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Streamlit Vega-Lite Charts

Try the Online Demo

Explore tabular datasets using Streamlit and Vega-Lite.

Requirements

Python 3.10

Poetry

Installation

Install dependencies: make install

Run the app

Run Streamlit app: make run (localhost:8501)

Check code quality

We use Black, Flake8 and isort to ensure standard coding practices.

Each commit and pull request triggers a CI (Continuous Integration) pipeline job that runs code quality checks remotely (see Github Actions).

(Optional) Run linters locally: pre-commit run -a

Features

  • Select one of 5 datasets from OpenML
  • Detecting continuous & categorical columns
  • Generate bar, histogram, timeseries, boxplot, scatter plots
  • Detecting datetime columns
  • Line, circular plots
  • Upload custom dataset

Contributing

To learn more about making a contribution to this repository, please see our Contributing guide.