| Module Title: | Data Visualisation |
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| Language of Instruction: | English |
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| Teaching & Learning Strategies: |
Teaching and learning will take place in the laboratory setting, hands on. |
| Module Aim: |
The aim of this module is to enable students to gain insight and practical skills for creating interactive web visualisations, Apps and dashboard powered by R. Additionally, students will be familiarised with the current trends and practices in data visualisation. |
| Learning Outcomes |
| On successful completion of this module the learner should be able to: |
| LO1 |
Apply and critically evaluate current trends and practices in data visualisation to produce informative, engaging and repeatable interctive web application |
| LO2 |
Apply selected and adequate open source methods and tools/ packages to produce interactive web application /graphic for data analysis |
| Pre-requisite learning |
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
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| No recommendations listed |
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. |
| No incompatible modules listed |
Co-requisite Modules
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| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. |
| No requirements listed |
Module Content & Assessment
| Indicative Content |
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Visualisation as a phase within the data science workflow
Data Science Workflow (Grolemund & Wickham); Visualisation - concepts, definitions, current trends ect.
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Introduction to R & RStudio (IDE) environments
RStudio: scripts, workflow, packages: ggplot,plotly, tidyverse (dplyr,readr, purrr,forcats,stringr), plots tab: Graphs export, 3D graphs
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The Grammar of Graphics
The layered grammar of graphic by Hadley Wickham; concepts, definitions, components and layers
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Producing the basic visualisations
The key packages: ggplot(), plot_ly (), plotly.js(), ggplotly(), functions and arguments
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Working with colours
RColorBrewer (Colorbrewer palettes),viridis (viridis color scales), wesanderson (Wes Anderson color palettes), ggsci (scientific journal color palettes); ggplot2 (grey color palettes), R base color palettes: rainbow, heat.colors, cm.colors
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3D charts
3D charts: Markers, Paths, Lines, Axes, Surfaes
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Publishing views
Saving and embedding HTML; Exporting static images,Editing views for publishing; Combining multiple views, Linking multiple views,
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Creating simple dashboard
flexdashboard library; layout, components (htmlwidgets), Sizing, Storyboards,
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Key HTML Widgets
rbookeh - an interface to Bookeh a framework for creating web-based plots; Leaflet library to create dynamic maps, dygraphs for charting time-series; Highcharter - rich R interface to the Highcharts JavaScript graphic library, visNetwork - an interface to the network visualisation capabilities of the vis.js library
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Creating interactive dashboard
Introducing Shiny package, and shiny components to enable reactivity;Input Sidebar, Shiny Modules
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Creating first Shiny app
Basic UI, Basic reactivity, Workfow, Layout, themes, HTML,
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Shiny in action
User feedback, Uploads and downloads, Dynamic UI, Bookmarking, Tidy evaluation
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Mastering reactivity
why reactivity, The reactive graph, Reactive building blocks, Escaping the graph
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Best practices
General guidelines, Functions, Shiny modules, Packages, Testing, Security, Performance
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| Assessment Breakdown | % |
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| Continuous Assessment | 100.00% |
| Continuous Assessment |
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| Assessment Type |
Assessment Description |
Outcome addressed |
% of total |
Assessment Date |
| Project |
Students are asked to apply the theory and the practical skills acquired throughout the class as well as explore any other neccessary materials to create interactive visualisation of their choice. Additionally, students will be asked to prepare presentation related to the produced visualisation. |
1,2 |
100.00 |
Week 11 |
| No End of Module Formal Examination |
SETU Carlow Campus reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Frequency |
Average Weekly Learner Workload |
| Lecture |
12 Weeks per Stage |
3.00 |
| Independent Learning |
15 Weeks per Stage |
5.93 |
| Total Hours |
125.00 |
Module Delivered In
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