MWirelabs/Northeast-India-Districts-and-Villages

🌄 Northeast India StateWise Districts and Villages Dataset

📊 Dataset Description

A comprehensive dataset mapping 49,275 villages across all 8 Northeast Indian states - the "Eight Sisters" of India. This dataset serves as a foundational resource for AI/ML applications, geographic analysis, and development planning in Northeast India.

🎯 Mission

"Building AI for Northeast India - One village at a time"

This dataset is a stepping stone towards digital transformation and AI-driven development in one of India's most diverse and culturally rich regions.

📈 Quick Statistics

State	Villages	Districts
Assam	28,818	35
Meghalaya	7,185	12
Arunachal Pradesh	5,485	26
Manipur	3,850	16
Nagaland	1,669	16
Tripura	898	8
Mizoram	885	11
Sikkim	485	6

• 🏘️ Rural Villages: 45,462 (92.3%)
• 🏢 Urban Villages: 150 (0.3%)
• 📍 Semi-Urban: 3,663 (7.4%)

🗂️ Dataset Structure

{
  'state': 'Assam',
  'district_name': 'Kamrup',
  'village_name': 'Guwahati',
  'village_category': 'Urban'
}

Data Fields

• state (string): Name of the state
• district_name (string): Name of the district
• village_name (string): Name of the village
• village_category (string): Classification (Rural/Urban/Semi-Urban)

💡 Use Cases & Applications

🚀 Current Applications

• Geographic Information Systems (GIS) - Mapping and spatial analysis
• NLP & Language Tech - Location entity recognition for Indian languages
• Development Analytics - Rural-urban development gap analysis
• Policy Planning - Resource allocation and scheme implementation
• Disaster Management - Flood mapping and evacuation planning

🔮 Future Possibilities

• Multi-lingual chatbots for government services
• Agricultural yield prediction at village level
• Healthcare accessibility modeling
• Internet connectivity priority mapping
• Migration pattern analysis
• Climate change impact assessment

🔧 Quick Start

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("MWirelabs/Northeast-India-Districts-and-Villages")

# Convert to pandas
import pandas as pd
df = pd.DataFrame(dataset['train'])

# Basic exploration
print(f"Total villages: {len(df)}")
print(f"States covered: {df['state'].nunique()}")
print(df['state'].value_counts())

📖 Source & Methodology

• Source: LGDirectory - Government of India
• Collection Date: 2024
• Cleaning Process:
  • Removed duplicates
  • Standardized naming conventions
  • Validated district-state mappings
  • Categorized village types

🤝 Contributing

We welcome contributions to enhance this dataset! Areas for expansion:

• Geographic coordinates (latitude/longitude)
• Population data
• Infrastructure indicators
• Connectivity status
• Local language names

📜 License

This dataset is released under CC BY 4.0 license. You are free to:

• Share and redistribute
• Adapt and build upon
• Use for commercial purposes

With attribution to the original source.

📚 Citation

@dataset{northeast_india_villages_2024,
  title={Northeast India StateWise Districts and Villages Dataset},
  author={MWire Labs},
  year={2024},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/MWirelabs/Northeast-India-Districts-and-Villages}
}

🌟 Acknowledgments

Special thanks to:

• Government of India's LGDirectory initiative
• The open-source community
• Researchers working on Northeast India development

📬 Contact

MWire Labs

• 🌐 Organization: MWirelabs
• 📧 For collaborations and queries, reach out through HuggingFace

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Building the future of Northeast India through data and AI 🚀