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sharjeelyunus/github-issues-dataset

📌 GitHub Issues Dataset 📂 Dataset Name: github-issues-dataset📊 Total Issues: 114073📜 Format: Parquet (.parquet)🔍 Source: GitHub Repositories (Top 100 Repos) 📖 Overview This dataset contains 114,073 GitHub issues collected from the top 100 repositories on GitHub.It is designed for issue classification, severity/priority prediction, and AI/ML training. ✅ This dataset is useful for: AI/ML Training: Fine-tune models for issue classification &… See the full description on the dataset page: https://huggingface.co/datasets/sharjeelyunus/github-issues-dataset.

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📌 GitHub Issues Dataset

![Hugging Face Dataset](https://huggingface.co/datasets/github-issues-dataset)

📂 Dataset Name: github-issues-dataset 📊 Total Issues: 114073 📜 Format: Parquet (`.parquet`) 🔍 Source: GitHub Repositories (Top 100 Repos)

📖 Overview

This dataset contains 114,073 GitHub issues collected from the top 100 repositories on GitHub. It is designed for issue classification, severity/priority prediction, and AI/ML training.

✅ This dataset is useful for:

—AI/ML Training: Fine-tune models for issue classification & prioritization.
—Natural Language Processing (NLP): Analyze software development discussions.
—Bug Severity Prediction: Train models to classify issues as Critical, Major, or Minor.

📂 Dataset Structure

The dataset is stored in Parquet format (`github_issues_dataset.parquet`) for efficient storage and fast retrieval.

Columns in the Dataset:

Column	Type	Description
`id`	`int`	Github issue id
`repo`	`str`	Repository name
`title`	`str`	Issue title
`body`	`str`	Issue description
`labels`	`list`	Assigned GitHub labels
`priority`	`str`	Estimated priority (`high`, `medium`, `low`)
`severity`	`str`	Estimated severity (`Critical`, `Major`, `Minor`)

📥 Download & Use

Using `datasets` Library

You can easily load this dataset using Hugging Face's datasets library:

python

from datasets import load_dataset

dataset = load_dataset("sharjeelyunus/github-issues-dataset")

📊 Sample Data

id	repo	title	labels	priority	severity
101	`pytorch/pytorch`	"RuntimeError: CUDA out of memory"	`["bug", "cuda"]`	high	Critical
102	`tensorflow/tensorflow`	"Performance degradation in v2.9"	`["performance"]`	medium	Major
103	`microsoft/vscode`	"UI freeze when opening large files"	`["ui", "bug"]`	low	Minor

🛠 How This Dataset Was Created

1.Collected open issues from the top 100 repositories on GitHub.
2.Filtered only English issues with assigned labels.
3.Processed priority and severity:
4.Used labels to determine priority & severity.
5.Used ML models to predict missing priority/severity values.
6.Stored dataset in Parquet format for ML processing.

🔍 Use Cases

—AI-Powered Bug Triage: Train AI models to predict priority & severity.
—NLP Research: Analyze software engineering discussions.

📜 License

This dataset is open-source and publicly available under the MIT License. Please cite this dataset if you use it in research.

📫 Feedback & Contributions

—Found an issue? Open an [issue](https://github.com/sharjeelyunus/github-issues-analyzer/issues).
—Want to contribute? Feel free to submit a PR.
—For any questions, reach out on [Hugging Face Discussions](https://huggingface.co/datasets/sharjeelyunus/github-issues-dataset/discussions).

⭐ Support

📌 If you find this dataset useful, please like ❤️ the repository! 🚀 Happy Coding! 🚀