23-27 July 2018
Princeton University
US/Eastern timezone

The Scientific Python Ecosystem

25 Jul 2018, 11:00
1h 30m
407 Jadwin Hall (Princeton University)

407 Jadwin Hall

Princeton University

Princeton Center For Theoretical Science (PCTS)


Jim Pivarski (Princeton University)


In recent years, Python has become a glue language for scientific computing. Although code written in Python is generally slow, it has a good C API and Numpy as a common data abstraction, and many data processing, statistical, and most machine learning software packages have a Python interface as a matter of course.

This tutorial will introduce you to core Python packages for science— Numpy, Pandas, SciPy, Numba, Dask— as well as HEP-specific tools— uproot, histbook, NumPythia, pyjet— and how to connect them in analysis code.

Presentation Materials