Skip to content
Switch branches/tags

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Repository of Python examples

These examples accompany the lecture "High dimensional probability towards data science" held by Prof. Dr. Anita Winter in the summer term 2021 at the university of Duisburg-Essen, Germany.


This repository provides some examples as interactive Jupyter Notebooks. More about Jupyter Notebooks can be found on the homepage of the Jupyter Project. The notebooks are viewed through a web browser but need a running python kernel to run the code. This kernel can be run either locally or remotely via a cloud service like binder.

Run Notebooks locally


This guide assumes you have already python3 installed on your system.

In order to run the Notebooks locally I recommend jupyterlab. Installing jupyterlab via pip is very simple, just run

pip install jupyterlab

in a terminal. More information is again available on the pages of the Jypyter Project.

I also recommend using git (git installation) to download the latest version of the repository.

Get the sources

You can either download the source files directly from this repository or you can clone the whole repository using git:

git clone

Once you have cloned the repository you can update the sources at anytime using git fetch

cd high-dimensional-probability
git fetch origin
git pull

Be aware that this overwrites local changes on the source files.

Install dependencies

The repository comes with a list of dependencies in requirements.txt. To install all dependencies at once run

pip install -r requirements.txt

from within the projects folder.

Run the jupyter kernel

Finally run the jupyter kernel


This starts the kernel and should open jupyter-lab in the system's default browser. If for some reason this does not work, the command outputs a url to copy and paste into a browser of your choice.

Run Notebooks remotely

Easier but possibly slower is the usage of a cloud service like binder. This repository comes with pre-build binder instances for each notebook.

Erdos-Renyi Examples



Accompanying examples to the lecture "High dimensional probability: towards datascience" held at the University of Duisburg-Essen in the Summer term 2021



No releases published


No packages published