In this talk, I’d be talking about Zarr, an open-source data format for storing chunked, compressed N-dimensional arrays. This talk presents a systematic approach to understanding and implementing Zarr by showing how it works, the need for using it, and a hands-on session at the end. Zarr is based on an open technical specification, making implementations across several languages possible. I’d mainly talk about Zarr’s Python implementation and show how it beautifully interoperates with the existing libraries in the PyData stack.
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PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people.
pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted!
If you don’t finish your contribution during the event, we hope you will continue to work on it after the tutorial. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html .
PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people.
pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted!
If you don’t finish your contribution during the event, we hope you will continue to work on it after the tutorial. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html .