🌦️ Weather Data Analysis Dashboard 📍 Chennai, Tamil Nadu, India 📌 Overview

This project performs real-time weather data analysis using statistical methods and visualizations. It automatically detects the user’s location, fetches 7-day hourly weather data, and generates a comprehensive statistical report along with a multi-panel dashboard.

📸 Project Output

🚀 Features 📍 Auto Location Detection using IP 🌐 Real-time Weather Data (Open-Meteo API) 📊 Statistical Analysis Mean, Median, Mode Standard Deviation & Variance Skewness & Kurtosis 🔗 Correlation Analysis (Pearson) 📈 Linear Regression Model ⚠️ Outlier Detection (Z-score) 📅 Daily Aggregated Insights 🎨 5-Panel Visualization Dashboard 📊 Visualizations Included 7-Day Temperature Trend (with rolling mean & regression) Daily Mean Temperature Bar Chart Temperature Distribution (Histogram + Normal Curve) Temperature Box Plot (per day) Temperature vs Humidity (Scatter + Regression) 🧠 Statistical Engine

The project computes a complete statistical report using custom logic implemented in 👉

It includes:

Descriptive statistics Correlation strength & significance Regression modeling Outlier detection ⚙️ How It Works

The entire pipeline is handled in 👉

Workflow:

Detect user location Fetch weather data Compute statistics Generate report Render charts 🌐 Data Source Open-Meteo API (No API key required) Configured in 👉 📦 Installation pip install -r requirements.txt

Dependencies listed in 👉

▶️ Run the Project python main.py 📁 Project Structure Weather-Data-Analysis/ │── main.py # Entry point
│── weather_api.py # Fetch weather data
│── statistics_engine.py # Statistical computations
│── visualizer.py # Dashboard generation
│── report.py # Console report
│── location.py # IP-based location detection
│── config.py # Config & constants
│── requirements.txt # Dependencies
📈 Key Insights (from your output) Temperature shows a steady increasing trend over the week Strong negative correlation between temperature & humidity Data approximately follows a normal distribution No extreme outliers detected High regression accuracy (R² ≈ 0.91) 💡 Learning Outcomes Real-world data handling & API integration Application of statistical concepts Data visualization using Matplotlib Building end-to-end data pipelines 🔮 Future Improvements Add multi-city comparison Build a web dashboard (React + Flask) Add ML-based weather prediction 📜 License

This project is for academic and educational use.