PyData Prague #8 - Collaborative dimensions

Covid-19 does not sleep but neither do we. The third season of PyData Prague meetups starts with the 8th meetup, for the first time a virtual one. This brings with it several changes (e.g. you will be responsible for your own refreshment and there is an even less formal dress code) but we believe the overall character of the event will be preserved: two interesting talks and enough (virtual) space for you to socialize. Our main goal is to build the community around Python and data and make it welcoming to people of various skills and experience levels.

The talks will start at 18.30 and after they finish, you will have time to discuss in breakout rooms. We will be using Zoom - the link is available in the details panel on the right.

📢 Talk 1: Jan Matas (Deepnote): Making data science notebook collaborative

Jupyter notebook is now one of the most popular tools for data scientists, even though it is fairly difficult to work with it in a team setting. In this talk, we will first explore how notebooks work under the hood, then we will discuss how we can build collaboration features to enable real-time editing (like google docs) and finally we will address some security challenges inherent to having collaborative data science tools in the cloud.

📢 Talk 2: Ondřej Grover (Institute of Plasma Physics, Czech Academy of Sciences): Xarray - more than Pandas in multiple dimensions

The Xarray library has in recent years become one of the de-facto standards for working with multi-dimensional datasets in Python. While calling it "a generalization of Pandas into multiple dimensions" gives a reasonable first impression, there is much more to it than that. For instance, the transparent and well structured API offers a concise handle on the depths of NumPy and Dask broadcasting magic. The API and helper functions also enable the construction of convenient and versatile wrappers of e.g. Scipy routines which then become applicable in any domain where data can be represented by Xarray containers. The talk will showcase the basic Pandas-like usage as well as some of the aforementioned advanced features.

⚡ If you are interested in giving a lightning talk (up to 5 minutes to present an idea, tool or results related at least to some degree to Python and/or data), please contact us before the event or at its beginning.

Please RSVP here and unregister if you know you are not able to attend. If you have any questions regarding the topics, timing, or anything else, don't hesitate to send us a message.