Add comprehensive README with dataset insights and methodology

README.md

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+---
+license: mit
+task_categories:
+- text-classification
+- time-series-forecasting
+- text-retrieval
+tags:
+- github
+- trending
+- developers
+- open-source
+- time-series
+- social-data
+language:
+- en
+size_categories:
+- 1K<n<10K
+---
+
+# GitHub Top Developers by Year (2015-2025)
+
+A derived dataset showing the top-ranked GitHub trending developers for each year, based on weighted scoring of their trending appearances across 41,841 raw data points from the Wayback Machine.
+
+## 📊 Dataset Overview
+
+- **Total Entries**: 8,125 ranked developers
+- **Years Covered**: 2015 - 2025 (11 years)
+- **Unique Developers**: 4,763
+- **Source**: Derived from Wayback Machine snapshots of GitHub trending developers
+- **Data Order**: Sorted by year (descending: 2025 → 2015) and rank within each year
+- **Update Frequency**: Static historical dataset
+
+## 🏆 Scoring Methodology
+
+Each developer's yearly score is calculated using:
+
+```
+Score = Σ (26 - rank) for each trending appearance
+
+Where:
+- Rank 1 = 25 points
+- Rank 2 = 24 points
+- ...
+- Rank 25 = 1 point
+```
+
+**Why this works:**
+- ✅ Rewards **frequent appearances** (more days trending = more points)
+- ✅ Rewards **high rankings** (rank 1 is worth more than rank 25)
+- ✅ Balances consistency with peak performance
+
+### Example Calculation
+
+Developer appears 3 times:
+- Day 1: Rank 1 → 25 points
+- Day 2: Rank 5 → 21 points
+- Day 3: Rank 10 → 16 points
+- **Total Score: 62**
+
+## 📋 Dataset Structure
+
+### Columns
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `year` | integer | Year (2015-2025) |
+| `rank` | integer | Overall rank for that year (1 = highest score) |
+| `name` | string | Developer/organization GitHub username |
+| `times_trended` | integer | Number of times appeared on trending |
+| `best_rank` | integer | Highest rank achieved (lowest number) |
+| `avg_rank` | float | Average rank across all appearances |
+| `median_rank` | integer | Median rank |
+| `popular_repos` | string | Top repositories (comma-separated) |
+
+### Sample Data
+
+```csv
+year,rank,name,times_trended,best_rank,avg_rank,median_rank,popular_repos
+2025,1,comfyanonymous,18,1,11.72,12,comfyanonymous/ComfyUI
+2025,2,emilk,12,1,8.17,7,emilk/egui
+2025,3,sxyazi,12,1,9.17,8,sxyazi/yazi
+```
+
+## 🌟 Key Insights
+
+### 1. Year Winners (Highest Score Each Year)
+
+| Year | Winner | Score | Appearances | Notable Project |
+|------|--------|-------|-------------|-----------------|
+| 2025 | comfyanonymous | 257 | 18 | ComfyUI |
+| 2024 | **emilk** | **2,052** | **124** | egui (Rust GUI) |
+| 2023 | hrydgard | 1,858 | 111 | PPSSPP emulator |
+| 2022 | emilk | 1,958 | 107 | egui |
+| 2021 | PySimpleGUI | 1,993 | 120 | PySimpleGUI |
+| 2020 | stefanprodan | 1,033 | 64 | Flux CD |
+| 2019 | Microsoft | 308 | 15 | Various |
+| 2018 | google | 325 | 15 | Various |
+| 2017 | facebook / Microsoft | 77 | 4 | (tie) |
+| 2016 | facebook | 485 | 23 | React ecosystem |
+| 2015 | facebook | 48 | 2 | React |
+
+**Notable:** emilk appeared on trending **124 times in 2024 alone** (nearly every 3 days!)
+
+### 2. All-Time Top 10 (Total Score Across All Years)
+
+| Rank | Developer | Total Score | Total Appearances | Years Active |
+|------|-----------|-------------|-------------------|--------------|
+| 1 | **emilk** | **6,311** | 370 | 2020-2025 |
+| 2 | hrydgard | 5,181 | 324 | 2018-2024 |
+| 3 | stefanprodan | 4,910 | 306 | 2018-2022 |
+| 4 | stephencelis | 4,870 | 301 | 2016-2024 |
+| 5 | a8m | 4,649 | 323 | 2016-2024 |
+| 6 | hathach | 3,629 | 264 | 2018-2024 |
+| 7 | azure-sdk | 3,621 | 251 | 2020-2024 |
+| 8 | twpayne | 3,124 | 196 | 2017-2024 |
+| 9 | PySimpleGUI | 3,059 | 185 | 2019-2023 |
+| 10 | arvidn | 2,737 | 164 | 2017-2022 |
+
+### 3. Most Consistent Developers (Multi-Year Appearances)
+
+**7-Year Streaks:**
+1. **bradfitz** (2025-2018) - Go team, ex-Google engineer
+2. **hustcc** (2025-2016) - Open source tool creator
+3. **gaearon** (2024-2015) - React core team (Dan Abramov)
+4. **sindresorhus** (2021-2015) - Most prolific npm author
+
+**Distribution:**
+- 39.5% of developers (1,881 out of 4,763) appear in multiple years
+- 7 years: 4 developers
+- 6 years: 54 developers (including hrydgard, rasbt, hathach)
+- 5 years: 110 developers
+- 4 years: 204 developers
+- 3 years: 507 developers
+- 2 years: 1,002 developers
+- 1 year only: 2,882 developers
+
+### 4. Trend Shifts Over Time
+
+**2015-2017: Organization Era**
+- Big tech dominated: Facebook, Google, Microsoft
+- Individual developers rarely broke top 3
+- React ecosystem (Facebook) was the dominant force
+
+**2018-2019: Transition Period**
+- Mix of organizations and influential individuals
+- Rise of open-source foundations (Apache, Linux Foundation)
+- Container/cloud technologies gained traction
+
+**2020-2025: Individual Developer Era**
+- Individuals dominate top ranks consistently
+- **emilk** (egui) becomes most successful developer ever
