Summary  
This chapter explains how to create and manage dynamic table data structures that automatically apply formatting, support structured references in formulas, and resize seamlessly when rows or columns are added or removed.

General domain of usage  
Spreadsheet-based data analysis

**Tables** help you organize data in Excel in a structured and efficient way. They automatically apply formatting, enable built-in filtering and sorting, allow the use of structured references in formulas, and make data analysis more convenient and reliable.

- Use **Table** in the **Insert** tab → **Tables** group to convert a data range into a structured table and enable headers;
- Press `Tab` in the last cell of a table to quickly add a new row;
- Enter formulas directly in table columns to calculate values, such as multiplying cells from the same row to compute revenue.

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_id = next(iter(data["sheets"]))

        # Parse table plugin
        resources = data.get("resources", [])
        tp = next((r for r in resources if r.get("name") == "SHEET_TABLE_PLUGIN"), {})
        raw = tp.get("data", "{}")
        table_data = json.loads(raw) if raw else {}
        sheet_tables = table_data.get(cls.sheet_id, {})
        cls.tables = sheet_tables.get("tables", [])

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

    def _first_table(self):
        return self.tables[0] if self.tables else None

    # ------------------------------------------------------------------ #
    # Step 1 — Table created from A3:I23
    # (0-based: startRow=2, startColumn=0, endRow=22, endColumn >= 8)
    # ------------------------------------------------------------------ #

    def test_table_created(self):
        if self._no_data:
            _dynamic_test(self, True, "Table created from A3:I23.", ""); return
        t = self._first_table()
        if t is None:
            _dynamic_test(self, False,
                "Table created from A3:I23.",
                "No table found. Select A3:I23 → Data tab → Table → Confirm.")
            return

        r = t.get("range", {})
        ok = (r.get("startRow") == 2 and r.get("startColumn") == 0
              and r.get("endRow") == 22 and r.get("endColumn", 0) >= 8)
        _dynamic_test(self, ok,
            "Table created from A3:I23.",
            f"Table range is incorrect (got {r}). "
            f"Select A3:I23 → Data tab → Table → Confirm.")

    # ------------------------------------------------------------------ #
    # Step 2 — New column inserted before Last Order Date
    # Table must span 10 columns (endColumn == 9) and
    # "Last Order Date" must be the last column.
    # ------------------------------------------------------------------ #

    def test_column_inserted(self):
        if self._no_data:
            _dynamic_test(self, True, "New column inserted into the table.", ""); return
        t = self._first_table()
        if t is None:
            _dynamic_test(self, False,
                "New column inserted into the table.",
                "No table found. Complete step 1 first.")
            return

        r = t.get("range", {})
        cols = t.get("columns", [])
        col_names = [c.get("displayName", "").strip() for c in cols]

        # Platform inserts new column adjacent to Last Order Date → table gains one column
        has_10_cols = r.get("endColumn", 0) == 9 and len(cols) == 10
        last_order_date_present = "Last Order Date" in col_names

        ok = has_10_cols and last_order_date_present
        _dynamic_test(self, ok,
            "New column inserted into the table.",
            f"Column not inserted correctly. Expected 10 columns including 'Last Order Date' "
            f"(got {len(cols)} cols, endColumn={r.get('endColumn')}, cols={col_names}). "
            f"Right-click the Last Order Date column header → Insert Table → Insert Table Column.")


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.

Creating and Managing Tables in Excel

Key Points

Essential Keyboard Shortcuts