dataset-hub 0.1.1

A unified API for exploring any ML task

DatasetHub: A Unified API for Exploring Any ML Task

DatasetHub is an educational project that provides a simple .get_<dataset>() API to access datasets.

import dataset_hub

titanic = dataset_hub.classification.get_titanic()
print(type(titanic)) # pandas.DataFrame

It lets beginners access datasets effortlessly, while giving practitioners a single interface to experiment with any open dataset or ML task.

Installation

# Python 3.10+
pip install dataset-hub

Available tasks and datasets:

dataset-hub.docs.com

Why this library exists

DatasetHub was created to provide a single, unified entry point for experimenting with any classic ML task — from scoring and forecasting to fraud detection and uplift modeling.

Looking ahead, the project focuses on two major directions:

1. Assemble a large collection of open datasets for a variety of classic ML tasks, all easily accessible through the unified .get_<dataset>() interface.

2. Provide realistic, ready-to-use synthetic datasets that mimic real-world business scenarios, enabling experimentation for niche tasks where open data is scarce.

API Disclaimer

1. Temporary issues
   Our dataset functions rely on external sources. If a source and mirror sources become unavailable or temporarily fail, a function may stop working temporarily or completely.
   If you encounter a persistent issue under such circumstances, please open an issue and provide detailed information about your attempts.

2. Dynamic API
   If all available sources and mirror sources for a dataset completely disappear and the dataset is no longer publicly accessible, our API may change, and the dataset may be removed. Please be prepared for this possibility.

3. Copyright concerns
   Similar changes may occur if a copyright holder requests the removal of access to a dataset.

For copyright holders

If you believe your data should not be included or accessible via this project, please contact us directly. We will promptly review your request and take appropriate action to remove or restrict access to the dataset in question.