Explore tabular datasets using Streamlit and Vega-Lite.
Python 3.10
Install dependencies: make install
Run Streamlit app: make run (localhost:8501)
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
- 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
To learn more about making a contribution to this repository, please see our Contributing guide.