Python For Plotting Timeseries & 3D Data - Qingkai Kong, Andy Haefner

Attending

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Qingkai Kong

I am PhD student at Berkeley Seismological Lab of Earth and Planetary Science Department. My research area is Earthquake Early Warning System, I am working on using your smartphones to detect earthquakes. I am also really interested in data science, now working on how to apply data science skills back to Seismology. You can chechout my Github here.

Code examples for my presentation can be found here.

Andy Haefner

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Code examples can be found here.

5:00pm Machine Learning Club

At 5:00pm, the Machine Learning Club will jump in and have a complementary talk on reproducible vizualizations using Lightning.

Abstract

Creating reproducible scientific research has been a goal of the academic community for as long as I have been a part of it and has seen great successes (such as the interactive Nature article and LIGO Gravitation wave analysis), in part due to the efforts of the Python (and Jupyter) community. But I like to believe that these efforts stem from a more human root cause to understand the world around us and as such should be relevant to anyone (not just the scientific Python community) trying to communicate the results of research.

In this talk give a brief history on why (and how) we need to make all of our analyses reproducible and how (web based) interactive visualizations are essential to making research much more accessible to the world at large. By creating a reusable (and extensible) chart using the Lightning visualization library I will highlight the role visualization plays in making analyses accessible to others and how web based technologies such as Javascript and D3 can liberate our results from the static prison of PDFs. And along the way I will (hopefully) show you the potential of interaction to change the hearts and minds of (colleagues) and the world.