This project is archived and kept for reference purposes only.
Thank You.
Hi there! 👋
This repository contains a collection of examples that demonstrate how to use Datapane to create and share data reports.
- Run
pip install -r requirements.txt
from an example folder to install dependencies. - 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
- the notebook, e.g.
- Open the saved report locally
- Hello, World!
- Classifier Dashboard
- Machine Learning Pipeline
- Sales
- Social Media Dashboard
- Sqlite Dashboard
- Stock Reporting
- Superstore Reporting
- Kaggle Survey
- Text Heavy
We're here to help you get up and running with Datapane. Check out the Datapane quickstart repo to get started, or visit any of the resources below.
- 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.