Python-Powered Excel
Published by O'Reilly Media, Inc.
Take Control of Your Data by Automating Excel Spreadsheets
Excel spreadsheets continue to be a fundamental tool for data analysis and reporting among business professionals. However, Excel exhibits limitations in developing repeatable and dynamic data processes. The recent incorporation of Python into Excel marks a major step forward in overcoming these limitations.
Join expert George Mount in a comprehensive course that explores the use of Python in Excel and its broader interoperability. Python, a renowned open-source programming tool, acts as a catalyst for generating swift, accurate spreadsheet reports and analysis. Although the prospect of learning a new programming language might seem daunting, your existing knowledge of data and coding forms a solid foundation for this journey.
What you’ll learn and how you can apply it
- When to use Excel for data analysis and reporting and when to use Python
- How Python can automate common data preparation and manipulation tasks often done in spreadsheets
- Where Python differs from Excel in how it stores and operates on data
And you’ll be able to:
- Execute Python code directly within your Excel workbook.
- Generate data analyses and visualizations with Python that would be difficult or impossible in Excel
- Navigate and run code within Jupyter notebooks.
- Completely automate the production of Excel workbooks using Python
This live event is for you because...
- You're an analyst responsible for collecting, analyzing, and interpreting data for business insights.
- You’d like to speed up, automate, and validate your reporting and analysis using open source software.
- You’re a spreadsheet user interested in learning more about data science or software development.
Prerequisites
- A working knowledge of basic tasks and functions in Excel, including sorting and filtering, IF statements, conditional aggregates like SUMIF() and COUNTIF(), and PivotTables and VLOOKUP()
- Familiarity with programming concepts like variables, arrays, functions, methods, and iterators (in any language, not necessarily Python)
- Download an Anaconda distribution of Python on your computer (instructions)
- Gain access to the Python in Excel preview by joining the beta channel of the Microsoft 365 Insider program (instructions)
Recommended preparation:
- Read “Preliminaries” and “Python Language Basics, IPython, and Jupyter Notebooks” (chapters 1 and 2 in Python for Data Analysis, second edition)
Recommended follow-up:
- Read Advancing into Analytics (book)
- Read Automate the Boring Stuff with Python, second edition (book)
- Read Python for Data Analysis, second edition (book)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Python in Excel: First steps (55 minutes)
- Presentation: Understanding the Python in Excel environment, loading Excel data into Python, converting Python objects to Excel values
- Exercises: Explore different ways to load Python data into Excel: ranges versus tables versus Power Query
- Q&A
Break (5 minutes)
From “That’s hard in Excel” to “That’s easy in Python!” (55 minutes)
- Presentation: Python in Excel for data analysis – data profiling, descriptive statistics, time series analysis; Python in Excel for data visualizations – distribution plots, pairplots, small multiples
- Exercises: Create analyses and visualizations using Python in Excel that would otherwise be difficult to build in Excel
- Q&A
Break (5 minutes)
There’s more to Python and Excel than Python in Excel (60 minutes)
- Presentation: Exploring what Python in Excel can and can’t do, introducing Excel automation with openpyxl, working with Python from Jupyter notebooks, adding conditional formatting, column adjustments and more to Excel from Python, surveying other Python packages for Excel
- Jupyter Notebook exercise: Fully automate the production of an Excel workbook from Python
- Q&A
Your Instructor
George Mount
George Mount is the founder and CEO of Stringfest Analytics, a consulting firm specializing in analytics education and upskilling. He has worked with leading bootcamps, learning platforms and practice organizations to help individuals excel at analytics.
George regularly blogs and speaks on data analysis, data education and workforce development and is the author of Advancing into Analytics: From Excel to Python and R (O'Reilly Media, 2021) and _Modern Data Analytics in Excel: Using Power Query, Power Pivot and More for Enhanced Data Analytics _(O'Reilly Media, 2024). He is a recipient of the Microsoft Most Valuable Professional (MVP) award for exceptional technical expertise and community advocacy in the field of Excel.
George holds a bachelor’s degree in economics from Hillsdale College and master’s degrees in finance and information systems from Case Western Reserve University. He resides in Cleveland, Ohio.