Students are taught the possibilities and importance of data visualisation. They are ready to use
\nvisualisation for the purpose of presenting arbitrary data, for the purpose of data analysis and visual data
\nmining with the aim of synthesising new knowledge. They are able to use the R language, JavaScript and
\nalternative open-source solutions for visualisation purposes.<\/p>\n
Visual data mining. Examples of visual data mining. Outliers, patterns, trends. Basics of creating
\npresentation graphics using R, a standard and a powerful tool for various visualisation applications.
\nVisualisation with JavaScript. Other open-source solutions. Detailed and complete code
\nexamples for line and column graphics, for population pyramids, Lorenz curves, box plots, scatter plots,
\ntime series, radial polygons, Gantt charts, heat maps, bump mapping, mosaic and balloon graphics,
\ncartograms, chord diagrams, as well as a series of different types of thematic graphics which can be
\ncreated using R’s basic graphic system. Social network visualisation. Social network parameters. Gephi
\n– open-source software.<\/p>\n
In R and other tools, students visualise the obtained data, as well as the data they scrape themselves.
\nThey compare the results and assess their usability.<\/p>\n","protected":false},"excerpt":{"rendered":"
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 … Read more<\/a><\/p>\n Read more<\/a>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[199],"tags":[],"class_list":["post-14057","post","type-post","status-publish","format-standard","hentry","category-subjects"],"acf":[],"yoast_head":"\n