Data Visualisation

Objectives and Outcomes
Students are taught the possibilities and importance of data visualisation. They are ready to use visualisation for the purpose of presenting arbitrary data, for the purpose of data analysis and visual data mining with the aim of synthesizing new knowledge. They can use R language, JavaScript and alternative open-source solutions for visualization purposes.

Lectures
Visual data mining. Examples of visual data mining. Outliers, patterns, trends. Basics of creating presentation graphics using R, a standard and a powerful tool for various visualization applications. JavaScript capabilities in visualization. Other open-source solutions. Detailed and complete code examples for line and column graphics, for population pyramids, Lorenz curves, box plots, scatter plots, time series, radial polygons, Gantt charts, heat maps, bump graphics, mosaic and balloon graphics, cartograms, chord diagrams, as well as a series of different types of thematic graphics which can be created using R’s basic graphic system. Social Network Visualization. Social Network Parameters. Gephi – open-source software.

Practical classes
In R and other tools, students visualize the obtained data, as well as the data they scrape themselves. They compare the results and assess their usability.