JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives:

• 1. To learn data wrangling techniques
• 2. To introduce visual perception and core skills for visual analysis

Course Outcomes

Upon completion of the course, the students will be able to

• 1. Perform data wrangling
• 2. Explain principles of visual perception
• 3. Apply core skills for visual analysis
• 4. Apply visualization techniques for various data analysis tasks
• 5. Evaluate visualization techniques

UNIT - I

Data Wrangling: Need of data cleanup, data clean up basics – formatting, outliers, duplicates, Normalizing and standardizing data.

UNIT - II

Introduction of visual perception, visual representation of data, Gestalt principles, information overloads. Creating visual representations, visualization reference model, visual mapping, visual analytics, Design of visualization applications.

UNIT - III

Classification of visualization systems, Interaction and visualization techniques misleading, Visualization of one, two and multi-dimensional data, text and text documents.

UNIT - IV

Visualization of groups, trees, graphs, clusters, networks, software, Metaphorical visualization.

UNIT - V

Visualization of volumetric data, vector fields, processes and simulations, Visualization of maps, geographic information, GIS systems, collaborative visualizations, evaluating visualizations.

TEXT BOOKS:

• 1. Jacqueline Kazil and Katharine Jarmul, Data Wrangling with Python: Tips and Tools to Make Your Life Easier, O’Reilly.
• 2. Ward, Grinstein Keim, Interactive Data Visualization: Foundations, Techniques, and Applications. Natick A K Peters, Ltd.

REFERENCE:

• 1. E. Tufte, The Visual Display of Quantitative Information, Graphics Press.