Datasets › notebookcdg

notebookcdg

Introduced by Xuye Liu et al. in HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks31 Mar 2021 archive 2025-07-28

Inspired by Wang et al. 2021, we decided to utilize the top-voted and well-documented Kaggle notebooks to construct the notebookCDGdataset

We collected the top 10% highly-voted notebooks from the top 20 popular competitions on Kaggle (e.g. Titanic). We checked the data policy of each of the 20 competitions, none of them has copyright issues. We also contacted the Kaggle administrators to make sure our data collection complies with the platform’s policy.

In total, we collected 3,944 notebooks as raw data. After data preprocessing, the final dataset contains 2,476 notebooks out of the 3,944 notebooks from the raw data. It has 28,625 code–documentation pairs. The overall code-to-markdown ratio is 2.2195

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Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC-BY

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • notebookcdg

1 variant name, as the archive lists them.

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