Climate & Consumption

lollipop-type chart with icons

Published

October 28, 2025

Main Format

To create new a Shiny App in RStudio: Click:

File > New File > Shiny Web App ...

After library call, there are three main components to every Shiny app.

ui: user interface
server the R-backend
ShinyApp function to connect them

library(shiny)

# define how the page looks & interacts
ui <- fluidPage() # standard basic template 

# define server logic
server <- function(input,output){
  # R-code for data-wrangling & plotting
}

# Run the application 
shinyApp(ui = ui, server = server)

User Interface Layout Options

Option	Description	Key Use Case
1. `fluidPage()` (Base Shiny)	A simple page layout that automatically adjusts to the user’s screen size (responsive design).	Simple/Basic Apps: Quickest way to build a functional, single-page app.
2. `page_sidebar()` / `sidebarLayout()` (Base Shiny/`bslib`)	Creates a two-panel layout: a narrow sidebar (often for inputs) and a main panel (for outputs).	Data Exploration: Classic layout for inputs on the left, main analysis/plots on the right.
3. `page_navbar()` (Base Shiny/`bslib`)	Provides a top-level navigation bar to create a multi-page application with tabs.	Multi-Section Apps: Organizes complex applications into distinct sections.
4. `bslib` Package	A modern package for unified theming and advanced layouts, including Cards, Value Boxes, and new layout functions.	Modern Look & Feel: Creating highly customizable, professional-looking dashboards.
5. `shinydashboard` Package	A dedicated package that provides a structured, fixed-style dashboard layout with a Header, Sidebar Menu, and Body.	Traditional Dashboards: Best for large-scale, enterprise-style monitoring and reporting applications.
6. `bs4Dash` Package	An evolution of `shinydashboard` that uses the more modern Bootstrap 4/AdminLTE 3 themes, offering more UI components.	Feature-Rich Dashboards: When `shinydashboard` isn’t flexible enough and you need more modern widgets/styles.
7. Multi-Column Layouts	Using functions like `layout_columns()` (or `fluidRow`/`column`) to organize content into a grid system (typically 12 columns).	Grid-Based Design: Precise control over where elements are placed on the page for a clean, non-sidebar layout.
8. `shinythemes` Package	Offers a variety of pre-packaged Bootstrap themes (Bootswatch) that can be applied instantly to change the app’s colors and fonts.	Quick Styling: Changing the entire app’s look with a single line of code.
9. `tabsetPanel()` (Base Shiny)	Displays content in multiple tabbed panels within the main body of a page.	Content Grouping: Organizing related content (e.g., different charts) without changing the overall page structure.
10. `shinyfluent` or other thematic packages	Packages that wrap other popular design frameworks like Microsoft’s Fluent UI or Material Design.	Specific Design Systems: Implementing a very specific, polished look and feel.

Options for Interactivity

Option	Function	Description	Key Use Case
1. Slider	`sliderInput()`	A slider bar for selecting a single numeric value or a range of values.	Tuning Parameters: Setting a number of clusters in k-means, or choosing a confidence interval.
2. Select Box	`selectInput()`	A drop-down menu that lets the user choose one or multiple options from a predefined list.	Choosing Variables: Selecting which column in a dataset to plot on the X-axis.
3. Action Button	`actionButton()` or `actionLink()`	A simple clickable button that generates an event when pressed.	Triggering Events: Refreshing a dataset, running a time-consuming calculation, or downloading a report.
4. Checkbox	`checkboxInput()`	A single box that can be either checked (TRUE) or unchecked (FALSE).	Toggling Features: Showing or hiding a data trend line on a plot.
5. Checkbox Group	`checkboxGroupInput()`	A group of checkboxes allowing the user to select multiple options from a list.	Filtering Data: Selecting which categories (e.g., product lines) to include in an analysis.
6. Radio Buttons	`radioButtons()`	A set of circular buttons where the user can choose only one option from the group.	Selecting Modes: Choosing between “Raw Counts” or “Per Capita” for a visualization.
7. Numeric Input	`numericInput()`	A text box specifically for entering numeric values, with optional minimum, maximum, and step controls.	Exact Entry: Allowing the user to enter a precise value, like a sample size.
8. Date Input	`dateInput()` or `dateRangeInput()`	A pop-up calendar widget for selecting a single date or a date range.	Time-Series Filtering: Defining the start and end dates for data displayed on a chart.
9. Text Input	`textInput()`	A simple text box for users to type in a short string of text.	Search/Labeling: Entering a search term to filter results, or providing a plot title.
10. File Upload	`fileInput()`	A button that opens the user’s file explorer, allowing them to upload a file (e.g., CSV, Excel) to the app.	Custom Data: Allowing users to analyze their own data files within the application.