Course Resources

ISSS608 Visual Analytics and Applications

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

Visual Analytics Toolkit

In this course, students will be expose to and gain hands-on experience on several generic visual analytics toolkit and specialised data visualisation applications. Below are a list of the core software tools for this course.

Commercial Visual Analytics software

Tableau

• Tableau home page [1]
• Training and Tutorials [2]
• Visual Gallery [3]
• Blogs that inspired
  • The Information Lab [4]
  • DataRemixed [5]

JMP Pro

• JMP home page [6]
• Discovering JMP [7]
• JMP Learning Library [8]
• JMP® for Students 1: Navigation and Use [9]

QlikView and/or Qlik Sense (Optional)

• Qlik home page [10]
• QlikView home page [11]
• Qlik Sense home page [12]

Power BI (Optional)

• Power BI homepage [13]
• Guided Learning [14]
• Power BI Documentation [15]

All About R

ggplot2

• ggplot2 [16]
• ggplot2 – The R graph Gallery [17]
• Introduction to R Graphics with ggplot2 [18]

ggplots Extension

• ggVis
• ggmap
• ggtern, an extension to ggplot2 specifically for the plotting of ternary diagrams [19]
• ggExtra, a collection of functions and layers to enhance ggplot2. The main function is ggMarginal, which can be used to add marginal histograms/boxplots/density plots to ggplot2 scatterplots. [20]
• ggthemes, some extra themes, geoms, and scales for 'ggplot2'. Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others. Provides 'geoms' for Tufte's box plot and range frame. [21]
• ggigraph lets R users to make ggplot interactive. [22]
• GGally extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks. [23]
• sjPlot-package, Data Visualization for Statistics in Social Science [24]

Other R graphics packages

• corrplot [25]
• corrgram calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. [26]
• vcd, Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. [27]

Specialised Data Visualisation Tools

Interactive Exploratory Data Analysis

• Mondrian [28]
• GGobi [29]

High-dimensional Data Visualisation

• Treemaps [30]
• Hierarchical Clustering Explorer [31]

Time-series Data Visualisation

• Time Searcher [32]

Graph Visualisation

• Gephi [33]
• Cytoscape [34]