README.md

---
dataset_info:
  features:
  - name: url
    dtype: string
  - name: repository_url
    dtype: string
  - name: labels_url
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  - name: comments_url
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    - name: site_admin
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    - name: starred_url
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    - name: type
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    - name: url
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    - name: user_view_type
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  - name: labels
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    - name: color
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    - name: default
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    - name: url
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  - name: locked
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  - name: assignee
    struct:
    - name: avatar_url
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    - name: events_url
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    - name: followers_url
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    - name: following_url
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    - name: gravatar_id
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    - name: html_url
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    - name: login
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    - name: organizations_url
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    - name: received_events_url
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    - name: repos_url
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    - name: site_admin
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    - name: starred_url
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    - name: type
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    - name: url
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    - name: user_view_type
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  - name: assignees
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    - name: events_url
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    - name: followers_url
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    - name: following_url
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    - name: gists_url
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    - name: html_url
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    - name: site_admin
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    - name: type
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    - name: url
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    - name: user_view_type
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  - name: milestone
    struct:
    - name: closed_at
      dtype: string
    - name: closed_issues
      dtype: int64
    - name: created_at
      dtype: string
    - name: creator
      struct:
      - name: avatar_url
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      - name: events_url
        dtype: string
      - name: followers_url
        dtype: string
      - name: following_url
        dtype: string
      - name: gists_url
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      - name: gravatar_id
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      - name: html_url
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      - name: id
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      - name: login
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      - name: node_id
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      - name: organizations_url
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      - name: received_events_url
        dtype: string
      - name: repos_url
        dtype: string
      - name: site_admin
        dtype: bool
      - name: starred_url
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      - name: subscriptions_url
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      - name: type
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      - name: url
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      - name: user_view_type
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    - name: description
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    - name: due_on
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    - name: html_url
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    - name: id
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    - name: labels_url
      dtype: string
    - name: node_id
      dtype: string
    - name: number
      dtype: int64
    - name: open_issues
      dtype: int64
    - name: state
      dtype: string
    - name: title
      dtype: string
    - name: updated_at
      dtype: string
    - name: url
      dtype: string
  - name: comments
    dtype: int64
  - name: created_at
    dtype: string
  - name: updated_at
    dtype: string
  - name: closed_at
    dtype: string
  - name: author_association
    dtype: string
  - name: type
    dtype: float64
  - name: active_lock_reason
    dtype: float64
  - name: draft
    dtype: float64
  - name: pull_request
    struct:
    - name: diff_url
      dtype: string
    - name: html_url
      dtype: string
    - name: merged_at
      dtype: string
    - name: patch_url
      dtype: string
    - name: url
      dtype: string
  - name: body
    dtype: string
  - name: closed_by
    struct:
    - name: avatar_url
      dtype: string
    - name: events_url
      dtype: string
    - name: followers_url
      dtype: string
    - name: following_url
      dtype: string
    - name: gists_url
      dtype: string
    - name: gravatar_id
      dtype: string
    - name: html_url
      dtype: string
    - name: id
      dtype: int64
    - name: login
      dtype: string
    - name: node_id
      dtype: string
    - name: organizations_url
      dtype: string
    - name: received_events_url
      dtype: string
    - name: repos_url
      dtype: string
    - name: site_admin
      dtype: bool
    - name: starred_url
      dtype: string
    - name: subscriptions_url
      dtype: string
    - name: type
      dtype: string
    - name: url
      dtype: string
    - name: user_view_type
      dtype: string
  - name: reactions
    struct:
    - name: '+1'
      dtype: int64
    - name: '-1'
      dtype: int64
    - name: confused
      dtype: int64
    - name: eyes
      dtype: int64
    - name: heart
      dtype: int64
    - name: hooray
      dtype: int64
    - name: laugh
      dtype: int64
    - name: rocket
      dtype: int64
    - name: total_count
      dtype: int64
    - name: url
      dtype: string
  - name: timeline_url
    dtype: string
  - name: performed_via_github_app
    dtype: float64
  - name: state_reason
    dtype: string
  - name: sub_issues_summary
    struct:
    - name: completed
      dtype: int64
    - name: percent_completed
      dtype: int64
    - name: total
      dtype: int64
  - name: issue_dependencies_summary
    struct:
    - name: blocked_by
      dtype: int64
    - name: blocking
      dtype: int64
    - name: total_blocked_by
      dtype: int64
    - name: total_blocking
      dtype: int64
  - name: is_pull_request
    dtype: bool
  splits:
  - name: train
    num_bytes: 30007928
    num_examples: 7744
  download_size: 5833903
  dataset_size: 30007928
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
annotations_creators: []
language:
- en
language_creators: []
multilinguality: []
pretty_name: GitHub Issues without Comments
source_datasets: []
task_categories:
- text-classification
- text-retrieval
task_ids:
- multi-class-classification
- multi-label-classification
- document-retrieval
---

