Course Resources
Jump to navigation
Jump to search
IS428 Visual Analytics for Business Intelligence
|
|
|
|
|
|
|
Contents
Data Visualisation Desinger
In this course, students will be exposed 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.
Desktop Data Visualisation Designer
Tableau
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)
Power BI (Optional)
Online Data Visualisation Designer
Flourish
Specialised Data Visualisation Tools
Interactive Exploratory Data Analysis
High-dimensional Data Visualisation
Time-series Data Visualisation
- Time Searcher [20]
Graph Visualisation
R Packages for Data Visualisation
Getting Started with R
- R for Data Science by Garrett Grolemund and Hadley Wickham.
- Modern R with the tidyverse by Bruno Rodrigues. Chapter 2 provides a detail discussion on R data objects.
ggplot2
ggplot2 Core
- ggplot2 [23]
- ggplot2 – The R graph Gallery [24]
- Introduction to R Graphics with ggplot2 [25]
- ggplot2 - A Short Tutorial [26]
ggplots Extension
- ggVis
- ggmap
- ggtern, an extension to ggplot2 specifically for the plotting of ternary diagrams [27]
- 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. [28]
- 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. [29]
- ggigraph lets R users to make ggplot interactive. [30]
- 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. [31]
- sjPlot-package, Data Visualization for Statistics in Social Science [32]
- ggstatsplot is an extension of ggplot2 package for creating graphics with details from statistical tests included in the plots themselves and targeted primarily at behavioral sciences community to provide a one-line code to produce information-rich plots.
plotly R
- plotly: Create Interactive Web Graphics via 'plotly.js'
- Interactive web-based data visualization with R, plotly, and shiny
- Plotly R Open Source Graphing Library
- Getting Started with Plotly and ggplot2
Other R graphics packages
- corrplot [33]. 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 [34] calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. [35]
- vcd, Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. [36]
- tmap [37] offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.
Web-based Visual Analytics Development tool in R
Getting Started
Shiny Applications
- Gallery
- Show Me Shiny
- Gallery of Plotly Graphs in R Shiny
- Fifteen New Zealand government Shiny web apps
- Introducing the New Zealand Trade Intelligence Dashboard
