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ISSS608 Visual Analytics and Applications
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Visually Driven Data Analytics Packages in R
Contents
Content
- Introduction to Visually Driven Data Analytics Packages
- The motivation
- Basic considerations
- EDA and CDA
- Bivariate Matrix
- Trellis
- Correlation Matrix
- Correlogram
- Multivariate Data Visualisation
- Ternary Plot
- Glyphs or Star Plot
- Heatmap
- Parallel Coordinate Plot
- Space-constrained visualization of hierarchies
- Treemaps
- Sunburst diagram
Readings
Core Readings
Multivariate Methods
- An Introduction to Visual Multivariate Analysis
- Corrgrams: Exploratory Displays for Correlation Matrices
- Ternary Plot
- Multivariate Data Glyphs
- Parallel Coordinates
- Wikipedia: Heatmap
Treemaps
- Shneiderman, Ben (2008) Treemaps for space-constrained visualization of hierarchies (http://www.cs.umd.edu/hcil/treemap-history/)
- Extending the Utility of Treemaps with Flexible Hierarchy
Optional Readings
Multivariate Methods
- The scatter-plot matrix: a great tool
- A Graphical Display of Large Correlation Matrices
- Ternary Diagram
- Reading a Ternary Diagram
- Multidimensional Detective
- Parallel Coordinates
- Multivariate Analysis Using Parallel Coordinates
- Ghosts on the Radar — Why Radar Charts Are Easily Misread
- Keep Radar Graphs Below the Radar - Far Below
- A Critique of Radar Charts
- Radar: More Evil Than Pie
Treemaps
- Treemaps
- Discovering Business Intelligence Using Treemap Visualization
- 10 Lessons in Treemap Design
- Bederson, Benjamin B.; Shneiderman, Ben; Wattenberg, Martin (2002). "Ordered and quantum treemaps: Making effective use of 2D space to display hierarchies". ACM Transactions on Graphics. 21 (4): 833.
- Bruls, Mark; Huizing, Kees; van Wijk, Jarke J. (2000). "Squarified treemaps". In de Leeuw, W.; van Liere, R. Data Visualization 2000: Proc. Joint Eurographics and IEEE TCVG Symp. on Visualization
- US Economic Census Treemap
- TreeCovery: Coordinated dual treemap visualization for exploring the Recovery Act
- Juice's Stimulus Bill Explorer
- Fundexplorer
- Map of the Market
- The HIVE Group
- Truck Sales Slip, Tripping Up Chrysler
- Newsmap
- Obama’s 2011 Budget Proposal: How It’s Spent
R Packages
Correlation Matrix
- ggscatmat and ggpairs of GGally
- corrplot. A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering. In addition, corrplot is good at details, including choosing color, text labels, color labels, layout, etc.
- corrgram calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals.
Heatmap
Static heatmap
- heatmap() of R stats package. It draws a simple heatmap.
- heatmap.2() of **gplots** R package. It draws an enhanced heatmap compared to the R base function.
- pheatmap() of **pheatmap** R package. **pheatmap** package also known as Pretty Heatmap. The package provides functions to draws pretty heatmaps and provides more control to change the appearance of heatmaps.
- **ComplexHeatmap** package of R/Bioconductor package. The package draws, annotates and arranges complex heatmaps (very useful for genomic data analysis). The full reference guide of the package is available [here](https://jokergoo.github.io/ComplexHeatmap-reference/book/).
- **superheat** package: A Graphical Tool for Exploring Complex Datasets Using Heatmaps. A system for generating extendable and customizable heatmaps for exploring complex datasets, including big data and data with multiple data types. The full reference guide of the package is available here.
Interactive Heatmap
- heatmaply: Make Interactive Cluster Heat Maps Using 'plotly'
- d3heatmap d3heatmap: Make Interactive Heat Maps Using 'htmlwidgets' and 'D3.js.
- iheatmapr: Make complex, interactive heatmaps. Detail information are available at here.
Treemaps
- Treemap Package
- Creating a Treemap in R
- treemap: mapping to color palettes
- Simple Steps to Create Treemap in R
- treemapify: Draw Treemaps in 'ggplot2'
- Introduction to treemapify
- Interactive visualization with R-Shiny versus with Tableau: Treemaps
