Exploring Python in Excel

Are you interested in using your Python skills within Excel? Would you like to share a data science project or visualization as a single Office file? This week on the show, we speak with Principal Architect John Lam and Sr. Cloud Developer Advocate Sarah Kaiser from Microsoft about Python in Excel.

John shares the multi-year journey of adding Python to Excel. He describes how the project moved beyond writing user functions in Python to something much more elaborate. He details assembling a team with diverse skills in interface design, languages, and security.

Sarah discusses the instant convenience of having familiar Python and pandas techniques at your fingertips inside Excel. We cover typical data science workflows and the potential of interactive visualizations within a spreadsheet. We also share multiple resources for you to learn more.

Note: Python in Excel is currently a preview accessible by joining the Microsoft 365 Insider Program and selecting the Beta Channel.

Course Spotlight: Data Cleaning With pandas and NumPy

In this video course, you’ll learn how to clean up messy data using pandas and NumPy. You’ll become equipped to deal with a range of problems, such as missing values, inconsistent formatting, malformed records, and nonsensical outliers.

Topics:

00:00:00 – Introduction

00:01:53 – Sr. Cloud Developer Advocate Sarah Kaiser

00:02:46 – Principal Architect John Lam

00:04:08 – What is Dev Div?

00:04:33 – Python data science inside Excel

00:09:05 – Designing features with a focus on sharing

00:14:28 – Moving between Excel and Python objects

00:18:20 – What libraries are imported by default?

00:23:11 – Sharing a workbook with others

00:26:12 – Recalculating data workflow

00:30:07 – Working in Jupyter Notebook vs Excel

00:33:03 – Creating a Python object

00:33:38 – Video Course Spotlight

00:35:02 – More history and project team

00:40:19 – Immediate wins of having Python in Excel

00:42:28 – Interactive visualizations

00:44:34 – Answering security concerns

00:49:17 – Limitations and potential

00:54:34 – Creating demo projects

01:00:25 – Resources to learn more

01:02:59 – What are you excited about in the world of Python?

01:10:41 – What do you want to learn next?

01:12:09 – How can people follow your work online?

01:13:26 – Thanks and goodbye

Show Links:

Python in Excel – Python to Excel - Microsoft 365

Get started with Python in Excel - Microsoft Support

Python in Excel DataFrames - Microsoft Support

Open-source libraries and Python in Excel - Microsoft Support

User guide and tutorial - seaborn 0.13.1 documentation

Assessing and Restoring Reproducibility of Jupyter Notebooks - IEEE Conference Publication - IEEE Xplore

Book of Python in Excel - John Lam’s Website

GitHub - microsoft/python-in-excel - Python in Microsoft Excel

Use Python in Excel to enhance your data science - Python Day - YouTube

Introducing Python in Excel: The Best of Both Worlds for Data Analysis and Visualization - Microsoft Community Hub

PEP 703 – Making the Global Interpreter Lock Optional in CPython - peps.python.org

Dr. Sarah Kaiser (@[email protected]) - Fosstodon

John Lam (@john_lam) - X

Level up your Python skills with our expert-led courses:

Data Cleaning With pandas and NumPy

Python Histogram Plotting: NumPy, Matplotlib, Pandas & Seaborn

The pandas DataFrame: Working With Data Efficiently

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