# Dataset Card for GitHub Issues without Comments


## Dataset Description

- **Point of Contact:** [Liang Jinbin](liangjinbin93@gmail.com)

### Dataset Summary

The GitHub Issues dataset contains issues and pull requests from the 🤗 Datasets [repository](https://github.com/huggingface/datasets) ,but it does not include the comments.It supports tasks like Text classification and text retrieval. Each entry is an English-language discussion centered around NLP, computer vision, and other machine learning datasets.

## Dataset Metadata
| Attribute                | Value                                                                 |
|--------------------------|-----------------------------------------------------------------------|
| **Modalities**           | Tabular, Text                                                         |
| **Data Formats**         | parquet                                                               |
| **Dataset Size**         | 1K – 10K samples (7.74k rows in total)                                |
| **Supported Libraries**  | Datasets, pandas, Croissant                                           |
| **Language**             | English (issue titles, bodies, and metadata are in English)           |
| **Original Source**      | https://huggingface.co/datasets/Jason-ice-SCUT/github-issues           |
| **License**              | Not specified (refer to original GitHub repository and Hugging Face terms for usage permissions) |
| **Primary Task**         | Text Classification, Text Retrieval                                   |
| **Sub-tasks**            | Multi-class classification, Multi-label classification, Document retrieval |
| **Data Split**           | Single split (`train`: 7.74k rows)                                    |

## Data Structure
The dataset includes over 30 columns covering issue metadata, content, contributor info, and interaction data. Key columns are detailed below (full schema includes additional nested fields):

| Column Name         | Data Type       | Description                                                                 |
|---------------------|-----------------|-----------------------------------------------------------------------------|
| `id`                | int64           | Unique GitHub issue ID (range: 599M – 3.53B)                               |
| `node_id`           | string          | GitHub node ID for the issue/pull request                                   |
| `number`            | int64           | Repository-specific issue/pull request number (range: 1 – 7.82k)            |
| `title`             | string          | Issue/pull request title (length: 1 – 290 characters)                       |
| `body`              | string          | Detailed content of the issue/pull request (length: 0 – 228k characters)    |
| `user`              | dict            | Contributor information (avatar URL, login, ID, profile URL, etc.)           |
| `labels`            | list            | Issue labels (length: 0 – 4; e.g., "enhancement", "bug")                    |
| `state`             | string          | Issue state (2 values: "open" or "closed")                                  |
| `locked`            | bool            | Whether the issue is locked (1 class: `false`)                              |
| `comments`          | int64           | Number of comments (range: 0 – 70)                                          |
| `created_at`        | string (date)   | Creation timestamp (range: 2020-04-14 – 2025-10-20)                        |
| `updated_at`        | string (date)   | Last update timestamp                                                       |
| `closed_at`         | string          | Closure timestamp (length: 3 – 25 characters; `NaT` if open)                |
| `author_association`| string          | Contributor's association with the repo (4 values: MEMBER, CONTRIBUTOR, NONE, etc.) |
| `is_pull_request`   | bool            | Whether the entry is a pull request (2 classes: `true`/`false`)              |
| `pull_request`      | dict            | Pull request details (diff URL, HTML URL, merged timestamp, etc.)            |
| `reactions`         | dict            | User reactions (e.g., "+1", "heart", "rocket"; includes total count)         |

