🌤️ Davis Weather Stations Visualizer

A modern and interactive web application built with Streamlit that enables real-time monitoring, analysis, and visualization of meteorological and air quality data from multiple Davis WeatherLink stations. This professional tool facilitates tracking of environmental variables through dynamic charts, cross-station comparisons, and flexible temporal analysis, making it ideal for researchers, students, and weather enthusiasts who need quick and efficient access to up-to-date meteorological data.

📋 Features

• Real-time visualization of multiple weather stations
• Interactive charts for temperature, humidity, PM2.5 and PM1
• Flexible time selection: last N hours or specific date range
• Station comparison on the same scales and timeframes
• Intuitive interface built with Streamlit

☁️ Monitored Variables

• 🌡️ Temperature (°C): Ambient temperature
• 💧 Humidity (%): Relative air humidity
• 🌫️ PM2.5 (μg/m³): Fine particles - air quality
• 💨 PM1 (μg/m³): Ultrafine particles - air quality

🛠️ Local Installation

Prerequisites

• Python 3.8+
• WeatherLink API account with valid credentials

Installation Steps

1. Clone the repository

   git clone https://github.com/your-username/visualizer_weatherlinkv2.git
   cd visualizer_weatherlinkv2

2. Install dependencies

   pip install -r requirements.txt

3. Configure secrets

   Create a .streamlit folder and secrets.toml file in the project root:

   mkdir .streamlit

   Create .streamlit/secrets.toml:

   WEATHERLINK_API_KEY = "your_api_key_here"
   WEATHERLINK_API_SECRET = "your_api_secret_here"

4. Run the application

   streamlit run visualizador_es.py

5. Open in browser

   The application will be available at http://localhost:8501

🔧 Configuration

Streamlit Secrets

• WEATHERLINK_API_KEY: Your WeatherLink API key
• WEATHERLINK_API_SECRET: Your WeatherLink API secret

Configure these in .streamlit/secrets.toml for local development, or in your Streamlit Cloud dashboard for deployment.

Stations

Stations are automatically loaded from your WeatherLink API account. Make sure your stations are configured and sending data.

📦 Main Dependencies

• Streamlit: Web application framework
• weatherlinkv2: Custom library for WeatherLink API
• Plotly: Interactive charts
• Pandas: Data manipulation

📝 Usage

1. Select stations: Use the multi-select dropdown in the sidebar
2. Configure time: Choose between "Last hours" or "Date range"
3. Update data: Press the "🔄 Update data" button
4. Visualize: View interactive charts with data from all selected stations

🤝 Contributions

Contributions are welcome. Please:

1. Fork the project
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

---

⭐ If you find this project useful, please give it a star on GitHub!