README.md

metadata

annotations_creators:
  - no-annotation
language:
  - en
language_creators:
  - found
license:
  - unknown
multilinguality:
  - monolingual
pretty_name: Pandas GitHub Issues
size_categories:
  - 1K<n<10K
source_datasets:
  - original
tags:
  - pandas
  - github
  - issues
task_categories:
  - text-classification
  - text-retrieval
task_ids:
  - multi-class-classification
  - multi-label-classification
  - document-retrieval
dataset_info:
  features:
    - name: id
      dtype: int64
    - name: number
      dtype: int64
    - name: title
      dtype: string
    - name: state
      dtype: string
    - name: created_at
      dtype: timestamp[s]
    - name: updated_at
      dtype: timestamp[s]
    - name: closed_at
      dtype: timestamp[s]
    - name: html_url
      dtype: string
    - name: is_pull_request
      dtype: bool
    - name: pull_request_url
      dtype: string
    - name: pull_request_html_url
      dtype: string
    - name: user_login
      dtype: string
    - name: comments_count
      dtype: int64
    - name: body
      dtype: string
    - name: labels
      list: string
    - name: reactions_plus1
      dtype: int64
    - name: reactions_minus1
      dtype: int64
    - name: reactions_laugh
      dtype: int64
    - name: reactions_hooray
      dtype: int64
    - name: reactions_confused
      dtype: int64
    - name: reactions_heart
      dtype: int64
    - name: reactions_rocket
      dtype: int64
    - name: reactions_eyes
      dtype: int64
    - name: comments
      list: string
  splits:
    - name: train
      num_bytes: 13757089
      num_examples: 5000
  download_size: 5167197
  dataset_size: 13757089
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Pandas GitHub Issues

This dataset contains 5,000 GitHub issues collected from the pandas-dev/pandas repository.
It includes issue metadata, content, labels, user information, timestamps, and comments.

The dataset is suitable for text classification, multi-label classification, and document retrieval tasks.

Dataset Structure

Columns:

• id — Internal ID of the issue (int64)
• number — GitHub issue number (int64)
• title — Title of the issue (string)
• state — Issue state: open/closed (string)
• created_at — Timestamp when the issue was created (timestamp[s])
• updated_at — Timestamp when the issue was last updated (timestamp[s])
• closed_at — Timestamp when the issue was closed (timestamp[s])
• html_url — URL to the GitHub issue (string)
• pull_request — Struct containing PR info (if the issue is a PR):
  • url — URL to PR
  • html_url — HTML URL of PR
  • diff_url — Diff URL
  • patch_url — Patch URL
  • merged_at — Merge timestamp (timestamp[s])
• user_login — Login of the issue creator (string)
• is_pull_request — Whether the issue is a pull request (bool)
• comments — List of comments on the issue (list[string])

Splits:

• train — 5,000 examples

Dataset Creation

The dataset was collected using the GitHub API, including all issue metadata and comments.

Usage Example

from datasets import load_dataset

dataset = load_dataset("your-username/pandas-github-issues", split="train")

# Preview first 5 examples
for i, example in enumerate(dataset[:5]):
    print(f"Issue #{example['number']}: {example['title']}")
    print(f"Created at: {example['created_at']}, Closed at: {example['closed_at']}")
    print(f"User: {example['user_login']}, PR: {example['is_pull_request']}")
    print(f"Comments: {example['comments'][:3]}")  # first 3 comments
    print()
___
## Citation

If you use this dataset, please cite it as:

```bibtex
@misc{yourusername_pandas_github_issues,
  author       = {Your Name},
  title        = {Pandas GitHub Issues Dataset},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/your-username/pandas-github-issues}}
}