https://github.com/mlucifer27/bilateral-visualization

Streamlit app visualizes bilateral relationship scores between 100 countries from 1945 to 2024. It supports interactive heatmaps, network graphs, pairwise comparisons, and more.
https://github.com/mlucifer27/bilateral-visualization

d3blocks data-analysis data-visualization plotly-python python streamlit

Last synced: 18 days ago
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Streamlit app visualizes bilateral relationship scores between 100 countries from 1945 to 2024. It supports interactive heatmaps, network graphs, pairwise comparisons, and more.

• Host: GitHub
• URL: https://github.com/mlucifer27/bilateral-visualization
• Owner: mlucifer27
• License: mit
• Created: 2025-07-06T21:44:34.000Z (12 months ago)
• Default Branch: master
• Last Pushed: 2025-07-06T21:55:34.000Z (12 months ago)
• Last Synced: 2025-07-06T22:35:05.615Z (12 months ago)
• Topics: d3blocks, data-analysis, data-visualization, plotly-python, python, streamlit
• Language: Python
• Homepage: https://bilateral-visualization.streamlit.app/
• Size: 0 Bytes
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Bilateral Relationship Visualization

This Streamlit app visualizes bilateral relationship scores between 100 countries from 1945 to 2024. It supports interactive heatmaps, network graphs, pairwise comparisons, and more.

## Features

- Heatmap of country-to-country relationships (overall, economic, political, security, cultural)

- Interactive tooltips and details on hover/click

- Year slider to explore changes over time

- Top-N strongest/weakest relationships

- Country relationship distribution (histogram, boxplot, summary stats)

- Country-to-network graph

- Pairwise comparison (table and line charts)

- Modular, efficient, and optimized for performance

## Screenshots

![Main Dashboard](images/1.png)

![Interactive Heatmap](images/2.png)

![Relationship Analysis](images/3.png)

![Network Graph](images/4.png)

![Pairwise Comparison](images/5.png)

![Distribution Analysis](images/6.png)

![Top Relationships](images/7.png)

![Country Details](images/8.png)

## Data

- `data/overall.csv`: Main dataset. Columns: `year`, `country1`, `country2`, `overall`, `economic`, `political`, `security`, `cultural`

- `data/countries.txt`: List of country names (one per line)

## Getting Started

### 1. Clone the repository

```bash

git clone https://github.com/mlucifer27/bilateral-visualization.git

cd bilateral-visualization

```

### 2. Install dependencies

It is recommended to use a virtual environment.

```bash

pip install -r requirements.txt

```

### 3. Run the app

```bash

streamlit run app.py

```

The app will open in your browser at `http://localhost:8501`.

## Deployment

### Streamlit Community Cloud

1. Push your code (including data files) to GitHub.

2. Go to [https://streamlit.io/cloud](https://streamlit.io/cloud) and sign in with GitHub.

3. Click "New app", select your repo, branch, and `app.py`.

4. Click "Deploy". Your app will be live at a public URL.

### Notes

- Ensure `data/overall.csv` and `data/countries.txt` are present in the repo for deployment.

- For large/private data, consider using cloud storage and loading data at runtime.

- For secrets, use Streamlit's [secrets management](https://docs.streamlit.io/streamlit-community-cloud/deploy-your-app/secrets-management).

## Customization

- All key parameters (year range, colormap, figure size, etc.) are modularized in the code for easy adjustment.

- The app is structured for easy extension and optimization.

## License

MIT