world-health

Overview

The World-Health project focuses on analyzing and visualizing global health data to provide insights into health conditions, medical indicators, and related factors across the world. This project leverages data from reliable sources to explore trends, compare countries, and support data-driven research or decision-making.

Objectives

• Collect and process health data from various countries.
• Build visualizations to represent key indicators (e.g., mortality rates, life expectancy, etc.).
• Analyze relationships between economic, social, and health factors.
• Provide open-source documentation and code for community use and contribution.

Projects Contents

• Data: Sourced from [specific source, e.g., World Bank, WHO] (please update with the actual source).

• Tools: R, Python, Git, GitHub.

• Key Files:

  • R/04_visualization.R: R script for data visualization.
  • [Add other files if applicable, e.g., data/cleaned_data.csv].

  Setup and Usage

  Requirements

  • R (version 4.x or higher).
  • Required R libraries: ggplot2, dplyr, tidyr (install using install.packages("package-name")).

  Intruction

1. Clone the repository:

   git clone https://github.com/NguyenDinhTrang04/world-health.git
   

2. Navigate to the project directory:

   cd world-health
   

3. Install required R libraries:

   install.packages(c("ggplot2", "dplyr", "tidyr"))
   

4. Run the visualization script:

   source("R/04_visualization.R")
   

Directory Structure

world-health/
├── R/                # Contains R scripts
│   └── 04_visualization.R
├── data/             # Contains raw and processed data
│   └── cleaned_data.csv
├── README.md         # This document
└── .gitignore        # Files to ignore in version control