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Course Outline
Introduction to Shiny
- Understanding what Shiny is and its operational mechanics.
- Installation procedures and initial setup.
- Exploring Shiny examples and the official gallery.
UI and Server Architecture
- Comprehending the roles of ui.R and server.R components.
- Utilizing fluidPage(), sidebarLayout(), and layout functions.
- Designing effective inputs and outputs.
Reactivity and Dynamic Interactions
- Working with reactive expressions and observers.
- Controlling application behavior through reactive inputs.
- Troubleshooting common reactivity issues.
Data Visualization and Reporting
- Integrating ggplot2 and plotly into Shiny applications.
- Constructing reactive tables using DT or reactable.
- Producing downloadable reports via rmarkdown.
Advanced UI and Customization
- Implementing tabs, conditional panels, and modals.
- Incorporating custom CSS and themes.
- Leveraging Shiny modules for code reusability.
Deployment and Hosting
- Deploying applications to Posit Cloud or Shinyapps.io.
- Running applications locally and on Shiny Server.
- Managing dependencies and software versions.
Case Study and Application Design
- Constructing a fully-featured dashboard from the ground up.
- Implementing interactive filters and user-driven insights.
- Best practices for performance, security, and scalability.
Summary and Next Steps
Requirements
- A foundational understanding of R programming.
- Practical experience with data analysis or visualization.
- While beneficial, familiarity with HTML and CSS is not mandatory.
Target Audience
- Data analysts and data scientists.
- R developers aiming to construct interactive dashboards.
- Researchers and educators looking to visualize data for public dissemination or internal use.
14 Hours
Testimonials (2)
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The real life applications using Statcan and CER as examples.
