Update README.md

README.md

@@ -49,14 +49,6 @@ Where:
 - ✅ 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
@@ -72,15 +64,6 @@ Developer appears 3 times:
 | `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)
@@ -116,25 +99,7 @@ year,rank,name,times_trended,best_rank,avg_rank,median_rank,popular_repos
 | 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
+### 3. Trend Shifts Over Time
 
 **2015-2017: Organization Era**
 - Big tech dominated: Facebook, Google, Microsoft
@@ -160,125 +125,8 @@ year,rank,name,times_trended,best_rank,avg_rank,median_rank,popular_repos
 - **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).*