Global Sustainable Energy: A Cross National Analysis (2000 to 2020)

Tutorial Section

TT3L

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Group 8

No.	Student ID	Student Name	Contribution
1	242UC244PP	NICHOLAS BEH ZHI YANG	25%
2	242UC244SX	YAP YANG YI	25%
3	242UC244M6	YAP HUI CHI	25%
4	252UC254MS	LIAW YONG LOON	25%

Note: Marks may vary among group members based on individual contributions. All members should agree on the contribution percentages listed above.

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YouTube Presentation Link

[Insert YouTube Link Here]

Please ensure that the submitted YouTube link is valid, accessible, and functioning properly at the time of assessment. The examiner will not notify the group if the link is unavailable or incorrect. Failure to provide a working and accessible link may result in a score of zero (0) for the presentation component.

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Dataset Information

Dataset Title

Global Data on Sustainable Energy (2000 to 2020)

Source and Link

Kaggle Dataset:
https://www.kaggle.com/datasets/anshtanwar/global-data-on-sustainable-energy

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Brief Description

This dataset contains annual sustainable energy indicators for 176 countries from 2000 to 2020, comprising 3,649 observations across 21 variables.

The variables include:

• Access to electricity
• Renewable energy share in total final energy consumption
• Electricity generation by fossil fuels, nuclear energy, and renewable sources
• CO₂ emissions
• Energy intensity
• GDP per capita
• GDP growth

The dataset is compiled from recognised international organisations such as the World Bank, the International Energy Agency (IEA), and Our World in Data. The dataset is distributed under the CC0 Public Domain licence.

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Download Instructions

1. Sign in to Kaggle.
2. Navigate to the dataset link above.
3. Download the dataset file.
4. Place the file below inside the ./data/ folder located in the same directory as the notebook:

global-data-on-sustainable-energy.csv

Directory structure:

project-folder/
│
├── data/
│   └── global-data-on-sustainable-energy.csv
│
├── notebook.ipynb
└── README.md

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How to Run the Project

1. Install Required Packages

pip install pandas numpy matplotlib seaborn scipy

Alternatively:

pip install -r requirements.txt

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2. Run the Notebook

Open the notebook and run all cells from top to bottom:

Kernel → Restart & Run All

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Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• SciPy
• Jupyter Notebook

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Licence

This project uses a dataset published under the CC0 Public Domain licence.