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Duration 14 hours
Course Outline
Introduction to Shiny
- Overview of Shiny and its operational mechanics
- Installation procedures and initial configuration
- Reviewing Shiny examples and the official gallery
UI and Server Architecture
- Analyzing the structure of ui.R and server.R components
- Utilizing fluidPage(), sidebarLayout(), and other layout functions
- Structuring user inputs and application outputs
Reactivity and Dynamic Interactions
- Understanding reactive expressions and observer functions
- Managing app behavior through reactive inputs
- Identifying and resolving reactivity-related issues
Data Visualization and Reporting
- Integrating ggplot2 and plotly libraries within Shiny apps
- Creating reactive tables using DT or reactable packages
- Generating downloadable reports via rmarkdown
Advanced UI and Customization
- Incorporating tabs, conditional panels, and modal windows
- Applying custom CSS styles and themes
- Leveraging Shiny modules to enhance code reusability
Deployment and Hosting
- Launching apps on Posit Cloud or Shinyapps.io
- Executing apps locally and via Shiny Server
- Overseeing dependencies and version control
Case Study and Application Design
- Constructing a comprehensive dashboard from the ground up
- Implementing interactive filters and user-driven insights
- Best practices for performance optimization, security, and scalability
Summary and Next Steps
Requirements
- Solid understanding of R programming principles
- Practical experience in data analysis or visualization
- Basic knowledge of HTML and CSS is advantageous but not mandatory
Target Audience
- Data analysts and scientists
- R developers looking to create interactive dashboards
- Researchers and educators presenting data to public or internal stakeholders
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.
