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Scientific Python Course (2025)

  1. Jupyter
  2. Numpy
  3. Pandas
  4. Seaborn
  5. Scipy
  6. Statsmodels
  7. Scikit-learn

Materials requirements

We will use jupyter notebook and some python libraries. The are 2 ways to create a suitable environment for this course:

  • from a python environment
  • from a conda/mamba environment

But whatever your choice you need to have git installed to get the course materials

from virtual environment

Warning do NOT use python 3.14

To create a python environment (to do only once)

python3 -m venv Scientific_Python
cd Scientific_Python
source bin/activate
git clone https://github.com/C3BI-pasteur-fr/scientific-python.git  Scientific_Python_ori
cp -r Scientific_Python_ori My_course
cd My_course
pip install -r requirements.txt

To exit from the environment

deactivate

To reactivate the environment

cd Scientific_Python
source bin/activate

# to run jupyter notenook server
jupyter-lab

Windows users must run Scripts\activate.bat (in cmd.exe) or Scripts\activate.ps1 (in PowerShell) instead of source bin/activate.

from conda/mamba (recommended for windows guys)

To create a Conda/mamba environement you have to install Conda(anaconda or miniconda) or mamba Then create your environement (to do only once)

mamba env create -n Scientific_Python -c conda-forge bioconda
conda activate Scientific_Python

# get the course materials
git clone https://github.com/C3BI-pasteur-fr/scientific-python.git Scientific_Python_ori
cp -r Scientific_Python_Course_ori  My_course
cd My_course

# install prerequisites
mamba install --file requirements.txt

To exit from the conda environment/mamba

conda deactivate

To reactivate the environment

conda activate Scientific_Python

# to run jupyter notebook server
jupyter-lab