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Medium Articles Dataset Generator

This project combines multiple datasets from Kaggle and Hugging Face to create a comprehensive collection of Medium articles. The combined dataset is available on Hugging Face Hub.

Dataset Description

This dataset is a unique compilation that not only combines multiple sources but also ensures data quality through normalization and deduplication. A key feature is that all entries in the text column are unique - there are no duplicate articles in the final dataset.

Data Sources:

Kaggle Sources:

  • aiswaryaramachandran/medium-articles-with-content
  • hsankesara/medium-articles
  • meruvulikith/1300-towards-datascience-medium-articles-dataset

Hugging Face Sources:

  • fabiochiu/medium-articles
  • Falah/medium_articles_posts

Features

  • Combines multiple data sources into a single, unified dataset
  • Ensures uniqueness: Each article appears only once in the dataset
  • Quality control:
    • Removes duplicate entries based on article text
    • Handles missing values
    • Normalizes data format
  • Saves the final dataset in efficient Parquet format
  • Publishes the dataset to Hugging Face Hub

Requirements

pip install datasets
pip install kagglehub huggingface_hub tqdm

Usage

  1. Set up your Hugging Face authentication token
  2. Run the script:
python combined_medium_ds_generator.py

Data Processing Steps

  1. Downloads datasets from Kaggle and Hugging Face
  2. Normalizes each dataset by:
    • Removing null values
    • Eliminating duplicates
    • Standardizing column names
  3. Combines all datasets into a single DataFrame
  4. Saves the result as a Parquet file
  5. Uploads the final dataset to Hugging Face Hub

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Acknowledgments

Special thanks to the original dataset creators:

  • aiswaryaramachandran
  • hsankesara
  • meruvulikith
  • fabiochiu
  • Falah