Summary
This chapter explains how to perform single- and multi-level sorting on tabular data by specifying keys (e.g., text, numbers, dates, colors, or icons), handling headers, and applying custom sort orders to maintain data integrity.

General domain of usage
Inventory management

**Sorting your data** in Excel isn't just about making things look tidy — it's about **making your data work** for you. 

- Use the **Sort** button in the **Data** tab → **Sort & Filter** group to organize data alphabetically, numerically, or by date;
- Sort a single column or multiple columns to manage complex datasets more efficiently.

Initial Workbook

import unittest
import json
import os


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):
        cls._no_data = True
        cls.sheet = {}
        cls.styles = {}
        if os.path.exists("payload.json"):
            try:
                with open("payload.json") as f:
                    raw = f.read().strip()
                if not raw:
                    return
                data = json.loads(raw)
            except (json.JSONDecodeError, ValueError):
                return
        else:
            return
        cls._no_data = False
        cls.sheet = next(iter(data["sheets"].values()))
        cls.styles = data.get("styles", {})

    # ------------------------------------------------------------------ #
    # Helper
    # ------------------------------------------------------------------ #

    def _cell(self, row, col):
        row_data = self.sheet.get("cellData", {}).get(str(row), {})
        cell = row_data.get(str(col))
        if cell:
            return cell
        for key, c in row_data.items():
            if "-" in key:
                try:
                    s, e = map(int, key.split("-", 1))
                    if s <= col <= e:
                        return c
                except ValueError:
                    pass
        return None

    def _col_values(self, col, start_row, end_row):
        """Return list of (row, value) for a column, skipping None."""
        result = []
        for r in range(start_row, end_row + 1):
            cell = self._cell(r, col)
            if cell and cell.get("v") is not None:
                result.append((r, cell["v"]))
        return result

    # ------------------------------------------------------------------ #
    # Step 3 (final state) — Data sorted by Last Order Date ascending
    # Column I = index 8, data rows 3–22 (0-based)
    # Dates stored as Excel serial numbers; ascending = oldest first.
    # ------------------------------------------------------------------ #

    def test_sorted_by_last_order_date_ascending(self):
        if self._no_data:
            _dynamic_test(self, True, "Data is sorted by Last Order Date (oldest to newest).", ""); return
        values = self._col_values(8, 3, 22)   # col I, rows 4-23 in Excel
        if len(values) < 2:
            _dynamic_test(self, False,
                "Data is sorted by Last Order Date (oldest to newest).",
                "Could not read Last Order Date column. Make sure A3:I23 is selected before sorting.")
            return

        dates = [v for _, v in values]
        out_of_order = [
            (i, dates[i], dates[i+1])
            for i in range(len(dates)-1)
            if isinstance(dates[i], (int, float)) and isinstance(dates[i+1], (int, float))
            and dates[i] > dates[i+1]
        ]
        if out_of_order:
            example = out_of_order[0]
            fail_msg = (f"Data is not sorted by Last Order Date in ascending order. "
                        f"Found {len(out_of_order)} out-of-order pair(s) (e.g. position "
                        f"{example[0]+1}: {example[1]} before {example[2]}). "
                        f"Select A3:I23 → Sort → Sort by: Last Order Date → Order: Ascending.")
        else:
            fail_msg = "Data is not sorted by Last Order Date in ascending order."
        _dynamic_test(self, len(out_of_order) == 0,
            "Data is sorted by Last Order Date (oldest to newest).",
            fail_msg)

    # ------------------------------------------------------------------ #
    # Verify header row is intact (row 2, 0-based = row 3 in Excel)
    # ------------------------------------------------------------------ #

    def test_header_row_intact(self):
        if self._no_data:
            _dynamic_test(self, True, "Header row is intact.", ""); return
        headers = {
            0: "Product ID", 1: "Product Name", 2: "Category",
            3: "Supplier", 8: "Last Order Date"
        }
        missing = []
        for col, expected in headers.items():
            cell = self._cell(2, col)
            v = cell.get("v", "") if cell else ""
            if str(v).strip() != expected:
                missing.append(f"col {col+1} (expected '{expected}', got '{v!r}')")
        _dynamic_test(self, len(missing) == 0,
            "Header row is intact.",
            f"Header row was altered or shifted: {missing}. "
            f"Make sure to tick 'First row does not participate in sorting' when sorting.")


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.

Sorting Data in Excel

Key Points