Summary  
This chapter introduces built-in functions for aggregating numeric data (SUM, AVERAGE, MIN, MAX, COUNT), shows how to combine functions for more complex calculations, and covers error checking in formulas.

General domain of usage  
Data analysis

Excel **functions** are the secret sauce that turns a simple spreadsheet into a powerful **data analysis** tool. 

This chapter will introduce you to some of the most **common** and **versatile functions**: `SUM`, `AVERAGE`, `MIN`, `MAX`, and `COUNT`. 

We'll also explore how to use the **AutoSum** feature, **combine functions** for complex calculations, and handle **error checking** in formulas.

## Key Points
- The `SUM` function **add up** a range of numbers, perfect for calculating totals;
- The `AVERAGE` function finds the **average value** in a range, ignoring empty cells and text;
- The `MAX` function identifies the **largest number** in a range;
- The `MIN` function finds the **smallest number** in a range;
- The `COUNT` function **tallies the number of cells** that contain numbers in a range;
- **AutoSum** quickly adds up a range of cells and can also be used for `AVERAGE`, `COUNT`, `MAX`, and `MIN`;
- You can **combine functions** to perform more complex calculations;
- Excel has multiple **Error Checking** tools for you to utilise.

import unittest
import json


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)


class TestUserCode(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        with open("payload.json") as f:
            data = json.load(f)
        cls.sheet = next(iter(data["sheets"].values()))

    def _cell_value(self, row, col):
        cell = self.sheet.get("cellData", {}).get(str(row), {}).get(str(col))
        return None if cell is None else cell.get("v")

    def _check_cell_value(self, row, col, cell_ref, *expected_values):
        actual = self._cell_value(row, col)

        _dynamic_test(
            self,
            actual in expected_values,
            f"{cell_ref} contains the correct formula or result.",
            f"{cell_ref} should contain one of {expected_values!r}, but found {actual!r}."
        )

    def test_l15_sum_formula_or_result_is_correct(self):
        self._check_cell_value(14, 11, "L15", "=SUM(L8:L14)", 164.680146, 164.68)

    def test_m15_sum_formula_or_result_is_correct(self):
        self._check_cell_value(14, 12, "M15", "=SUM(M8:M14)", 13694.118273, 13694.12)

    def test_i31_average_formula_or_result_is_correct(self):
        self._check_cell_value(30, 8, "I31", "=AVERAGE(I22:I28)", 1956.2842857142857, 1956.28)

    def test_i32_max_formula_or_result_is_correct(self):
        self._check_cell_value(31, 8, "I32", "=MAX(I22:I28)", 2834.12)

    def test_i33_min_formula_or_result_is_correct(self):
        self._check_cell_value(32, 8, "I33", "=MIN(I22:I28)", 950.62)

    def test_i34_average_max_min_formula_or_result_is_correct(self):
        self._check_cell_value(
            33, 8, "I34",
            "=AVERAGE(MAX(I22:I28),MIN(I22:I28))",
            1892.37
        )

    def test_m31_average_formula_or_result_is_correct(self):
        self._check_cell_value(30, 12, "M31", "=AVERAGE(M22:M28)", 10107.05)

    def test_m32_max_formula_or_result_is_correct(self):
        self._check_cell_value(31, 12, "M32", "=MAX(M22:M28)", 14247.82)

    def test_m33_min_formula_or_result_is_correct(self):
        self._check_cell_value(32, 12, "M33", "=MIN(M22:M28)", 5677.52)


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

test_main.py

Dive into the world of Excel with this comprehensive video course, designed to take you from basic navigation to mastering functions and basic data analysis. Starting with foundational skills like data entry and cell formatting, you'll quickly progress to using powerful tools. Whether you're organizing large datasets, performing statistical analysis, or creating dynamic charts, this course equips you with the practical skills needed in today’s data-driven environment.

Kickstart your journey with Excel by understanding its interface, basic functions, and essential data entry techniques. Learn how to navigate toolbars, worksheets, and master the fundamental elements to set a solid foundation.

Dive deeper into Excel by exploring advanced data entry and formatting options. Sharpen your skills in text and number formatting, discover how to effectively use styles, and enhance spreadsheet readability and functionality.

Unleash the power of Excel with an introduction to basic formulas and functions. Gain confidence in creating calculations, using cell references, and employing key functions like SUM, AVERAGE, MIN and MAX to automate and simplify your data analysis tasks.

In this section, you will master advanced Excel formulas and functions, enhancing your ability to manage complex calculations. Learn to display and audit formulas, utilize nested and logical statements, and apply conditions effectively to streamline your data analysis tasks.

Explore comprehensive techniques for sorting, filtering, and managing data efficiently. This section covers everything from basic data organization to advanced filtering and table management, ensuring you can handle and analyze data effectively.

Dive into the art of data visualization using Excel's powerful charting tools. You'll learn to create various types of charts, customize them to enhance visual appeal, and manipulate data within charts to present clear and compelling visual stories.

Gain proficiency in managing worksheets and workbooks within Excel. This section teaches you how to effectively organize and manipulate workbook elements, utilize formatting tools, and secure your work with passwords, providing a thorough grounding in workbook operations.

Essential Excel Functions

Key Points

Solution