☔️ The Daily Drip

The Daily Drip is an interactive Streamlit dashboard for exploring and visualizing daily rainfall data. It provides a clean, engaging UI to upload, clean, and analyze rain measurements, including donut charts for rain intensity, daily distributions, and key weather stats.

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📊 Features

• 📤 Upload your own CSV rain dataset from MeteoBlue
• 🧹 Built-in data cleaning
• 📅 Date range filtering
• 🌧️ Rain intensity classification
• 📈 Donut chart + bar chart visualizations with Plotly
• 📥 Download cleaned data

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📁 Project Structure

Project Structure

daily-drip/
├── data-prep
|   ├── data-prep-rain.ipynb     # 1st try at data cleaning logic via notebook
|   ├── rain-data-processed.csv
├── historical-data             # where historical data is stored
|    ├── original-data.csv
├── main.py                     # Streamlit app – handles UI, charts, and layout
├── data_cleaning.py            # Data cleaning logic – handles formatting and classification
├── fallback.csv                # Default dataset used when no CSV is uploaded
├── requirements.txt
├── README.md

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🚀 Getting Started

🔧 Requirements

• Python 3.9+
• pip or uv (Rust-based package manager)

📦 Install Dependencies

pip install -r requirements.txt
# or if using uv
uv pip install -r requirements.txt

▶️ Run the App

streamlit run main.py

Then open http://localhost:8501 in your browser.

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📂 How It Works

• If a user uploads a CSV file, it is cleaned via data_cleaning.py.
• If no upload is provided, a default dataset (fallback.csv) is loaded.
• Data is processed and classified by rain intensity, then plotted.
• Metrics like total, average, max rainfall, and frequency are calculated.
• All visuals are updated based on user-selected date filters.

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🧠 Tech Stack

• Streamlit
• Plotly
• Pandas
• Python 3.9+

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💡 Future Ideas

• Multi-location data selection
• Export to Excel not just csv
• Long-term trend analysis

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👤 Author

Made with ☕ and ☔️ by @Tiago3BC

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