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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

200176

Credits

4.0

Responsible teacher

Manuel Forjaz de Sampaio Sousa Lima

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.

Nathan Yau (2011). Visualize this – The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc.

Teaching method

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

Evaluation method

1st phase

  • Project report and presentation (70%).
  • All deliverables have a 2.5% penalty for each day after the deadline.
  • Test during classes (30%).
  • There is no 1st phase exam.

 

2nd phase

  • Project report and presentation (50%). The date of delivery of the report is the same of the first phase. It is not possible to improve the grade of the project presented on 1st phase.
  • 2nd phase Exam (50%). If the project is not delivered, the exam will count 100%. Check the date of the exam for the 2nd phase on the official exam calendar.

Subject matter

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