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| license: apache-2.0 |
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| This dataset provides a rich, multi‑faceted snapshot of GitHub’s global open‑source ecosystem. It is built by querying the GitHub REST API with a focus on: |
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| Active users per country – the most followed developers in each of 39 countries (up to 20 per country), capturing their public profile information, follower counts, repository counts, and account creation dates. |
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| Repositories owned by those users – up to 5 repositories per user, with detailed metadata (stars, forks, language, topics, license, etc.). |
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| Top‑starred repositories by language – for 12 mainstream programming languages, the 15 most starred repositories (stars > 1000), plus a global Top 50 (stars > 5000) across all languages. |
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| All timestamps have been normalised to naive (timezone‑free) format for easy analysis. The dataset is ideal for: |
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| Studying the geographical distribution of GitHub activity and influence. |
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| Analysing trends in popular repositories and language ecosystems. |
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| Building recommendation systems, social network graphs, or developer analytics dashboards. |
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| Exploring correlations between developer metrics (followers, repos, account age) and project popularity. |
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| 📁 Included Files |
| File Name Content |
| github_users_by_country.csv User profiles (login, name, location, company, email, bio, public repos, followers, following, created/updated dates, HTML URL, account age in days) |
| github_user_repos.csv Repositories owned by the users above (full name, description, language, stars, forks, watchers, open issues, license, creation/update/push dates, topics, archived flag, plus user login and country) |
| github_starred_repos.csv Famous repositories per language + global top (full name, owner, description, language, stars, forks, watchers, open issues, license, dates, topics, archived, plus the language filter used for collection) |
| github_country_stats.csv Aggregated statistics by country (user count, total followers, total public repos) |
| dataset_summary.json Metadata about the dataset (creation time, number of users, countries, languages, etc.) |
| 🔍 Collection Methodology |
| Data source: GitHub REST API via PyGithub. |
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| Authentication: Personal Access Token (rate limit ~5000 requests/hour). |
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| Countries: 39 countries (major developer hubs across Asia, Europe, Americas, Africa, and Oceania). |
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| User selection: For each country, sorted by follower count descending, taking the top 20. |
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| User repos: Up to 5 most recent repositories per user (determined by API order). |
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| Starred repos: For each of 12 languages (Python, JavaScript, TypeScript, Java, Go, Rust, C++, Ruby, PHP, Swift, Kotlin, Shell), repositories with >1000 stars, sorted by stars, taking the top 15. Plus a separate global query for >5000 stars taking the top 50. |
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| Rate‑limit handling: Exponential backoff with automatic retry on 403 errors. |
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| Data cleaning: All datetime fields are converted to naive (timezone‑neutral) to avoid compatibility issues. |
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| 📅 Data Snapshot |
| Creation date: (included in dataset_summary.json) |
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| Total users: ~780 (varies per run) |
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| Total countries: 39 |
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| Total user repositories: ~3,700 |
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| Total starred repositories: ~230 |
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| 🔧 Use Cases |
| Geographic analysis: Compare developer density, activity, and influence across regions. |
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| Language popularity: Identify which languages dominate in terms of high‑star projects. |
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| Trend spotting: Monitor growth of individual developers or repositories over time (via account age and update dates). |
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| Network analysis: Build collaboration graphs using user‑repo ownership links. |
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| Recommendation engines: Suggest repositories or users based on similarity metrics. |
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| 📋 License & Attribution |
| This dataset is compiled from public GitHub data. Please respect GitHub’s Terms of Service and API Terms. When using this dataset, we kindly request that you cite the original source (GitHub) and, if applicable, link to this dataset description. |
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