Data Analysis for Surface Temperature vs GDP

This project focuses on analyzing the relationship between surface temperature and GDP using Python, Pandas, and Tableau. The goal is to gain insights into how changes in surface temperature may correlate with the economic growth of different countries.

Table of Contents

• Introduction
• Technologies Used
• Dataset
• Analysis
• Results
• Usage
• Contributing
• License
• Acknowledgements

Introduction

The increasing concerns about climate change and its potential impact on various aspects of life, including the economy, have led to a growing interest in understanding the relationship between surface temperature and GDP. This project aims to explore this relationship by performing data analysis using Python, Pandas, and visualizing the results with Tableau.

Technologies Used

• Python
• Pandas
• Tableau

Dataset The analysis is conducted using a dataset that includes historical surface temperature data and GDP data for different countries over a specific time period. The dataset is obtained from a reliable source

• https://www.kaggle.com/datasets/berkeleyearth/climate-change-earth-surface-temperature-data
• https://www.kaggle.com/datasets/zackerym/gdp-annual-growth-for-each-country-1960-2020

Analysis

The analysis involves the following steps:

1. Data Loading: The dataset is loaded into a Python environment using the Pandas library.

2. Data Cleaning: Any missing or erroneous data is identified and handled appropriately. Data types are converted as necessary, and any outliers are addressed.

3. Data Exploration: The dataset is explored to understand its structure and characteristics. Descriptive statistics and visualizations are generated to gain insights into the data.

4. Data Integration: The surface temperature and GDP data are merged based on common attributes, such as country and time.

5. Correlation Analysis: The correlation between surface temperature and GDP is calculated to determine the strength and direction of their relationship.

6. Visualization: The analysis results are visualized using Tableau to create interactive and informative visual representations of the data.

Results

The analysis provides insights into the relationship between surface temperature and GDP. The findings may reveal patterns or trends that suggest a correlation or lack thereof between these two variables. These results can be used to draw conclusions and make informed decisions regarding climate policies, economic planning, and sustainability efforts.

Usage To replicate the analysis:

1. Clone the repository:

• git clone https://github.com/your-username/surface-temp-gdp-analysis.git

2. Install the required dependencies (provide details if necessary).
3. Load the dataset into the Python environment.
4. Run the analysis scripts in the specified order.
5. Use Tableau to create visualizations based on the generated results.
6. Interpret and analyze the findings.

Contributing

Contributions to this project are welcome. To contribute, follow these steps:

1. Fork the repository.
2. Create a new branch.
3. Make your enhancements or fixes.
4. Commit and push your changes.
5. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details