Introduction to Python in Excel

This hands on course is designed for Excel users who want to extend their skills using Python directly inside Excel. You will learn foundational Python concepts—data types, structures, functions—and progress into working with Python in Excel using Pandas DataFrames, enabling powerful automation and analysis workflows.  The course blends ACE’s practical teaching approach with real-world exercises, ensuring you gain confidence applying Python to everyday Excel tasks.

This course is ideal for: 

• Excel users who want to expand into Python for analysis and automation 
• Business analysts, administrators, and reporting professionals 
• Anyone beginning their Python journey with a focus on practical, Excelbased outcomes

To get the most from this course, learners should: 

• Be comfortable using Microsoft Excel 
• Have basic analytical or data-handling experience 

No prior programming knowledge is required.

By the end of this course, you will be able to:

• Understand core Python concepts and how they integrate with Excel
• Write and execute Python code inside Excel cells and formulas
• Manipulate data using Python lists, tuples, sets, and dictionaries
• Build repeatable workflows using Python functions
• Use Pandas DataFrames for high‑powered analysis in Excel
• Automate logical workflows using if, for, and while statements

1. Introduction to Python in Excel

• What is Python and why use it in Excel?
• Understanding Python integration in Excel
• Running your first Python cell
• Safe environments and supported libraries

• Strings, integers, floats, booleans
• Converting between data types
• Inputs, outputs, and quick transformations

• Creating and manipulating lists
• Indexing and slicing
• List methods (append, extend, sort, remove, etc.)
• Using lists with Excel data ranges

• Immutable tuples and when to use them
• Sets for uniqueness and membership testing
• Dictionaries for key–value storage
• Practical examples with Excel‑sourced data

• Writing and calling reusable functions
• Function arguments and return values
• Using functions to automate Excel workflows
• Practical examples: cleaning data, calculations, formatting outputs

• Introduction to the Pandas library
• Creating DataFrames from Excel tables
• Cleaning, reshaping, and analysing data
• Filtering, sorting, grouping, merging
• Exporting results back into Excel

• Conditional logic with if
• Looping with for and while
• Real‑world automation patterns
• Error handling and best practices