The Complete Course of R Shiny 2025

Install the shiny package and create a project, then build a shiny web app with a slider controlling a histogram of old faithful geyser data, and explore ui and server.

Learn to build a single-page shiny app using a fluid page with title, sidebar, and main panels, and place a slider input and histogram in a responsive 12-column grid.

Learn to build a multi-page Shiny app using tabsetPanel and tabPanel to host plots and a slider input across tabs, with a nav bar page and title panels.

Explore the basic elements of UI in shiny apps, including inputs and outputs, input IDs and output IDs, and how each output pairs with its render function for dynamic rendering.

Learn to configure a shiny slider input in RStudio, setting min, max, and default values, with step, animation, ticks, range, pre and post labels, and number formatting.

Explore numeric inputs in R Shiny by creating a numeric input in a sidebar layout with an id, label, min, max, default value, and step, and adjust width.

Explore text input types in R Shiny, including text input, text area input, and password input, and configure id, label, default value, placeholder, width, and resize.

Learn how data inputs work in Shiny, with hands-on examples of date input, custom formats, start view, disabling specific dates, and date range input with minimum and maximum settings.

Explore select input in R Shiny, learn how to set options, enable multiple selections, adjust size, use placeholders, and organize options with lists for better form design.

Learn to use text outputs with render functions in Shiny, bind inputs by ID, and display dynamic text and retirement calculations using numeric inputs and conditional logic.

Customize the output area in a Shiny app by adjusting plotly output height and width (e.g., 500 px, 60% width) and styling other outputs with css or html tags.

Learn to display a data table in a shiny app by loading a csv dataset, using a select input, and rendering with table output or data table output.

Learn to build bar plots in R Shiny using plot output and render plot, create interactive ggplot charts with plotly, and enable dynamic variable selection via a select input.

Learn the basics of reactivity in shiny apps, including why server-side code cannot set numeric input values and how render functions enable reactive outputs like render text.

Learn how to use the basic reactive function in R Shiny to control reactivity, share data across render functions, and build interactive plots and tables.

Control reactivity in a shiny app using a reactive timer and event-driven inputs to auto-update histograms and plots from mean and standard deviation.

Learn to dynamically update Shiny inputs with update slider input and update select input as users interact, using reactive data filtered by territory, customer name, and order number.

Upload csv or json data to a shiny app, preview uploads in a data table, and download filtered results with a download handler and customizable file names.

Learn to connect a SQL server to a shiny app, create a database connection, list tables and fields, and run queries with data rendering in the app.

Connect a json file from the web to a shiny app using jsonlite fromJson and as.data.frame to load the raw dataset and render a data table with filters.

Learn to build interactive ggplot2 plots in shiny, from scatter plots of mpg vs hp using the empty cars data to a CO2 bar plot with theme customization.

Demonstrate interactive ggplot2 visuals in shiny, including box plots of iris sepal length by species with color fills, and faceted line plots of ozone by month from airquality.

Learn to make ggplot2 plots interactive in shiny by converting with ggplotly, applying render plotly, and adding tooltips, while exploring interactive scatter, bar, and bubble charts using plotly.

Explore creating interactive leaflet maps in shiny apps, including markers, circle markers, popups, minimap, polygons from geojson, and viridis color palettes with data-driven legends.

Explore advanced layout design with shinydashboard and shinydashboardPlus, building dynamic dashboards using dashboard header, sidebar, and body, adding collapsible boxes, info boxes, value boxes, and responsive plots.

Learn to embed html tags inside a shiny app, including p, h1, h2, h3, div, and img with src, plus css tweaks and raw html via the html function.

Master applying css inside shiny apps using html tags, text style, and selectors. Use class, id, and inline style to control color, alignment, borders, and backgrounds.

Learn to apply bootstrap themes in shiny apps by loading bootstrap and thematic libraries, previewing themes, and synchronizing UI and plot styling.

Build an interactive Shiny dashboard plus by integrating Shiny dashboard plus, shiny themes, tidyverse, and plotly; explore customer reviews and company data with filters, infoboxes, bar and line plots.

Explore building a shiny dashboard with plotly and ggplot visualizations, leveraging datasets, theming, and interactive filters across multiple tabs and info boxes.