Data Visualization

Objectives

This course will teach how to create visualizations that effectively communicate the meaning behind data through visual perception. Concepts about human perception of graphic information as well as different ways of mapping different forms of quantitative and qualitative data will be addressed. We will use Python software to complete data visualization exercises aiming to explore visual interaction with data for analysis and communication.

General characterization

Code

200162

Credits

7.5

Responsible teacher

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

None

Bibliography

Tamara Munzner (2014). Visualization Analysis and Design. CRC Press.

 

Teaching method

Theoretical-practical classes related with Data Visualization concepts and specific software (Python) and Tableau.

Evaluation method

1st phase

  • Project report and presentation (50%).  
  • Test during the class (50%) (multiple choice and T or F questions, no minimum grade). There is no 1st phase exam.

 2nd phase

  • Project report and presentation (50%). It is not possible to improve the grade of the project. The date for delivery of the project is the same as in the 1st phase.
  • 2nd phase Exam (100%, or 50% if the projects was delivered and presented on 1st phase) (minimum grade of the exam is 9.5. The date of the 2nd phase exam is published in the exam’s calendar.

Subject matter

  • Introduction to visualization
  • Data Abstraction and data types
  • Marks and channels
  • Visualizing Tables.
  • Spatial Data.
  • Graphs. Networks and Trees.
  • Color.
  • Storytelling