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Duration 14 hours
Course Outline
Getting Started with Shiny
- Overview of Shiny and its underlying mechanics
- Setting up the environment and installing Shiny
- Reviewing existing Shiny examples and exploring the gallery
UI and Server Architecture
- An analysis of ui.R and server.R components
- Implementing layouts with fluidPage(), sidebarLayout(), and other layout functions
- Structuring application inputs and outputs
Reactivity and Dynamic Interactions
- Mastery of reactive expressions and observers
- Managing application logic through reactive inputs
- Strategies for debugging reactivity-related issues
Data Visualization and Reporting
- Embedding ggplot2 and plotly visualizations within Shiny apps
- Creating reactive data tables using DT or reactable
- Producing downloadable reports via rmarkdown
Advanced UI and Customization
- Enhancing interfaces with tabs, conditional panels, and modals
- Applying custom CSS styles and professional themes
- Leveraging Shiny modules to promote code reusability
Deployment and Hosting
- Publishing applications to Posit Cloud or Shinyapps.io
- Running applications locally or via Shiny Server
- Overseeing dependency management and version control
Case Study and Application Design
- Constructing a comprehensive dashboard from the ground up
- Implementing interactive filters to drive user insights
- Best practices for optimizing performance, security, and scalability
Recap and Future Directions
Requirements
- Solid understanding of R programming principles
- Practical experience in data analysis or visualization
- Knowledge of HTML and CSS is advantageous but not mandatory
Target Audience
- Data analysts and data scientists
- R developers looking to construct interactive dashboards
- Researchers and educators who need to present data for public or internal audiences
Testimonials (3)
a multitude of points
Joanna - Instytut Ekonomiki Rolnictwa i Gospodarki Zywnosciowej-PIB
Course - Statistical Analysis with Stata and R
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.
