Human Life Expectancy Exploration and Analysis

This project seeks to better understand the life expectancy of humans around the world. This project will analyze the factors affecting the life expectancy of a person, see which countries sustain both healthy lifestyles and growth, compare life expectancy between males and females around the world, and develop a model to predict the life expectancy and see how it has been defined based on a given set of parameters.

Technologies

In order to build this project, you will need:
-Python3
-Anaconda
-Pandas
-Numpy
-Geopandas
-Matplotlib
-Plotly, Dash
-Sklearn

You can install python packages using:
-pip installer
-Anaconda

Data Sources

Data was sourced from the WHO (https://www.who.int/data/gho/data/themes/topics/indicator-groups/indicator-group-details/GHO/life-expectancy-and-healthy-life-expectancy) and World Bank (https://data.worldbank.org/indicator/SP.DYN.LE00.MA.IN), (https://data.worldbank.org/indicator/SP.DYN.LE00.FE.IN)

Project Questions and Hypotheses

Questions:

-What external factors affect life expectancy and which have the greatest affect?
-How has life expectancy changed over time around the world?
-How does life expectancy differ from males to females?

Hypotheses:

-Schooling, GDP, low alcohol consumption, low rates of chronic diseases, and increased access to vaccinations against chronic illnesses will have strong positive affects on life expectancy.
-Life expectancy has overall increased as time has increased around the world.
-Females have higher life expectancies than males do in all countries.