Introduction
Interactive coding transforms how you learn and work with data by providing real-time feedback and dynamic outputs—all within your web browser. In this section, you’ll discover a comprehensive suite of tutorials designed to help you master interactive programming using Quarto Live.
Lessons Overview
Here’s how you can explore the content efficiently:
- Click on a lesson title to open and view its contents.
- Click on the
+or-button next to a lesson to expand or collapse its subcategories (nested lessons).
- Expanded lessons will have an orange button (
-), while collapsed ones will have a blue button (+).
- This lesson hierarchy is also available in the left sidebar—when you click on a specific lesson, you’ll see its structure there as well.
Lessons
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Overview of interactive coding tutorials using R and Python. -
Set up and understand the fundamentals of interactive coding environments. -
Step-by-step installation of Quarto Live and WebAssembly engines for R and Python. -
Basics of creating and running interactive code blocks. -
Effective techniques to manage execution environments and variable sharing. -
How to install and use packages in interactive environments. -
Creating plots interactively with R and Python.
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Interactive coding tutorials dedicated to R. -
Get started with interactive R scripting and coding essentials. -
Create interactive visualizations with ggplot2, Plotly, and Shiny. -
Embed Shiny apps directly into Quarto documents. -
Design exercises with hints, solutions, and automatic grading. -
Use htmlwidgets and Jupyter widgets for interactive outputs in R. -
Run Shiny apps entirely in the browser using Shinylive. -
Install and set up the Shinylive R package. -
Create and export basic Shiny applications using Shinylive. -
Advanced customization and troubleshooting for Shinylive in R.
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Interactive coding tutorials specifically for Python. -
Set up interactive Python environments and run your first interactive script. -
Step-by-step interactive lessons to learn Python. -
Run Shiny Python applications entirely in the browser with Shinylive. -
Install and configure Shinylive for Python. -
Learn to create and deploy Shinylive Python apps. -
Integrate Shinylive Python applications seamlessly into Quarto documents. -
Advanced troubleshooting and customization for Shinylive Python apps.
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Advanced methods for interactive coding in R and Python. -
Combining pre-rendered and live interactive content. -
Creating reactive interactive documents using OJS variables. -
Implement automated feedback and grading in interactive exercises.
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Concise cheatsheets summarizing key interactive coding techniques.
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Why Interactive Coding?
Interactive coding enables you to:
- Experiment in Real-Time: See immediate feedback on your code changes.
- Visualize Data Dynamically: Build interactive plots and dashboards that respond to user inputs.
- Enhance Learning: Combine narrative text with live code to deepen your understanding.
- Deploy Serverlessly: Use Quarto Live to run your interactive code in the browser without dedicated servers.
Getting Started
Our tutorials provide a step-by-step approach tailored for both R and Python. Start with our beginner-friendly guides, then progress to advanced techniques as you grow more comfortable with interactive content.
Conclusion
Interactive R and Python tutorials in this section are designed to empower you with the skills to build dynamic, interactive documents using Quarto Live. Whether you’re experimenting with data visualization, integrating Shiny apps, or designing interactive exercises, you’ll find comprehensive resources to guide you every step of the way.
Reuse
Citation
@online{kassambara2025,
author = {Kassambara, Alboukadel},
title = {Overview of {Interactive} {R} \& {Python}},
date = {2025-03-17},
url = {https://www.datanovia.com/learn/interactive/index.html},
langid = {en}
}