Data visualization using Python and Jupyter Notebooks

To book, please visit:

We will introduce displaying and exploring data with Python in an interactive coding environment (Jupyter Notebooks). We will cover some of the history of data visualization as well as the wealth of options and opportunities for graphical display of data today. The focus of the examples will be the Python programming language and in particular the libraries. The talk is meant as a starting point and will providing links to resources for further learning.

Topics to be covered
Exploring and communicating with data.
Why use interactive notebooks in data visualization?
Jupyter: installing and getting started.
Tools for data visualization.
Data viz: the Python ecosystem.
Holoviz and other resources for data visualization.

Learning Objectives
Methods of communication with data
The value of interactive notebooks in data visualization?
Installing Conda and Jupyter
High-level vs low-level control of plotting
Create basic plots for numerical and geographical data
Export plots for web and print

Prior knowledge required
Some programming experience would be useful. Code will be in Python, but lack of experience should not be a barrier for participation.

Intended Audience
Anyone who is exploring and analysing data. Researchers learning Python.

Type of Session
Short talk plus live-coding and a Q&A. Option to follow along with either pre-shared notebooks or with and any web browser.

Software Required
None necessary, although materials could be made available for those who have brought laptops with them with Miniconda (, or the full Anaconda Python distribution installed.