans_id) AS transaction_count,
        MAX(t.date) AS last_transaction_date,
        SUM(CASE WHEN t.type = 'PRIJEM' THEN t.amount ELSE 0 END) AS total_income,
        SUM(CASE WHEN t.type = 'VYDAJ' THEN t.amount ELSE 0 END) AS total_expense
    FROM account a
    LEFT JOIN trans t ON a.account_id = t.account_id
    GROUP BY a.account_id
),
district_metrics AS (
    SELECT 
        d.district_id,
        d.A2 AS district_name,
        d.A11 AS avg_salary,
        d.A12 AS unemployment_rate_95,
        RANK() OVER (ORDER BY d.A11 DESC) AS salary_rank,
        RANK() OVER (ORDER BY d.A12) AS unemployment_rank
    FROM district d
)

SELECT 
    COUNT(c.card_id) AS eligible_classic_cards,
    dm.district_name,
    ROUND(AVG(ls.avg_loan_amount), 2) AS avg_loan_amount,
    ROUND(AVG(aa.total_income - aa.total_expense), 2) AS avg_account_balance,
    SUM(ls.good_loans) AS total_good_loans,
    SUM(ls.bad_loans) AS total_bad_loans,
    ROUND(AVG(dm.avg_salary), 2) AS district_avg_salary,
    ROUND(AVG(dm.unemployment_rate_95), 2) AS district_unemployment_rate
FROM card c
INNER JOIN disp d ON c.disp_id = d.disp_id
INNER JOIN account a ON d.account_id = a.account_id
INNER JOIN district_metrics dm ON a.district_id = dm.district_id
LEFT JOIN loan_stats ls ON a.account_id = ls.account_id
LEFT JOIN account_activity aa ON a.account_id = aa.account_id
WHERE c.type = 'classic' 
AND d.type = 'OWNER'
GROUP BY dm.district_name
HAVING COUNT(c.card_id) > 0
ORDER BY eligible_classic_cards DESC, avg_loan_amount DESC;