Life Expectancy Health Dataset
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Life Expectancy Health Dataset
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Life Expectancy Health Dataset
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Life Expectancy Health Dataset
Use Case
Life Expectancy Health Dataset
Description
Explore a comprehensive dataset on life expectancy across countries, including key socio-economic and health indicators.
Description:
The Life Expectancy and Socio-Economic Health Indicators dataset provides comprehensive, averaged life expectancy data for countries across the world, combined with key socio-economic and health factors. This dataset allows for deep analysis of the correlation between life expectancy and various development indicators, highlighting regional disparities and trends over time.
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Key Features:
- Country & Region Data: Includes life expectancy data from countries across diverse continents, categorized by regions (e.g., Asia, Europe, Africa, etc.).
- Life Expectancy: The average life expectancy in years for each country, allowing comparisons and trend analysis.
- Socio-Economic Indicators:
- GDP per capita: A measure of the economic development of each country.
- Education: Average years of schooling, reflecting access to education as a development factor.
- Alcohol Consumption: Alcohol use as a socio-economic health indicator.
- Economic Status: Categorized by whether a country is developed or developing.
- Health Indicators:
- Infant and Adult Mortality Rates: Key health metrics influencing life expectancy.
- HIV Prevalence: The rate of HIV infection as a contributing health factor.
- Immunization Rates: Data on vaccinations for diseases like Hepatitis B and Polio.
- Prevalence of Diseases: Includes incidence rates for measles, diphtheria, and other diseases.
- Body Mass Index (BMI): General health indicator based on BMI data.
- Child and Adolescent Health: Data on thinness prevalence among young populations.
Purpose of the Dataset:
This dataset is designed to support:
- Exploratory Data Analysis (EDA): Analyze and understand trends in life expectancy across different regions and economic statuses.
- Data Visualization: Create impactful visualizations, such as choropleth maps and scatter plots, to showcase relationships between socio-economic, health factors, and life expectancy.
- Machine Learning: Develop predictive models to estimate life expectancy based on socio-economic and health data.
- Policy Research: Provide valuable insights to guide policy decisions and identify critical factors affecting life expectancy globally.
Use Cases:
- Researchers: Ideal for health and economic researchers focusing on the determinants of life expectancy.
- Developers & Data Scientists: A great resource for building predictive models and conducting analysis in public health.
- Policy Makers: A valuable tool for understanding key factors influencing life expectancy to help inform public health policies.
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