Summary  
This chapter covers using the AVG() aggregate function to compute the average value of a numeric column, with optional filtering of rows via a WHERE clause.

General domain of usage  
Database querying and data analysis

`AVG()` returns the average value of a certain column. 
Let's see an example: 

`AVG()` can also be used to find the average of a selected set of columns or rows that meet certain conditions. Here’s an example:

SELECT AVG(population) 
FROM country
WHERE population < 4478500;

import unittest
import psycopg2
import pandas as pd
import decimal

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_avg_surfacearea_correctness(self):
        """Check that the query returns the correct average of the surfacearea column from country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Calculate expected average
        self.cursor.execute("SELECT surfacearea FROM country")
        surfaceareas = [row[0] for row in self.cursor.fetchall() if row[0] is not None]
        expected_avg = sum(surfaceareas) / len(surfaceareas) if surfaceareas else None

        self.cursor.execute(query)
        result = self.cursor.fetchone()[0]
        # Accept float rounding error up to 6 decimals
        if isinstance(result, decimal.Decimal):
            result_float = float(result)
        else:
            result_float = result
        if isinstance(expected_avg, decimal.Decimal):
            expected_avg_float = float(expected_avg)
        else:
            expected_avg_float = expected_avg
        condition = expected_avg is not None and abs(result_float - expected_avg_float) < 1e-6
        _dynamic_test(
            self,
            condition,
            "Query returns the correct average value of surfacearea.",
            f"Expected average: {expected_avg}, but got: {result}."
        )

    def test_query_uses_avg_function(self):
        """Check that the query uses the AVG() function."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = "avg" in query.lower()
        _dynamic_test(
            self,
            condition,
            "Query uses the AVG() function.",
            "Query does not use the AVG() function."
        )

    def test_query_uses_select(self):
        """Check that the query uses the SELECT statement."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = query.strip().lower().startswith("select")
        _dynamic_test(
            self,
            condition,
            "Query uses the SELECT statement.",
            "Query does not use the SELECT statement."
        )

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):
    import re
    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

This course is perfect for beginners ready to explore the world of SQL. Whether you're just starting out in database management or aiming to use SQL for your application development projects, this course covers the essentials. You'll quickly learn how to leverage the full potential of SQL, from querying and managing data to seamlessly integrating it into real-world applications. By the end of the course, you'll have the confidence and skills to solve practical problems with SQL and enhance your development process.

The AVG() Function

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