plotly/onboarding-starter-app — explained in plain English
Analysis updated 2026-08-14 · repo last pushed 2025-01-27
Build an interactive line chart dashboard from sample data using Dash.
Turn notebook-based data analysis into a shareable web app colleagues can click through.
Learn how to create various chart types using Plotly by following a guided notebook.
Deploy a finished dashboard to Dash Enterprise for internal sharing.
| plotly/onboarding-starter-app | andy1li/udacity-reinforcement | anil-matcha/langchain-course | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Jupyter Notebook | Jupyter Notebook | Jupyter Notebook |
| Last pushed | 2025-01-27 | 2021-05-13 | 2023-05-20 |
| Maintenance | Stale | Dormant | Dormant |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 2/5 | 3/5 | 1/5 |
| Audience | data | researcher | developer |
Figures from each repo's GitHub metadata at analysis time.
Just run the Jupyter Notebook or execute the Dash script, both rely on standard Python data science packages.
The onboarding-starter-app from Plotly is a beginner-friendly starter kit for learning how to create interactive charts and web applications using Python. Instead of dealing with complex web development languages, you can use familiar data analysis tools to build visual dashboards that display your data. The project includes two main pieces. First, there is a Jupyter Notebook, a popular interactive document format for data science, that walks you through creating various charts using the Plotly graphing library. Second, there is a script that runs a simple web application using Dash, Plotly's framework for building interactive web apps. The app pulls in sample data and displays a basic line chart. Both pieces are heavily commented so you can understand what each part of the code does. This starter kit is designed for data analysts, researchers, or anyone comfortable with Python who wants to turn raw data into shareable, interactive web pages. For example, if you normally analyze data in spreadsheets or notebooks but want to present your findings to colleagues through a live web dashboard they can click around, this project shows you exactly how that workflow looks. A notable feature of the project is how it highlights the connection between data analysis and web deployment. The same Python code you write to visualize data in a notebook can be used to power an interactive web app, meaning you do not need to learn separate tools for analysis and presentation. The project also includes instructions for deploying your app to Dash Enterprise, Plotly's platform for hosting and sharing dashboards internally.
A beginner-friendly starter kit that teaches you to build interactive charts and web dashboards using Python, Plotly, and Dash, no separate web development skills required.
Mainly Jupyter Notebook. The stack also includes Python, Jupyter Notebook, Plotly.
Stale — no commits in 1-2 years (last push 2025-01-27).
The explanation does not specify a license for this project.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly data.
This repo across BitVibe Labs
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