Summary  
This chapter covers dynamic data binding for charts, showing how to modify series definitions, add or remove series, swap row/column orientation, and change chart types at runtime.

General domain of usage  
Data visualization

This lesson focuses on **editing chart data** directly in Excel.

You will learn how to modify existing data series, add new ones, and remove unnecessary series to keep your charts accurate and up to date.

- Use the **Chart Design** tab → **Data** group → **Select Data** to edit existing data series by changing the series name or adjusting the data range;
- New data series can be added through the **Select Data** dialog by specifying the series name and values range;
- The **Change Chart Type** option in the **Chart Design** tab → **Type** group allows you to convert a chart to a different chart type, such as switching to a Clustered Column chart.

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 chart plugin
        resources = data.get("resources", [])
        cp = next((r for r in resources if r.get("name") == "SHEET_CHART_PLUGIN"), {})
        raw = cp.get("data", "{}")
        chart_data = json.loads(raw) if raw else {}
        cls.charts = chart_data.get(cls.sheet_id, [])

    # ------------------------------------------------------------------ #
    # Helpers
    # ------------------------------------------------------------------ #

    def _chart_range(self, chart):
        return chart.get("rangeInfo", {}).get("rangeInfo", {}).get("range", {})

    def _chart_title(self, chart):
        return chart.get("style", {}).get("titles", {}).get("title", {}).get("content", "")

    def _revenue_charts(self):
        """Revenue chart — identified by title 'Revenue' or as the single-series chart on A3:B15."""
        by_title = [c for c in self.charts if self._chart_title(c) == "Revenue"]
        if by_title:
            return by_title
        # Fallback: chart with endColumn==1 (A3:B15 range, single Income series)
        return [c for c in self.charts if self._chart_range(c).get("endColumn") == 1]

    # ------------------------------------------------------------------ #
    # Step 1 — Revenue chart type changed from Pie to Column
    # chartType: 8 (Pie) → 4 (Column)
    # ------------------------------------------------------------------ #

    def test_revenue_chart_type_changed(self):
        if self._no_data:
            _dynamic_test(self, True, "Revenue chart type changed from Pie to Column.", ""); return
        if not self.charts:
            _dynamic_test(self, False,
                "Revenue chart type changed from Pie to Column.",
                "No charts found. Make sure you are working on the correct sheet.")
            return

        revenue_charts = self._revenue_charts()
        if not revenue_charts:
            _dynamic_test(self, False,
                "Revenue chart type changed from Pie to Column.",
                "No Revenue chart found. Make sure the Revenue chart is still present on the sheet.")
            return

        chart_types = [c.get("chartType") for c in revenue_charts]
        ok = any(ct == 4 for ct in chart_types)
        _dynamic_test(self, ok,
            "Revenue chart type changed from Pie to Column.",
            f"Revenue chart is not a Column chart (types found: {chart_types}). "
            f"Click the Revenue chart → top-right button → chart panel → "
            f"change Chart Type to Column Chart → Confirm.")


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.

Editing Chart Data in Excel

Key Points

Editing Chart Data in Excel

Key Points