Difference between revisions of "Assignment"
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= Submission Instructions = | = Submission Instructions = | ||
− | * The assignment report must be written using R Markdown. It can be in either '''[https://rstudio.github.io/distill/ Distill]''' or '''[https://github.com/rstudio/blogdown blogdown]''' format. You are required to publish the | + | * The assignment report must be written by using R Markdown. It can be in either '''[https://rstudio.github.io/distill/ Distill]''' or '''[https://github.com/rstudio/blogdown blogdown]''' format. You are required to publish the assignment report on '''[https://www.netlify.com/ netlify]''' and provide the link on the assignment submission page on elearn. |
− | * | + | * Upload the R Markdown document, web report and data to your team Visual Analytics Project Github repository and provide the link on the assignment submission page on eLearn. |
− | + | * To encourage peer-learning, students must provide the link to the web blog your prepared in the table below. | |
− | * To encourage peer-learning, students must | + | |
= Deliverable = | = Deliverable = | ||
− | * | + | * |
* Knit the R Markdown document into web blog format and publish it on Netlify. | * Knit the R Markdown document into web blog format and publish it on Netlify. | ||
* You are required to provide the links for both the web blog and Tableau Public on eLearn and on course wiki. | * You are required to provide the links for both the web blog and Tableau Public on eLearn and on course wiki. |
Revision as of 17:05, 17 March 2021
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The Task
The assignment is part of the bigger Shiny-based Visual Analytics Application (Shiny-VAA) project. Each team member is required to select a sub-module from the proposed Shiny-VAA and to complete the tasks below:
- Conducting literature review on how the analysis were performed before. The focus should be on identifying gaps whereby interactive web approach and visualanalytics techniques can be used to enhance user experience on using the analysis techniques.
- Preparing the storyboard for the design of the sub-module.
- Extracting, wrangling and preparing the input data required to perform the analysis. The focus should be on exploring appropriate tidyverse methods
- Testing and prototyping the proposed sub-module in R Markdown. The R Markdown document must be in full working html report format. This link provides a useful example for your reference.
Submission Instructions
- The assignment report must be written by using R Markdown. It can be in either Distill or blogdown format. You are required to publish the assignment report on netlify and provide the link on the assignment submission page on elearn.
- Upload the R Markdown document, web report and data to your team Visual Analytics Project Github repository and provide the link on the assignment submission page on eLearn.
- To encourage peer-learning, students must provide the link to the web blog your prepared in the table below.
Deliverable
- Knit the R Markdown document into web blog format and publish it on Netlify.
- You are required to provide the links for both the web blog and Tableau Public on eLearn and on course wiki.
- Provide the links for both the Visual Analytics Project Github repository and web blog of Netlify on eLearn.
Submission date
4th April 2021 (Sunday), mid-night 11:59pm.