https://github.com/ornella-gigante/wildlife-data-analysis-toolkit-ml
A data-driven exploration of Canis lupus signatus (Iberian) and Canis lupus labradorius (Labrador) subspecies, leveraging Jupyter Notebook and pandas to analyze weight distributions (25-56 kg), geographic patterns, and reproductive behaviors. Features size-weight correlations and NaN-handling workflows for robust ecological insights
https://github.com/ornella-gigante/wildlife-data-analysis-toolkit-ml
analysis data datasets jupyter-notebook pandas-dataframe python
Last synced: 14 days ago
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A data-driven exploration of Canis lupus signatus (Iberian) and Canis lupus labradorius (Labrador) subspecies, leveraging Jupyter Notebook and pandas to analyze weight distributions (25-56 kg), geographic patterns, and reproductive behaviors. Features size-weight correlations and NaN-handling workflows for robust ecological insights
- Host: GitHub
- URL: https://github.com/ornella-gigante/wildlife-data-analysis-toolkit-ml
- Owner: Ornella-Gigante
- License: gpl-3.0
- Created: 2024-02-28T18:04:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-07T09:22:10.000Z (9 months ago)
- Last Synced: 2025-03-11T14:53:53.920Z (8 months ago)
- Topics: analysis, data, datasets, jupyter-notebook, pandas-dataframe, python
- Language: Jupyter Notebook
- Homepage:
- Size: 1.28 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# WolfTrackr 🐺 - Wildlife Data Analysis Toolkit
**Unveiling the secrets of wolf subspecies through data-driven insights** 🌍📊
---
## 📌 Project Overview
**WolfTrackr** is a comprehensive data analysis project focusing on two wolf subspecies:
- **Iberian Wolf** (*Canis lupus signatus*) 🇪🇸🇵🇹
- **Labrador Wolf** (*Canis lupus labradorius*) 🇨🇦
This Jupyter Notebook-based toolkit explores biological metrics, geographic distribution, and population trends using advanced statistical methods and visualizations.
---
## 🚀 Key Features
- **📥 Data Cleaning**: Handles missing values (`NaN`) and normalizes datasets for accurate analysis.
- **🔍 Exploratory Analysis**: Compares size, weight, and reproductive patterns across subspecies.
- **📈 Weight Metrics**:
- Female Weight Range: 25-35 kg (Iberian) vs. 32-56 kg (Labrador)
- Male Weight Range: 36-55 kg (Iberian) vs. 39.7-48.2 kg (Labrador)
- **🌎 Geographic Insights**: Maps subspecies distribution in Northern Spain, Portugal, and Northern Quebec.
- **🖼️ Visualizations**: Interactive plots showing size/weight correlations and regional comparisons.
---
## 🛠️ Installation
```bash
# Clone the repository
git clone https://github.com/yourusername/WolfTrackr.git
# Install dependencies
pip install jupyter pandas numpy matplotlib seaborn
```
---
## 🧩 Dataset Structure
| Column | Description | Example Values |
|--------|-------------|----------------|
| `Adults_size(inches)` | Shoulder height | 44.4 (Iberian), 224.6 (Labrador) |
| `Female_Adults_weight(kg)` | Female weight range | 27-32 kg (Iberian) |
| `location` | Geographic region | Northern Spain, Portugal, Quebec |
| `mating_time` | Breeding season | "Feb-Mar" (Labrador), "little known" (Iberian) |
---
## 🎯 Usage
1. **Launch Jupyter Notebook**:
```bash
jupyter notebook WolfTrackr_Analysis.ipynb
```
2. **Key Analyses**:
- Compare subspecies weight distributions:
```python
df.groupby('Scientific_name')['Male_Adults_weight(kg)'].describe()
```
- Generate location-based heatmaps.
**Sample Output**:
Weight Distribution Comparison
---
## 🤝 How to Contribute
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/AmazingFeature`)
3. Submit a Pull Request
---
## 📜 License
Distributed under MIT License. See `LICENSE` for details.
---
## ✨ Acknowledgements
- Wildlife conservation datasets from [Global Wolf Initiative](https://example.com)
- Iconography by [FontAwesome](https://fontawesome.com)