Planning a beginner open source sprint day for data scientists

Emily Thompson
Feb 23 · 10 min read

Preparation

Sprint day — February 18, 2019

“I have a fairly new machine so setting up my machine to communicate with GitHub was a great exercise to get started. It was like riding a bike after not doing it for a while. The other thing I learned was that package managers get better and better as the years go by! I remember when Macports was the only thing available. I had to set up Homebrew and pip and pipenv to even be ready to get started.”

— Katie

“First I tried to do an R repo but there didn’t seem to be many issues. So then I looked at statsmodels but none of the issues spoke to me. So then I looked at pandas. There were more issues to pick from that were related to documentation and good for beginners. I also feel most comfortable with pandas and so thought it would be a good repo to dig into.”

— Alyssa

“I poked around on numpy and scikit-learn before settling on pandas — their ‘how to contribute’ docs were generally helpful and friendly”

— Liz

Everyone concentrating on finding issues. Dads in the back present for moral support and baby duty.

“Be bold! Not sure if you have a working C compiler and can’t quite understand the instructions? Just try building and see if it works! (It did!) It’s pretty hard to seriously screw up your environment — it’s why we have local copies that we can nuke and start over if things go wrong. Things are always much more fun with support from a group!”

— Liz

Future contributors

“AHHH MY CHABGED WAS MEGED DGEKEMD [sic]”

— Alyssa, seconds after her PR was accepted.

“Pull-requests can be easy and I started out knowing nothing, now I know a little and can push myself forward to learn a lot. I feel much more prepared to contribute. Start simple. Give yourself some credit. Eat cookies. Follow up.” — Katie

Participants: alyssafuward, wsoofi, ethompso28, ehines623, kcamrine, aggiezx

Lessons learned

Special thanks!

Resources

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