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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.
2. 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
3. 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.

• Read the documentation

• 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.