This project analyzes global primary energy consumption trends for various countries and regions. It includes data processing, visualization, statistical analysis, and machine learning to make predictions about future energy consumption.
This project focuses on exploring and analyzing global energy consumption data using Python. Key insights include:
The dataset contains the following key columns:
- Entity: Country, region, or continent.
- Code: ISO 3-letter country code.
- Year: The year of the data entry.
- Primary energy consumption (TWh): The primary energy consumption measured in terawatt-hours.
- Clone this repository:
git clone https:///~https://github.com/Sydney205/Primary-energy-consumption.git
- Navigate to the project directory:
cd energy-consumption-analysis
- Bar plot displaying total primary energy consumption by country.
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- A line plot comparing energy consumption trends between China and the United States from 1965 onwards.
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- A line plot showing the year-on-year growth percentage in primary energy consumption for China.
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- Scatter plot showing the actual vs predicted values for energy consumption in the United States.
- Predictions for future energy consumption until 2050 using a linear regression model.
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- Python 3.x
- pandas
- matplotlib
- scikit-learn
To install the dependencies, run:
pip install pandas matplotlib scikit-learnThis project is licensed under the APACHE License - see the LICENSE file for details.
- The dataset was obtained from https://ourworldindata.org.
- Libraries used:
pandas,matplotlib,scikit-learn.