https://github.com/datapane/examples

Datapane Examples
https://github.com/datapane/examples

data-science datapane jupyter python

Last synced: 3 months ago
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Datapane Examples

• Host: GitHub
• URL: https://github.com/datapane/examples
• Owner: datapane
• License: apache-2.0
• Archived: true
• Created: 2023-01-10T16:33:13.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-09-07T11:34:57.000Z (about 1 year ago)
• Last Synced: 2024-06-29T04:35:11.459Z (5 months ago)
• Topics: data-science, datapane, jupyter, python
• Language: Jupyter Notebook
• Homepage: https://www.datapane.com
• Size: 5.95 MB
• Stars: 27
• Watchers: 4
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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---

### NOTE: Datapane is no longer actively maintained.

This project is archived and kept for reference purposes only.

Thank You.

## Welcome to Datapane's Examples Repository

Hi there! 👋

[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=587390080&devcontainer_path=.devcontainer%2Fdevcontainer.json)

This repository contains a collection of examples that demonstrate how to use Datapane to create and share data reports.

1. Run `pip install -r requirements.txt` from an example folder to install dependencies.

1. Depending on the format of the example, either run:

    - the notebook, e.g. `app.ipynb`, through Jupyter Lab,

    - the script, e.g. `python app.py`

1. Open the saved report locally

### Reports

- [Hello, World!](./reports/hello-world/report.ipynb)

- [Classifier Dashboard](./reports/classifier-dashboard/report.ipynb)

- [Machine Learning Pipeline](./reports/machine-learning-pipeline/report.ipynb)

- [Sales](./reports/sales-report/report.ipynb)

- [Social Media Dashboard](./reports/social-media-dashboard/report.ipynb)

- [Sqlite Dashboard](./reports/sqlite-dashboard/report.ipynb)

- [Stock Reporting](./reports/stock-reporting/report.ipynb)

- [Superstore Reporting](./reports/superstore-reporting/report.ipynb)

- [Kaggle Survey](./reports/survey-data-report/report.ipynb)

- [Text Heavy](./reports/text-heavy-report/report.py)

## Resources

We're here to help you get up and running with Datapane. Check out the [Datapane quickstart repo](https://github.com/datapane/dp-quickstart/) to get started, or visit any of the resources below.

- [Read the documentation](https://docs.datapane.com)

## What makes Datapane special?



  

    

  



- **Static generation:** Sharing an app shouldn't require deploying an app. Render a standalone HTML bundle which you can share or host on the web.

- **API-first and programmatic:** Programmatically generate apps from inside of Spark, Airflow, or Jupyter. Schedule updates to build real-time dashboards.

- **Dynamic front-end components**: Say goodbye to writing HTML. Build apps from a set of interactive components, like DataTables, tabs, and selects.