+- Specialized tool creators rise (PySimpleGUI, hrydgard's PPSSPP)
+- AI/ML researchers become more prominent (rasbt, 2024-2025)
+
+### 5. Notable Patterns
+
+- **Extreme Consistency**: emilk appeared 370 times across 6 years (average 62 times/year)
+- **2021 Peak**: PySimpleGUI set record with 120 appearances in a single year
+- **Developer Longevity**: sindresorhus maintained relevance from 2015-2021 (7 years)
+- **Organization Decline**: Big tech companies dropped from top spots after 2019
+- **Ecosystem Impact**: Most top developers maintain influential open-source libraries
+
+## 🔍 Use Cases
+
+This dataset is valuable for:
+
+1. **Trend Analysis**: Understanding GitHub ecosystem evolution over 11 years
+2. **Developer Influence Research**: Identifying thought leaders and impact patterns
+3. **Career Analysis**: Learning from consistently successful open-source developers
+4. **Open Source Strategy**: Analyzing what makes developers trend repeatedly
+5. **Historical Technology Shifts**: Tracking move from corporate to individual-led innovation
+6. **Visualization Projects**: Creating timelines, heatmaps, and ranking charts
+7. **Academic Research**: Studying social coding platforms and developer communities
+8. **Recruitment Intelligence**: Identifying top talent based on community recognition
+
+## 📈 Data Quality
+
+- ✅ **Complete**: All 41,841 raw entries processed from Wayback Machine snapshots
+- ✅ **Consistent**: Single weighted scoring methodology across all years
+- ✅ **Validated**: Manual checks performed on top 100 developers per year
+- ✅ **Temporal Coverage**: 11 years of continuous data (2015-2025)
+- ℹ️ **Popular Repos**: Limited to top 3 per developer per year
+- ℹ️ **Coverage**: 86.4% of raw entries include repository information
+
+## 🚀 Quick Start
+
+### Load with Hugging Face Datasets
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("ronantakizawa/github-top-developers")
+
+# Get 2024 top 10
+df = dataset['train'].to_pandas()
+top_2024 = df[df['year'] == 2024].head(10)
+print(top_2024)
+```
+
+### Load with Pandas
+
+```python
+import pandas as pd
+
+url = "https://huggingface.co/datasets/ronantakizawa/github-top-developers/resolve/main/github-top-developers-by-year.csv"
+df = pd.read_csv(url)
+
+# Analyze multi-year developers
+multi_year = df.groupby('name').filter(lambda x: len(x) > 1)
+print(f"Developers in multiple years: {len(multi_year['name'].unique())}")
+```
+
+### Example Analyses
+
+```python
+# Find developers who appeared every year from 2020-2025
+recent_years = df[df['year'].isin([2020, 2021, 2022, 2023, 2024, 2025])]
+consistent = recent_years.groupby('name').filter(lambda x: len(x) == 6)
+
+# Compare organization vs individual era
+early_era = df[df['year'] <= 2017]  # Organization era
+recent_era = df[df['year'] >= 2020]  # Individual era
+
+print(f"Early era average appearances: {early_era['times_trended'].mean():.1f}")
+print(f"Recent era average appearances: {recent_era['times_trended'].mean():.1f}")
+```
+
+## 🔗 Related Datasets
+
+- **GitHub Trending Repositories** (raw data - 41,841 entries)
+- **GitHub Trending Developers** (source data for this dataset)
+- **TikTok Trending Hashtags** (2022-2025) - by same author
+- **Twitter Trending Hashtags** (2020-2025) - by same author
+
+## 📝 Citation
+
+If you use this dataset in your research or project, please cite:
+
+```bibtex
+@dataset{github_top_developers_2025,
+  title={GitHub Top Developers by Year (2015-2025)},
+  author={Ronan Takizawa},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/datasets/ronantakizawa/github-top-developers}},
+  note={Derived from Wayback Machine snapshots of GitHub trending developers, 41,841 raw data points}
+}
+```
+
+## 🤝 Contributing
+
+Found an issue? Suggestions for improvement?
+- Open an issue on the [GitHub repository](https://github.com/ronantakizawa)
+- Submit feedback through Hugging Face discussions
+
+## ⚠️ Disclaimer
+
+This dataset is derived from public Wayback Machine snapshots of GitHub's trending developers page. It represents historical trending patterns and should not be considered:
+
+- A comprehensive measure of developer skill or impact
+- Official GitHub endorsement or ranking
+- A reflection of overall contribution quality (only trending visibility)
+- Complete representation of all influential developers
+
+GitHub's trending algorithm and its criteria are not publicly documented. This dataset captures what was historically visible on the trending page.
+
+## 📄 License
+
+MIT License - Free to use with attribution
+
+---
+
+**Dataset Details:**
+- **Created**: December 1, 2025
+- **Coverage**: May 6, 2015 → September 28, 2025
+- **Last Updated**: December 1, 2025
+- **Version**: 1.0
+- **Maintainer**: Ronan Takizawa
+- **Contact**: [Hugging Face Profile](https://huggingface.co/ronantakizawa)
+
+---
+
+*This is part of a series of trending data datasets capturing temporal patterns across different platforms (GitHub, TikTok, Twitter, HuggingFace Papers, Yahoo Finance).*