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<font size = 5; color="#FFFFFF">ISSS608 Visual Analytics and Applications</font>
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[[Course_information| <font color="#FFFFFF">About</font>]]
 
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[[VAProject| <font color="#FFFFFF">Visual Analytics Project</font>]]
 
 
 
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<br/>
 
=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===
 
 
* Tableau home page [http://www.tableausoftware.com/]
 
* Training and Tutorials [http://www.tableausoftware.com/learn/training]
 
* Visual Gallery [http://www.tableausoftware.com/learn/gallery]
 
* Blogs that inspired
 
**  The Information Lab [http://www.theinformationlab.co.uk/blog/]
 
**  DataRemixed [http://dataremixed.com/]
 
 
===JMP Pro===
 
 
* JMP home page [http://www.jmp.com/software/]
 
* Discovering JMP [http://www.jmp.com/support/help/Discovering_JMP.shtml]
 
* JMP Learning Library [http://www.jmp.com/academic/learning_library.shtml]
 
* JMP® for Students 1: Navigation and Use [http://www.jmp.com/about/events/ondemand/ondemand-viewer.shtml?reglink=701a0000001s1Zc&series=academic]
 
 
===QlikView and/or Qlik Sense (Optional)===
 
 
* Qlik home page [http://www.qlik.com/]
 
* QlikView home page [http://www.qlik.com/us/explore/products/qlikview]
 
* Qlik Sense home page [http://www.qlik.com/us/explore/products/sense]
 
 
===Power BI (Optional)===
 
* Power BI homepage [https://powerbi.microsoft.com/en-us/]
 
* Guided Learning [https://powerbi.microsoft.com/en-us/guided-learning/?WT.mc_id=PBIService_GettingStarted]
 
* Power BI Documentation [https://powerbi.microsoft.com/en-us/documentation/powerbi-landing-page/]
 
 
 
==Online Data Visualisation Designer==
 
 
===Flourish===
 
* [https://flourish.studio/features/ Features]
 
* [https://flourish.studio/examples/ Examples]
 
* [https://flourish.studio/blog/ Blog]
 
 
 
=Specialised Data Visualisation Tools=
 
 
==Interactive Exploratory Data Analysis==
 
*  Mondrian [http://www.theusrus.de/Mondrian/]
 
*  GGobi [http://www.ggobi.org/]
 
 
==High-dimensional Data Visualisation==
 
*  Treemaps [http://www.cs.umd.edu/hcil/treemap/]
 
*  Hierarchical Clustering Explorer [http://www.cs.umd.edu/hcil/hce/]
 
 
 
==Time-series Data Visualisation==
 
*  Time Searcher [http://www.cs.umd.edu/hcil/timesearcher/]
 
 
==Graph Visualisation==
 
===Gephi===
 
*  Gephi [https://gephi.org/]
 
*  Webpage [http://gephi.org/]
 
*  Download [http://gephi.org/users/download/]
 
* Tutorial: Quick Start [http://gephi.org/users/quick-start/], Visualization [http://gephi.org/users/tutorial-visualization/], and Layouts [http://gephi.org/users/tutorial-layouts/]
 
*  Forum [http://forum.gephi.org/]
 
* [https://seinecle.github.io/gephi-tutorials/ Gephi Tutorial]
 
* [http://www.martingrandjean.ch/gephi-introduction/ GEPHI – Introduction to Network Analysis and Visualization]
 
===Cytoscape===
 
*  Cytoscape [http://www.cytoscape.org/]
 
 
 
=Getting Started with R=
 
* [https://r4ds.had.co.nz/ R for Data Science] by Garrett Grolemund and Hadley Wickham.
 
* [https://b-rodrigues.github.io/modern_R/ Modern R with the tidyverse] by Bruno Rodrigues. [https://b-rodrigues.github.io/modern_R/objects-types-and-useful-r-functions-to-get-started.html Chapter 2] provides a detail discussion on R data objects.
 
 
=R Packages for Data Visualisation=
 
 
==ggplot2==
 
 
===ggplot2 Core===
 
* ggplot2 [https://ggplot2.tidyverse.org//]
 
* ggplot2 – The R graph Gallery [http://www.r-graph-gallery.com/portfolio/ggplot2-package/]
 
* Introduction to R Graphics with ggplot2 [http://tutorials.iq.harvard.edu/R/Rgraphics/Rgraphics.html#org93999d8]
 
* ggplot2 - A Short Tutorial [http://r-statistics.co/ggplot2-Tutorial-With-R.html]
 
* [https://bookdown.org/tpemartin/minicourse_ggplot2/ ggplot2 介紹]
 
 
===ggplots Extension===
 
* ggVis
 
* ggmap
 
* ggtern, an extension to ggplot2 specifically for the plotting of ternary diagrams [http://www.ggtern.com/]
 
* 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. [https://github.com/daattali/ggExtra]
 
* 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. [https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html]
 
* ggigraph lets R users to make ggplot interactive. [https://cran.r-project.org/web/packages/ggiraph/vignettes/an_introduction.html]
 
* 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. [http://ggobi.github.io/ggally/]
 
* sjPlot-package, Data Visualization for Statistics in Social Science [http://www.strengejacke.de/sjPlot/]
 
* [https://cran.r-project.org/web/packages/ggstatsplot/index.html 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.
 
