This project explores a global climate change dataset sourced from Kaggle . The goal is to analyze and visualize climate-related metrics across countries and years to uncover patterns, trends, and insights that can help shape policies for combating climate change.
Perform Exploratory Data Analysis (EDA) on climate indicators.
Identify relationships and correlations among climate metrics.
Explore trends over time such as rising CO₂ emissions, temperature changes, and renewable energy adoption.
Provide actionable insights for policymakers and environmental organizations.
Keep the focus on interpretability (no machine learning models used).
The dataset includes multiple climate-related indicators across countries and years.
Key Columns:
Year → Year of data point
Country → Country/region name
Average Temperature (°C) → Annual average temperature
CO2 Emissions (Tons/Capita) → Per capita carbon emissions
Sea Level Rise (mm) → Annual sea level rise
Rainfall (mm) → Total annual rainfall
Population → Total population
Renewable Energy (%) → Share of energy from renewable sources
Extreme Weather Events → Count of events (storms, floods, etc.)
Forest Area (%) → Percentage of land covered by forests
📎 Dataset link: Kaggle - Climate Change Dataset
Python
Pandas → Data manipulation
NumPy → Numerical analysis
Matplotlib / Seaborn / Plotly → Data visualization
Jupyter Notebook → Interactive analysis
📈 Example Analyses
✔️ Trend of CO₂ emissions vs. renewable energy usage ✔️ Correlation between average temperature and sea level rise ✔️ Country-level analysis of forest area changes ✔️ Visualization of extreme weather events over time
- Clone the Repository git clone 📁 Deep_DataHack
cd climate-change-analysis
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Install Dependencies pip install -r requirements.txt
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Run Jupyter Notebook jupyter notebook
Open the notebook and start exploring the dataset.
Add interactive dashboards (e.g., using Streamlit or Dash).
Expand analysis with regional comparisons.
Integrate external datasets (e.g., WHO, UN climate reports).
Contributions are welcome! Feel free to fork this repo, create a branch, and submit a pull request.