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Course Outline
Introduction to Shiny
- Overview of Shiny and its functionality
- Installation and initial setup
- Exploration of Shiny examples and the gallery
UI and Server Architecture
- Comprehending the ui.R and server.R components
- Utilizing fluidPage(), sidebarLayout(), and layout functions
- Designing inputs and outputs
Reactivity and Dynamic Interactions
- Reactive expressions and observers
- Managing app behavior through reactive inputs
- Resolving reactivity-related issues
Data Visualization and Reporting
- Integrating ggplot2 and plotly into Shiny applications
- Creating reactive tables using DT or reactable
- Generating downloadable reports via rmarkdown
Advanced UI and Customization
- Adding tabs, conditional panels, and modals
- Implementing custom CSS and themes
- Utilizing 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 versions
Case Study and Application Design
- Constructing a comprehensive dashboard from scratch
- Interactive filters and user-driven insights
- Best practices for performance, security, and scalability
Summary and Next Steps
Requirements
- Understanding of R programming
- Experience with data analysis or visualization
- Familiarity with HTML and CSS is beneficial but not mandatory
Audience
- Data analysts and scientists
- R developers looking to build interactive dashboards
- Researchers and educators visualizing data for public or internal consumption
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.