### Sample Data
| id           | number | title                                  | state | is_pull_request | created_at           | comments |
|--------------|--------|----------------------------------------|-------|-----------------|----------------------|----------|
| 3531240254   | 7824   | Fix batch_size default description in to_polars docstrings | open  | true            | 2025-10-20 06:41:20  | 1        |
| 3525440347   | 7823   | Fix random seed on shuffle and interleave_datasets | open  | true            | 2025-10-17 14:11:18  | 0        |
| 3520913195   | 7821   | Building a dataset with large variable size arrays results in error | open  | false           | 2025-10-17 09:52:05  | 0        |

## Content Categories
The dataset’s entries can be categorized by type and purpose, reflecting common GitHub workflow activities:

### 1. Pull Requests (Majority of Samples)
- **Bug Fixes**: Resolve technical issues (e.g., "Fix random seed on shuffle", "Fix nested data conversions error in parquet loading").
- **Feature Additions**: Introduce new functionality (e.g., "Add nifti support", "Allow streaming hdf5 files", "Add `num_proc` argument to `Dataset.to_sql`").
- **Documentation Updates**: Improve docs (e.g., "Fix batch_size default description in docstrings", "Docs: fix typo, improve readability").
- **Dependency & CI Adjustments**: Update dependencies or CI configurations (e.g., "fix conda deps", "Define CI future").

### 2. Issues
- **Bug Reports**: Report technical problems (e.g., "Audio dataset is not decoding on 4.1.1", "Cannot load dataset with nested data").
- **Feature Requests**: Propose new features (e.g., "Support scientific data formats", "Concatenate IterableDataset instances in RoundRobin manner").
- **Documentation Feedback**: Highlight missing or incorrect docs (e.g., "Missing documentation for `Dataset.from_dict`").

## Dataset Characteristics
- **Rich Metadata**: Includes detailed contributor, timestamp, and interaction data for contextual analysis.
- **Real-World Relevance**: Captures authentic software development workflows and challenges in the Hugging Face ecosystem.
- **Structured & Unstructured Data**: Combines tabular metadata (e.g., `state`, `comments`) with unstructured text (e.g., `title`, `body`).
- **Time-Span Coverage**: Spans 5+ years, enabling trend analysis of project development and issue patterns.

## Usage Scenarios
- **Text Classification**: Train models to classify issue types (bug vs. feature request), pull request purposes, or contributor roles.
- **Text Retrieval**: Build systems to retrieve similar issues/pull requests for duplicate detection or solution reference.
- **Software Engineering Research**: Analyze issue resolution times, contributor collaboration patterns, or bug frequency in open-source projects.
- **Sentiment Analysis**: Evaluate sentiment in issue discussions (e.g., frustration, approval) to inform community management.
- **Automated Issue Triage**: Develop tools to auto-label issues or assign contributors based on content and metadata.

## Limitations
- **Repository-Specific**: Focuses exclusively on `huggingface/datasets`, limiting generalizability to other GitHub projects.
- **No Multilingual Support**: All content is in English, excluding non-English GitHub communities.
- **Nested Data Complexity**: Some columns (e.g., `user`, `pull_request`) are nested dictionaries, requiring preprocessing for simple analysis.
- **Missing Context**: May lack external context (e.g., linked commits, external references) that could enhance analysis.

## Recommended Usage
- **Preprocessing**: Flatten nested columns (e.g., extract `user.login` from `user` dict) for tabular analysis.
- **Text Cleaning**: Remove code blocks, URLs, and markdown formatting from `body` for NLP tasks like classification.
- **Combination with Other Data**: Pair with GitHub commit or repository data to enrich analysis of issue-resolution workflows.
- **Filtering**: Subset data by `is_pull_request`, `state`, or `labels` to focus on specific task needs (e.g., bug fix classification).

## Example Code Snippet
Load the dataset and explore key fields:
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Jason-ice-SCUT/github-issues", split="train")

# Inspect basic info
print(f"Dataset size: {len(dataset)}")
print(f"Column names: {dataset.column_names[:10]}")  # Show first 10 columns

# Filter pull requests related to "bug fixes"
bug_fixes = dataset.filter(
    lambda x: x["is_pull_request"] and "fix" in x["title"].lower()
)
print(f"Number of bug fix PRs: {len(bug_fixes)}")

# Extract issue titles and bodies for text classification
text_data = dataset.select_columns(["title", "body", "is_pull_request"])