Difference between revisions of "Lesson 7"

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<font size="5">'''Introduction to Visual Analytics'''</font>
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<font size="5">'''Visualising and Analysing Multivariate Data'''</font>
  
 
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Revision as of 10:11, 1 October 2019

Va.jpg IS428 Visual Analytics for Business Intelligence

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

 



Visualising and Analysing Multivariate Data

Content

  • Introduction to Multivariate Data
  • Trellis
  • Correlation Matrix
  • Ternary Plot
  • Glyphs or Star Plot
  • Heatmap
  • Parallel Coordinate Plot
  • Treemap


Readings

Core Readings


Optional Readings


R Methods

Ternary Plot

  • R packages for creating ternary plot
    • Ternary, which employs the native plot functions;
    • Plotly, which uses a bespoke suite of plotting functions;
    • vcd, which contains the function ternaryplot;
    • ggtern, an extension to ggplot2.


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