Wine and Climate Change: Impact Analysis on Global Production

By: Amanda Derdiger, Andrew Koller, Can "Jon" Ayter, Lindsay McFayden

Introduction

This project investigates the relationship between climate change and global wine production. We analyze temperature trends and wine production data to uncover potential correlations and impacts across various geographical regions.

Research Questions

• Is there a correlation between rising temperatures and its effect on wine production?
• Is there a correlation between rising temperatures and the creation of new wine industries in regions previously unfit for wine production? Which geographical regions can expect to see an increase in wine production and which regions can expect to see a decrease in wine production given the expected rise in temperature?

Data

Our dataset comprises:

• Global Land Temperatures by Country
• Global Temperature Data
• Wine Production Data
• Merged Data (combining temperature and wine production)
• Country-specific Data

Process

Data Preparation and Cleaning

• Imported necessary libraries (Pandas, Matplotlib, Seaborn, SciPy)
• Loaded and merged multiple datasets
• Cleaned data, handled missing values, and converted units where necessary

Analysis Techniques

• Time series analysis of temperature and wine production
• Correlation analysis between temperature and wine production
• Statistical significance testing (p-values and r-values)
• Visualization of trends using various plot types (scatter, bar, regression)

Key Findings

• Weak to moderate correlations found in some countries between rising temperatures and wine production changes
• No conclusive evidence of a global trend across all countries
• Some regions (e.g., New Zealand) showed significant wine production growth not directly correlated with temperature changes
• Other factors beyond temperature likely influence wine production trends

Visualizations

• Wine Production Over Time
• Average Temperature Over Time
• Wine Production vs. Average Temperature
• Countries with Sharp Increase in Wine Production

Tools Used

• Python
• Pandas for data manipulation
• Matplotlib and Seaborn for visualizations
• SciPy for statistical analysis
• Jupyter Notebooks for interactive development

How to Use This Project

• Clone the repository
• Install required dependencies (Pandas, Matplotlib, Seaborn, SciPy)
• Run the Jupyter Notebook to see the analysis and results
• Use interactive widgets to explore data for different countries and time periods

Future Work

• Incorporate additional climate variables (precipitation, soil moisture)
• Analyze economic and policy factors influencing wine production
• Extend the dataset to include more recent years
• Develop predictive models for future wine production based on climate projections

Limitations and Considerations

• Data limitations in some regions and time periods
• Complex interplay of factors affecting wine production beyond climate
• Need for more comprehensive datasets for definitive conclusions