Python packages needed/recommended

Most modern laptops already have Python installed, so always check, if that is the case, before installing further!

However, we will mainly/also be running Python through a Jupyter notebook on the science faculty server ERDA, so in principle a browser is enough. But in order to be able to run your Python code independently of network, we strongly recommend, that you also have Python 3.6+ installed on your laptop (possibly through an Anaconda environment.

Python is often used with packages, which enables new (and often extremely useful and fast) features possible in your programs.
We will of course make use of packages (the most common ones, and a few specific for statistics), which in this course are:

  • scipy - A collection of tools for scientific computing.
  • numpy - Numerical Python, with powerful N-dim arrays and linear algebra commands.
  • matplotlib - The Python standard for plotting graphs and histograms.
  • iminuit - The Python interface to the minimisation package Minuit for fitting.
  • seaborn - Plotting library built on top of Matplotlib and contains many nice tools for statistical visualization. If the above doesn't work, please write us.
    Last updated 5th of November 2019.