Introduction to data visualization in Python
Information
The estimated time to complete this training module is 3h.
The prerequisites to take this module are:
If you have any questions regarding the module content please ask them in the relevant module channel on the school Discord server. If you do not have access to the server and would like to join, please send us an email at school [dot] brainhack [at] gmail [dot] com.
Resources
This module is built around one Jupyter notebook and one set of exercises, all available in the module repository.
Original lecture
This module was first presented by Jacob Vogel during the QLSC 612 course in 2020, and the associated notebook is available here. (Note: if you did the BIDS module, the dataset to download is the same - ds000228! A few functions now throw warnings, you can ignore these, or fix them if you like.)
The video of the presentation is available below (1h09):
Exercise
In the exercise notebook (exercise_visu_en.ipynb), you will have to create static and interactive visualization to explore the phenotypic and fMRI data from the ADHD200 dataset available through nilearn.
The exercise is structured as follows:
- Part 1 : Exploring phenotypic data: you will visualize some clinical and demographic variables of the ADHD200 dataset.
- Part 2 : Exploring fMRI data: you will explore the functional fMRI data from the ADHD200 dataset through visualizations.
Important: follow the parameter specifications given in each question exactly — the exercise uses automated grading that compares results to reference values.
Follow up with your local TA(s) to validate you completed the exercises correctly.
More resources
Other great resources to get started with plotting in python:
Interactive plotting:
Gallery: