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.

• Project Overview
• Data Description
• Installation
• Visualizations
  • Top 10 Energy Consuming Countries
  • China vs United States Energy Consumption
  • Year-on-Year Growth in China
  • Anomaly Detection in US Energy Consumption
  • Linear Regression Predictions
• Dependencies
• License

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.

1. Clone this repository:

   git clone https:///~https://github.com/Sydney205/Primary-energy-consumption.git

2. Navigate to the project directory:

   cd energy-consumption-analysis

• Bar plot displaying total primary energy consumption by country.
• 

• A line plot comparing energy consumption trends between China and the United States from 1965 onwards.
• 

• A line plot showing the year-on-year growth percentage in primary energy consumption for China.
• 

• 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.
• 

• Python 3.x
• pandas
• matplotlib
• scikit-learn

To install the dependencies, run:

pip install pandas matplotlib scikit-learn

This 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.

• blob:https://ourworldindata.org/45aa90b8-7da0-4181-8920-2bb89fec0a9e