Difference between revisions of "Lesson05"
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* [https://www.tableau.com/learn/whitepapers/visualizing-survey-data?ref=wc&signin=87976443b721a885b33a300166b02e22 Visualizing Survey Data] | * [https://www.tableau.com/learn/whitepapers/visualizing-survey-data?ref=wc&signin=87976443b721a885b33a300166b02e22 Visualizing Survey Data] | ||
* [https://onlinelibrary-wiley-com.libproxy.smu.edu.sg/doi/full/10.1002/wics.1192 Mosaic Plots] | * [https://onlinelibrary-wiley-com.libproxy.smu.edu.sg/doi/full/10.1002/wics.1192 Mosaic Plots] | ||
| + | * [https://www.jstatsoft.org/article/view/v057i05 Design of Diverging Stacked Bar Charts for Likert Scales and Other Applications] | ||
* [https://kosara.net/papers/2010/Kosara_BeautifulVis_2010.pdf Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project] | * [https://kosara.net/papers/2010/Kosara_BeautifulVis_2010.pdf Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project] | ||
Revision as of 22:30, 23 September 2018
ISSS608 Visual Analytics and Applications
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Contents
Readings
Core Readings
- Visualizing Survey Data
- Mosaic Plots
- Design of Diverging Stacked Bar Charts for Likert Scales and Other Applications
- Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project
Optional Readings
- Visualizing Survey Data from Data Revolution
- Do not use averages with Likert scale data
- Visualizing Contingency Tables
- Multivariate Categorical Data-Mosaic Plots
- Understanding Area Based Plots: Mosaic Plots
- Mosaic Plots and Their Variants
- Social Factors That Influence Use of ICT in Agricultural Extension in Southern Africa
- Visualizing Defect Percentages with Parallel Sets
- Parallel Sets vs. Mosaic Plots (Take I)
- Discovery Exhibition: Parallel Sets
R Methods
Ternary Plot
- R packages for creating ternary plot
Heatmap
- Using R to draw a Heatmap from Microarray Data
- R packages for creating heatmap
- heatmap() [R base function, stats package]: Draws a simple heatmap.
- heatmap.2() [gplots R package]: Draws an enhanced heatmap compared to the R base function.
- pheatmap() [pheatmap R package]: Draws pretty heatmaps and provides more control to change the appearance of heatmaps.
- Heatmap() [ComplexHeatmap R/Bioconductor package]: Draws, annotates and arranges complex heatmaps (very useful for genomic data analysis)
- Superheatmap
- d3heatmap() [d3heatmap R package]: Draws an interactive/clickable heatmap
