Data Visualization & Visual Analytics (elective) (WP)*

English version available soon

The participants:
• can describe data visualization and visual communication.
• can develop visualizations independently and use them for communication purposes.
• can work with different presentation tools and presentation libraries to present data and analysis results in a meaningful way.

None

• Evaluation tools with visual orientation, e.g. Bl tools such as MS PowerBl, Tableau, QlikView
• Display libraries, e.g. matplotlib. pyplot, gglot2
• Rules of visual communication, e.g. Hichert SUCCESSSS

• Chang, W. (2013): R Graphics Cookbook: Practical Recipes for Visualizing Data (Ed. 1), O'Reilly, Farnham (ISBN: 978-1449316952)
• Chen, C.; Härdle, W. K.; Unwin, A. (2008): Handbook of Data Visualization (Ed. 1), Springer, Berlin (ISBN: 978-3-662-50074-3)
• Dale, K. (2016): Data Visualization with Python and Javascript: Scrape, Clean, Explore & Transform Your Data (Ed. 1), O'Reilly, Farnham (ISBN: 978-1491920510)
• Murray, S. (2017): Interactive Data Visualization for the Web: An Introduction to Designing with D3 (Ed. 2), O'Reilly, Farnham (ISBN: 978-1491921289)

Seminar paper

English

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Lecture with discussion, interactive workshop, case studies

3