This project explores the relationship between climate change and its impact on agriculture through detailed data analysis. The study examines various factors such as temperature, precipitation, CO2 emissions, and their influence on crop yield and agricultural practices. The goal is to provide insights into trends and correlations within the data that highlight the effects of climate change on farming.
- Data Analysis: A comprehensive examination of how climate change variables (e.g., temperature, CO2 emissions) affect crop yield, regional differences, and agricultural practices.
- Data Visualization: A wide range of charts and graphs to visualize climate impacts on agriculture, helping to uncover key patterns.
- Insights: Identification of correlations between climate factors and agricultural outcomes, including crop yields and economic impacts.
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Clone the repository:
git clone https://github.com/yourusername/climate-change-agriculture-analysis.git -
Navigate to the project directory:
cd climate-change-agriculture-analysis -
Install the required dependencies:
pip install -r requirements.txt -
Run the Jupyter notebook or Python script:
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To run the notebook:
jupyter notebook climate_change_agriculture_analysis.ipynb
Or to run the script:
python analysis.py
Dependencies
Python 3.x Jupyter Notebook Pandas Matplotlib Seaborn NumPy Scikit-learn
Dataset
The dataset contains multiple variables related to agriculture and climate, such as year, region, crop type, temperature, precipitation, CO2 emissions, and crop yield. The dataset helps in understanding the long-term effects of climate change on agricultural production and economic outcomes.
Dataset Link: https://www.kaggle.com/datasets/waqi786/climate-change-impact-on-agriculture
Uploaded Date: 9/6/2024
License
This project is licensed under the MIT License - see the LICENSE file for details.