 
 
==Interactive Data Visualisation with R==
 
 
===plotly R===
 
* [https://cran.r-project.org/web/packages/plotly/index.html plotly: Create Interactive Web Graphics via 'plotly.js']
 
* [https://plotly-r.com/ Interactive web-based data visualization with R, plotly, and shiny]
 
* [https://plot.ly/r/ Plotly R Open Source Graphing Library]
 
* [https://plot.ly/ggplot2/getting-started/ Getting Started with Plotly and ggplot2]
 
 
 
==Other R graphics packages==
 
* corrplot [https://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html]. 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 [https://cran.r-project.org/web/packages/corrgram/index.html] calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. [https://cran.r-project.org/web/packages/corrgram/index.html]
 
* vcd, Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. [https://cran.r-project.org/web/packages/vcd/index.html]
 
* tmap [https://cran.r-project.org/web/packages/tmap/index.html] 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==
 
* [https://shiny.rstudio.com/ Shiny from R Studio]
 
* [https://shiny.rstudio.com/tutorial/ Learn Shiny]
 
* [http://shiny.rstudio.com/reference/shiny/latest/ Function reference]
 
* [https://shiny.rstudio.com/images/shiny-cheatsheet.pdf The Shiny Cheat sheet]
 
* [https://bookdown.org/tpemartin/shiny_intro/shiny-part-i.html Shiny 入門]
 
 
 
==Shiny Applications==
 
* [https://mastering-shiny.org/ Mastering Shiny]
 
* [https://shiny.rstudio.com/gallery/ Gallery]
 
* [https://community.rstudio.com/t/shiny-contest-winners-2019-full-list/36347 Shiny Contest Winners 2019 - Full List]
 
* [http://freerangestats.info/blog/2018/05/13/nz-govt-shinyapps Fifteen New Zealand government Shiny web apps]
 
* [https://nzprimarysectortrade.w ordpress.com/2018/10/15/introducing-the-new-zealand-trade-intelligence-dashboard/ Introducing the New Zealand Trade Intelligence Dashboard]
 
 
 
=github=
 
* [https://happygitwithr.com/ Happy Git and GitHub for the useR]. Highly recommended to beginners.
 
* [https://resources.github.com/whitepapers/github-and-rstudio/ GitHub and RStudio]
 
* [https://nceas.github.io/training-git-intro/getting-started-with-git-rstudio.html Getting starting with git and GitHub using RStudio]
 
* [https://cfss.uchicago.edu/setup/git-with-rstudio/ Using Git within RStudio]
 
* [https://docs.github.com/en github doc]
 
* [https://rtask.thinkr.fr/transform-a-folder-as-git-project-synchronized-on-github-or-gitlab/ Transform a folder as git project synchronized on Github or Gitlab]
 
 
=R Markdown=
 
* [https://bookdown.org/yihui/rmarkdown/ R Markdown: The Definitive Guide]. Highly recommended to beginners.
 
* [https://rmarkdown.rstudio.com/lesson-1.html R Markdown from R Studio]
 
* [https://bookdown.org/yihui/rmarkdown-cookbook/ R Markdown Cookbook]
 
* [https://rmd4sci.njtierney.com/ RMarkdown for Scientists]
 
* [https://towardsdatascience.com/ten-awesome-r-markdown-tricks-56ef6d41098 Ten awesome R Markdown tricks]
 
 
=blogdown=
 
 
* [https://bookdown.org/yihui/blogdown/ blogdown: Creating Websites with R Markdown]. Highly recommended to beginners.
 
* [https://github.com/rstudio/blogdown blogdown]
 
* [https://bookdown.org/yihui/blogdown/netlify.html 3.1 Netlify]
 
* [https://www.storybench.org/how-to-build-a-website-with-blogdown-in-r/ How to build a website with Blogdown in R]
 
* [http://estebanmoro.org/post/2019-02-02-setting-up-your-blog-with-rstudio-and-blogdown-i-creating-the-blog/ Setting up our blog with RStudio and blogdown I: Creating the blog]
 
* [http://estebanmoro.org/post/2019-02-01-setting-up-your-blog-with-rstudio-and-blogdown/ Setting up your blog with RStudio and blogdown II: Workflow]
 
* [http://estebanmoro.org/post/2019-02-04-setting-up-your-blog-with-rstudio-and-blogdown-iii-modify-your-theme/ Setting up your blog with RStudio and blogdown III: modify your theme]
 

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