metadata
license: mit
language:
- en
size_categories:
- 100K<n<1M
task_categories:
- text-classification
- text-retrieval
tags:
- github
- issues
- bug-tracking
- multi-label
- priority-classification
- severity-classification
pretty_name: 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 & 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:
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
- Collected open issues from the top 100 repositories on GitHub.
- Filtered only English issues with assigned labels.
- Processed priority and severity:
- Used labels to determine priority & severity.
- Used ML models to predict missing priority/severity values.
- 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.
- Want to contribute? Feel free to submit a PR.
- For any questions, reach out on Hugging Face Discussions.
⭐ Support
📌 If you find this dataset useful, please like ❤️ the repository!
🚀 Happy Coding! 🚀