Update README.md

README.md

@@ -34,13 +34,6 @@ This dataset captures the evolution of GitHub's trending repositories over time,
 - **Community interests** and shifts in developer focus over 12 years
 - **Viral repository dynamics** and sustained popularity patterns
 
-**Key Statistics:**
-- 📊 **423,098** trending repository entries
-- 🗂️ **14,500** unique repositories
-- 📅 **128 months** of coverage (2013-08 to 2025-11)
-- ⭐ **89.8%** scraping success rate from Wayback Machine
-- 🏆 **Pre-processed monthly rankings** with weighted scoring
-
 ## 🔧 Dataset Configurations
 
 This dataset has **two configurations** defined in the YAML header:
@@ -107,133 +100,10 @@ This rewards both **consistency** (frequent appearances) and **position** (highe
 **Snapshots:** 17,127 successfully scraped from 19,064 available
 **Retry Logic:** Up to 15 retries with exponential backoff
 
-## ⚠️ Known Limitations
-
-### 1. **Missing Star/Fork Data (Pre-2020)**
-- **100% of 2013-2019 entries** lack star/fork counts
-- Only **67.8% of dataset** has popularity metrics
-- **Impact:** Cannot compare absolute popularity for historical projects
-
-### 2. **Uneven Temporal Distribution**
-- Snapshot frequency: **1 to 31 per month** (31x variance)
-- 2019-2020 heavily over-represented
-- **Impact:** Monthly scores favor periods with more snapshots
-
-### 3. **Star Count Timing Inconsistency**
-- Star counts are "maximum ever recorded" across all snapshots
-- A 2015 project's stars might be from 2025 scraping
-- **Impact:** Can't fairly compare popularity across eras
-
-See `DATASET_ISSUES.md` for comprehensive analysis.
-
-## 📈 Data Quality by Era
-
-| Era | Quality | Star Data | Snapshot Density | Grade |
-|-----|---------|-----------|------------------|-------|
-| **2013-2019** | Limited | ❌ 0% | Low-Medium | **C+** |
-| **2020-2025** | Excellent | ✅ 100% | High | **A-** |
-
-**Recommendation:** Use 2020-2025 data for analyses requiring star/fork counts
-
-## 💡 Usage Examples
-
-### Load with Hugging Face Datasets (Recommended)
-
-```python
-from datasets import load_dataset
-
-# Load complete daily dataset (423,098 entries)
-ds_full = load_dataset('ronantakizawa/github-top-projects', 'full')
-df_full = ds_full['train'].to_pandas()
-
-# Load monthly top 25 dataset (3,200 entries)
-ds_monthly = load_dataset('ronantakizawa/github-top-projects', 'monthly')
-df_monthly = ds_monthly['train'].to_pandas()
-
-# Filter to 2020+ (with star data)
-df_recent = df_full[df_full['date'] >= '2020-01-01']
-
-# Get November 2025 top 10
-nov_2025 = df_monthly[df_monthly['month'] == '2025-11'].head(10)
-print(nov_2025[['rank', 'repository', 'star_count', 'ranking_appearances']])
-```
-
-### Time Series Analysis
-
-```python
-import pandas as pd
-import matplotlib.pyplot as plt
-from datasets import load_dataset
-
-ds = load_dataset('ronantakizawa/github-top-projects', 'full')
-df = ds['train'].to_pandas()
-df['date'] = pd.to_datetime(df['date'])
-
-# Analyze a specific project over time
-project = 'microsoft/vscode'
-project_df = df[(df['repo_owner'] == 'microsoft') & (df['name'] == 'vscode')]
-
-# Plot trending frequency over time
-monthly_counts = project_df.groupby(project_df['date'].dt.to_period('M')).size()
-monthly_counts.plot(title=f'{project} Trending Frequency')
-plt.ylabel('Days in Trending')
-plt.show()
-```
-
-## 🔍 Research Applications
-
-This dataset enables analysis of:
 
-1. **Trending Dynamics** - What makes a repository go viral?
-2. **Technology Adoption** - Rise and fall of programming languages
-3. **Open Source Evolution** - Growth of educational repositories
-4. **Predictive Modeling** - Forecasting future trending projects
-5. **Developer Behavior** - Community interest shifts
-
-## 📊 Example Insights
+## 📊 Insights
 
 **Most Consistently Trending (2020-2025):**
 1. `jwasham/coding-interview-university` - 1,948 appearances
 2. `TheAlgorithms/Python` - 1,891 appearances
 3. `donnemartin/system-design-primer` - 1,865 appearances
-
-## 📜 License
-
-**MIT License**
-
-This dataset is released under the MIT License. You can:
-- ✅ Use for commercial purposes
-- ✅ Modify and distribute
-- ✅ Use in research (attribution appreciated!)
-- ✅ Include in proprietary software
-
-## 🙏 Acknowledgments
-
-- **GitHub** for maintaining the trending page
-- **Internet Archive** for the Wayback Machine
-- **Open Source Community** for creating amazing projects
-
-## 📖 Citation
-
-If you use this dataset in your research, please cite:
-
-```bibtex
-@dataset{github_trending_2013_2025,
-  title={GitHub Trending Projects Dataset (2013-2025)},
-  author={Ronan Takizawa},
-  year={2025},
-  publisher={Hugging Face},
-  url={https://huggingface.co/datasets/ronantakizawa/github-top-projects}
-}
-```
-
-## 📅 Updates
-
-- **2025-12:** Initial release (2013-08 to 2025-11)
-- Future updates planned quarterly
-
----
-
-**Last Updated:** December 2025
-**Dataset Version:** 1.0
-**Status:** ✅ Complete and ready for use