🌦️ Weather Visualization Project

📌 Overview

This project focuses on exploring and visualizing historical weather data.
The goal is to analyze patterns, trends, and anomalies in temperature, humidity, wind, and other features using Python.
Visualizations help to understand the dataset better and can be extended for future machine learning models.

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📂 Project Structure

weather-visualization/
│
├── data/               # Raw datasets (not pushed to GitHub if large)
│   └── weatherhistory.csv
│
├── notebooks/          # Jupyter notebooks for exploration and visualization
│   ├── 01_exploration.ipynb
│   └── 02_visualizations.ipynb
│
├── src/                # Python scripts (reusable functions)
│   ├── data_loader.py
│   └── visualization.py
│
├── README.md           # Project documentation
├── requirements.txt    # List of dependencies
├── .gitignore          # Files ignored by git

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🚀 Getting Started

1️⃣ Clone the Repository

git clone https://github.com/YOUR_USERNAME/weather-visualization.git
cd weather-visualization

2️⃣ Create Virtual Environment (recommended)

python -m venv venv

• On Mac/Linux:

  source venv/bin/activate

• On Windows:

  venv\Scripts\activate

3️⃣ Install Requirements

pip install -r requirements.txt

4️⃣ Run Jupyter Notebook

jupyter notebook

Open notebooks/01_exploration.ipynb and start exploring!

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📊 Features

• Load and clean weather data
• Explore statistical summaries
• Create visualizations for:
  • Temperature trends over time
  • Humidity distribution
  • Wind speed and direction patterns
  • Seasonal comparisons

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📈 Future Enhancements

• Build an interactive dashboard (using Plotly Dash / Streamlit)
• Add predictive modeling (e.g., forecasting temperature)
• Improve visualizations with animations

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📑 Dataset

The dataset used: Weather History (from Kaggle).
⚠️ Due to size limits, raw data is not pushed to GitHub.
You can download it here: Weather History Dataset on Kaggle

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