Python packages for the course

You should have Python (3.11 or later) running on your laptop! Most modern laptops already have Python installed. Possibly, you'll have to update Python, and we recommend 3.13.9, as the latest version 3.14.0 is just out 7th of October 2025, and thus not very "mature" (but anything 3.11 and up is OK). This should be where you have the programs used in the course and develop a toolbox of data analysis methods.

An additional option is 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 and access, we strongly recommend, that you have Python installed on your laptop (possibly through an Anaconda environment).

Python packages needed:

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:
  • matplotlib - The Python standard for plotting graphs and histograms.
  • numpy - Numerical Python, with powerful N-dim arrays and linear algebra commands.
  • scipy - A collection of tools for scientific computing, including "stats" for statistics.
  • iminuit - The Python interface to the minimisation package Minuit for fitting (currently v2.31.3 is the latest).
  • pandas - Data reading, analysis, and manipulation tool.
  • sympy - Analytic calculation library, very useful for differentiation and integration within Python code.

    If you are using conda, then the following is a guide to install all required packages in a separate conda environment:
    1. Download provided AppStat25_environment.yaml file.
    2. In your terminal run the following command to install the environment: "conda env create -f AppStat25_environment.yaml"
           Note: installation requires ~1G of disk space.
    3. Everything is ready. To activate the 'appstat25' environment, type: "conda activate appstat25"
           To deactivate: "conda deactivate"
           To remove the environment with its packages when you don't need it: "conda remove --name appstat25 --all"

    If the above doesn't work, please write us.

    Python packages that are possibly useful:

    In addition to the above packages, you/we will surely use more packages. One continuously find additional packages, which makes life easier, your plotting more clear, and your coding more powerful. Below are some examples for inspiration.
  • seaborn - Plotting library built on top of Matplotlib and contains many nice tools for statistical visualization.
  • iwidgets - For interactive plots.
  • Last updated 6th of November 2025.