PyData Prague #12 - Minutes to a Degree

Hello Python & Data maniacs!
The 12th Prague PyData meetup will take place at new LMC offices. As usual, the talks will start at 18:30 but we encourage you to come as soon as 18:00 to enjoy the opportunity to socialize and refresh yourselves (which you can continue doing during the break and after the talks). Our main goal is to build the community around Python and data and make it welcoming to people of various skills and experience levels.

⚡ 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.

📢 Talk 1: Machine Translation Usable in Practice, Let's Move to Minuting
Ondřej Bojar (Charles University profile here)

During the last eight years of deep neural networks rewriting the landscape of machine translation (MT), we got to the stage where MT is clearly usable and progress hard to measure for language pairs covered well with data. Let us now apply similar technologies to the task of automatic creation of minutes from project meetings ("minuting"). With a similar devotion, we should make automatic minutes usable in a couple of years. And perhaps machine understanding will be necessary at last; to my surprise, it was not needed for MT.

📢 Talk 2: A Gentle Introduction to Spatial Data in the Pandas Ecosystem
Martin Fleischmann

"Everything is related to everything else, but near things are more related than distant things”
That is the first law of geography. But how do we apply it to data science? How do we ensure that our analysis has a spatial dimension and that it can be mapped? How can we combine data based on their location? Are there any spatial patterns? These are the questions you will be able to answer after a gentle introduction to spatial data science in the pandas ecosystem. We will start with a brief explanation of the key concepts like geometries and projections to introduce GeoPandas, a package that brings geo to pandas. Then we’ll check how the ecosystem supporting GeoPandas looks like and what it offers, followed by a short excursion to the realm of spatial analytics using the packages from the PySAL (Python Spatial Analysis Library) project. We will be able to expand traditional exploratory data analysis with spatial using the esda package, interpolate data between different spatial units using the tobler package or analyse the structure of cities using momepy. Finally, when the data begin to look too large to work with, we switch to distributed dask-geopandas and wrap up our journey with spatial operations powered by Dask somewhere in the cloud.

Please, RSVP here.
See you soon,
PyData Prague team