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732A98 Visualization

Course Materials


Course literature

  • WGK: "Interactive Data Visualization" by Ward, Grinstein and Keim. Second edition, ISBN 9781482257373 (main course book)
  • SIE: Interactive web-based data visualization with R, plotly, and shiny by Carson Sievert. Accessible here
  • SR: Text Mining with R by Silge and Robinson. Accessible here

Note: Pictures in the lecture slides and codes are partly borrowed from these sources.


Topic 1: Introduction to Data Visualization. Introduction to Ggplot2, Plotly and Shiny.

Read:
  • WGK, ch 1.1, 1.3-1.8 and 2
  • Manual to InkScape, accessible here
  • Wickham, H. (2010). A layered grammar of graphics. Journal of Computational and Graphical Statistics, 19(1), 3-28.
  • SIE, ch 1, 2.1, 2.3, 13, 32
  • GGplot2 book by Wickham, H., ch 1-7, accessible here (browse through)
  • Basics of Shiny Apps, accessible here
  • Important: Some tutorials on DPLYR and TIDYR packages, for ex this one.
Lecture 1a: Slides are here
Lecture 1b: Slides are here
Tutorial: here
Codes: app1.R, app2.R, app3.R
Lab 1: See LISAM, Submissions.

Topic 2: Perception and Visualization. Data preprocessing

Read:
  • WGK, ch. 3.1, 3.3, 3.5, 13
  • Cox, AA, and Cox, T.F.: "Multidimensional scaling." Handbook of data visualization. Springer, Berlin, Heidelberg, 2008. 315-347.
  • SIE, ch 3,5,6
Lecture 2: Slides are here
Codes: barChart.R, metricMDS.R, nonMetricMDS.R, shephard.R, music-sub.csv
Lab 2: See LISAM, Submissions.

Topic 3: Basic graphs. Geospatial visualization.

Read:
  • WGK, ch. 6
  • SIE, ch 4,7 and 13
Lecture 3: Slides are here
Codes: densityPlots.R, splom.R, surfacecontour.R, choroplethMap.R, lineMaps.R, symbol_dotMap.R, GBcities.csv
Lab 3: See LISAM, Submissions.

Topic 4: Multivariate data visualization

Read:
  • WGK, ch. 8
  • Hahsler, M., Hornik, K., & Buchta, C. (2008). Getting things in order: an introduction to the R package seriation. Journal of Statistical Software, 25(3), 1-34
  • (Browse through) Ankerst, M., Berchtold, S., & Keim, D. A. (1998, October). Similarity clustering of dimensions for an enhanced visualization of multidimensional data. In Information Visualization, 1998. Proceedings. IEEE Symposium on (pp. 52-60). IEEE.
  • Becker, R. A., Cleveland, W. S., & Shyu, M. J. (1996). The visual design and control of trellis display. Journal of computational and Graphical Statistics, 5(2), 123-155.
Lecture 4: Slides are here
Codes: seriation.R,radarChart.R, parallelCoord.R, heatmap.R, facetsTrellis.R
Lab 4: See LISAM, Submissions.

Topic 5: Graph visualization. Animation.

Read:
  • WGK, ch. 9, 12.7
  • SIE, ch. 14
  • Cook, D., Buja, A., Lee, E. K., & Wickham, H. (2008). Grand tours, projection pursuit guided tours, and manual controls. In Handbook of data visualization (pp. 295-314). Springer, Berlin, Heidelberg.
  • Introduction to network analysis with IGRAPH, accessible here
  • Working with visNetwork, accessible here
  • Working with ggraph, accessible here
Lecture 5: Slides are here
Codes: network.R, motion.R, tours.R, treeMap.R, treeVis.R, sunBurst.R, circlePacking.R, edges.csv, nodes.csv,
Lab 5: See LISAM, Submissions.

Topic 6: Interactive visualization. Text visualization.

Read:
  • WGK, ch. 10,11
  • SIE, ch. 15, 16
  • SR, ch. 1, 2.1, 2.2, 2.5, 3.1, 3.3, 4.1.1, 4.1.4
  • Van Ham, F., Wattenberg, M., & Viégas, F. B. (2009). Mapping text with phrase nets. IEEE transactions on visualization and computer graphics, 15(6).
  • Wattenberg, M., & Viégas, F. B. (2008). The word tree, an interactive visual concordance. IEEE Transactions on Visualization & Computer Graphics, (6), 1221-1228.
Lecture 6: Slides are here
Codes: interaction.R, interactionWithShiny.R, steamGraph.R, wordCloud.R, textProcessing.R, phraseNet.R, australian-crabs.csv, flea.csv, romeo.txt
Lab 6: See LISAM, Submissions.



Page responsible: Oleg Sysoev
Last updated: 2023-08-01