Sarah Kaiser
Sarah has spent most of her career developing technology in the lab, from virtual reality hardware to satellites. She got her PhD in Physics by starting plasma fires with lasers, Python, and Jupyter Notebooks. She has also written tech books for folks of all ages, including ABCs of Engineering and Learn Quantum Computing with Python and Q#. As a Cloud Developer Advocate for Python at Microsoft and a Python Software Foundation Fellow, she finds all kinds of new ways to build and break OSS tools for data science and machine learning. When not at her split ergo keyboard, she loves boating in the Seattle area, laser cutting everything, and playing with her German Shepard, Chewie.
Sessions
Spreadsheets are one of the most common ways to share and work with data which helpfully also works great in Python! In this tutorial, we will cover some of the basics and best pratice of consuming and producing spreadsheets in Python as well as a deep dive into how to run Python directly in your spreadsheets. We will introduce and dive deep into the new Python in Excel features as well as the Anaconda Toolbox for Excel add-in.
Working with data in grids or spreadsheets is great for collaboration as there are many different tools to view and edit the files. Data science workflows often include packages like openpyxl to create, load, edit, and export spreadsheets that then are shared with others who can use other tools like Excel, Google Sheets, or IDEs to view them. The new Python in Excel feature as well as the Anaconda Toolbox add-in provides the tools to run Python directly in cells in a spreadsheet, making it easier for Pythonistas to access and collaborate on code. This talk will introduce how these features work, demo collaborating on Python code in a worksheet, and talk about some case studies where these tools have been used to teach and collaborate with Python.