PyData Yerevan Open Source pandas Sprint

About the Event: 

PyData Yerevan invites you to the Open Source Sprint aimed at contributing to pandas!

pandas is a data-wrangling platform for Python widely adopted in the scientific computing community.

What to expect during the Sprint?

This Newcomer Sprint will guide you as a new contributor on how to make your own contributions to the open source library.

During the sprint, you will:

• Create your own development environment or use a remote development setup
• Learn about how you can contribute and what to expect
• Start working (and hopefully finishing) your first pull request!

In case you do not finish your contribution, you can continue to work on it after the Sprint.

What are the requirements to participate?

• Working knowledge of Python
• Use of own laptop
• Github account
• Git installed on your laptop

📌Date: June 25

🕖Time: 7:00-9:00pm

📍Location: Room 415W, PAB; American University of Armenia

Agenda

7:00-7:10pm – Welcome and networking

7:10-7:30pm – Introduction: how to set up your development environment, how to contribute, and what you can work on

7:30-9:00pm – “Office hours,” during which you will be mentored through setting up a development environment and making your first contribution to pandas

Attendees 

Everyone is welcome to attend this session! If you have never contributed to open-source software before, then you will learn how to do so.

If you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. If you do not have much experience with contributing, you might expect to spend time “learning by doing.”

🔗 Register by June 20: https://forms.gle/zqvgVSNu1BnCwLQ7A 

Please note that seats to attend the Sprint are limited, so registration is based on a first-come-first-serve basis.

About the Speaker 

Patrick Hoefler is a member of the pandas core team and a Dask maintainer. He is currently working at Coiled, where he focuses on Dask development and the integration of a logical query planning layer into Dask to make it more competitive with Spark. He holds an M.S. degree in mathematics and is currently working toward an M.S. in software engineering at the University of Oxford.

Hoefler has been a member of the pandas core team since early 2021 and focuses his development time on pandas internals, i.e., implementing Copy-on-write and better Apache Arrow support. He has held numerous sprints for different PyLadies chapters, together with organizers from the PyLadies ecosystem. He is a regular speaker at different PyData and PyCon conferences.