**サブクエリ**を活用して部門ごとの給与データを分析する実践的なシナリオ。企業全体の平均給与を上回る給与を支払っている部門を特定するケース。各部門の平均給与と全従業員の平均給与を比較する必要あり。この課題を通じて、SQLにおける比較分析のための**サブクエリ**の理解を深める内容。

import unittest
import psycopg2
import pandas as pd

class TestPostgresQuery(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        cls.connection = psycopg2.connect(
            host="localhost",
            user="agent",
            password="qwerty",
            dbname="testdb",
            sslmode="disable"
        )
        cls.cursor = cls.connection.cursor()

    def test_correct_departments_returned(self):
        """Check if only departments with above-average salaries are returned."""
        with open("query.sql", "r") as file:
            query = file.read()

        # Calculate company-wide average salary
        self.cursor.execute("SELECT AVG(salary) FROM employees;")
        company_avg = float(self.cursor.fetchone()[0])

        # Get department average salaries
        self.cursor.execute("""
            SELECT d.name, AVG(e.salary) as avg_salary
            FROM departments d
            JOIN employees e ON d.department_id = e.department_id
            GROUP BY d.department_id, d.name
        """)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        dept_avg_df = pd.DataFrame(rows, columns=columns)

        # Departments with avg_salary > company_avg
        expected_names = set(dept_avg_df[dept_avg_df['avg_salary'] > company_avg]['name'])

        # Run user query
        self.cursor.execute(query)
        user_rows = self.cursor.fetchall()
        user_names = set([row[0] for row in user_rows])

        condition = user_names == expected_names
        _dynamic_test(
            self,
            condition,
            "Returned departments match those with above-average salaries.",
            f"Expected departments: {sorted(expected_names)}, but got: {sorted(user_names)}."
        )

    def test_query_uses_subquery(self):
        """Check that the query uses a subquery to calculate the company-wide average salary."""
        with open("query.sql", "r") as file:
            query = file.read().lower().replace('\\n', ' ')
        subquery_found = "select avg(" in query and "from employees" in query
        _dynamic_test(
            self,
            subquery_found,
            "Query uses a subquery to calculate overall average salary.",
            "Query does not use a subquery to calculate overall average salary."
        )

    def test_grouping_by_department(self):
        """Check that the query groups results by department."""
        with open("query.sql", "r") as file:
            query = file.read().lower().replace('\\n', ' ')
        group_by_found = "group by" in query and ("department_id" in query or "d.name" in query or "departments.name" in query)
        _dynamic_test(
            self,
            group_by_found,
            "Query groups by department.",
            "Query does not group by department."
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

if __name__ == "__main__":
    unittest.main()


test_solution.py

実際のシナリオを通じて、SQLにおけるサブクエリの記述と応用の技術を習得します。本モジュールでは、サブクエリの理論と実践、SELECT、WHERE、FROM句での利用、相関サブクエリについて解説します。

注文、顧客、商品に焦点を当てたeコマースデータセットを使用してサブクエリを探求します。サブクエリを活用してインサイトを抽出し、ビジネス上の課題を解決する方法を学びます。

チャレンジ：平均給与を上回る部門

解答