JupyterCon 2023

Getting Started With Python

  • 05-11, 10:30–13:00, Room 3 (Tutorial)
  • 05-11, 14:00–16:30, Room 3 (Tutorial)

All times in Europe/Paris

While the tutorial attendance is comprised in the conference pass, we ask you to register for this tutorial on https://www.jupytercon.com/tickets as the seats available are limited.


This tutorial is an introduction to Python programming using JupyterLab. It is aimed at students with little or no programming experience, and is intended as a follow-along tutorial. It draws inspiration from the late Boston Python Workshop and uses materials from Software Carpentry, which are available under the CC-BY license.

If you register to the tutorial, it is very important that you install the required software ahead of the tutorial. Please refer to the setup instructions below and follow them step by step.

Setup instructions

  1. Open https://docs.conda.io/en/latest/miniconda.html in your web browser.
  2. Click on the latest installer link depending on your OS: Miniconda3 Windows 64-bit for Windows, Miniconda3 macOS Intel x86 64-bit pkg for MacOS, Miniconda3 Linux 64-bit for Linux.
  3. Install Python 3 by running the Miniconda installer (double click on the downloaded file) using all of the defaults for installation. On MacOS and Linux, make sure to check Add Miniconda to my PATH environment variable.
  4. On Windows: open the Anaconda Prompt from the Start menu. On MacOs and Linux: open the Terminal app. Run the following lines (i.e., copy-paste them in the window that just opened up and press Enter):
conda config --add channels conda-forge
conda install ipywidgets=7.6.5 jupyterlab=3.5.3 matplotlib=3.7.0 pandas=1.5.3 voila=0.3.6

You have just installed the packages required to follow the tutorial.
5. Type jupyter lab in the Anaconda Prompt / Terminal. After JupyterLab has launched, click the “Python 3” button under “Notebook” in the launcher window, or use the “File” menu, to open a new Python 3 notebook.
6. To test your setup, run the following code in a cell of the notebook:

import pandas as pd
table = pd.DataFrame(
    {'Time': [0, 1, 2, 3],
     'Emma': [0, 10, 20, 30]}

You should see a plot display right below the code cell.

Marianne Corvellec is a core developer of scikit-image, a popular Python library for scientific image processing, where she specializes in biomedical applications. Her technical interests include data science workflows, data visualization, and best practices from testing to documenting. She holds a PhD in statistical physics from École normale supérieure de Lyon, France. Since 2013, she has been a regular speaker and contributor in the Python, Carpentries, and FLOSS communities.

Maria Teleńczuk, PhD, is a Data Scientist at Owkin and a PyLadies Paris Organiser. She is a firm believer in an open-source and advocate for good coding practices. She enjoys participating in initiatives which aim to empower people of various origins, ages and backgrounds.