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---
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](https://github.com/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
```python
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}}
} |