Data Visualization Project

Groups constitution

Most of the students will be working in groups of 3. If the number of students is not a multiple of 3, we will also form groups of 4 (as few as possible).

Project data requirements

The dataset must be relevant in order to use the concepts and the different data visualization techniques we will learn during this course.
The teacher will validate the dataset

Grading criteria

  • 5 points for the substance of the story you will tell
  • 9 points for the usage of the different concepts and data visualization techniques
  • 3 points for your proficiency with matplotlib
  • 3 points for your proficiency with bokeh

Deliverable

  • A bokeh server application (this is the recommended option)
  • A notebook with the code and the visualizations
  • A one page report of the project

Bokeh server applications seem to be the easiest to implement. Indeed, interactions with JupyterLab (or any browser based environment for execution or rendering) implies implementing by hand the logic of update when using widgets. Therefore, without this very low level logic implementation, bokeh looses some very interesting features.

Step by step guide

StepSessionMilestoneDeliverable
1Session 1Group formationGroups of 3-4 students formed
2Session 2Dataset selectionInitial dataset chosen by group
3Session 2Project planningProject planning (ask teacher's opinion)
4Session 3Data validationDataset approved by teacher
5Session 3Story scriptingPreliminary story outline & key insights identified
6Session 3-4First graphsInitial visualizations with matplotlib
7Session 4Advanced visualizationsInteractive graphs with bokeh
8Session 5Final polishComplete notebook + one-page report
9Session 5PresentationProject presentation to class
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