Open and Reproducible Data Visualization
Open and Reproducible Data Visualization
with demos in Python

May 10, 2024, 4 pm
In-person: Thompson House Restaurant
Online: https://mcgill.zoom.us/j/8332985940

Kendra Oudyk
PhD candidate, McGill University

Kendra is a PhD candidate in the lab of Jean-Baptiste Poline, where she works on neuroimaging meta-research.

Abstract

This talk explores the principles and practices of open and reproducible data visualization, with demonstrations in Python. We will cover best practices for creating transparent, shareable, and reproducible visualizations, emphasizing the importance of open-source tools and reproducible workflows.

Key topics include:

  • Data visualization principles and best practices
  • Demonstrations of visualization techniques using Python libraries such as Matplotlib, Seaborn, and Plotly
  • Documenting code for reproducible data visualization pipelines

Attendees will learn how to create a wide range of visualizations, and how to document their code for full reproducibility. Whether you are new to data visualization or looking to improve your skills, this talk will provide you with the knowledge and tools you need to create effective and transparent visualizations.

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This event is organized by the Open Science Office Hours (OSOH) and the Tanenbaum Open Science Institute (TOSI) Trainee Council. We are grateful to have funding by TOSI and the McConnell Foundation

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