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初级

统计各支行本月存款笔数与金额汇总

未完成
初级参考 完整示例代码供参考,建议自己理解后重新输入
def solve():
    from pyodide.http import open_url
    offices_csv = open_url("https://data.zuihe.com/dbd/core/state_02/offices.csv").read()
    staff_csv = open_url("https://data.zuihe.com/dbd/core/state_02/staff.csv").read()
    savings_products_csv = open_url("https://data.zuihe.com/dbd/core/state_02/savings_products.csv").read()
    clients_csv = open_url("https://data.zuihe.com/dbd/core/state_02/clients.csv").read()
    savings_accounts_csv = open_url("https://data.zuihe.com/dbd/core/state_02/savings_accounts.csv").read()
    savings_account_transactions_csv = open_url("https://data.zuihe.com/dbd/core/state_02/savings_account_transactions.csv").read()
    import sqlite3
    import pandas as pd
    from io import StringIO

    conn = sqlite3.connect(':memory:')
    pd.read_csv(StringIO(offices_csv)).to_sql('offices', conn, index=False, if_exists='replace')
    pd.read_csv(StringIO(savings_accounts_csv)).to_sql('savings_accounts', conn, index=False, if_exists='replace')
    pd.read_csv(StringIO(savings_account_transactions_csv)).to_sql('savings_account_transactions', conn, index=False, if_exists='replace')

    result = pd.read_sql_query("""
        SELECT o.name AS office_name, COUNT(t.id) AS deposit_count, SUM(t.amount) AS total_deposit
        FROM savings_account_transactions t
        JOIN savings_accounts a ON t.account_id = a.id
        JOIN offices o ON a.office_id = o.id
        WHERE t.transaction_type = 'DEPOSIT'
          AND t.transaction_date LIKE '2026-06%'
        GROUP BY o.id, o.name
        ORDER BY total_deposit DESC
    """, conn)
    print(result.to_string(index=False))
    conn.close()

示例

输入
solve()
期望输出
office_name  deposit_count  total_deposit
   阳光商业银行总行              3      2425000.0
     上海浦东支行             12       783600.0
   阳光银行上海分行              1       620000.0
   阳光银行北京分行              2       500000.0
   阳光银行广州分行              2       275000.0
     北京朝阳支行              9       164500.0
     广州天河支行             10       141800.0
     北京海淀支行              8        76700.0
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