Summary  
This chapter covers how to apply an automatic filter to a dataset, allowing rows to be selectively displayed based on specified criteria and how to combine multiple filters to iteratively refine results.

General domain of usage  
Data analysis

Imagine having a magic magnifying glass that only shows you the data you need. That's what using **AutoFilter** in Excel is like. 

## Key Points

- Activate the **AutoFilter** feature from the **Data** tab → **Sort & Filter** group to begin filtering your data;
- Apply **multiple filters** to fine-tune your dataset based on varied criteria.

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 filter plugin
        resources = data.get("resources", [])
        fp = next((r for r in resources if r.get("name") == "SHEET_FILTER_PLUGIN"), {})
        raw = fp.get("data", "{}")
        filter_data = json.loads(raw) if raw else {}
        cls.filter = filter_data.get(cls.sheet_id)   # None if no filter applied

    # ------------------------------------------------------------------ #
    # Helper: find a filterColumn entry by colId
    # ------------------------------------------------------------------ #

    def _filter_col(self, col_id):
        if not self.filter:
            return None
        for fc in self.filter.get("filterColumns", []):
            if fc.get("colId") == col_id:
                return fc
        return None

    def _filter_values(self, col_id):
        """Return set of filter string values for a column, or empty set."""
        fc = self._filter_col(col_id)
        if not fc:
            return set()
        return set(str(v) for v in fc.get("filters", {}).get("filters", []))

    # ------------------------------------------------------------------ #
    # Check filter is applied at all (SHEET_FILTER_PLUGIN present)
    # ------------------------------------------------------------------ #

    def test_filter_applied(self):
        if self._no_data:
            _dynamic_test(self, True, "Filter is applied to the data range.", ""); return
        ok = self.filter is not None and bool(self.filter.get("filterColumns"))
        _dynamic_test(self, ok,
            "Filter is applied to the data range.",
            "No filter found. Select A3:I23 → Data tab → Filter, then apply the required filters.")

    # ------------------------------------------------------------------ #
    # Step 2a — Category filtered to "Books"
    # Category = column C = colId 2
    # ------------------------------------------------------------------ #

    def test_filter_category_books(self):
        if self._no_data:
            _dynamic_test(self, True, "Category filter set to 'Books'.", ""); return
        vals = self._filter_values(2)
        ok = "Books" in vals
        _dynamic_test(self, ok,
            "Category filter set to 'Books'.",
            f"Category column is not filtered to 'Books' (found: {vals or 'no filter'}). "
            f"Open the Category drop-down → select 'Books' → OK.")

    # ------------------------------------------------------------------ #
    # Step 2b — Supplier filtered to "Orion Distributors"
    # Supplier = column D = colId 3
    # ------------------------------------------------------------------ #

    def test_filter_supplier_orion(self):
        if self._no_data:
            _dynamic_test(self, True, "Supplier filter set to 'Orion Distributors'.", ""); return
        vals = self._filter_values(3)
        ok = "Orion Distributors" in vals
        _dynamic_test(self, ok,
            "Supplier filter set to 'Orion Distributors'.",
            f"Supplier column is not filtered to 'Orion Distributors' (found: {vals or 'no filter'}). "
            f"Open the Supplier drop-down → select 'Orion Distributors' → OK.")

    # ------------------------------------------------------------------ #
    # Step 2c — Reorder Level filtered to 53, 58, 61
    # Reorder Level = column E = colId 4
    # ------------------------------------------------------------------ #

    def test_filter_reorder_level(self):
        if self._no_data:
            _dynamic_test(self, True, "Reorder Level filter set to 53, 58, and 61.", ""); return
        vals = self._filter_values(4)
        required = {"53", "58", "61"}
        missing = required - vals
        ok = len(missing) == 0
        _dynamic_test(self, ok,
            "Reorder Level filter set to 53, 58, and 61.",
            f"Reorder Level filter is missing values: {missing}. "
            f"Open the Reorder Level drop-down → select 53, 58, and 61 → OK.")


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


test_main.py

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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.

Filtering Data Using AutoFilter

Key Points

Filtering Data Using AutoFilter

Key Points