##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:
Female refers to gender = 'F'; Sokolov is a district name in column A2; loan status 'A' means contract finished with no problems, 'D' means running contract with client in debt; only account owners are considered

##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: What is the average age at account opening, total number with loans, number with successfully completed loans, and number currently in debt for female clients born before 1950 from Sokolov who own accounts? Also, what are the earliest and latest years these accounts were opened?
Evidence: Female refers to gender = 'F'; Sokolov is a district name in column A2; loan status 'A' means contract finished with no problems, 'D' means running contract with client in debt; only account owners are considered
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: account: account_id; client: birth_date, client_id, district_id, gender)
Gold SQL: WITH female_clients_from_sokolov AS (
    SELECT 
        c.client_id,
        c.birth_date,
        STRFTIME('%Y', c.birth_date) AS birth_year,
        d.A2 AS district_name
    FROM 
        client c
    INNER JOIN 
        district d ON c.district_id = d.district_id
    WHERE 
        c.gender = 'F' 
        AND STRFTIME('%Y', c.birth_date) < '1950' 
        AND d.A2 = 'Sokolov'
),
client_accounts AS (
    SELECT 
        fc.client_id,
        fc.birth_year,
        a.account_id,
        a.date AS account_open_date,
        STRFTIME('%Y', a.date) AS account_open_year,
        CAST(STRFTIME('%Y', 'now') AS INTEGER) - CAST(fc.birth_year AS INTEGER) AS client_age_now,
        CAST(STRFTIME('%Y', a.date) AS INTEGER) - CAST(fc.birth_year AS INTEGER) AS client_age_at_opening
    FROM 
        female_clients_from_sokolov fc
    INNER JOIN 
        disp d ON fc.client_id = d.client_id
    INNER JOIN 
        account a ON d.account_id = a.account_id
    WHERE 
        d.type = 'OWNER'
),
client_loan_status AS (
    SELECT 
        ca.client_id,
        ca.account_id,
        ca.birth_year,
        ca.account_open_date,
        ca.client_age_at_opening,
        CASE 
            WHEN l.loan_id IS NOT NULL THEN 'Has Loan'
            ELSE 'No Loan'
        END AS loan_status,
        CASE
            WHEN l.status = 'A' THEN 'Contract Finished/No Problems'
            WHEN l.status = 'B' THEN 'Contract Finished/Loan Not Paid'
            WHEN l.status = 'C' THEN 'Running Contract/OK So Far'
            WHEN l.status = 'D' THEN 'Running Contract/Client in Debt'
            ELSE 'No Loan'
        END AS loan_details
    FROM 
        client_accounts ca
    LEFT JOIN 
        loan l ON ca.account_id = l.account_id
)
SELECT 
    COUNT(DISTINCT cls.client_id) AS total_female_clients,
    AVG(cls.client_age_at_opening) AS avg_age_at_account_opening,
    SUM(CASE WHEN cls.loan_status = 'Has Loan' THEN 1 ELSE 0 END) AS clients_with_loans,
    SUM(CASE WHEN cls.loan_details = 'Contract Finished/No Problems' THEN 1 ELSE 0 END) AS clients_with_good_loans,
    SUM(CASE WHEN cls.loan_details = 'Running Contract/Client in Debt' THEN 1 ELSE 0 END) AS clients_with_debt,
    MIN(STRFTIME('%Y', cls.account_open_date)) AS earliest_account_year,
    MAX(STRFTIME('%Y', cls.account_open_date)) AS latest_account_year
FROM 
    client_loan_status cls;